bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐C‐L100J‐08: Image Quality and Dose in Large Bore CT
Authors: Boedeker K , Mather R , MacLeod M
Published: July 2007

Purpose: As large bore CT scanners are becoming more prevalent in the marketplace, so have questions about the image quality and dose associated with these scanners. The aim of this work is to compare the image quality and dose characteristics of a large bore 16‐slice CT scanner with a standard 16‐slice CT scanner. Methods: Two CT scanners, a large bore CT (Aquilion Large Bore, Toshiba) and a standard 16‐slice CT (Aquilion 16, Toshiba) were compared with respect to noise, spatial resolution, CT number accuracy, and low contrast. The technique factors on the large bore were adjusted to yield the same dose as a standard abdominal protocol on a standard 16‐slice scanner. Noise was measured on a 24cm water phantom, spatial resolution via the Fourier transform of bead, CT number via several known materials contained in a 32cm diameter phantom, and low contrast via a traditional low contrast phantom. Dose was measured via standard CTDI measurements. Results: The large bore required an increase in mAs of approximately 30% to yield the same dose as a standard 16‐slice scanner. After this adjustment was made, the image quality metrics for both scanners were identical. Conclusion: The large bore CT in this study yielded the same image quality in all four categories as the standard 16‐slice protocol.

K. Boedeker, R. Mather, and M. MacLeod are employees of Toshiba America Medical Systems.
TU‐C‐L100J‐10: Combining Measurement and Monte Carlo Methods for Dose Assessment in Flat‐Detector CT
Authors: Kyriakou Y , Krause J , Langner O , Deak P , Kalender W
Published: July 2007

Purpose: Dose assessment in flat‐detector CT (FD‐CT) combining measurements and Monte Carlo (MC) simulations. Material and Methods: FD‐CT scanners provide large irradiation fields of typically 100 mm to 250 mm in the longitudinal direction. In consequence dose assessment according to the current definition of the CTDI would demand larger ionization chambers and phantoms which are not practical. We propose a method which includes a measurement in air or in a phantom with an integrating dosimeter to assess the dose at that point and to combine it with MC simulations to assess 3D dose distributions and integral dose for arbitrary objects and geometries. For validation purposes measurements were performed on a C‐arm system (Siemens Medical Solutions, Forchheim, Germany) equipped with a flat‐detector of 40 × 30 cm2. Dose was assessed for various tube voltages in cylindrical PMMA phantoms of 16 cm and 32 cm diameter with a varying z‐extent from 15 to 60 cm. The MC results were compared to the values obtained with calibrated ionization chambers of 100 mm and 250 mm length and to TLD dose profiles along the complete z‐extent of the phantoms. Additionally a comparison to measurements of dose distribution in an anthropomorphic phantom was performed. Results: The MC simulation was in agreement with the reference TLD measurements to within better than 10%. Standard CTDI phantoms with a z‐extent of 15 cm underestimate the dose at the center by up to 20% whereas a z‐extent of 300 mm appears to be sufficient for FD‐CT. The 100 mm chamber underestimates the measured CTDI value by over 40%. The MC tool can be used to calibrate the measurements with the ionization chamber of 100 mm. Conclusion: The combination of measurement and validated MC tool appears to be a flexible solution to assess arbitrary dose characteristics.
TU‐C‐M100J‐01: Assessing Residual Motion for Gated Proton‐Beam Radiotherapy
Authors: Sharp G , Lu H , Trofimov A , Tang X , Jiang S , Turcotte J , Gierga D , Chen G , Hong T
Published: July 2007

Purpose: To examine the influence of phase delays and baseline drifting on residual motion in gated radiotherapy. Method and Materials: Four patients with hepatocellular carcinoma were studied within a phase I clinical trial for gated proton beam radiotherapy. Between 3 and 5 gold fiducial markers were implanted in or near the tumor site to serve as internal surrogates for the treatment target. The Varian Real‐time Position Management (RPM) system was used as an external surrogate for respiration. The RPM was synchronized to an orthogonal bi‐plane fluoroscopic imaging system, and simulation sessions were conducted under free breathing. The three‐dimensional coordinates of each marker were tracked retrospectively, and compared with the synchronized RPM signal. The phase delay from internal position to external surrogate, and baseline drifting of the exhale position over the course of several minutes were measured, and their impact on gated treatment was assessed. Results: Phase delays were found, ranging from −0.02 seconds to +0.22 seconds, indicating that motion inside the liver may not be seen immediately on the external surface. Phase delays varied from marker to marker, and also over time during the course of 4 to 6 minutes. Baseline drifting was also found in two of the four patients, indicating that the exhale position of the liver may not be stable within the first several minutes after lying on the treatment couch. The baseline drift was usually from inferior to superior, with values ranging from −1 mm to 6 mm. The worst‐case residual motion of an amplitude‐gated treatment was estimated to be 7.4 mm. Conclusion: We observed phase delays of more than 100 ms in two of four patients, and baseline drifting of 5 mm or more in two of four patients. The utility of external surrogates for gating should be studied in more detail.
TU‐C‐M100J‐02: Direct Detection of the Tumor Trajectory Using Raw Cone Beam CT Projections
Authors: Hugo G , Liang J , Yan D
Published: July 2007

Purpose: To develop and evaluate a template matching algorithm for direct detection of a lung tumor trajectory in the raw projections acquired from a cone beam CT. Method and Materials: A planning respiration‐correlated CT (pRCCT) was used to construct digitally‐reconstructed radiographic (DRR) templates for registration with raw projection data of a free‐breathing cone beam CT (FB‐CBCT). The pRCCT and FB‐CBCT were first registered to obtain the approximate mean 3D position of the tumor. This position was applied as a shift to the planning isocenter in the pRCCT. Next, 72 DRRs were generated at 5 degree angular increments around this shifted position, for each phase in the pRCCT. The appropriate phase DRR template for registration was selected using the measured phase of the FB‐CBCT projection. This phase was measured by tracking the diaphragm apex position in the projections. Two template matching algorithms were compared: normalized cross correlation and a block normalized cross correlation. A dynamic phantom was induced to move reproducibly 2cm during planning and 3cm during online CBCT imaging. The phantom was imaged at isocenter and with a 1cm translational shift from isocenter. Results: The tumor excursion measured with the normalized cross correlation method was 28.7 mm, and 28.5 mm with the block normalized cross correlation. The error in detecting the daily standard deviation of tumor position was 0.1mm for both methods. The mean absolute difference in detected tumor position was 1.07 mm, with a 95% confidence value of 2.43 mm. Block normalized cross correlation reduced the maximum error in tumor position detection slightly, in relation to normalized cross correlation. Conclusion: Direct detection of the tumor position from cone beam CT projections is feasible with template matching, provided that appropriate and accurate templates are used. Conflict of Interest: Supported in part by NIH R01 CA116249 and Elekta, Inc.
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‐05: Image Guided 4D Monte Carlo Study of the Dosimetric Effects of Intra/inter Fraction Motion in Lung Tumors
Authors: Seco J , Gianolini S , Sharp G , Wu Z , Gierga D , Buettner F , Paganetti H
Published: July 2007

Purpose: Application of an image guided 4D Monte Carlo framework to the evaluation of intra/inter fraction motion effects between patient organ‐movement and dynamic delivery effects Materials & Methods: An IGMC toolkit that accounts for time‐dependent geometries of organ motion and dynamic delivery and provides accurate dosimetry was developed for lung cancer patients. Fluence calculation for VARIAN‐2100C/D photon accelerator is performed with EGSnrc and for patient dose calculation we use dose‐planning‐method. The time dependent beam delivery information is obtained from the treatment‐planning program in the form of MLC leaf‐sequencing files, while the organ motion pattern was obtained with the use of RPM signal and 4D‐CT. A voxel displacement map is used to quantify the motion of the organ in the voxelized geometry. The study was performed for lung patient for several breathing phases. The data analysis was performed with the freely available package VODCA. Results: Differences between the conventional CORVUS dose plan and the Monte Carlo dose results suggest that Monte Carlo dose calculation is vital for assessing effects in lung tissue. For the free breathing CT, CORVUS was under‐dosing the lung‐tumor by approximately 3Gy. When accounting for temporal effects, comparison between IGMC dose distributions for free breathing, inhale and exhale phases, show that dose coverage of the primary/secondary tumors was significant worse in the inhale phase relative to the exhale/free‐breathing phases. For inhale phase, 5–10% of the volume was receiving 10Gy less than in exhale or free‐breathing phases, leading to large cold spots inside the tumor. This is mainly due to the motion of the diaphragm, which subsequently moves the tumor in the superior‐inferior by more than 2 cm. Conclusions: Image guided 4DMC methods can significantly improve the planning of lung tumor treatments by accurately modeling the motion of the tumors and large heterogeneity in the tumor region. Supported NIH/NCI‐R01/CA111590.
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‐M100J‐10: Respiration Motion Prediction Using Time‐Delay Kernel Regression Modeling
Authors: Seibert R , Ramsey C , Harris C , Garvey D , Hines W
Published: July 2007

Purpose: The purpose of this study was to develop a novel technique for dynamically predicting respiration motion and uncertainty up to 1.5 seconds in the future in real‐time using Time‐Delay Kernel Regression (TDKR) modeling. Unlike neural network based prediction techniques, kernel regression models are continuously learning new respiration cycles for each patient without the need for computationally and time intensive re‐training. Method and Materials: Recorded respiration data from a real‐time respiratory gating system was used to develop a model to predict the amplitude of the marker block at a future time. An empirical TDKR model was designed to compensate for the latency that occurs between the acquisition of the image and the point at which the beam actually turns on/off in beam tracking systems. This non‐parametric model incorporates the temporal information present in the input data. The model was tested using respiration data from 4 patients. Results: The rootmean squared error (RMSE) between the model prediction's and the measured data was computed for each patient at different latencies, and then the average was taken over all the patients. For predictions 1.5 seconds into the future the average RMSE was 1.4%. For predictions 1 second into the future, the RMSE dropped to 1.2%, and for 0.5 seconds it was only 0.7%. The average uncertainty for the predictions at 0.5, 1, and 1.5 seconds into the future was 2.4%, 3.2%, and 3.4%, respectively. Conclusion: This study proves that a TDKR model can learn the relationships present in respiration data. The reported results showed that the TDKR model has the same, if not better predictive performance, as previously studied parametric models. However, because TDKR is non‐parametric, it has several distinct advantages over these models that make it more suited for respiratory gating applications.
TU‐C‐M100F‐02: Quantification of Global Changes in Normal Appearing Brain Tissue of Cerebral Tumor Patients During Early‐Delayed Phase After Radiation Therapy
Authors: Nagesh V , Chenevert T , Tsien C , Junck L , Ross B , Lawrence T , Cao Y
Published: July 2007

Purpose: Radiation therapy (RT) affects the central nervous system manifesting in neurological complications. The aim was to quantitatively assess early‐delayed changes in normal‐appearing brain tissue (NAT) ensuing RT using diffusion tensor imaging (DTI). We hypothesize that there are diffuse changes in NAT with degradation in structural integrity due to radiation. Methods: Twenty‐five patients with cerebral tumor (17 men, 8 women, median age 60 years) participated in IRB approved clinical MRI studies. Temporal changes in NAT were studied pre‐RT, 3‐ and 6‐weeks during RT, and post RT at ten‐, and 19‐weeks from start of RT. RT doses ranged from 50 to 81Gy. The DTI indices of fractional anisotropy (FA), mean diffusivity 〈D〉, eigen‐diffusivities parallel (λ∥) and perpendicular (λ⊥) to axonal fibers, of water diffusion were calculated on a voxel‐by‐voxel basis from DTI. Normal brain tissue, excluding tumor and cerbero‐spinal‐fluid was categorized into two volumes of interest, either ipsilateral or contralateral to tumor hemisphere. Temporal changes in DTI indices were expressed as percentages. For example, percent change in FA during third week of RT is expressed as = 100*[(FAt=3week − FAt=Pre‐RT)/ FAt=Pre‐RT]. Results: There were significant changes in DTI indices after completion of RT in both the ipsilateral and contralateral NAT. Post RT at 19‐weeks, there was 10% increase in λ∥, 15% increase in λ⊥, 13% increase in 〈D〉, and 13% decrease in FA. The λ⊥ increase was 1.5 times that of λ∥. Magnitude of change was higher in ipsilateral compared to contralateral, with ipsilateral changes assuming significance earlier. However, contralateral changes tended to approach those of ipsilateral at 19‐weeks. Conclusions: Significant and gradual increases in eigen‐diffusivities indicate degradation of structural integrity. Changes in ipsilateral and contralateral hemispheres during and post RT signify diffuse bilateral structural degradation. Spatio‐temporal radioresponses noted herein emphasize minimizing dose to critical CNS structures and pathways.
TU‐C‐M100F‐06: Assessment of Lung Tumor Response Using CT‐Based Image Guided Therapy
Authors: Ramsey C , Seibert R , Hines W , Meeks S , Langen K , Li X
Published: July 2007

Purpose: The purpose of this study was to develop and test a novel model for actively predicting the tumor's size, location, and mass while the patient is undergoing radiation therapy. Given that local failure represents the most common mode of failure for lung cancer, the ability to predict changes in the size and mass of the residual tumor mass has a high level of clinical significance. By predicting the tumor's future behavior, it is possible to prospectively design an integrated boost to the location of the residual tumor mass. Method and Materials: For 23 easily visualized lesions, tumor volume was measured over the course of treatment using MVCT imaging. The masses of 15 lesions were also measured. Individual response models were created for these lesions using Locally Weighted Regression (LWR). Each model was created using the measured volumetric and mass responses for the remaining lesions. All data related to the lesion being used to test the model were excluded. The model inputs included the measured volume or mass from early in the treatment. Which variables to include, and the combination of observation days was determined using a genetic algorithm (GA) based optimization. Results: The average error between the true and predicted final volumes was 4.5%, while the error for the final mass predictions was 14.6%. The LWR model was accurate in its predictions made at the end treatment. However, the uncertainty in the shape of the tumor response curve increased near the middle of treatment. Conclusion: A novel technique has been developed for predicting lung tumor response. Even with a relatively small patient database, the predicted responses (and their associated uncertainties) at the end of treatment were in agreement with measurement. These results confirm the accuracy that can be achieved by this non‐parametric model when applied to lung data.
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‐AUD‐01: Visual Sensations During Megavoltage Radiotherapy to the Orbit Attributable to Cherenkov Radiation
Authors: Asadi‐Zeydabadi M , Newman F , Stuhr K , Ding M , Durairaj V , Kavanagh B
Published: July 2007

Purpose: To compute and to verify experimentally Cherenkov radiation production inside the eye from direct and indirect high energy x‐ray irradiation of the orbit and that it exceeds detectability of Cherenkov radiation in scotopic vision. We show that the Cherenkov yield for direct and indirect irradiation exceeds the detection threshold of 6.4×107 photons/m2s. Methods: In photon and electron beam radiotherapy of intraorbital and periorbital tissues, patients commonly report having light sensations during treatment. The explanation usually offered is that ‘nerve stimulation’ is occurring. The radiotherapy literature reports the effect to be the result of ‘phosphenes’. Although phosphenes may play a role, we propose instead that patients are predominantly seeing Cherenkov radiation resulting from electrons inside the eye having kinetic energy exceeding the Cherenkov radiation threshold of 0.26 MeV. We consider calculations for direct irradiation of the eye from a portal image and indirect irradiation from treatment of peri‐orbital tissues and show that it exceeds threshold detection. Results: We calculate the Cherenkov yield using analytic methods and the measurements were in good agreement with our calculations. The Cherenkov radiation from a distilled water phantom, a square plastic phantom and an anthropomorphic plastic phantom were readily visible with a high quality CCD video camera. A digital camera captures the images from the console monitor. Threshold detection of Cherenkov radiation emanating from the water phantom through the video camera was determined and compared to a measurable source. The calculations for the water phantom match reasonably well with measurements and are roughly 1 lux and 3 lux respectively. Conclusion: We show images of Cherenkov radiation emanating from routine radiotherapy treatments and demonstrate that measurements corresponding to these images match well with calculations. We show that the Cherenkov component generated inside ocular media is sufficient to be detected by the patient.
TU‐C‐AUD‐05: Energy‐Range Relations and An Analytical Integration Procedure of Bethe‐Bloch Equation
Authors: Ulmer W
Published: July 2007

Purpose: A calculation procedure of energy‐range relations of protons, of the residual energy E(z) and its gradient dE(z)/dz according to Bragg‐Kleeman rule and its relativistic generalization and to an analytical integration of Bethe‐Bloch equation (BBE) is presented. The determination of LET as a function of E(z) only works reliably on the base of BBE. Method and Materials: The Bragg‐Kleeman rule results from a modified Langevin equation. A relativistic extension reads: , where E0: initial energy, RCSDA: range according to continuous‐slowing‐down‐approximation, and Mc2: proton rest energy. A suitable transformation provides a complete integration of BBE. The solutions are compared with GEANT4. Results: The dimensionless power p of Bragg‐Kleeman rule is energy‐dependent, if the same accuracy of RCSDA, E(z) and dE(z)/dz as by BBE is required. The exact integration of this theory removes the singularities occurring in numerical Monte‐Carlo procedures (cutoff in GEANT4: 1 MeV) mainly by the shell correction, which compensates the logarithm term of BBE. For therapeutic proton energies with E0 ⩽ 300 MeV simple analytical solutions of RCSDA(E0), E(z) and dE(z)/dz will be presented in terms of a power expansion and/or of a sum of 5 exponential functions. Conclusion: The new integration procedure of BBE prevents singularities in the domain of the Bragg peak and at . This provides an accurate determination of the LET (dE/dz as a function of residual energy E). A subjection of the analytical solutions to a convolution (energy‐straggling) reduces the LET in the environment of the Bragg peak and at the distal end of the Bragg curves. The calculation of LET according to Bragg‐Kleeman rule should also be avoided, since it implies a singularity at .
TU‐C‐AUD‐10: Evaluation of a Model Based Segmentation Algorithm for Automatic Contouring
Authors: Chase D , Ramsey C , Seibert R , Robison B
Published: July 2007

Purpose: The purpose of this study was to quantitatively evaluate the commercially available Model Based Segmentation (MBS) tools in Pinnacle. The first specific aim was to compare the time required to contour structures manually verses the automatic MBS. The second specific aim was to evaluate the algorithm's ability to propagate GTV contours from the treatment planning dataset to CT images obtained during image‐guided radiation therapy. Method and Materials: The MBS algorithm was evaluated using the time required to generate the contours, a visual evaluation of the contour accuracy, and a quantitative analysis of the volumes. The quantitative evaluation of volumes was performed by comparing the calculated contour volume for both techniques. The propagation of contours was evaluated using the daily MVCT images of 8 lung cancer patients. For each patient, the GTV was manually contoured on the treatment planning CT image, and on all MVCT images. The treatment planning contours were used to create a new MBS model for each patient that was then propagated and adapted to each MVCT image. The mesh structures were then converted to contours and evaluated for accuracy. Results: The study showed that using MBS can save a significant amount of time on many structures, but that the rectum, bladder, and orbits took longer to contour with MBS. It was also found that the MBS tools could successfully propagate contours from the treatment plan. Without MBS, 45 to 120 minutes were spent manually contouring the GTV on each MVCT dataset. In contrast, the time required to perform the propagation of contours to +20 MVCT datasets was less than 5 minutes. Conclusion: Model‐Based Segmentation is an efficient alternative to manual contouring. It can be especially helpful for IGRT applications. With the MBS tools, it is possible to rapidly contour and measure tumor response to treatment.
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‐D‐L100J‐04: Respiration Motion Correction in Helical Tomotherapy Imaging
Authors: Outten S , Seibert R , Ramsey C
Published: July 2007

Purpose: In helical tomotherapy, Megavoltage CT (MVCT) images are acquired at a rate of one transverse slice per five seconds. The slow acquisition of raw data results in CT images with varying degrees of motion‐induced artifacts. In addition, the high energy of the x‐ray beam (4–6 MV) presents unique challenges for image reconstruction. The purpose of this work was to correct for motion in the superior‐inferior (S/I) direction using retrospective manipulation of the unprocessed sinogram data. Method and Materials: A respiratory motion platform with a S/I motion range of 3‐cm, and periods of 2, 4 and 6 seconds was used to move an ACR CT accreditation phantom and a anthropomorphic thorax phantom in the superior‐inferior direction. The motion of the respiratory platform was measured using the Varian respiratory gating system. Sinogram data was acquired axially with the couch stationary for 5 complete rotations of the gantry. The respiration cycle was synchronized to the projections in the raw sinogram so that the position of the moving object was known in each projection. Motion correction was performed by identifying and extracting projections occurring within a specified respiration phase, correcting for missing projections, and then reconstructing the CT images. Results: Images acquired with the ACR CT phantom showed considerable improvement with motion correction using temporal re‐binning over the uncorrected images. Images acquired with the RANDO phantom suffered from greater image artifacts than the ACR phantom because of the larger variation in the phantom's anatomy over the 3‐cm range of S/I motion. Improvement was seen for each period, however only slight improvement was seen for the 2‐second period of motion. Conclusion: Temporal re‐binning can successfully reduce S/I motion artifacts in reconstructed MVCT images. Conflict of Interest: This research is supported by TomoTherapy, Inc.
TU‐D‐L100J‐07: The Use of CT Dual‐Energy Subtraction Imaging to Detect Kidney Stones Amid Iodinated Contrast Material
Authors: Dzyubak OP , Primak AN , Takahashi N , Vrtiska TJ , Hartman RP , Kawashima A , Fletcher JG , Yu L , McCollough CH
Published: July 2007

Purpose: Iodinated contrast excreted into the renal collecting systems and ureters is of similar CT attenuation as kidney stones, making stones difficult or impossible to detect in contrast‐enhanced CT scans. This necessitates precontrast imaging for kidney stone work‐up. Our purpose was to determine the ability of CT dual‐energy subtraction imaging to selectively remove iodine signal while preserving the signal from kidney stones. Method and Materials: A phantom containing twenty kidney stones with different composition (calcium oxalate monohydrate, calcium hydroxyapatite, uric acid) and size (2 – 6 mm) was scanned with the stones surrounded by water or an iodine/water solution (500, 1000, 1400, 1900, 2300 HU at 120 kV) using a dual‐source CT system (Siemens Definition) and 80/140 kV tube potentials. Iodine calibration curves were generated to determine the CT‐number ratio between the low and high‐kV images and energy subtraction images created. Patients with known stone disease were scanned using the same radiation dose as for single‐energy CT as part of clinically‐indicated examinations. Subtraction images were created and compared to images of the known stone location. Results: Image subtraction performed using the empirical calibration curves was successful in removing iodine signal and preserving stone signal for all evaluated stones. One calibration factor to remove iodine signal was successful for all concentrations below the saturation limit, demonstrating independence of the technique on iodine concentration. In initial patient studies, the stone(s) remained visible after subtraction of the iodine signal, demonstrating the potential of the technique in vivo. Conclusion: Dual energy CT can successfully remove iodine while preserving the signal associated with renal stones. This capability may allow the elimination of the non‐contrast phase of CT urogram studies, which may decrease the radiation dose to the patient by 50%. Conflict of Interest: Partial research support from Siemens Medical Solutions.
TU‐D‐L100J‐08: Image Quality Enhancement in MVCT Scanning
Authors: Overbeck C , Varadhan  , Hui S
Published: July 2007

Purpose: TomoTherapy uses Megavoltage CT (MVCT) to verify patient position and alignment prior to treatment and it is usually good enough to verify the patient's position and anatomy prior to treatment. However, sometimes, a greater resolution and contrast in patient images obtained by the MVCT scan would be beneficial in verifying patient anatomy and set‐up. The effects of changing different machine parameters and consequently the signal to noise ratio (SNR) had on MVCT image quality and resolution were studied. Method and Materials: The machine parameters were changed in two ways and their effects on MVCT image quality were studied, first by imaging with different doses, and then with different beam energies. A cylindrical phantom with a resolution plug (different size holes) was scanned. The machine pulse amplitude control (PAC) value was varied in intervals to adjust delivered dose and the resulting images were analyzed. CTDI measurements were then made at each of the varying PAC values. A Catphan phantom was imaged to measure low contrast visibility, uniformity, and spatial resolution. Next, the injector current (INJI) was changed to modify the MVCT beam energy. The cylindrical phantom was scanned again and the Catphan phantom tests were repeated Results: Increasing the PAC value leads to an increase in dose. In observing the images that were taken, it can be see that the resolution and quality of the image improves as the PAC value is increased. Also the low contrast visibility and uniformity of the images improve. The images were not noticeably improved as much for changes to INJI as measured visually or by imaging tests. Conclusion: Slightly higher dose during a MVCT scan can improve the image quality and resolution for the TomoTherapy system. These observations will be used in future investigation of more complex imaging tasks to improve MVCT imaging.
TU‐D‐M100J‐01: The Great Debate: The Future of IGRT Is…Megavolt CT…Kilovoltage CT…Ultrasound‐Based Hybrids…MRI Guidance…3D Deformable Image Registration
Authors: Pouliot J , Sonke J , Tome W , Lagendijk J , Brock K , Kessler M , Siewerdsen J
Published: July 2007

Introduction: Image‐guided radiation therapy (IGRT) promises to reduce or eliminate conventional limitations posed by geometric uncertainty, opening the way for dose escalation, margin reduction, innovative treatment techniques, hypofractionation, patient‐specific protocols, reduced normal tissue toxicity, and increased tumor control. This symposium presents a debate regarding the numerous technologies brought to bear in IGRT, including image — and information‐based technologies for therapy guidance. Topics and Speakers: The symposium features five distinguished speakers. Dr. J. Pouliot will present on the topic of megavoltage (MV) CT and cone‐beam CT (CBCT), reviewing the advances and advantages associated with imaging the patient in the treatment position with the therapy beam itself. Dr. J.‐J. Sonke will present the case for kilovoltage (kV) CBCT, discussing the latest advances in CBCT technology, image quality and accuracy, and protocols for offline, adaptive, and online 3D and 4D guidance. In light of the radiation risk posed by such modalities, Dr. W. Tome will present a strategy that hybridizes MV or kV CBCT (obtained at weekly intervals) with 3D ultrasound (obtained for daily guidance), wherein a (weekly) gold‐standard 3D ultrasound image provides close correspondence to CBCT. In this way, conventional uncertainties in ultrasound‐based alignment are minimized, and accurate daily ultrasound guidance is achieved with a ∼80% reduction in cumulative dose to the patient. Dr. J. Lagendijk will offer an innovative approach in which the treatment machine is fully integrated with magnetic resonance imaging (MRI), allowing precise soft‐tissue visualization for online guidance, verification, monitoring, and biological optimization. The technological challenges and advances in such development are described, including potential applications in treatment of the prostate, cervix, liver, and lung. Finally, Dr. K. Brock will argue that the future of IGRT lies not within a given imaging modality, but in the use of multiple structural and functional modalities geometrically resolved by means of deformable modeling. By combining diagnostic quality images with daily IGRT, accurate tumor targeting can be achieved in a manner that accounts not only for daily setup error but also morphological deformation and physiological change over the course of treatment. Format: The debate will consist of three rounds: 1.) a summary / overview of each IGRT approach; 2.) presentation, debate, and rebuttal regarding the role of each approach in the future of IGRT; and 3.) open format question and answer from the panel and audience. Time and technology permitting, a winner will be informally determined by feedback from the audience.
TU‐D‐AUD‐05: Comparison for Analytical Anisotropic Algorithm and Adaptive Collapse Cone Convolution Algorithm for Small Field Dosimetry
Authors: Rong Y , Mubata C , Tewatia D , Paliwal B
Published: July 2007

Purpose: The objective of this study is to compare the calculation accuracy of Analytical Anisotropic Algorithm (AAA) to that of Adaptive Collapse Cone Convolution (CCC) algorithm for small beam sizes where the electron disequilibrium becomes significant. Method and Materials: The comparison of CCC and AAA calculations were performed for various field sizes (2×2, 4×4, 6×6 and 10×10) at 6‐ and 10‐MV photon energies on different phantom situations (homogeneous water phantom, cork/water heterogeneous phantoms, step phantom and IMRT lung phantom). Treatment plans for open beams, MLC shaped beams and IMRT plans were created and calculated by each algorithm. Absolute dose comparisons were made based on measurements, calculations and Monte Carlo Simulations. The XV radiographic films, GAFCHROMIC_EBT radiochromic films, PTW Ion Chamber and Sun Nuclear Map checker were used for measurements. Results and Conclusions: Point dose comparison along the central axis of beams shows that in homogeneous phantom AAA predicts dose within 2%, which is compatible to CCC. For the heterogeneous phantom with vertical density gradient, AAA predicts an up to 5% difference and compared to CCC with less than 2.5% difference. Depth Dose curves also showed that AAA overestimates the dose after passing through low density region. But inside the low density region, AAA gives a compatible prediction to CCC for very small fields. For those points far from heterogeneity, AAA results show a relatively good estimation. Profiles at different depths in the phantoms with density gradient along horizontal direction show that AAA does not model lateral scatter adequately which leads to discrepancies of up to ± 7% in the region of ±1cm lateral from the heterogeneous interface, compared to less than 2% for CCC. Planar dose comparison for IMRT plans shows AAA calculated dose fluence matches with film measured data.
TU‐D‐AUD‐07: The Design and Performance of a Simplified Independent Tomotherapy Treatment Planning System
Authors: Shaw R , Kao M , Steidley K
Published: July 2007

Purpose: A simplified helical‐tomotherapy independent planning system (SHIPS) is developed for independent verification of the TomoTherapy Hi‐ART (TomoTherapy Inc. Madison, WI) treatment scheme and to provide an alternative method to produce helical tomotherapy plans. The SHIPS software is designed to be simple, so the program can run a desktop PC, straightforward, so the delivery scheme is intuitive, and streamlined, to speed the treatment planning process. Treatment plans created with SHIPS may be used in cases where the Hi‐ART's inverse planner may be unnecessarily complex. We present the design of SHIPS and compare its results against forty Hi‐ART treatment plans. Several SHIPS derived tomotherapy plans are presented. Methods and Materials:SHIPS produces a treatment delivery scheme based on patient geometry and contours, prescription, delivery settings (e.g. pitch, field size, and modulation factor), and measured beam data. SHIPS calculates a leaf‐sequencing pattern (a treatment sinogram), gantry rotation period (GRP), couch speed (CS), couch travel length (CTL), monitor units (MU), and time of treatment (T). Treatment plans used to compare against SHIPS consist mostly of prostate patients with some head and neck, pelvis, lung, and phantom cases. SHIPS is used to create example prostate, breast, and brain treatments. Results: SHIPS can produce conformal tomotherapy plans for imbedded (i.e. prostate), distal/convex (i.e. breast), and large/shallow (i.e. brain) targets in less than 30 seconds. When compared against Hi‐ART treatment schemes, the average deviation of the calculated CTL, T, CS, and MU are, respectively, 0.08%, 0.05%, 0.37%, and 0.74%. Conclusion: SHIPS bypasses the Hi‐ART's optimizer producing independently derived plans, quickly. SHIPS can be used for quality assurance of the entire treatment planning process. Treatment parameters generated from SHIPS agree within 1% of the Hi‐ART values. SHIPS challenges the degree of which the Hi‐ART's complex inverse‐planning is necessary.