bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐C‐M100J‐03: Objective Assessment of Deformable Image Registration in Radiotherapy — a Multi‐Institution Study
Authors: Kashani R , Balter J , Kessler M , Hub M , Dong L , Zhang L , Xing L , Xie Y , Hawkes D , Schnabel J , McClelland J , Joshi S 
Published: July 2007

Purpose: The looming potential of deformable alignment tools to play an integral role in adaptive radiotherapy suggests a need for objective assessment of these complex algorithms. Current studies of accuracy require analytically generated deformations applied to sample image data, or use of contours or bifurcations, with inherent uncertainty as well as potential bias, as these visible features are likely to dominate the local deformation parameters. Method and Materials: A deformable phantom was embedded with 48 small radiopaque markers, placed in regions varying from high contrast to roughly uniform regional intensity, and small to large regional discontinuities in movement. CT volumes of this phantom were acquired in two different deformation states. After manual localization of marker coordinates, images were edited to remove the markers. The resulting image volumes were sent to 4 collaborating institutions, each of which has developed previously published deformable alignment tools routinely in use. Alignments were done, and applied to the list of reference coordinates. The transformed coordinates were compared to the actual marker locations. Results: 5 alignment techniques were tested from the 4 institutions. All algorithms performed generally well, as compared to previous publications. Average errors in predicted location ranged from 1.7–3.9 mm, depending on technique. No algorithm was uniformly accurate across all regions of the phantom, with maximum errors ranging from 5.5 – 15.4 mm. Larger errors were seen in regions near significant shape changes, as well as areas with uniform contrast but large local motion discontinuity. Conclusion: An objective test of deformable alignment is feasible. Reasonable accuracy was achieved, although variable errors in different regions suggest caution in globally accepting the results from deformable alignment. Valuable feedback from investigators is being applied to development of further generations of deformable phantoms for alignment experiments.Sponsored by NIH P01‐CA59827.
TU‐C‐M100J‐08: Objective Characterization, Estimation and Prediction for Modeling Breathing‐Related Movement
Authors: Ruan D , Fessler J , Balter J 
Published: July 2007

Purpose: To propose a hierarchical model for estimation, tracking, and prediction of respiratory tumor motion. To incorporate modeling on different scales: semi‐reproducibility globally and slow frequency/displacement variation locally. Method and Materials: The problem is formulated with a hierarchy of scales: On the finer scale, a databased approach is used to estimate the local variation of both displacement and frequency, utilizing classic control and chaos theory. A warping procedure is used to “counteract” local variation, resulting in a much more regular post‐warping signal. On the global level, the post‐warping (phase‐synchronized) signal is modeled as a noisy observation of an intrinsic periodic system, and the best periodic pattern is estimated within a nonparametric optimization setting. For tracking and prediction purposes, the locally estimated warping map (together with proper interpolation or extrapolation, whichever applies) is used to un‐warp the globally obtained periodic pattern. A recursive method is devised to further improve the efficiency for real‐time processing. Results: The obtained estimation/prediction signal demonstrates similar local variation as the raw observation, while semi‐periodicity is incorporated to decrease its noise sensitivity and enhance prediction accuracy. Verification using RPM data shows that the proposed method reduces 1‐period look‐ahead prediction error (RMSE) by more than 50% compared to perfect periodic modeling. Conventional local linear models generally fail in such long‐term prediction tasks. Conclusions: This work provides an infrastructure for incorporating information on different knowledge levels, and offers the flexibility to adaptively balance the roles of physical prior knowledge and data fidelity. The model‐based method on the global level incorporates the well‐recognized semi‐periodicity pattern of respiratory motion, overcoming the myopia of local state models. Data‐driven local phase map estimation used in warping and un‐warping fully utilizes the observation and enjoys the freedom of nonparametric setup.This work is sponsored by NIH P01‐CA59827.
TU‐C‐M100F‐07: Detecting Dose Reconstruction Errors
Authors: Zhong Hualiang , Weiss Elisabeth , Siebers Jeffrey 
Published: July 2007

Purpose In radiation therapy, delivered doses can be accumulated over fractions for adaptive treatment planning. However, the dose reconstruction fidelity can be compromised by image registration errors. The resultant dose discrepancy is hard to measure. This paper proposes a new method to assess the difference between the delivered dose and the warped dose. Method and Materials: The dose warping discrepancy is dominated by deformable image registration errors and source‐dose distributions. Registration errors can be specified within a finite element framework as an unbalanced energy δR, which is defined at element j by
urn:x-wiley:00942405:media:mp1348:mp1348-math-0001 where E0 and di are Young's modulus and the displacement vector fields of the registration R. E0Φj is an assembly of all the element forces relating to the node i. Consequently the dose warping discrepancy at voxel k can be defined as the convolution of the dose divergence Div(D) and δR:
urn:x-wiley:00942405:media:mp1348:mp1348-math-0002 The effectiveness of the dose‐discrepancy‐convolution (DDC) defined above is demonstrated through applying it to dose computed on ten prostate‐CT images. An IMRT treatment plan is developed on the planning image. In nine subsequent treatments, images are acquired to calculate the corresponding delivered doses. Their mean and standard‐deviation in Ci, a target contour automatically expanded from prostate delineated on the time‐of‐treatment image i, are compared with those of their warped doses measured on the planning target volume. The differences in their means and standard‐deviations are denoted by Eε and Eσ, respectively.Results δR, εD,R, Eε and Eσ are computed for the nine treatment fractions. Fraction one and eight have the largest warping discrepancies identified in all the four evaluation criterions. Conclusion Defined in terms of the deformable registration error, the voxel‐based DDC can be employed for the automatic evaluation of dose reconstruction in the whole dosing domain. Its measurement is consistent to the contour‐based dose warping evaluation performed in the planning target volume.
TU‐C‐BRB‐01: Errors — Why They Occur, How to Minimize Them (Part I)
Authors: Pawlicki T , Klein E , Dunscombe P 
Published: July 2007

Errors — Why They Occur, How to Minimize Them is a 2‐day symposium focused on quality of treatment in medical physics and the challenges associated with actual clinical operations. Three presentations will be given on each day of the symposium. This abstract describes the Day 1 presentations.The first presentation in this session provides an overview of the 2‐day symposium. It includes a summary of Failure Modes and Effects Analysis as well as other process oriented quality tools. The second presentation will examine potential errors in terms of scenarios, pathways of occurrence, and dosimetry. The goal is to prioritize error prevention according to likelihood of events and their dosimetric impact. The identification and prioritization of potential errors according to frequency and dosimetric impact will be discussed. As record and verify systems become more automated; more accurate and efficient data transfer will occur, hopefully reducing paths of certain errors, but potentially introducing new paths if systematic checks are not introduced. The final presentation in this session will be in the form of a case study of three incidents: Glasgow, Epinal, and another centre. Each incident will be described. The quality of the investigations following each incident will be discussed. Finally, the major root causes will be elucidated along with the relevance of lessons learnt from each incident.Presentation 1 Introduction: why errors occur and methods to how them.Presentation 2 Pathways and dosimetric impact of errors in radiation oncology.Presentation 3 Case studies in radiotherapy errors.
TU‐C‐BRA‐04: Should We Worry About Neutrons?
Authors: Paganetti H 
Published: July 2007

Advanced treatment techniques (e.g., IMRT, protons) are able to deliver more conformal dose distributions. However, they may cause potential risks for second malignancies due to increased scattered radiation.Protons deposit secondary dose outside the treatment volume mainly via neutrons (generated either in the patient or the treatment head). In particular for passive scattered proton beams, a general statement about this dose cannot be made because the yield and energy of these neutrons depends on several factors, e.g. the characteristics of the beam entering the treatment head, the material in the double scattering system and the modulator wheel, and the field size incident to the patient specific collimator. The latter can easily cause neutron dose variations up to two orders of magnitude (the neutron dose delivered by treatment head generated neutrons decreases with increasing collimator opening). Several experimental and simulated data from passive scattered proton beams show that the biologically effective neutron dose (weighted by a quality factor) could be higher or even lower than scattered doses in photon therapy. However, depending on the beam line design and the field size used for a specific treatment it might be significantly higher in some rare cases. Because the neutron dose is dominated by the contribution from the treatment head, proton beam scanning produces a much lower neutron background than passive scattering. Presumably, it delivers the lowest scattered dose of all treatment modalities.The likelihood of developing secondary cancer depends on both the scattered dose to the whole body and the high‐dose volume. Depending upon the dose response relationship, a main concern may not be the dose far away from the field (e.g. from neutrons), but the dose delivered to, or directly adjacent to, the target. The integral dose with any type of photon beams is higher than with proton beams.Educational Objectives:1. To understand the determinants of neutron radiation in proton beam therapy.2. To understand risks associated with neutrons doses.
TU‐EE‐A3‐02: Registration of Ultrasound Tissue‐Typing Images with CT Images for Image‐Guided Prostate Cancer Radiation Therapy
Authors: Zhou J , Zhang P , Schiff P , Kutcher G , Liu T 
Published: July 2007

Purpose: To develop an image registration scheme, which combines both rigid and deformable registration techniques, to map the ultrasonic tissue typing (UTT) images to the computed tomography (CT) images for tumor targeted prostate IMRT treatment. Method and Materials: UTT spectrum analysis can identify the cancerous regions inside the prostate to guide prostate radiation therapy. Current IMRT treatment plans for the prostate are designed on CT images. We developed a rigid registration followed by a deformable registration scheme for tumor region mapping between CT and UTT images. The rigid registration was achieved by adjusting the relative position of the two image sets until the mutual information between them was maximized. The deformable registration was based on a biomechanical model and finite element method (FEM). The prostate from both image sets was outlined by the clinician and the surface deformation between the two contour sets were fed into the FEM software algorithm to derive the volumetric displacement inside the prostate. When the voxel points correspondence between two image sets were known, the tumor area detected with UTT was mapped onto the CT images and used for 3D planning for dose escalation. Results: The algorithm was validated using a tissue mimicking deformable prostate phantom and ten prostate specimens. The urethra served as a marker for verifying the registration process. For phantom and ex vivo study, the displacement of the urethra matched well between the CT images and the deformed ultrasound images. The distribution of the 2D matching errors for the urethra central point had a mean and standard deviation of 2.0mm ± 1.1mm. We started to apply our registration scheme using in vivo prostate scans.Conclusion: We validated our registration scheme with our phantom and ex vivo studies. We demonstrated the feasibility of clinically employing this UTT method for intra‐prostatic tumor dose escalation.
WE‐C‐L100J‐06: Linear Systems Analysis for a New Solid State X‐Ray Image Intensifier (SSXII) Based On Electron‐Multiplying Charge‐Coupled Devices (EMCCDs)
Authors: Kuhls A , Yadava G , Patel V , Bednarek D , Rudin S 
Published: July 2007

Purpose: To objectively evaluate and optimize performance of a new SSXII using linear‐systems analysis with varying constituent elements. Method and Materials: An imaging module of the SSXII consists of a fluorescent phosphor, a minifying fiber‐optic taper (FOT), and a fiber‐optic plate (FOP) coupled directly to the sensor of an EMCCD camera. An array of such modules is used to achieve the desired field‐of‐view (FOV). Linear‐systems analysis was applied to a module to determine system performance for various combinations of components whose properties were estimated using known physical constants and manufacturer specifications. A 350μm thick CsI(Tl) structured phosphor deposited on an additional FOP was considered in this analysis; however the phosphor may be grown directly on the FOT for improved optical transfer efficiency. New back‐thinned sensors, offering high optical quantum efficiencies (>90%), are also considered. Various FOT minifications were studied to evaluate the tradeoffs between a larger field‐of‐view (FOV) per module and potential DQE degradation. Results: Initial calculations indicate elimination of a FOP in the imaging chain could improve the integral DQE by 30–80%, depending on the FOT minification. Use of a back‐thinned sensor could offer additional improvements of 10–25% over a front‐illuminated EMCCD. Increasing the FOT minification factor from 3:1 to 6:1 would tend to decrease the integral DQE by ∼50%, which could be more than compensated for by making the above two design improvements. Calculated MTFs and DQEs will be presented for various minifications, exposures, and gains. A prototype SSXII (16μm pixels) demonstrated 20 lp/mm bar‐pattern resolution radiographically and fluoroscopic image sequences with exposures of <3 μR/frame. Conclusion: The linear‐systems analysis indicates current designs for the SSXII will provide high‐resolution, low‐noise, real‐time imaging. With component optimization, an acceptable DQE can be maintained with taper minifications as large as 6:1.(Partial support: the UB Foundation and NIH grants R01‐EB002873, R01‐NS43924.)
WE‐C‐L100J‐10: Three Dimensional Vessel Centerline Reconstruction and Imaging System Calibration From a Single Vessel in Angiograms
Authors: Walczak AM , Hoffmann KR , Singh V , Dashkoff N , Kassab M , Iyer VS 
Published: July 2007

Purpose: Three dimensional (3D) vessel reconstructions can be useful in assisting clinicians with diagnosing and treating vascular disease, providing information about vessel diameter, length, and tortuosity. Reconstruction of 3D vessels from two views requires knowledge or calibration of the geometry relating the two imaging systems. We introduce a geometry calibration technique that performs this calibration using only a single indicated vessel segment in the angiograms. Methods: Vessel segments of interest were indicated in two angiographic views. The initial imaging geometry is estimated using each view's gantry information, and corresponding points along the vessels in both views are determined using epipolar constraints. The 3D position of the vessel is determined by triangulation of the found corresponding points. The geometry is corrected by varying nine of the imaging system's parameters using the Nelder‐Mead Downhill Simplex Method, with an objective function that minimizes the distance between the reprojection of the reconstructed 3D vessel centerlines and the 2D indicated vessel centerlines in both views. Results were compared with the enhanced‐Metz‐Fencil (EMF) geometry correction technique, which requires identification of additional corresponding points in both views. Results: Variations in the shapes obtained from our single vessel technique (SVT) and the EMF were comparable, median RMS of 0.47 and 0.34 mm, respectively, with magnification variations of 2.2% and 0.7%, respectively. Median errors in 2D reprojections of the 3D data for our technique and the EMF were both 0.12 mm, indicating very good agreement with the 2D indicated centerlines. Conclusion: We have developed an imaging geometry correction technique for two views based on alignment of reprojected 3D data with its respective 2D image information using only a single indicated vessel segment. This technique is reliable and comparable to other geometry correction techniques requiring additional user input.Supported by NIH grant ♯HL52567 and Toshiba Medical Systems Corporation.
WE‐C‐M100J‐02: Image‐Guided Photodynamic Therapy of Prostate Cancer
Authors: Zhu T 
Published: July 2007

Purpose: This study analyzes the results of image‐guided prostate photodynamic therapy (PDT) that integrates PDT dosimetry, light source optimization, computerized light power adjustment, and volumetric real‐time light fluence calculation to deliver uniform photodynamic dose to the target volume (prostate) and spares the critical structures (rectum and bladder). Methods and Materials: All procedures are under the image guidance of transrectal ultrasound. The PDT dosimetry includes multi‐channel real‐time in‐vivo light dosimetry, absorption and fluorescence spectroscopy for 3D optical properties, drug concentrations, and tissue oxygenation. Drug concentration is also determined using fluorescence from a single optical fiber. These measurements are made before and after motexafin lutetium (MLu)‐mediated photodynamic therapy (PDT) using a computerized step motor. The light fluence rate distributions are also measured along the catheters during PDT and compared to the 3D volumetric light fluence calculations. Real‐time light fluence calculation was performed on the 3D target volumes using ultrasound image guidance. An optimization algorithm determines the light source strength, lengths, location, and retraction for cylindrical diffusing fibers (CDF) based on the 3D heterogeneous optical properties. The resulting light source power is feedback into a 12‐channel beamsplitter that is connected to a motorized attenuator system to control the light source intensity interactively during PDT. Results: Preliminary data have shown widespread heterogeneities of optical properties and photosensitizing drug distribution. As a result of these heterogeneities, methods to quantifying the three‐dimensional (3D) distributions of these quantities in individual prostate are essential for the successful application of PDT. Comparison of light fluence rate between real‐time measurements and calculation is performed in heterogeneous medium and the standard deviations are within 30% with a simplified model and better than 11% for an improved model. Conclusions: We have shown the rational and potential for an integrated system that is capable of obtaining critical parameters (light, drug, and oxygenation) and using the PDT dosimetry result as feedback to optimize treatment delivery. We concluded that a real‐time dosimetry and feedback system for monitoring PDT dose during treatment is both achievable and required for clinical interstitial PDT applications.Educational Objectives:1. To explain the basic principle of PDT dosimetry.2. To review explicit PDT dosimetry techniques to characterize tissue optical properties, drug concentration, tissue oxygen concentration, and PDT efficacy.3. To discuss the rational and requirement for a feedback system incorporating PDT dosimetry, PDT dose optimization, and computerized light delivery.4. Summarize the clinical results of Prostate PDT.
WE‐C‐BRA‐03: TCP Model Parameters — Extracting These From Clinical Data on ‘Movable’ Patients
Authors: Witte M , Schneider C , Heemsbergen W , Lebesque J , van Herk M 
Published: July 2007

The Tumor Control Probability function (TCP, Webb & Nahum) models radiation induced cell kill and uses Poisson statistics to estimate the probability of local control. Its parameters may be derived by correlating archived plan data and treatment outcome results of clinical trials. We will exploit the data of a large randomized prostate trial (68Gy against 78Gy, 600+ patients) of patients treated between the years 1999 and 2003. For these patients the planning CT scan and organ delineations, and the 3D dose distribution as generated by the treatment planning system are electronically available.However, we have no patient specific information on the location of tumor tissue inside the prostate (as could nowadays be imaged using MRI). Furthermore, the dose absorbed by the clonogen cells will have been influenced by errors in daily set‐up and by organ motion. Although portal images were acquired for an off‐line bony set‐up protocol, no in‐room soft tissue imaging was available to monitor organ motion. An additional uncertainty is introduced by the fact that the primary method of clinical follow‐up is based on blood PSA levels, which means a detected failure may not be local.To describe the interplay between the location of clonogen cells and the varying day‐to‐day position of the prostate, we use Monte Carlo treatment plan evaluation software that was developed in‐house. This software samples population distributions of random and systematic errors to simulate many possible treatment histories. Maximum likelihood methods are then applied to determine the most probable TCP model parameters α and σα. Inspired by surveys of pathological specimens, the assumed density distribution of clonogen cells inside the prostate is modulated, and a body of clonogens located posteriorly outside the CTV is introduced to model extra capsular extension. The effects of such modulations on the TCP parameters and on the likelihood of the fit is studied.In future trials, additional imaging will increase the amount of patient specific data on geometric variations and cell distributions, leading to a more accurate TCP model.The TCP parameters thus acquired may be used for treatment planning purposes. If MRI imaging is available to gain knowledge about the location of tumor tissue inside the gland, treatment planning may be performed by optimizing the TCP function using a heterogeneous clonogen cell distribution. By using probability based optimization techniques (in which the effect of geometric errors on the tumor cell kill is modeled in the same way as in the TCP fitting procedure above), no PTVs need to be defined, and the optimization procedure can directly aim for the largest expected TCP (for a given expected rectum NTCP).Educational Objectives:1. Identify sources of uncertainty when basing a TCP model on clinical data.2. Understand a method to determine TCP parameters in the face of such uncertainties.3. Understand how these parameters may be used for treatment planning.