Abstract

We describe a software system that enables the measurement

and analysis of tissue engineering scaffold materials from

three dimensional images that were generated with X-ray

micro-computed tomography (μCT), segmented and

converted to a polygonal representation. We use this system

to compare an ‘as designed’ scaffold with a manufactured

scaffold to determine differences in strut properties. Essential

to this work is the use of an immersive visualization (virtual

reality) system that gives the researcher the ability to

interact directly with data representations in ways that are

not possible with desktop systems. Structures can be

inspected and measurements can be made and analyzed

during the immersive session. Using these measurements,

researchers can assess the fidelity of actual scaffolds to the

design model and evaluate scaffold manufacturing processes.

We describe future directions for more automatic

measurement techniques for three dimensional images, and

the role of immersive visualization in understanding and

evaluating these techniques.

Introduction

Tissue engineering is an emerging interdisciplinary field that

has evolved because of the dire need for compatible,

replacement organs and tissues in light of the shortages of

transplantable organs and the problems associated with

biomaterial implants. Four issues critical to the success of tissue

engineering were identified in a recent review.1 One of the

issues is the optimization of the matrix, or scaffold, for cell

proliferation, differentiation and tissue remodeling. It is widely

recognized that factors that influence cell response to scaffolds

include chemistry, surface roughness, elastic modulus and

structure. The structure also influences media transport

through the scaffold. In order to understand how the structure

influences cell response, structural descriptors such as porosity,

pore size distribution, tortuosity, and connectivity are

generated through analytical or computational means.

We are pursuing the processing of 3D images of scaffold

materials in the context of an immersive (virtual reality)

visualization environment (IVE). We use the IVE to measure

scaffold descriptors and to present them in a clear and

interactive manner. 

An immersive visualization environment provides the

researcher with the illusion that visual data representations are

present in a volume of space within which the user can move.

The user has the experience of being immersed in a virtual

scene where he or she can view and manipulate elements of

the virtual world. We prefer to use the term immersive

visualization (IV) rather than virtual reality in order to

emphasize our use of the technology for data visualization and

to highlight the user’s sense of being present in the midst of

the data space. At the National Institute of Standards and

Technology (NIST), we have created an IV environment

which is shown in Figure 1.

The user can move around, look in different directions, and

even interact with the data representations as if they were

present. Interactions are often accomplished with a hand-held

device (a wand) that is also motion-tracked. This environment

provides the user with three dimensional (3D) visual and

kinesthetic cues that are impossible to achieve with desktop

displays. The IV environment provides perceptual cues (both

visual and kinesthetic) that are extremely advantageous in

understanding, measuring, and analyzing 3D structures.

Feature

By John Hagedorn1, Joy Dunkers2,

Adele Peskin1, John Kelso1,

Judith Devaney Terrill1

Quantitative, Interactive 

Measurement of Tissue 

Engineering Scaffold Structure in an

Immersive Visualization Environment

6 BIOMATERIALS FORUM • Fourth Quarter 2006

Figure 1. A user in the NIST 

immersive visualization environment.

Figure 2. As-designed scaffold, synthetically constructed based on the

design specifications (A.), 3D reconstruction of the scaffold made by

SFF (B.).
Previous work applied measurement and 3D image analysis in

an immersive environment to the understanding of

microscopic biological structures.2,3

We are pursuing the use of the IV environment as a framework

for more easily measuring scaffold descriptors, for support in

developing consensus definitions of scaffold descriptors, for

understanding automatic descriptor measurement methods,

and for qualitatively evaluating and validating scaffold

manufacturing techniques. 

In this initial effort, we apply IV techniques to a

straightforward manual linear measurement task to derive

quantitative structural information from a digital 3D image of

a tissue engineering scaffold. 

3D Image Generation and Processing

The poly(E-caprolactone) (PCL) scaffold examined in this

work was manufactured by a process called solid freeform

fabrication (SFF).4 The struts are designed to be 400 μm in

diameter and are laid down in a 0o-60o-120o layer pattern.

The gap width is 1.0 mm. 

The μ-CT images of the scaffold were generated by a Skyscan

1072 micro-computed tomography scanner with voxel spacing

of 12.9 μm in each direction. The images were output as

bitmap files. 

These bitmap files were processed by custom software in

conjunction with open source software to produce files suitable

for input to the IVE. Segmentation was performed by applying

a threshold, and a 3D polygonal representation was generated

based on the threshold. 

Image Measurement and Analysis

While the initial processing of the image data was relatively

straightforward, the analysis and measurement of geometric

descriptors was more challenging. The latter motivated the use

of IV. We do not have algorithms for the automatic threedimensional measurement and analysis of the image data, so

we used the IVE to interactively measure the desired features.

Our objective was to build a software system within the IV

environment that integrated the following tasks: 1.

measurement of scaffold characteristics; 2. analysis of the

collected measurements; 3. display of the analysis; 4.

interactions with the data and analyses that will enable

grouping of results. The goal of these tasks was to achieve

greater understanding of the structural characteristics of the

scaffold material.

The initial measurement task that we undertook was the

manual measurement of linear distances. It was felt that this

step would enable the understanding of several important

scaffold characteristics, one of which is strut diameter

distribution and any associated anisotropy. We decided that

the specific scenario for this first implementation would be: 1.

The user collects a set of linear measurements; 2. A simple

statistical analysis is made; 3. The analysis, including the

distribution of measurements, is presented to the user; 4. The

user can interact with the measurement distribution in order to

highlight measurements that fall within any selected range of

values. All of these tasks are to be performed in real-time

during the IV session. 

BIOMATERIALS FORUM • Fourth Quarter 2006 7

continued on page 8
The underlying software on which our immersive system is

built is DIVERSE,5 which provides a portable, modular, open

source software platform that manages all aspects of the IVE.

For the presentation of the data analyses and for some aspects

of the user interaction, we used VEWL6 which enables the use

of standard desktop user interfaces within the IV environment.

VEWL is a software subsystem that operates within the

DIVERSE framework.

There are two main components to our implementation. The

first component allows the user to manually make a series of

linear measurements in the IV environment. The other

component is a standard 2D user interface (displayed with

VEWL) for displaying the measurement statistics and

distribution in tabular and histogram form.

Our main objective in designing the user interface was to make

the 3D measurement task direct and natural. The user makes a

linear measurement simply by moving the hand-held wand to

a point in the 3D virtual environment, pressing a button on

the device, then moving to a second point and pressing the

button again. Visual feedback is given at each step of the

process and the user is able to adjust each end point simply by

grabbing it with the wand and repositioning it. The process is

fast, simple, and direct.

As a first demonstration of the quantitative IV, we compare

the strut dimensions of the manufactured scaffold in Figure

(2B) to the as-designed scaffold shown Figure (2A). We

examine in detail the diameters at the strut junctions as

compared to the inter-junction diameters.

We made two types of measurements: strut diameters and strut

layer thickness. Strut diameters were measured directly at

several points on each strut in a vertical direction in between

the junctions (Figure 2). Strut layer thickness was found by

measuring the vertical distance between the bottoms of struts

on adjacent layers. We made layer thickness measurements at

several junctions for each layer.

These two types of measurements were made on the “asdesigned” scaffold model (generated synthetically from the

design) and on the image of the actual manufactured scaffold

material. The measurements of the “as-designed” scaffold are

intended to validate the measurement method. The

measurements of the experimental data will be used to

understand the scaffold structural characteristics and

fabrication method.

Figure 3 shows the PCL scaffold as it appears within the IVE,

including several menus that allow the user to control the

system. The box around the image data enables the researcher

to interactively access features of interest for measurement

throughout the volume of the 3D image. The IVE also enables

the scientist to inspect various features and size ranges within

the dataset. In Figure 4, the scientist has specified a range in

the histogram. The corresponding measurements are

highlighted in the display, providing additional visual feedback

on scaffold uniformity. 

Results and Discussion

As mentioned above, the as-designed scaffold model was made

with 400 μm diameter struts arranged in layers that contacted.

This configuration results, of course, in strut layer thickness of

400 μm. Our measurements resulted in these statistics:

Strut diameter: mean 399.3 μm std dev 1.3 μm n=63

Layer thickness: mean 399.8 μm std dev 1.6 μm n=24

The numbers clearly indicate that the measurement procedure

is capable of producing valid results. During the collection of

these data, we noticed that the distribution of diameter

measurements was skewed slightly to the low side of 400 μm,

likely because the cylindrical struts were being represented by

polygonal approximations. 

The measurements of the data representing the actual scaffold

material yielded these results:

8 BIOMATERIALS FORUM • Fourth Quarter 2006

Figure 3. Cross-section of PCL scaffold with 

measurements of strut diameter.

continued from page 7

Figure 4. Selected histogram bins are highlighted in visualization

showing distribution of strut diameters in the range of 200 to 320

Ìm. The struts have been removed from the scene in order to make

the measurements more visible.
BIOMATERIALS FORUM • Fourth Quarter 2006 9

Strut diameter: mean 325.2 μm std dev 31.2 μm n=82

Layer thickness: mean 271.1 μm std dev 22.2 μm n=33

These manual measurements required the user to exercise

judgment in selecting the measurement end points. Also note

that, just as with the as-designed model, we perform our

measurements using polygonal representations that are,

inherently, approximations to the true form of the scaffold.

We see from the measurements of the actual scaffold that the

mean inter-junction strut diameter is significantly more than

the mean layer thickness (strut diameter) at the junctions. A

qualitative sense of this effect can be seen in the IV

environment; the struts appear to be fused and somewhat

overlapping at the junctions. We also note, of course, that the

actual strut diameter differs significantly from the as-designed

model. The effect of these differences on the function of the

scaffold is unclear and is the subject of future study. It is clear,

however, that the IV environment has provided us with a way

of making a meaningful quantitative characterization of

scaffold structure. From this analysis, we find no anisotropy or

gradients in inter-junction or at junction strut diameters. 

Conclusion and Future Directions

We have found that IV is a technology that enables both

qualitative and quantitative understanding of 3D structure of

tissue engineering scaffolds that was not otherwise possible.

The measurements made within the virtual environment

would have been very difficult to make with typical desktop

visualization techniques. We also plan to use the immersive

environment in conjunction with automatic measurement

techniques that we are developing to aid in understanding the

action of the automatic algorithms and as a way of validating

those methods.

The measurements and analyses enabled comparison of key

scaffold descriptors across images. We have found that the

inter-junction strut diameter is about 19% smaller than the asdesigned model. The at-junction strut diameter (or layer

thickness) is about 33% smaller than the as-designed model.

IV measurement of these descriptors should be implemented

for a further evaluation of the SFF manufactured scaffold: layer

planarity, strut diameter uniformity, strut circularity, and strut

location.

Disclaimer

Certain commercial products may be identified in this paper in

order to adequately describe the subject matter of this work.

Such identification is not intended to imply recommendation

or endorsement by the National Institute of Standards and

Technology, nor is it intended to imply that the identified

products are necessarily the best available for the purpose.

1 Scientific Applications and Visualization Group,

Mathematical and Computational Sciences Division, National

Institute of Standards and Technology (NIST), Gaithersburg,

MD 

2 Biomaterials Group, Polymers Division, NIST, Gaithersburg,

MD

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812.

Congratulations to:

SFB President Mauli Agrawal, who has been appointed as

Dean of the College of Engineering of the University of

Texas at San Antonio.

Dr. Tony Mikos, the J.W. Cox Professor of Bioengineering

and Professor of Chemical and Biomolecular Engineering

at Rice University, who is the recipient of the 2007

BMES Distinguished Scientist and Lecturer Award. Tony

will be recognized in next year’s BMES meeting in Los

Angeles. 

Dr. Linda Griffith, who is the recipient of a 2006

MacArthur Fellowship, given by the John D. and

Catherine T. MacArthur Foundation. The MacArthur

Fellowship is a five-year grant to individuals who show

exceptional creativity in their work and the prospect for

important future advances. Linda is a Professor in the

Departments of Biological and Mechanical Engineering

and Director of the Biotechnology Process Engineering

Center at the Massachusetts Institute of Technology.

Dr. Kinam Park, Professor of Pharmaceutics and

Biomedical Engineering at Purdue University, who was

recently named Showalter Distinguished Professor of

Biomedical Engineering. Kinam is the Program Chair for

the 2007 SFB Annual Meeting.

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