Reporting of Computational 
Modeling Studies in Medical Device 
Submissions  
 
 
Guidance for Industry and Food and 
Drug Administration Staff  
 
               Document issued on: September 21, 2016. 
 
The draft of this document was issued on January 17, 2014. 
 
For questions about this document, contact Tina M. Morrison, Ph.D., Division of Applied 
Mechanics, Office of Science and Engineering Laboratories, (301) 796-6310, 
tina.morrison@fda.hhs.gov. 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Devices and Radiological Health 
Office of Device Evaluation 
Office of Science and Engineering Laboratories 
 
 
 
    Contains Nonbinding Recommendations 
 
Preface 
 
 
Public Comment 
 
You may submit electronic comments and suggestions at any time for Agency consideration to 
http://www.regulations.gov . Submit written comments to the Division of Dockets 
Management, Food and Drug Administration, 5630 Fishers Lane, Room 1061, (HFA-305), 
Rockville, MD 20852. Identify all comments with the docket number FDA-2013-D-1530. 
Comments may not be acted upon by the Agency until the document is next revised or updated. 
 
Additional Copies 
 
Additional copies are available from the Internet. You may also send an e-mail request to 
CDRH-Guidance@fda.hhs.gov to receive a copy of the guidance. Please use the document 
number 1807 to identify the guidance you are requesting. 
 
 
 
  Contains Nonbinding Recommendations 
 
Table of Contents 
 
 
Introduction ............................................................................................................................... 1 
Scope ......................................................................................................................................... 2 
Outline of the CM&S Report .................................................................................................... 2 
I.  Executive Report Summary ....................................................................................... 3 
II.  Background/Introduction ........................................................................................... 3 
III.  Code Verification ....................................................................................................... 3 
IV.  System Configuration ................................................................................................ 4 
V.  Governing Equations/Constitutive Laws ................................................................... 4 
VI.  System Properties....................................................................................................... 5 
VII.  System Conditions ..................................................................................................... 5 
VIII.  System Discretization ................................................................................................ 5 
IX.  Numerical Implementation ........................................................................................ 6 
X.  Validation ................................................................................................................... 6 
XI.  Results ........................................................................................................................ 7 
XII.  Discussion .................................................................................................................. 7 
XIII.  Limitations ................................................................................................................. 7 
XIV.  Conclusions ................................................................................................................ 7 
XV.  References .................................................................................................................. 7 
Glossary .................................................................................................................................... 8 
Subject Matter Appendix I  Computational Fluid Dynamics  and Mass Transport.............. 10 
Subject Matter Appendix II  Computational Solid Mechanics ............................................. 19 
Subject Matter Appendix III  Computational Electromagnetics and Optics ........................ 27 
Subject Matter Appendix IV  Computational Ultrasound .................................................... 35 
Subject Matter Appendix V  Computational Heat Transfer ................................................. 41 
 
  Contains Nonbinding Recommendations 
 
Reporting of Computational 
Modeling Studies in Medical Device 
Submissions 
 
  
 
Guidance for Industry and  
Food and Drug Administration Staff 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA 
or Agency) on this topic.  It does not establish any rights for any person and is not binding 
on FDA or the public.  You can use an alternative approach if it satisfies the requirements 
of the applicable statutes and regulations.  To discuss an alternative approach, contact the 
FDA staff or Office responsible for this guidance as listed on the title page. 
Introduction  
For many years, computational modeling and simulation (CM&S) studies have been used by 
sponsors to support device design/development and have been reported in medical device 
submissions.  These studies have traditionally been used in the areas of fluid dynamics (e.g., 
calculate shear stress in ventricular assist devices), solid mechanics (e.g., determine 
maximum stress locations in a hip implant), electromagnetics and optics (e.g., radiofrequency 
safety in magnetic resonance imaging, fluorescence for fiber optic spectroscopy devices), 
ultrasound propagation (e.g., absorbed energy distribution for therapeutic ultrasound), and 
thermal propagation (e.g., temperature rises with radiofrequency and laser ablation devices).  
The purpose of this guidance document is to provide recommendations to industry on the 
formatting, organization, and content of reports of CM&S studies that are used to support 
medical device submissions.  Moreover, this guidance is also for FDA Staff, to improve the 
consistency and predictability of the review of CM&S studies and to better facilitate full 
interpretation and complete review of those studies. 
 
FDA's guidance documents, including this guidance, do not establish legally enforceable 
responsibilities.  Instead, guidances describe the Agency's current thinking on a topic and 
should be viewed only as recommendations, unless specific regulatory or statutory 
requirements are cited.  The use of the word should in Agency guidances means that 
something is suggested or recommended, but not required.  
  1  Contains Nonbinding Recommendations 
 
Scope 
Computational modeling and simulation studies, together with bench, nonclinical in vivo, and 
clinical studies, can be used to evaluate the safety and effectiveness of medical devices.  In 
order for the CM&S studies to serve as valid scientific evidence in regulatory submissions, 
specific details need to be included in the report of such studies.  In this guidance, the term 
CM&S report refers to the part of a regulatory submission that provides information about 
a CM&S study; the term does not describe a new submission requirement. 
 
The recommended format provided in this document aims to establish uniformity in reporting 
CM&S studies.  FDA recognizes that the level of detail to be reported will vary and will 
depend on the context of use for the CM&S studies.  Moreover, there are a variety of CM&S 
modalities and thus the specific details will vary across disciplines.  Therefore, we have 
provided a general outline in the main body of this document and five subject matter 
appendices for CM&S modalities that are widely used in regulatory submissions.  The main 
body is written in general terms to capture reporting for any modality.  The five appendices 
provide more background, structure, and specific terminology for the following subject areas: 
 
I.  Fluid Dynamics and Mass Transport 
II.  Solid Mechanics 
III.  Electromagnetics and Optics 
IV.  Ultrasound 
V.  Heat Transfer 
 
For multiphysics modeling, recommendations in several of these appendices may apply.   
 
The scope of this guidance is limited to how CM&S studies and its outcomes can be used to 
support a regulatory submission when medical devices use such studies to determine safety 
and effectiveness.  This guidance document does not address or make a determination 
whether CM&S tools may be considered medical devices. 
 
While verification and validation of the CM&S studies are necessary components of the 
report, this document does not establish the amount or type of verification and validation 
needed to support using the CM&S studies in regulatory submissions.  Further, this guidance 
document does not address how to conduct a computational modeling or simulation study, 
nor does adherence to this guidance ensure that your computational modeling or simulation 
study is adequate or appropriate.  This guidance only provides guidelines for reporting this 
information to FDA and highlights some common issues with models and simulations. 
 
Outline of the CM&S Report  
In the following section, we provide the recommended headings and details for a CM&S 
report contained within a regulatory submission. 
  2  Contains Nonbinding Recommendations 
 
I.  Executive Report Summary 
We recommend that you provide a concise and complete overview of the report of the 
computational modeling and/or simulation study, that includes the following: 
  Context of use of the CM&S study including a clear identification of the 
quantity(s) of interest (QOI) (e.g., to determine the maximum stress value(s) and 
location(s)) 
  Scope of the analysis (e.g., for a device that has multiple sizes and/or 
configurations, specify which sizes and/or configurations were modeled, and how 
the computational model relates to the intended patient population) 
  Type of analysis (e.g., fluid dynamics and mass transport, solid mechanics, 
electromagnetics and optics, ultrasound, heat transfer) 
  Conclusions with respect to the context of use 
  Keywords: we recommend that you provide up to five keywords or key phrases 
that describe the modeling modality, the device product code, any relevant 
materials of the device, analysis type, and if applicable, location in the body.  For 
more information on the device product code, refer to the FDA guidance entitled 
Medical Device Classification Product Codes issued on April 11, 2013.  The 
following are examples of keywords that outline this information:  
  e.g., finite element analysis, MIH, nitinol, fatigue, aorta 
  e.g., radiofrequency dosimetry, OQG, cobalt chromium, magnetic 
resonance safety, hip 
This information will be used for semantic text mining of CM&S reports to better 
understand the impact of this guidance on CM&S studies used in regulatory 
submissions. 
II.  Background/Introduction 
We recommend that you provide a brief description of the device system and intended 
use environment.  Discuss the context of use of the analysis, as this will dictate the 
relevant details necessary for review. 
III.  Code Verification 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed.  Code verification 
establishes the correctness of the code used as software tools for CM&S and establishes 
the correctness and fidelity of the numerical algorithms; this is accomplished through 
SQA and NCV.  Software tools include off-the-shelf, modified-off-the-shelf, or user-
developed.  Code verification is important, regardless of the software type. 
 
A.  Details 
SQA ensures that the code is functioning correctly and produces repeatable results on 
specified computer hardware and in a specified software environment.  NCV ensures 
correct implementation and functioning of the numerical code, which is typically 
accomplished by, for example, comparison to bench-mark solutions, method of 
manufactured solutions.  You should briefly describe the code verification activities.  
  3  Contains Nonbinding Recommendations 
 
You may reference available documentation and verification results from the software 
developer.   
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationale for differences 
between the code used for verification and the code used for the context of use.  
Moreover, provide rationale to support the selection of the numerical settings, 
regardless if the settings are default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in System Discretization and Numerical 
Implementation, sections VIII and IX, respectively. 
 
IV.  System Configuration 
We recommend that you provide information regarding the system configuration (e.g., 
the geometry of the device, the computational domain, the structure of a physiological 
control system, the in vitro test that is modeled). 
 
A.  Details 
You should describe the components of the system (e.g., device, in vivo and/or in 
vitro environment), including appropriately scaled/dimensioned images and/or 
diagrams. 
 
You should describe the methods (e.g., image reconstruction and resolution, computer 
aided design (CAD)) used to generate the system configuration, including format, and 
discuss how the configuration was appropriately captured for the intended analysis. 
 
You should describe the software used to generate the system configuration (e.g., 
CAD software, image segmentation software, control-system simulation software).    
Describe the imaging modality if image reconstruction was used to generate 
geometry. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to generate the system configuration as compared to the actual device and 
environment.  If appropriate, provide a clinical rationale for the in vivo/in vitro 
models (e.g., size, disease state, mathematical convenience versus clinical relevance). 
V.  Governing Equations/Constitutive Laws 
We recommend that you provide information regarding the governing equations and/or 
constitutive laws used to perform the computational analysis. 
 
A.  Details 
  4  Contains Nonbinding Recommendations 
 
You should provide a description of the governing equations/constitutive laws for the 
system.  Provide the actual equations, if appropriate.    
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the governing equations/constitutive laws chosen to represent the system.   
VI.  System Properties 
We recommend that you provide information regarding the biological, chemical, physical 
and physiological properties of the system, as appropriate. 
 
A.  Details 
You should describe and quantify all system properties used in the analysis.  These 
might include biological material properties (e.g., cells, tissues, organs) and/or 
processes (e.g., cell signals), and/or states (e.g., diseased, healthy), chemical 
properties, physiological properties and physical properties that define the materials 
and/or process characteristics.  Please also discuss the variability (e.g., temporal, 
spatial, across individuals/samples) of system properties, if applicable. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the system properties.  Identify the source and provide the 
reference for the properties (e.g., literature, in vivo, ex vivo, in vitro testing). 
VII.  System Conditions 
We recommend that you provide information regarding the conditions that were imposed 
on the system.  These might include, but are not limited to, the boundary and loading 
conditions, initial conditions, and other constraints that control the system. 
 
A.  Details 
You should describe the system conditions imposed on the model and their 
variability, if applicable.  If appropriate, provide a graphical representation of the 
conditions, depicting how they are applied to the system. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the conditions applied on the system.  Provide appropriate 
documentation (e.g., literature, test reports, clinical data, medical imaging data). 
VIII. System Discretization 
We recommend that you provide information regarding the discretization and refinement 
techniques applied to the system for solving it numerically. 
 
A.  Details 
You should describe the system discretization methods and how they were applied to 
the computational domain.  Describe the calculation verification methodology (e.g., 
  5  Contains Nonbinding Recommendations 
 
mesh refinement study) used to ensure that the computational domain was suitably 
resolved.  If applicable, provide a representative image of the discretization in the 
areas of interest of the computational domain.  You should describe the type and 
quality of the discretization.  As part of the calculation verification process, report the 
criteria used to determine that the solution was sufficiently resolved. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to discretize the computational domain.  Report the criteria used to determine 
that the discretization was sufficient to resolve the QOI(s). 
 
IX.  Numerical Implementation 
We recommend that you provide information regarding the numerical implementation 
used to solve the governing equations. 
 
A.  Details 
You should describe the numerical implementation methodology and/or numerical 
method used to solve the governing equations.  State the solver parameters (e.g., 
tolerance, relaxation) and convergence criteria. 
 
B, Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the solver and associated parameters.  Note that rationale should be 
provided for the solver settings, whether they are adjusted from the default settings or 
not. 
X.  Validation 
We recommend that you provide information regarding the method(s) employed to 
validate the computational model for the context of use. 
 
A.  Details 
You should describe the method (e.g., in vivo, ex vivo or in vitro comparator) used to 
assess the validity of the computational model.  Report and compare the QOI(s) from 
the computational model and the comparator.  Describe the sensitivity of the QOI(s) 
on key parameters and provide a systematic analysis of the uncertainty in relation to 
the key parameters, as appropriate. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide the rationale for the assumptions and simplifications 
of the method (e.g., in vivo, ex vivo or in vitro test) used to validate the computational 
model.  You should discuss why the method of comparison and the degree of 
agreement between QOI(s) from the comparator and computational model are 
appropriate for using the computational model in the context of use. 
  6  Contains Nonbinding Recommendations 
 
XI.  Results 
We recommend that you present the quantitative results, the QOI(s), from the CM&S 
study.  You should provide the results with sufficient level of detail, including labels and 
legends.  The results may be presented in more than one format (e.g., table, graph).   
XII.  Discussion 
We recommend that you discuss how the results from the CM&S study relate to the 
context of use.  If appropriate, discuss the regulatory and/or clinical relevance of the 
results. 
XIII. Limitations 
We recommend that you provide details regarding how the assumptions, simplifications, 
sensitivity and uncertainty analyses described in the previous sections might affect the 
output of the computational model, the interpretation of the results, and the relevance to 
the context of use. 
XIV. Conclusions 
We recommend that you state the overall conclusions of the CM&S study and if the 
regulatory objective(s) have been met.  
XV.  References 
We recommend that you provide a list of the appropriate references used to support the 
CM&S study.    
  7  Contains Nonbinding Recommendations 
 
Glossary 
For purposes of this guidance, the following terms are defined. 
 
Accuracy: the difference between a parameter, variable or derived quantity (or a set of 
parameters or variables) within a model, simulation, or experiment and the true value or the 
assumed true value. 
 
Analysis: any post-processing or interpretation of the individual values, arrays, files of data, 
or suites of executions resulting from a simulation. 
 
Calculation Verification: the process of determining the solution accuracy of a particular 
calculation. 
 
Code Verification: the process of determining that the numerical algorithms are correctly 
implemented in the computer code and identifying errors in the software. 
 
Comparator: the experimental methodology that is used to perform validation.  The 
comparator data can be taken from a laboratory bench-test, an animal study, an imaging 
study, or a clinical study.  The selection of the comparator should be based on the context of 
use. 
 
Computational domain: the spatial and/or temporal domain for which the analysis was 
conducted.  See also System Discretization. 
 
Computational model: the numerical implementation of the mathematical model performed 
by means of a computer.  
 
Constitutive law: an expression which describes the relationship between biological, 
chemical or physical quantities for a specific material or substance and an external stimuli 
(e.g., Hookes Law). 
 
Context of use: the purpose or intent of the computational model and/or simulation study, 
specifically the role of the CM&S study in the regulatory submission. 
 
Convergence analysis: the process of ensuring the solution resolves the physics of interest 
and the variation of the solution remains within a pre-specified range as the discretization is 
refined. 
 
Governing equation: the mathematical relationship that describes the phenomena of 
interest. 
 
Mathematical model: the mathematical equations, boundary values, initial conditions, and 
modeling data needed to describe the conceptual model. 
 
  8  Contains Nonbinding Recommendations 
 
Model: a description or representation of a system, entity, phenomena, or process (adapted 
from Banks, J., ed. (1998). Handbook of Simulation. New York: John Wiley & Sons).  Any 
data that go into a model are considered part of the model.  Models may be mathematical, 
physical, or logical representations of a system, entity, phenomenon, or process.  Models can 
be used by simulation to predict a future state, if so desired. 
 
Quantity of Interest: the desired output from the computational model.  For a particular 
context of use, there can be multiple quantities of interest. 
 
Sensitivity: the degree to which the output is affected by a particular input. 
 
Simulation: the imitation of the characteristics of a system, entity, phenomena, or process 
using a computational model; a specific run of the model with one set of parameters that 
results in the quantity of interest or multiple quantities of interest. 
 
Subject matter: a particular technical discipline, system, or process regarding computational 
modeling methodologies. 
 
System discretization: the division of the computational domain of the system into discrete 
parts for numerical implementation. 
 
Uncertainty: the estimated amount or percentage by which an observed or calculated value 
may differ from the true value (The American Heritage Dictionary of the English Language, 
4th ed.). 
 
Validation: The process of determining the degree to which a model or a simulation is an 
accurate representation of the real world from the perspective of the intended uses of the 
model or the simulation (American Society of Mechanical Engineering Verification 
&Validation Guide  ASME V&V 10-1-2012).  
 
Verification: The process of determining that a computational model accurately represents 
the underlying mathematical model and its solution from the perspective of the intended uses 
of modeling and simulation (American Society of Mechanical Engineering Verification 
&Validation Standard  ASME V&V 20-2009).  See also Code Verification and Calculation 
Verification.  
  9  Contains Nonbinding Recommendations 
 
Subject Matter Appendix I  
Computational Fluid Dynamics  
and Mass Transport 
 
For questions regarding this appendix, contact Matthew Myers, Ph.D. at (301) 796-2525 or at 
rrcm@fda.hhs.gov.   
 
 
Introduction/Scope of the Appendix  
The purpose of this appendix is to provide recommendations on the formatting, organization, 
and content of reports for computational fluid dynamics and mass transport modeling and 
simulation studies in medical device regulatory submissions. 
 
Specific examples provided in this appendix, such as output metrics, are only examples and 
should not be considered as requirements or recommendations for the type of CM&S studies 
and validation to complete. 
 
Outline of the Report 
In the following section, we provide an outline for reporting the details of your 
computational modeling and simulation study. 
 
I.  Executive Report Summary 
We recommend that you provide a concise and complete overview of the report of the 
computational modeling and/or simulation study, which includes the following: 
  Briefly summarize the context of use and scope of the analysis, as well as the 
rationale for choosing the computational modeling approach as opposed to other 
approaches (e.g., experimental). 
  Briefly summarize the type(s) of analysis(es) conducted in the CM&S study (e.g., 
fluid mechanics, diffusion, diffusion/convection). 
  Briefly summarize the model, including geometry, material properties, and 
boundary/initial conditions. 
  If the device has multiple sizes and/or configurations, provide rationale for the 
sizes and configurations of the device system evaluated and not evaluated.  
  State whether the analysis code/software is commercially available, open source, 
and/or user developed. 
  Discuss the simulation results, the quantities of interest, and their implications for 
device safety and effectiveness.  Summarize the validation activities and how they 
are appropriate to support the use of the CM&S study in the context of use. 
  Summarize the limitations. 
  Summarize the conclusion(s). 
  10  Contains Nonbinding Recommendations 
 
  Keywords  please provide up to five keywords or key phrases that describe the 
modeling modality, the device product code, any relevant materials of the device, 
analysis type and if applicable, location in the body (e.g., computational fluid 
dynamics, NIQ, stainless steel, drug transport, coronary artery).  For example, the 
following are sample keywords relevant to this subject matter:  
  biofluid mechanics, drug delivery, blood flow, transport, finite volume 
method, finite element method, pump. 
 
II. Background/Introduction 
We recommend that you state the context of use of the analysis, because this will 
determine the relevant details necessary for review.  Provide a brief description of the 
device, along with its intended use environment and deployment/implantation procedure. 
The details provided in this section should correspond to the objectives of the analysis, 
which should be outlined in the context of use statement.  
 
III.  Code Verification 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed on the software used 
for the CM&S study.  Software tools include off-the-shelf, modified-off-the-shelf, or 
user-developed.  Code verification is important, regardless of the software type. 
 
A.  Details 
You should briefly describe the code verification activities and provide the following: 
  comparisons to simplified systems which have an analytical solution;  
  sensitivity analyses of the discretization scheme and solver parameters 
performed using the actual system (i.e., timestep, grid size (grid refinement)) 
and convergence criteria (e.g., 1E-6 vs 1E-7)); 
  a description of how the simulation numerically converged via residual 
reductions and/or monitoring of physically relevant fluid flow quantity at a 
probe point or surface location; and 
  a method to demonstrate that the basic conservation laws were obeyed. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationale for differences 
between the code used for verification and the code used for the context of use.  
Moreover, provide rationale to support the selection of the numerical settings, either 
default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in System Discretization and Numerical 
Implementation, sections VIII and IX, respectively. 
 
IV.  System Geometry (System Configuration) 
  11  Contains Nonbinding Recommendations 
 
We recommend that you provide information regarding the system configuration (e.g., 
the geometry of the device, the computational domain, the structure of a physiological 
control system, the in vitro test that is modeled). 
 
A.  Details 
You should describe the components of the system (e.g., device, vessel, organ, organ 
system) to be evaluated.  Provide all relevant dimensions of the device and geometry.  
Include diagrams, schematics, and photos, as needed. 
 
You should describe methods/software (e.g., image reconstruction, CAD) used to 
generate the geometry in order to demonstrate that the configuration was captured 
appropriately for the intended analysis.  In particular, describe any scaling or 
similarities (e.g., geometric and dynamic similarity). 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to generate the system configuration as compared to the actual device and 
environment.   
 
For example, if the entire device system was not modeled or if simplifications were 
made to the geometry, you should provide rationale for the system geometry that was 
analyzed (e.g., the use of symmetry, only a portion of device, or representative inlet 
and outlet geometries), including the following: 
 
  Describe any differences between the model and the actual configuration. 
  Discuss how manufacturing tolerance dimensions might influence the results 
compared to nominal dimensions. 
  Describe how the inlet and outlet geometries were selected and how these 
might affect the flow regime. 
  If the device has unique geometric features (e.g. surface topography) that 
might affect the analysis, then describe how those were or were not accounted 
for in the model. 
  Include relevant information on limitations and assumptions (e.g., scaling) 
image resolution, smoothing, image segmentation errors, as related to the 
geometry. 
 
V. Governing Equations/Constitutive Laws 
We recommend that you provide information regarding the governing equations and/or 
constitutive laws used to perform the computational analysis. 
 
A.  Details 
You should provide the governing equations/constitutive laws for the system, 
including the following: 
  the equations defining the model (e.g., Navier-Stokes equations for fluid flow, 
Ficks equations for diffusion, Darcys equations for porous flow); 
  12  Contains Nonbinding Recommendations 
 
  the constitutive relationships used in the simulation (e.g., the relation between 
shear stress and velocity gradient for fluid flow, the relation between diffusive 
flux and concentration gradient for diffusion, the relation between discharge 
flux and pressure gradient for porous flow); 
  the turbulence modeling used, if any, including any specialized wall functions 
used; and 
  any other specialized mathematical modeling employed (e.g., blood damage 
models). 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the governing equations and constitutive laws chosen to represent the system, 
including the following: 
  the simplifications of the basic mathematical equations based on assumptions 
and rationale (purpose) of the simulation being undertaken; 
  the assumptions and rationale involved in simplifying the governing equations 
(e.g., use of steady rather than unsteady flow); 
  the information that confirms that the constitutive model(s) captures the actual 
behavior being modeled; and 
  the use of any turbulence model or wall functions, as well as other equations 
used to capture additional phenomena (e.g., blood damage models). 
 
VI.  System Properties 
We recommend that you provide information regarding the biological, chemical, and 
physical properties of the system. 
 
A.  Details 
You should provide, preferably in a tabular form, all physical properties, coefficients, 
and descriptive equations used in the simulation and post processing, such as: 
  fluid viscosity and density 
  gas solubility and diffusivity 
  diffusion and reaction coefficients of constituents 
  permeability and porosity 
  temperature dependence of properties if the simulation is not isothermal 
You should provide a report of any testing conducted to generate the system 
properties, if available. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the system properties.  Identify the sources of the physical 
properties and coefficients adopted (e.g., literature, in vivo, ex vivo, in vitro testing).  
If literature data are cited, discuss their applicability to the specific conditions.  If 
testing is conducted to determine the parameters, then provide appropriate details 
regarding the test.  If applicable, discuss any relevant aspects related to the tissue 
physiology used (e.g., young versus mature, healthy versus diseased). 
 
  13  Contains Nonbinding Recommendations 
 
If there are uncertainties associated with the data (e.g., due to inaccuracies, 
simplifications, or variations), describe the sensitivity analysis performed, if 
appropriate, to address the effect of the uncertainties on the simulation results. 
 
VII.  Boundary and Initial Conditions (System Conditions) 
We recommend that you provide information regarding the conditions that were imposed 
on the system.  These might include, but are not limited to, the boundary and loading 
conditions, initial conditions, and other constraints that control the system. 
 
A.  Details 
You should describe the boundary conditions (e.g., inlet and outlet, walls) of the 
model.  You should describe any global boundary conditions used to represent the 
simulation in global terms (e.g., pressure drop, mass flow rates, revolutions per 
minute). 
 
If the model was time dependent, provide the following: 
  the initial conditions; 
  if applicable, the transient boundary conditions (e.g., function, table); 
  if the model was pulsatile, the number of initial cycles modeled to damp out 
initial transient effects, if any; 
  any unsteady model(s) employed as an adjunct to a steady model using a 
rotating or moving frame of reference (e.g., for blood pump); and 
  a description of how the natural development and physical character of the 
flow was unaffected by the boundaries of the simulation; 
 
You should provide any relevant nondimensional numbers, such as: 
  Reynolds number 
  Strouhal or Womersley number (pulsatile flows) 
  Peclet or Sherwood number (diffusion/convection) 
  Dean number (curved flow) 
 
If symmetry was used to reduce the size of the model, then you should describe the 
symmetry boundary conditions.  
 
If a turbulence model was used, then you should provide the turbulence boundary 
conditions. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the conditions applied on the system.  Provide appropriate 
documentation the system conditions (e.g., literature, test reports, clinical data, 
medical imaging data). 
 
In particular, you should describe any differences or simplifications between the 
simulation environment and the actual environment, such as, 
  choice of initial and boundary conditions used; 
  14  Contains Nonbinding Recommendations 
 
  operating conditions of the simulation, especially if the simulation did not 
cover the expected range of use of the device; and 
  other simplifications (e.g., use of symmetry, use of rotating frame of reference 
instead of unsteady simulation for centrifugal pump). 
 
VIII. System Discretization 
We recommend that you provide information regarding the discretization and refinement 
techniques utilized during the numerical solution as outlined below. 
 
A.  Details 
You should describe the following regarding the spatial and temporal discretization: 
  the software used for generating the mesh; 
  the mesh in all regions of the computational domain (e.g., device, fluid, 
surrounding tissue); 
  the quality of the mesh (e.g., element/cell types, sizes, shapes, quality metrics 
(i.e., aspect ratios)); 
  the local mesh refinement in areas of interest (e.g., areas of high shear stress, 
recirculation zones, critical concentrations, interactions between the device 
and the body), and provide representative images of the mesh in these areas; 
  any special elements/cells used if a turbulence model (or any other numerical 
method requiring special elements/cells) was used; and  
  for unsteady models, describe how time steps were determined and were 
deemed appropriate for the analysis (e.g., time step refinement study). 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the following regarding the mesh 
refinement study that supports the mesh: 
  any adaptive meshing or automatic mesh refinement used; 
  the methods of the mesh refinement study, and provide representative images 
of the meshes used in the refinement study; 
  the mesh sensitivity analysis performed to justify the production mesh used 
for the subsequent simulations, that is, to demonstrate that the mesh density 
did not affect the numerical results; 
  the numerical metrics (e.g., shear rates, concentration gradients) chosen to 
establish the mesh density; and  
  the algorithm for assigning the mesh density or distribution. 
 
IX.  Numerical Implementation 
We recommend that you provide information regarding the numerical implementation 
used to solve the governing equations. 
 
A.  Details 
You should describe the discretization of the equations, including: 
  numerical method used (e.g., finite element, finite volume, finite difference); 
  temporal discretization, if any (e.g., explicit, implicit, semi-implicit); 
  15  Contains Nonbinding Recommendations 
 
  spatial discretization (i.e., interpolation of field variables between grid points); 
and 
  method for interpolating from face to nodes or vice versa (e.g., upwind, power 
law).  
 
You should describe the solution methods and provide the following: 
  solver method (e.g., Newton, multigrid); 
  solver parameters (e.g., linear solver and tolerance, preconditioners, analytic 
or numerical Jacobian); 
  type of software (e.g., commercial, open-source, user-developed) and name, if 
applicable; 
  details regarding code verification of the user-supplied subroutines/code; and 
  convergence criteria (e.g., error method, error threshold, sampling locations 
and variables used). 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the solver and associated parameters.  For example, provide 
rationale for the discretization/solver choices made (i.e., benefits over other choices) 
and discuss the ramifications of the particular choice (i.e., discretization errors). 
 
X. Validation 
We recommend that you provide information regarding the method(s) employed to 
validate the computational model [1].  We recommend the following format for 
presenting that information. 
 
A.  General Description   
  You should describe, if any, the experimental or analytical comparator that 
was used for model validation study (e.g., velocity, wall shear stress 
calculations, hydrodynamic pressure loss).  If a comparator was used, describe 
if the comparison was made in a quantitative (preferred) or qualitative 
manner. 
   You should describe experimental uncertainty estimates if an experimental 
comparison is performed. 
B.  Methods 
  You should describe the validation test conditions and geometry.  
  You should describe the region of interest where validation(s) are performed. 
  You should provide diagrams and data to support the assessment of the model.   
  You should describe instrumentation and calibration. 
  If a biological process was modeled (e.g., hemolysis, platelet damage, binding 
of drug in vessel tissue), then you should describe how the biological 
calculations were verified and validated. 
C.  Assumptions and Rationale 
  You should describe any simplifications for experimental comparator (e.g., 
use of surrogates when biological information is lacking). 
  16  Contains Nonbinding Recommendations 
 
You should provide a rationale to support any differences between the 
operating and boundary conditions of the comparator experiments and 
simulations. 
  You should describe any sensitivity analysis performed to determine how the 
solution varied as a function of parameters that are not well known (e.g., 
parameters contained in turbulence models, boundary conditions, fluid 
properties). 
  You should provide a rationale for any geometric and dynamic scaling 
assumptions. 
D.  Validation Study Results 
  You should provide qualitative comparisons between the QOI from the 
computational model and experimental results.  For example, images that 
directly compare model and experimental results (e.g., velocity or shear 
stress) can provide an overall qualitative assessment of how well the model 
can capture relevant behavior. 
  You should provide quantitative comparisons for critical areas of relevance to 
the goals of the study [2, 3]. 
E.  Discussion 
  You should discuss the degree of agreement between the computational and 
experimental results. 
  You should discuss the relevance of your validation experiment to expected 
clinical loading conditions, implications of model and experimental 
assumptions on the results, limitations on the agreement between the 
validation model and experiment, and the extent of predictability to your 
device or device-tissue model. 
  If predictions of behavior are given in areas that are not accessible by 
experiment, you should provide a measure of confidence, as well as the risk 
associated and how it influenced your decision. 
 
XI.  Results 
We recommend that you present the quantitative results from the computational modeling 
study.  You should provide the results with sufficient level of details, including labels and 
legends.  The results may be presented in more than one format (e.g., table, graph, plot).   
 
Specifically, we recommend that you present the results in regions of interest graphically 
and quantitatively.  Additionally, please consider providing the following, as applicable: 
  a statement of biological and other formulations (e.g., hemolysis); 
  a description of the results in relation to the goals of the study; 
  a method to demonstrate that the basic conservation laws were obeyed; 
  if limited studies were performed, a statement that the worst-case was 
modeled and a description of that worst-case; 
  for biological extrapolations, a description of relevant variables (e.g., shear 
rates, exposure times, recirculation zones, drug concentrations); 
  a description of any adverse effects of device flow on tissues or organs; and 
  a description of acceptable performance factors based on the results. 
  17  Contains Nonbinding Recommendations 
 
 
XII.  Limitations 
We recommend that you provide details regarding how the assumptions/simplifications 
described in the previous sections might affect the output of the computational model and 
simulation, the interpretation of the results, and the relevance to the purpose of the study.   
 
Because assumptions and simplifications are made in the generation of the model device, 
in the performance of the simulation, and in the interpretation of the analysis, it is 
important to describe the limitations of the use of the computational model and the 
interpretation of the results.  Therefore, we recommend that you discuss how the 
assumptions/simplifications might affect the output of the model and simulation and the 
interpretation of its relevance to device performance and safety. 
 
For example, it is important to know whether the simulation of blood flow through a 
small gap in a blood pump was based on the nominal dimensions or whether it includes 
the limits of the manufactured component tolerances.  If you believe that your results are 
significantly dependent on the assumptions and/or simplifications in your model, you 
should consider performing sensitivity analyses on the computational model parameters 
associated with the assumptions and simplifications. 
 
XIII. Discussion/Conclusion 
We recommend that you summarize the CM&S study with respect to the context of use 
and how it relates to the regulatory submission (e.g., selecting the device size that is 
expected to perform the worst under the simulated use conditions, establishing the 
loading conditions for bench testing).  Discuss how the results compare with 
experimental results, literature results and/or prior product performances, if these results 
exist.  Discuss the assumptions and simplifications that were made to the model and how 
they are expected to affect the results and interpretation of the results.  Discuss the 
strength of your conclusions in terms of the limitations of the model that you have 
identified.  Discuss how your results convey acceptable performance of the product in 
vivo, if applicable. 
XVI. References 
Please provide a list of the appropriate references used to support the CM&S study. 
 
 
Bibliography 
[1] ASME V&V20-2009, Standard for Verification and Validation in Computational Fluid 
Dynamics and Heat Transfer 
 
[2] Oberkampf, W.L., Trucano, T.G., and Hirsch, C., 2004 Verification, validation, and 
predictive capability in computational engineering and physics, Applied Mechanics 
Reviews, 57, pp. 345384. 
 
[3] Oberkampf W.L. and Barone M.F., 2006 Measures of agreement between computation 
and experiment: Validation metrics, Journal of Computational Physics, 217, pp. 5-36. 
  18  Contains Nonbinding Recommendations 
 
Subject Matter Appendix II  
Computational Solid Mechanics 
 
For questions regarding this appendix, contact Jason Weaver, Ph.D. at (301)-796-2504 or at 
rrcm@fda.hhs.gov. 
 
Introduction/Scope of the Appendix  
The purpose of this appendix is to provide recommendations on the formatting, organization, 
and content of reports for computational solid mechanics modeling studies in medical device 
regulatory submissions. 
 
Specific examples provided in this appendix, such as output metrics, are only examples and 
should not be considered as requirements or recommendations for the type of CM&S studies 
and validation to complete. 
 
The scope of this appendix is limited to finite element analysis (FEA).  FDA acknowledges 
that there are other types of computational modeling modalities that can be used to evaluate 
the mechanics and kinematics of medical devices.  Additionally, FDA acknowledges the 
issues and considerations for non-finite element analyses are similar to those raised for FEA 
and aspects of this guidance might be applicable.  However, there might be aspects of the 
non-FEA approaches that are distinct from FEA and could present other issues which are not 
addressed in this appendix but should be included in the reporting of those studies. 
 
Outline of the Report 
In the following section, we provide an outline for reporting the details of your 
computational modeling and simulation study. 
 
I.  Executive Report Summary 
We recommend that you provide a concise, high-level overview of the entire report 
including the following: 
  You should briefly summarize the context of use of the CM&S study with respect 
to the regulatory submission, scope and quantities of interest of the analysis. 
  You should briefly summarize the model, including geometry, material properties, 
and boundary conditions. 
  You should state the code/software used.  
  You should briefly summarize the validation method and results. 
  You should discuss the simulation results and how they relate to the regulatory 
purpose of the CM&S study.   
  You should briefly summarize the conclusion(s). 
  Keywords - please provide up to five keywords or key phrases that describe the 
modeling modality, the device product code, any relevant materials of the device, 
  19  Contains Nonbinding Recommendations 
 
analysis type, and location in the body for intended use (e.g., finite element 
analysis, MIH, nitinol, fatigue safety factors, aorta).   
 
II. Background/Introduction 
You should describe the context of use of the CM&S study, as this will dictate the 
relevant details necessary for review.  We recommend that you give a brief device 
description along with its intended use environment, specifically noting all causes of 
loading/deformation on/from the device. 
 
III.  Code Verification 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed on the software used 
for the CM&S study.  Software tools include off-the-shelf, modified-off-the-shelf, or 
user-developed.  Code verification is important, regardless of the software type.   
 
A.  Details 
You should briefly describe the code verification activities.  You may reference 
available documentation and verification results from the software developer.   
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationale for differences 
between the code used for verification and the code used for the context of use.  
Moreover, provide rationale to support the selection of the numerical settings, either 
default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in System Discretization and Numerical 
Implementation, sections VIII and IX, respectively. 
 
IV.  System Geometry (System Configuration) 
We recommend that you provide information regarding the geometry of the device, the 
computational domain, or the in vitro test being modeled. 
 
A.  Details 
We recommend that you provide details regarding the device and/or tissue geometry 
that was modeled and the method used to create the computational representation of 
your geometry.  This section might include CAD drawings or reconstructed digital 
images. 
 
B.  Assumptions, simplifications, and rationale 
If you did not model the entire device, you should describe and provide rationale for 
the portion of the device that was modeled (e.g., utilized symmetry).  If the device is 
available in different sizes or configurations, describe which sizes or configurations 
were modeled and provide rationale to support the analysis of those sizes.  If the 
device and/or tissue has unique geometric features that might affect the analysis (e.g., 
  20  Contains Nonbinding Recommendations 
 
surface topography) then you should describe how those were or were not accounted 
for in the model.  Finally, regarding the method of construction, please include 
relevant information on limitations and assumptions (e.g., image resolution and 
smoothing) as related to the geometry. 
 
V. Constitutive Laws 
We recommend that you provide details for all of the constitutive relationships used to 
describe the mechanical behavior of the device material(s) and, if appropriate, the 
surrounding anatomy.  
 
A.  Details 
You should describe the stress-strain relationship, including any material 
nonlinearities that were included in the model (e.g., linear, hyperelastic, elastic-
plastic, viscoelastic, poroelastic) of the device and/or tissue material(s).  Specify the 
degree of anisotropy (e.g., isotropic, orthotropic) of the material(s).  If appropriate, 
the constitutive relationships may be presented graphically and/or with equations. The 
numerical inputs for the parameters within the constitutive model should be provided 
in Section VI  Material Properties.    
 
B.  Assumptions, simplifications, and rationale 
You should provide rationale for the constitutive relationship chosen to represent the 
material behavior and discuss why the assumptions are appropriate.  For example, if 
you employed linear elastic constitutive laws then, in general, only small-strain 
deformations should be presented. A rationale should be presented if post-yield 
stresses are observed and plasticity is omitted.   
 
VI.  Material Properties (System Properties) 
We recommend that you provide details regarding all materials used in the CM&S study.  
 
A.  Details 
For all materials modeled, you should report the numerical inputs necessary to fully 
characterize the mechanical behavior.  Some examples of important material inputs 
include: 
  constitutive law coefficients 
  elastic modulus 
  ultimate tensile strength 
  fatigue life/endurance limit 
  plateau stresses and elastic strain limits for shape memory or superelastic 
materials (e.g., Nitinol) 
  strain at break 
  viscoelastic properties 
 
B.  Assumptions, simplifications, and rationale 
You should provide rationale for the sources of material inputs, and state any 
assumptions or limitations that were inherent from the sources you reference or the 
testing that you conducted.  
  21  Contains Nonbinding Recommendations 
 
 
If the inputs were obtained from testing, you should provide a description of the 
testing (e.g., uniaxial tension, 3-point bend, in vivo imaging, implanted sensor) 
including sample conditions (e.g., geometry, processing, heat treatment), protocol 
(e.g., loading rate, frequency, mean strain), environment (e.g., temperature, humidity, 
solution), and, if necessary, the method(s) used to determine the material properties 
from the test data.   
 
Additionally, for the material properties of the device, state whether testing was 
conducted on finished devices; if it was not, provide rationale. Similarly, for the 
material properties of the surrounding biological materials, you should state whether 
the materials tested capture the important aspects of the target patient population 
(e.g., healthy versus diseased, young versus mature); if they do not, provide rationale. 
 
VII.  Boundary & Initial Conditions (System Conditions) 
We recommend that you provide information regarding the boundary and loading 
conditions, initial conditions, and other constraints that control the system. 
   
A.  Details 
You should describe the conditions of the computational model.  Examples include, 
but are not limited to, stresses and strains imposed from manufacturing (residual), 
implantation, and physiologic/pathologic loading.  If applicable, we recommend the 
following for each analysis step: 
  You should provide an overall schematic or diagram that clearly depicts the 
location and direction of the imposed boundary conditions. 
  You should specify the three-dimensional magnitude and direction of the 
applied displacements, forces, pressures, or moments. 
  You should describe any constraints used in the model, including the 
location(s) and the degrees of freedom for each fixed or free constraint. 
  You should explain how the components are expected to interact.  We 
recommend that you provide a description of the interaction (i.e., contact) 
between the device and other components within the model, as well as those 
components that self-contact (e.g., stent struts under axial compression).   
 
B.  Assumptions, simplifications, and rationale 
You should provide rationale that describes how each imposed condition is 
appropriate for the relevant aspect of the context of use.  You should describe the 
sources and/or methods used to obtain the loading mode and magnitude (e.g., 
literature data, standards, imaging, other analytic methods).  
 
VIII. Mesh (System Discretization) 
A.  Details 
We recommend that you provide the following details regarding the mesh. 
  Specify the type and number of elements use for the mesh.  Include any mesh 
refinement or adaptive meshing in transition regions or regions of complex 
geometry.  We recommend that you provide figures depicting the mesh at 
  22  Contains Nonbinding Recommendations 
 
relevant scales, especially in transition regions or regions of complex 
geometry and regions of high stress or strain. 
  You should provide details of the mesh refinement or convergence analysis 
used to demonstrate that the QOI are independent of element size. 
  Report the number of mesh densities used to demonstrate convergence 
stability of the QOI with respect to element size. 
  Report the metric(s) of the mesh refinement analysis in graphical or 
tabular format and clearly identify the mesh chosen for the analysis 
against the criterion. 
 
B.  Assumptions, simplifications, and rationale 
Regarding the mesh refinement study, you should provide rationale for the type of 
element selected and for the numerical criterion chosen (e.g., principal stress, 
displacement) to evaluate the mesh density. 
 
IX.  Solver (Numerical Implementation) 
We recommend that you provide the following details regarding the software used in the 
numerical implementation of the analysis. 
  You should provide the name (including version number) of the software used 
to solve the model(s). 
  If custom subroutines are used, you should provide information on code 
verification (e.g., test case) and details of the implementation. 
  You should describe the type of analysis completed (e.g., static structural, 
vibration, buckling). 
  You should provide details on the solver routine used including, at a 
minimum, the following parameters: 
  state whether the solver is implicit or explicit.  If the latter, include and 
provide rationale for the analysis time frame, time step size, material(s) 
density and any mass scaling used 
  indicate if the solver accounted for nonlinear geometric changes. 
  state the convergence criteria and iteration method. 
 
X. Validation 
We recommend that you provide information regarding the methods employed to validate 
the computational model [1].  The results of a validation study support the choice of the 
input parameters to the computational model. 
 
You should describe how the validation study supports the context of use of the CM&S 
study. Specify the QOI(s) from the validation experiment and their relationship to 
computational model of the validation experiment. We suggest the following format for 
reporting the validation study. 
 
A.  Details 
i.  Comparator 
You should describe the comparator (e.g., physical test, in vivo study, 
literature) used for validation.  Include the following: 
  23  Contains Nonbinding Recommendations 
 
a.  mode of loading;  
b.  boundary and loading conditions including the loading and 
unloading path, as applicable;  
c.  environmental parameters within the experiment (e.g., temperature, 
humidity); and 
d.  manufacturing processes or pre-conditioning applied to the device 
prior to conducting the experiment, if applicable.  For example, if the 
model is designed to predict safety of a nitinol cardiovascular stent, 
specify if the device was loaded onto a delivery systems and tracked 
through a representative anatomical model prior to experimental 
measurements. 
You should describe the apparatus used to capture data during the 
experiment, the level of measurement accuracy and uncertainty.  For 
example, if the validation study compares uniaxial force-extension data 
between the computational model and an experiment, present the capacity 
and accuracy of the load cell used to measure force data. 
 
You should describe the locations on the device or tissue where the 
experimental measurements were acquired.  For example, if your study is 
designed to analyze strain in a hip stem, describe where strain gauges were 
placed to acquire the data. 
 
ii.  Computational model of the Validation Setting 
You should describe the boundary and loading conditions used for the 
validation model and describe how they relate to the experimental 
comparator.  For example, the rate and magnitude of applied torsion to a 
pedicle screw system in the computational model should match that applied 
to the device mounted on a mechanical testing system. 
 
You should describe the validation model QOI.  If applicable, describe any 
post-processing calculations.   
 
Include images that directly compare the validation model and experimental QOIs 
(e.g., deformation or stress contours) to demonstrate that the computational model is 
able to capture relevant behavior. 
 
You should present a quantitative comparison of the QOI from the computational 
model and experimental at relevant steps in the analysis.  For example, if the 
validation study compared the radial force generated by the stent during the step of 
being loaded on to the delivery system, it might be more insightful to compare this 
force at several diameters between nominal and loaded diameter rather than at the 
final loaded diameter. 
 
B.  Assumptions, simplifications and rationale 
You should discuss the relevance of the validation experiment to expected loading 
conditions as described in the context of use, implications of model and experimental 
  24  Contains Nonbinding Recommendations 
 
assumptions on the results, limitations on the agreement between the validation model 
and experiment, and the extent of predictive capability of the general model. 
 
If the validation model parameters are different from those used in the computational 
model for the context of use, you should provide rationale for the differences. 
 
You should list and discuss the assumptions for the validation model (i.e., neglecting 
viscous behavior if you are comparing instantaneous force values). 
 
You should list and discuss the simplifications for the validation model.  These 
simplifications might include geometric, such as axisymmetry, or may consist of 
explanations for testing device sub-components (e.g., validating the wear scar on 
articulating components in a total disc replacement device may not necessitate 
modeling of the device-bone interface). 
 
You should provide a discussion of the extent to which the validation model captures 
the observed validation experimental behavior and its limitations. 
 
XI.  Results 
We recommend that you provide the following for each analysis step: 
  rationale for the QOI(s) reported (e.g., component, principal, von Mises); 
  specific values for the QOI(s), along with a detailed description and/or plot 
demonstrating the loading history of the critical regions; and  
  a statement about whether the QOI(s) are reported from integration points or 
nodes. If applicable, provide a contact map which depicts the interactions 
between contact surfaces and discuss the results. 
 
We recommend that you provide the following for monotonic loading: 
  a statement and rationale for the failure criterion (e.g., Maximum Shear Stress, 
Mohr-Coulomb), along with a graphic or equation that clearly demonstrates 
how factors of safety were calculated; 
  the QOI values and graphically display the location(s) of the critical stresses, 
strains, forces, or displacements; and  
  the safety factors.  For reporting the safety factors: 
  provide a table that specifies the safety factors for each case (i.e., 
device size, loading mode(s), and analysis step); and 
  show locations of minimum safety factor(s) on the device graphically.  
 
We recommend that you provide the following for fatigue evaluation: 
  a description of the method used to calculate mean and alternating 
stresses/strains (e.g., scalar, tensor); 
  a statement on whether cyclic loading results in rotations of the principal 
directions; 
  a description of the fatigue criterion (e.g., Goodman, Soderberg), along with a 
graphic or equation that clearly demonstrates how fatigue factors of safety are 
calculated; and 
  25  Contains Nonbinding Recommendations 
 
  the fatigue safety factors.  For reporting fatigue safety factors: 
  provide a table that specifies the critical mean and alternating 
stresses/strains and the resulting safety factors for each device size, 
loading mode(s), and analysis step; 
  Show locations of minimum safety factor(s) on the device graphically; 
and 
  Plot mean and/or alternating stress/strains on a point cloud graph and 
include fatigue criterion if applicable. 
 
For other analysis types (e.g., vibration or buckling), we recommend that you provide all 
relevant results including critical stresses or strains and their locations on the device as 
well as describe any post-processing techniques used to evaluate safety and/or 
performance.  
 
If multiple loading modes were modeled separately, we recommend that you provide 
rationale and discuss the implications of superposition of stress or strain states for each 
loading mode (e.g., location, direction, and phase of the critical stresses or strains). 
 
XII.  Limitations 
We recommend that you discuss the major limitations of the computational model 
identified in Sections II-XI above. Discuss any inconsistencies between the results and 
the assumptions and simplifications. 
 
If the conclusions of the analysis are significantly dependent on the assumptions and/or 
simplifications of the computational model, we recommend that you report on a 
sensitivity analysis of the parameters associated with those assumptions and/or 
simplifications. 
 
XIII. Discussion/Conclusion 
You should state the overall conclusions of the CM&S study and whether the objective(s) 
outlined in the context of use have been met. 
 
We recommend that you discuss the results with respect to the context of use.  For 
example, discuss how critical stresses or strains obtained from the computational model 
relate to failure locations observed in bench testing and/or the potential consequences of 
failure at locations of minimum safety factor. 
 
XIV. References 
Please provide a list of the appropriate references used to support the CM&S study. 
 
 
Bibliography 
 
[1] ASME V&V10-2006, Guide for Verification and Validation in Computational Solid 
Mechanics 
  26  Contains Nonbinding Recommendations 
 
Subject Matter Appendix III  
Computational Electromagnetics and 
Optics 
 
For questions regarding this appendix, contact Leonardo Angelone, Ph.D., at (301) 796-2595 
for computational electromagnetics or Quanzeng Wang, Ph.D. at (301) 796-2612 for 
computational optics, or both at rrcm@fda.hhs.gov. 
  
 
Introduction/Scope of the Appendix  
The purpose of this appendix is to provide recommendations to industry on the formatting, 
organization, and content of the reports for computational electromagnetic (EM) and optical 
modeling and simulation studies used in medical device regulatory submissions to assess (1) 
safety (e.g., energy deposition, temperature rise, voltages, and thermal damage induced in the 
human body by medical devices using EM/optical energy) and (2) effectiveness (e.g., how 
internal or external EM/optical sources and physical properties of devices and tissue affect 
the effectiveness) of medical devices. 
 
Examples of such studies include safety and effectiveness evaluation of the following 
medical devices: electrophysiology monitoring devices, magnetic resonance imaging (MRI) 
systems, magnetic resonance (MR) Conditional passive or active implanted devices (e.g., 
orthopedic devices, stents, pacemakers, or neurostimulators), devices for radiofrequency 
ablation, optical diagnostic devices (e.g., optical coherence tomography devices, fluorescence 
spectroscopy devices), and optical therapeutic devices (e.g., laser surgery devices). 
 
Outline of the Report 
In the following section, we provide an outline for reporting the details of your 
computational modeling and simulation study. 
 
I.  Executive Report Summary 
We recommend that you provide a concise and complete overview of the report of the 
CM&S study that includes the following: 
 Context of use of the CM&S study, including any relevance/correlation to other 
studies (e.g., bench, clinical) for validation purposes 
 Type of the analysis (e.g., photobiological safety, MRI safety, spectroscopy 
device penetration depth) 
 Scope of the analysis (e.g., for a device that has multiple sizes or configurations, 
discuss what sizes or configurations were modeled, and how the computational 
model and simulation relates to the intended patient population) 
 Conclusions with respect to the context of use and how they relate to the 
regulatory submission. 
  27  Contains Nonbinding Recommendations 
 
 Keywords - please provide up to five keywords or key phrases that describe the 
modeling modality, the device product code, any relevant materials of the device 
analysis type, and if applicable, location in the body for intended use (e.g., 
radiofrequency dosimetry, OQG, cobalt chromium, magnetic resonance safety, 
hip).  The following are sample keywords relevant to this subject matter that can 
be used:  
  electrophysiology, radiofrequency, optical imaging, laser therapy, 
magnetic resonance imaging, active implants, Monte Carlo simulation, 
finite difference time domain 
 
II. Background/Introduction 
We recommend that you provide a brief description of the device system and intended 
use environment.  Describe the purpose of the analysis, as this will dictate the relevant 
details necessary for review.  Introduce the background and principles of the model and 
simulation, and provide rationale for why it is appropriate to apply the model to the 
device system. 
 
III.  Code Verification 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed on the software used 
for the CM&S study.  Software tools include off-the-shelf, modified-off-the-shelf, or 
user-developed.  Code verification is important, regardless of the software type. 
 
A.  Details 
You should briefly describe the code verification activities.  You may reference 
available documentation and verification results from the software developer.   
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationalize the differences 
between the code used for verification and the code used for the context of use.  
Moreover, You should provide rationale to support the selection of the numerical 
settings, either default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in Section VIII System Discretization and Section IX 
Numerical Implementation, respectively 
 
IV.  System Geometry (System Configuration) 
We recommend that you provide information regarding the device and tissue geometry 
that was modeled (e.g., the geometry of the device, the computational domain, the in vivo 
or in vitro test that is modeled). 
 
A.  Details 
  28  Contains Nonbinding Recommendations 
 
You should describe the components of the system (e.g., device, in vivo or in vitro 
environment) to be evaluated.  Include images, diagrams (with appropriate scaling bar 
or dimensions), and a brief description of the model. 
 
You should describe the methods (e.g., image reconstruction, computer aided design) 
used to generate the system configuration and discuss how the configuration was 
captured appropriately for the intended analysis. If image reconstruction was used to 
generate geometry, describe the imaging modality. 
 
You should describe the software used to generate the system configuration (e.g., 
computer aided design software, image segmentation software) and describe the 
methods used to verify the software.   
 
You should describe the geometrical characteristics necessary for a comprehensive 
description of the methodology.   
 
Because there are different applications of computational EM and optical modeling, 
we have provided the following examples. 
 
1.  For EM simulations in MRI environment, please describe:  
  the geometrical and physical characteristics of the radiofrequency coils (e.g., 
geometrical dimensions, number of rungs, number of sources, lumped 
elements used, tuning/matching elements, if any) and their clinical 
significance; 
  the physical characteristics of the phantom/anatomical models (e.g., size, 
dimensions, posture, body mass index, and number of anatomical structures) 
used in the simulations and their clinical significance with respect to the 
indications of use;  
  the landmark positions of the phantom/anatomical models with respect to 
the coil and their clinical significance; 
  the geometrical and physical characteristics of the device (e.g., material 
properties, path of the implant inside anatomical model) and their clinical 
significance. 
2.  For optical simulations, please describe: 
  the geometrical and physical characteristics of the light source, such as the 
distance and angle between the light source and tissue surface, the beam 
size, and beam intensity profile (e.g., Gaussian beam). Describe whether and 
how the illumination takes into consideration of specific optical 
components, such as fiber optic probes, lenses or mirrors;   
  the geometrical and physical characteristics of the detector, such as the 
detected wavelength range, the aperture used to select optical signal, spatial 
and angular restrictions on detected light, as well as the justification for 
these restrictions (or lack of restrictions);  
  the geometrical characteristics of the simulated tissue (e.g., size of simulated 
region, mesh density for simulation, surface morphology, and tissue 
structures such as layers, vessels, tumors or cysts) and the rationale for 
  29  Contains Nonbinding Recommendations 
 
implementation of this geometry (e.g., tissue types represented, layers or 
structures present, and simulated conditions such as normal, metaplastic or 
neoplastic tissue). 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to generate the system configuration (e.g., excluding static field magnet or 
gradient field coil in MRI RF models, assuming the tissue has a flat interface between 
two layers in the model) as compared to the actual device, tissue object, and 
environment.  If appropriate, provide clinical rationale for the in vivo/in vitro models 
(e.g., size, disease state, mathematical convenience versus clinical relevance). 
 
V. Governing Equations/Constitutive Laws 
We recommend that you provide information regarding the governing equations and/or 
constitutive laws used to perform the computational analysis. 
 
A.  Details 
You should provide the governing equations/constitutive laws for the system. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the governing equations (e.g., Laplace, Maxwell, Radiative Transport) or constitutive 
laws chosen to represent the system.  If a thermal analysis is included, please report 
the results as recommended in Appendix V Computational Heat Transfer. 
 
VI.  System Properties 
We recommend that you provide information regarding the relevant system properties 
(e.g., biological, chemical, physiological, physical). 
 
A.  Details 
You should provide the parameters used in the analysis that define the material and/or 
process characteristics, and their variability, if applicable.  These might include 
properties of biological materials (e.g., cells, tissues, organs), non-biological 
materials (device components, implants, contrast agents), and/or processes (e.g., cell 
signals), such as states (e.g., diseased, healthy), biological properties, chemical 
properties, and physical properties.  Identify the source of biological, chemical, and 
physical properties (e.g., literature, in vivo, in vitro testing). 
 
Specifically please provide the following inputs, when appropriate for your 
simulation. 
1.  For EM simulations,  
provide electrical properties of the device (e.g., conductivity, permittivity), the 
tissue (e.g., conductivity, permittivity, anisotropy), and any relevant, non-
biological materials (e.g., air, water, high-dielectric pads surrounding the body). 
2.  For optical simulations,  
  30  Contains Nonbinding Recommendations 
 
  provide optical properties of the device (e.g., refractive index of probe 
surface, numerical aperture, beam convergence or divergence, focal spot 
size), the tissue or non-tissue object (e.g., absorption coefficient, scattering 
coefficient, refractive index, scattering anisotropy, quantum yield for 
fluorescence), and any relevant, non-biological materials (e.g., contrast 
agents, nanoparticles), along with their variation in space and time (e.g., 
different tissue components, dynamic changes due to temperature or 
hydration); 
  describe any simplifications of the optical properties (e.g., phase function) 
for the tissue and any relevant, non-biological materials (probes, 
nanoparticle or dye-based contrast agents)  and state whether a diffusion 
condition was assumed; 
  provide the key properties of the optical radiation simulated, including the 
spectral distribution of irradiance, total energy and/or power, spatial 
intensity distribution, and angular illumination distributions;  
  state whether or not coherence, polarization and fluorescence were 
considered. 
3.  For simulations that also include thermal analysis,  
  provide the system properties of the object (tissues and non-tissue) used for 
the simulations (e.g., mass density, thermal conductivity, capacitance, blood 
perfusion rate, Arrhenius thermal damage coefficients, electrical 
conductivity and permittivity); 
  provide data (e.g., equation, table or graph) describing any assumed 
temperature dependence;   
  specify any non-linear or coupling between EM/optical and thermal models. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the system properties.  If the properties are derived from literature 
data, please provide a reference to the publications and discuss their applicability to 
the specific study (e.g. ex-vivo vs. in-vivo).  If the properties are derived from bench 
testing, please provide a full and comprehensive report of the test. 
 
You should describe any assumptions made with respect to the variation of the object 
system (tissue or non-tissue) properties with position, direction, time, wavelength, 
light intensity, temperature, and thermal damage.  Please describe any assumptions 
made with respect to the nonlinearity of system properties incorporated in the model 
and whether they may affect the modeling results.  Please specify any spatial 
heterogeneity, including anisotropy, and any time dependence.  Please describe the 
sensitivity of outcome results on key parameters and provide a systematic analysis of 
data uncertainty in relation to system properties. 
 
VII.  System Conditions 
We recommend that you provide information regarding the conditions that were imposed 
on the system.  These might include, but are not limited to, the boundary and loading 
conditions, initial conditions, and other constraints that control the system. 
  31  Contains Nonbinding Recommendations 
 
 
A.  Details 
You should describe the system conditions imposed on the model and their 
variability, if applicable.  If appropriate, provide a graphical representation of the 
conditions, depicting how they are applied to the system. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the conditions applied on the system.  Provide appropriate 
documentation (e.g., literature, test reports, clinical data, medical imaging data) to 
support the system conditions. 
 
Specifically, state whether the boundary conditions of the simulations represent a true 
physical boundary.  You should provide evidence demonstrating that boundary 
conditions do not cause the simulation to generate non-physical results.  Moreover, 
where relevant, you should describe how the physical properties of surrounding 
materials between device and tissue (e.g., air, water) will affect the boundary 
conditions and how the boundary condition will in turn affect the simulation results. 
 
For simulations of optical systems with the purpose of calculating light intensity or 
energy delivered to human tissue, you should provide information on all the 
assumptions made to model each optical element.  For example, light intensity or 
energy attenuated by each optical element due to reflection, absorption, and scattering 
at certain wavelength or incident angle, should be specified to properly obtain light 
intensity and energy delivered to the human tissue. 
 
VIII. System Discretization 
We recommend that you provide information regarding the discretization and refinement 
techniques applied to the system for solving it numerically. 
 
A.  Details 
You should describe the system discretization methods and how they were applied to 
the computational domain.  Describe the methodology (e.g., mesh refinement study) 
used to verify proper numerical discretization.  If applicable, provide a representative 
image of the discretization in the areas of interest of the computational domain.  
Report the criteria used to determine that the discretization was sufficient to resolve 
the physics of interest. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to discretize the computational domain. 
 
IX.  Numerical Implementation 
We recommend that you provide information regarding the numerical implementation 
strategy that yielded the solution to the governing equations. 
 
  32  Contains Nonbinding Recommendations 
 
A.  Details 
You should describe the numerical implementation methodology (e.g., boundary 
element method, finite difference time domain, methods of moments, finite element 
method, and Monte Carlo simulation) and numerical solver employed to yield the 
solution to the governing equation.  Explain the calculation verification process used 
to ensure the governing equations were solved correctly.  State the solver parameters 
(e.g., tolerance, relaxation) and convergence criteria, and describe any stability 
criteria required.  For integral models (e.g., Arrhenius equation), discuss the method 
of numerical integration. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to choose the solver and associated parameters. Specifically, please provide 
rationale  quantitative analysis demonstrating that the parameters selected are 
sufficient to achieve a convergent solution appropriate for the context of use, specify 
the convergence criteria and describe why it was appropriate (e.g., time-steps used for 
finite difference time domain; simulation stopping criteria such as number of photons 
for Monte Carlo simulation). 
 
X. Validation 
We recommend that you provide information regarding the methods employed to validate 
the computational model [1]. 
 
A.  Details 
You should describe the method used to assess the predicative capability of the 
computational model (e.g., in vivo or in vitro comparator) for the context of use.  You 
should provide sufficient details that describe how the measurements were taken from 
the comparator and post-processing of the computational model, and used to assess 
the accuracy of the predicted numerical output.  For example, validation for RF 
simulations in MRI may be conducted with respect to B  field, validation for optical 
1
modeling might be conducted with respect to detected light intensity, and validation 
for optical/thermal or radiofrequency/thermal modeling might be conducted with 
respect to temperature or thermal damage.  Please demonstrate that the error level 
provides sufficient accuracy for the given application. If an analytical closed-form 
equation is used to support the validation, please provide the source of the equation. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the method used to validate the computational model.  Explain the difference between 
the measured and predicted value, and discuss its significance with respect to the 
purpose of the analysis. 
 
XI.  Results 
We recommend that you present the quantitative results from the computational modeling 
study.  You should provide the results with sufficient level of details, including labels and 
  33  Contains Nonbinding Recommendations 
 
legends.  The results may be presented in more than one format (e.g., tables, graphs, 
plots).   
 
XII.  Discussion 
We recommend that you discuss how the results relate to the purpose of the 
computational modeling study and the clinical relevance, if appropriate, and how the 
results compare with the experimental and literature results. 
 
XIII. Limitations 
We recommend that you provide details regarding (1) how the assumptions and 
simplifications described in the previous sections might affect the output of the 
computational model and simulation, (2) the interpretation of the results, and (3) the 
relevance to the purpose of the study.  Describe the outcomes and implications of the 
uncertainty analysis performed on the system properties and conditions.   
 
XIV. Conclusions 
We recommend that you summarize the computational study with respect to the purpose 
of the study and how it relates to the regulatory submission. 
 
XV.  References 
You should provide a list of the appropriate references used to support the CM&S study. 
 
 
Bibliography 
 
[1] IEEE 1597.1-2008 - IEEE Standard for Validation of Computational Electromagnetics 
Computer Modeling and Simulations   
  34  Contains Nonbinding Recommendations 
 
Subject Matter Appendix IV  
Computational Ultrasound 
 
For questions regarding this appendix, contact Joshua Soneson, Ph.D. at (301) 796-2512 or at 
rrcm@fda.hhs.gov.  
 
 
Introduction/Scope of the Appendix  
The purpose of this appendix is to provide recommendations on the formatting, organization, 
and content of reports for studies in computational ultrasound in support of device 
submissions.   
 
Outline of the Report 
In the following section, we provide an outline for reporting the details of your 
computational modeling and simulation study. 
 
I.  Executive Report Summary 
We recommend that you provide a concise, high-level overview of the assumptions and 
rationale for the methodology/modeling approach, and the following: 
  Context of use of the CM&S study including a clear identification of the 
quantity(s) of interest and describe any relevance/correlation to bench testing for 
validation purposes 
  Describe the type(s) of analysis(es) conducted in the computational modeling 
study (e.g., wave propagation, heat transfer, fluid flow, thermal dose) 
  State whether the analysis software is open-source, commercial, or developed in-
house 
  Keywords - please provide up to five keywords or key phrases that describe the 
modeling modality, the device product code, any relevant materials of the device, 
analysis type, and if applicable, location in the body for intended use (e.g., finite 
difference method, KZK, ultrasound, hystotripsy, prostate).  For example, the 
following are sample keywords relevant to this subject matter that can be used: 
  imaging, cavitation, therapeutic ultrasound, histotripsy, acoustic radiation 
force impulse, Sommerfeld integral, Rayleigh integral, Westervelt, KZK. 
 
II. Background/Introduction 
We recommend that you provide a brief device description along with its intended use 
environment, deployment/implantation procedure and patient population, as appropriate.  
Additionally, describe the purpose and scope of the analysis, as this will dictate the 
relevant details necessary for review.  The details provided in this section should 
correspond to the objectives of your analysis. 
 
III.  Code Verification 
  35  Contains Nonbinding Recommendations 
 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed on the software used 
for the CM&S study.  Software tools include off-the-shelf, modified-off-the-shelf, or 
user-developed.  Code verification is important, regardless of the software type. 
 
A.  Details 
You should briefly describe the code verification activities.  You may reference 
available documentation and verification results from the software developer.   
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationale for differences 
between the code used for verification and the code used for the context of use.  
Moreover, provide rationale to support the selection of the numerical settings, either 
default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in System Discretization and Numerical 
Implementation, sections VIII and IX, respectively. 
 
IV.  System Geometry (System Configuration) 
We recommend that you provide details regarding the device and/or tissue geometry that 
was modeled.  The configuration defines the geometry of the device, computational 
domain and the anatomical structure included within the computational domain. 
 
A.  Details 
You should describe the components of the system (e.g., device, in vivo and/or in 
vitro environment) to be evaluated.   
 
Regarding the ultrasound source, you should include images, diagrams (with 
appropriate scaling bar or dimensions), and a brief description of the model(s).  
Specifically, discuss whether the ultrasound source is a spherical bowl or phased-
array transducer.  If it is the latter, include a scaled diagram indicating the 
arrangement of the elements.  Finally, provide the dimensions of the device and its 
geometry. 
 
Regarding the anatomy, you should describe the methods (e.g., image reconstruction) 
used to generate the simulated anatomy and discuss the techniques used to 
demonstrate that the configuration was captured appropriately for the intended 
analysis, if applicable.  For example, if bone is included in the computational domain, 
describe how it was modeled.  If blood vessel are included in the computational 
domain, describe the blood vessels that were modeled and represented (e.g., 
statistically versus simulating a single representative geometry).  Indicate how other 
anatomical features are included.  Finally, describe any scaling or similarities used in 
the modeling approach. 
 
  36  Contains Nonbinding Recommendations 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to generate the system configuration as compared to the actual device and 
environment.  If the entire device system was not modeled or if simplifications were 
made to the geometry, then provide rationale for the system geometry that was 
analyzed (e.g., use of symmetry).  You should describe the difference between the 
model and the real situation as it pertains to the purpose of the computational 
modeling study.  For example, if bones are present, describe if the shear-wave 
propagation (and heating due shear-wave absorption) was modeled.  Indicate the 
transducer apodization.  If integral methods are used, discuss how acoustic diffraction 
affects the solution.  Additionally, as manufacturing tolerances can affect device 
functionality, describe how the range of design and manufacturing tolerance 
dimensions influence the results compared to nominal dimensions. 
 
V. Governing Equations 
We recommend that you provide information regarding the governing equations used to 
perform the computational analysis. 
 
A.  Details 
You should describe the basic equations used in the simulation.  Specifically, state 
whether the propagation model is full-wave or parabolic, and linear or nonlinear.  For 
nonlinear or broadband modeling, discuss the frequency dependence of acoustic 
attenuation.  Indicate whether the pressure wave or displacement wave is modeled, 
and whether shear waves are taken into account.  If acoustic streaming, mechanical, 
and/or thermal effects are included, discuss the coupling of the system. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the basic mathematical equations that were implemented for the model and 
simulation, specifically regarding the type of propagation model employed. 
 
VI.  System Properties 
We recommend that you provide, preferably in tabular format, all physical properties, 
coefficients, descriptive equations used in the simulation and post processing.   
 
A.  Details 
We have provided the following as an example of how to report the system 
properties. 
 
Tissue properties  
Property  Numerical value  Unit 
Small signal sound speed     
Mass density     
Absorption     
Coefficient of nonlinearity     
  37  Contains Nonbinding Recommendations 
 
Heat capacity     
Thermal conductivity     
Perfusion rate     
 
Transducer characteristics 
  Characteristic  Numerical value  Unit 
Acoustic power     
Frequency     
Pressure/phase distribution     
 
 
We recommend that you indicate the dependence of properties on other variables, 
such as temperature, frequency, thermal dose and location, if included. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the system properties.  Identify the sources of the physical 
properties and coefficients adopted (e.g., literature, in vivo, ex vivo, in vitro testing). 
 
If literature data are cited and the data are condition-specific, discuss their 
applicability to the model.  If testing is conducted to determine the parameters, you 
should describe describe the test methods and results as applicable to the model.   
 
If there are uncertainties associated with the data (i.e., due to accuracies, 
simplifications, or variations), perform a sensitivity analysis, if appropriate, to address 
the effect of the uncertainties on the simulation results. 
 
VII.  Boundary & Initial Conditions (System Conditions) 
We recommend that you provide a complete description of the initial and boundary 
conditions that are imposed on the model.  These include, but are not limited to, 
absorbing boundaries and transducer loading.  If absorbing boundaries are used, discuss 
the details of the implementation and show their effectiveness.  You should provide a 
rationale for the choice of the initial/boundary conditions and if appropriate, provide a 
graphical representation of the conditions, depicting how they are applied to the system. 
 
VIII. System Discretization 
We recommend that you provide the following details regarding the spatial discretization. 
 
A.  Details 
You should describe the spatial discretization method and, if applicable, the technique 
used to integrate the evolution variable.  If complex geometry requires the use of a 
non-uniform mesh, provide images/diagrams of the mesh.  Additionally, you should 
indicate the details of the mesh.  Specifically, 
  38  Contains Nonbinding Recommendations 
 
  you should describe and provide rationale for the quality of the mesh (e.g., 
element/cell types, sizes, shapes, quality metrics (e.g., aspect ratios) and 
formulations chosen for the production mesh for the analysis domain); and. 
  you should discuss mesh refinement in areas of interest, for example, where 
the field changes rapidly in space. 
If adaptive meshing refinement techniques were employed, then you should discuss 
the methods and provide details regarding the finished mesh. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to discretize the computational domain and, if applicable, the integration 
scheme. Perform a convergence analysis (solution as a function of mesh density) and 
provide details that demonstrate that discretization adequately resolved the physics of 
interest. 
 
IX.  Numerical Implementation 
We recommend that you provide the following details regarding the software used in the 
numerical implementation of the analysis.  For models using differential equations, 
discuss the method used to solve the discrete equations.  For integral models, discuss the 
method of numerical integration.  You should provide a rationale for the choice of the 
methods used and possible effects on the solution.  Finally, you should describe and 
provide rationale for any techniques used to accelerate the computation, such as 
neglecting terms in regions where they have subleading order, adaptive time-stepping or 
variable number of harmonics. 
 
X. Validation 
We recommend that you provide information regarding the methods employed to validate 
the computational model.  Specifically, you should describe the method(s) used to assess 
the predictive capability of the computational model with appropriate bench methods, 
conserved quantities and known analytical solutions.  You should provide diagrams and 
data to support the assessment of the model.  You should provide details on how the 
measurements were taken from the bench test and compared to the computational model.  
Discuss any differences between bench testing/known solutions and results from the 
computational model. 
 
XI.  Results 
We recommend that you present the quantitative results from the computational modeling 
study over the range of intended use parameters.  You should provide the results with a 
sufficient level of details, including labels and legends.  The results may be presented in 
more than one format (e.g., table, graph, plot). 
 
XII.  Discussion 
We recommend that you discuss how the results relate to the context of use of the CM&S 
study, and if appropriate the clinical relevance and how the results compare with 
experimental and literature results, if these results exist. 
 
  39  Contains Nonbinding Recommendations 
 
XIII. Limitations 
Describe the assumptions/simplifications made in the model generation, simulation and 
analysis.  Discuss how those assumptions/simplifications might affect the output of the 
model and the interpretation of its relevance to the device and safety.  You should 
describe the outcomes and implications of all the available uncertainty analyses 
performed on the system properties and conditions. 
 
XIV. Conclusions 
We recommend that you summarize the CM&S study with respect to the context of use 
and how it relates to the regulatory submission. 
 
XV.  References 
You should provide a list of the appropriate references used to support the CM&S study. 
 
 
  40  Contains Nonbinding Recommendations 
 
Subject Matter Appendix V  
Computational Heat Transfer 
 
For questions regarding this appendix, contact Joshua Soneson, Ph.D. at (301) 796-2512 or at 
rrcm@fda.hhs.gov. 
 
 
Introduction/Scope of the Appendix  
The purpose of this appendix is to provide recommendations on the formatting, organization, 
and content of reports for studies in computational heat transfer in support of device 
submissions. 
 
Outline of the Report 
In the following section, we provide an outline for reporting the details of your 
computational modeling and simulation study. 
 
I.  Executive Report Summary 
We recommend that you provide a concise, high-level overview of the assumptions and 
rationale for the methodology/modeling approach, and the following: 
  Context of use of the CM&S study including a clear identification of the 
quantity(s) of interest and describe any relevance/correlation to bench testing for 
validation purposes  
  Describe the type(s) of analysis(es) conducted in the computational modeling 
study (e.g., radiation or conduction heat transfer, fluid flow, chemical reaction, 
EM or acoustic absorption) 
  State whether the analysis software is open-source, commercial, or developed in-
house 
  Keywords - please provide up to five keywords or key phrases that describe the 
modeling modality, the device product code, any relevant materials of the device, 
analysis type, and if applicable, location in the body for intended use (e.g., finite 
difference method, MNB, heat conduction, thermal ablation, uterus).  For 
example, the following are sample keywords relevant to this subject matter that 
can be used: 
  thermal diffusivity, source, diffusion equation, heat capacity, radiation, 
conduction. 
 
II. Background/Introduction 
We recommend that you provide a brief device description along with its intended use 
environment, deployment/implantation procedure and patient population, as appropriate.  
Additionally, you should describe the purpose and scope of the analysis, as this will 
  41  Contains Nonbinding Recommendations 
 
dictate the relevant details necessary for review.  The details provided in this section 
should correspond to the objectives of your analysis. 
 
III.  Code Verification 
We recommend that you provide a brief description of the software quality assurance 
(SQA) and numerical code verification (NCV) that you performed on the software used 
for the CM&S study.  Software tools include off-the-shelf, modified-off-the-shelf, or 
user-developed.  Code verification is important, regardless of the software type. 
 
A.  Details 
You should briefly describe the code verification activities.  You may reference 
available documentation and verification results from the software developer.   
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the applicability of the verified code to 
your computational domain.  If applicable, describe and rationale for differences 
between the code used for verification and the code used for the context of use.  
Moreover, provide rationale to support the selection of the numerical settings, either 
default or modified. 
 
Note that the details regarding calculation verification, the other component to the 
verification process, are provided in System Discretization and Numerical 
Implementation, sections VIII and IX, respectively. 
 
IV.  System Geometry (System Configuration) 
We recommend that you provide details regarding the device and/or tissue geometry that 
was modeled.  The configuration defines the geometry of the device, computational 
domain and the anatomical structure included within the computational domain. 
 
A.  Details 
You should describe the components of the system (e.g., device, in vivo and/or in 
vitro environment) to be evaluated.   
 
Regarding the heat source, you should include images, diagrams (with appropriate 
scaling bar or dimensions) and a brief description of the model(s).  Additionally, 
provide dimensions of device and geometry. 
 
Regarding the anatomy, you should describe the methods (e.g., image reconstruction) 
used to generate the simulated anatomy and discuss the techniques used to 
demonstrate that the configuration was captured appropriately for the intended 
analysis, if applicable.  Finally, describe any scaling or similarities used in the 
modeling approach. 
 
You should describe the methods for quantifying temperature-induced bioeffects such 
as phase change or thermal damage.   
 
  42  Contains Nonbinding Recommendations 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to generate the system configuration as compared to the actual device and 
environment.  If the entire device system was not modeled or if simplifications were 
made to the geometry, then provide rationale for the system geometry that was 
analyzed (e.g., use of symmetry).  You should describe the difference between the 
model and the real situation as it pertains to the purpose of the computational 
modeling study.  Additionally, as manufacturing tolerances can affect device 
functionality, describe how the range of design and manufacturing tolerance 
dimensions influence the results compared to nominal dimensions. 
 
 
V. Governing Equations 
We recommend that you provide information regarding the governing equations used to 
perform the computational analysis. 
 
A.  Details 
You should describe the basic equations used in the simulation.  Specifically, state 
whether materials are isotropic and if not, describe how anisotropy is addressed.  You 
should describe the coupling to other physical processes (i.e., fluid flow, heat sources 
in domain or on boundary) that were included in the model. 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications of 
the basic mathematical equations that were implemented for the model and 
simulation, as well as the methods for quantifying thermal damage. 
 
VI.  System Properties 
We recommend that you provide, preferably in tabular format, all physical properties, 
coefficients and descriptive equations used in the simulation and post processing. 
 
A.  Details 
We have provided the following as an example of how to report the system 
properties. 
 
Tissue properties  
Property  Numerical value  Unit 
Mass density     
Heat capacity     
Thermal conductivity     
Perfusion rate     
 
We recommend that you indicate the dependence of properties on other variables, 
such as temperature, frequency, thermal damage and location, if included. 
 
  43  Contains Nonbinding Recommendations 
 
B.  Assumptions, simplifications, and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to determine the system properties.  Identify the sources of the physical 
properties and coefficients adopted (e.g., literature, in vivo, ex vivo, in vitro testing). 
 
If literature data are cited and the data are condition specific, you should discuss their 
applicability to the model.  If testing is conducted to determine the parameters, you 
should describe the test methods and results as applicable to the model.   
 
If there are uncertainties associated with the data (i.e., due to accuracies, 
simplifications or variations), perform sensitivity analysis, if appropriate, to address 
the effect of the uncertainties on the simulation results. 
 
VII.  Boundary & Initial Conditions (System Conditions) 
We recommend that you provide a complete description of the initial and boundary 
conditions that are imposed on the model.  You should provide rationale for the choice of 
the initial/boundary conditions and if appropriate, provide a graphical representation of 
the conditions, depicting how they are applied to the system. 
 
VIII. System Discretization 
We recommend that you provide the following details regarding the spatial discretization. 
 
A.  Details 
You should describe the spatial discretization method and, if applicable, the technique 
used to integrate the evolution variable.  If complex geometry requires the use of a 
non-uniform mesh, provide images/diagrams of the mesh.  Additionally, indicate the 
details of the mesh.  Specifically, you should: 
  describe and provide rationale for the quality of the mesh (e.g., element/cell 
types, sizes, shapes, quality metrics (e.g., aspect ratios) and formulations 
chosen for the production mesh for the mesh of the analysis domain); and. 
  discuss mesh refinement in areas of interest, for example, where the field 
changes rapidly in space. 
If adaptive meshing refinement techniques were employed, then you should discuss 
the methods and provide details regarding the finished mesh. 
 
B.  Assumptions, simplifications and rationale 
You should describe and provide rationale for the assumptions and simplifications 
used to discretize the computational domain and, if applicable, the integration 
scheme. You should perform a convergence analysis (solution as a function of mesh 
density), a stability analysis where applicable, and provide details that demonstrate 
that the discretization adequately resolved the physics of interest. 
 
IX.  Numerical Implementation 
We recommend that you provide the following details regarding the software used in the 
numerical implementation of the analysis.  For models using differential equations, 
discuss the method used to solve the discrete equations.  For integral models, discuss the 
  44  Contains Nonbinding Recommendations 
 
method of numerical integration.  You should provide a rationale for the choice of the 
methods used and possible effects on the solution.  Finally, you should describe and 
provide rationale for any techniques used to accelerate the computation, such as 
neglecting terms in regions where they have subleading order, adaptive stepping, etc. 
 
X. Validation 
We recommend that you provide information regarding the methods employed to validate 
the computational model.  Specifically, you should describe the method(s) used to assess 
the predictive capability of the computational model with appropriate bench methods, 
conserved quantities and known analytical solutions.  Provide diagrams and data to 
support the assessment of the model.  Provide details on how the measurements were 
taken from the bench test and compared to the computational model.  Discuss any 
differences between bench testing/known solutions and results from the computational 
model. 
 
XI.  Results 
We recommend that you present the quantitative results from the computational modeling 
study over the range of intended use parameters.  You should provide the results with 
sufficient level of details, including labels and legends.  The results may be presented in 
more than one format (e.g., table, graph, plot). 
 
 
XII.  Discussion 
We recommend that you discuss how the results relate to the context of use of the CM&S 
study, and if appropriate the clinical relevance and how the results compare with 
experimental and literature results, if these results exist. 
 
XIII. Limitations 
You should describe the assumptions/simplifications made in the model generation, 
simulation and analysis.  Discuss how those assumptions/simplifications might affect the 
output of the model and the interpretation of its relevance to the device and safety.  
Describe the outcomes and implications of all the available uncertainty analyses 
performed on the system properties and conditions. 
 
XIV. Conclusions 
We recommend that you summarize the CM&S study with respect to the context of use 
and how it relates to the regulatory submission. 
 
XV.  References 
You should provide a list of the appropriate references used to support the CM&S study. 
 
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