bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐I‐158: A Feasibility Study of SPECT Mode in Multi‐Modality System Based on Fabricated CsI(Tl)‐PIN Photodiode Detector in Circular Geometry
Authors: NA T , HA J , KIM H , Lee R
Published: November 2011

Purpose: During the past several years there has been used of SPECT for optimizing the diagnostic capabilities by single photon imaging. SPECT produces computer‐reconstructed gamma‐ray images by up‐taken radiotracer. The existing clinical SPECT have two scintillation NaI(Tl) detectors, positioned at 90° to 180°. The purpose of this study is to test the feasibility of SPECT system consisted of fabricated CsI(Tl)‐PIN photodiode detectors with circular geometry like PET and CT geometry for multi‐modality applications. Methods: The sensors are fabricated with CsI(Tl) scintillator which is matched with PIN photodiode. And The single CsI(Tl)‐PIN photodiode detector are housed with a preamplifier and a shaping amplifier. Each detectorˈs energy spectrum was measured by standard NIM module system. The detectors of SPECT system were positioned at angular interval of 18° in circular geometry. The imaging data of 137 Cs source was obtained by an SCA(single channel analyzer) and a counter system. Results: The average energy resolution of detectors was 11.16 % at 662 keV from 137Cs gamma‐ray source. The feasibility test of SPECT system for image was performed at five positions included center position of system. Conclusions: In this study, CsI(Tl)‐PIN photodiode detectorsˈ energy spectrum were measured. The feasibility test was performed for SPECT system application. The detectors show appropriate energy resolution for SPECT application. By measuring of gamma‐rays at separated positions, we could reconstructed gamma‐ray images according to various source locations.
SU‐E‐I‐159: Delaunay Triangulation for Angular Interpolation and Single Stage Reconstruction of EPRI
Authors: Bryant Jonathan H. , Epel Boris , Halpern Howard J.
Published: November 2011

Purpose: To employ Delaunay Triangulation of projection orientations in 3D electron paramagnetic resonance imaging (EPRI) for multidimensional angular interpolation and the duel tessellation (Voronoi diagram) for weighting coefficients enabling reconstruction by single stage inverse Radon Transform without the necessity of regridding data. Methods: Standard 3D pulsed EPR oxygen images were acquired of an OX063 phantom with projections in an approximately uniform but none rectilinear fashion. The projection orientation was mapped to a unit sphere, and the Delaunay triangulation was calculated for these points on the surface. Projections were interpolated to the incenter of each triangulation using a weighted mean of projections located at the vertices. The Voronoi diagram was then calculated, partitioning the surface of the sphere such that each projection was associated with a spherical polygon. The area of these polygons was used as a weighting coefficient for calculation of the discrete surface integral in the filtered backprojection (FBP) algorithm. Results: We were able to successfully reconstruct images using angular interpolation and the FBP algorithm without decomposition of the problem into stages of 1D interpolation and line integrals. Examination of images indicates improved ability to resolve oxygen concentration of phantoms Conclusions: Direct single stage reconstruction from non rectilinear sampling is an important progression in ERPI as it avoids the filtering effects of interpolation in regridding and multistage reconstruction. Proper analysis of the angular distributions of projections will allow for unrestricted sampling choices and potential optimization. Since sampling requirements of the discrete inverse Radon transform scale rapidly with higher dimension, angular projection interpolation is an important technique for artifact avoidance that must be reproduced in the move from single to multistage reconstruction. This work will form the basis for future investigation into the reconstruction of EPRI.
SU‐E‐I‐160: Initial Scatter Quantification in Flat Panel Based First Generation Coherent Scatter CT of the Breast
Authors: Ahmad B , Aviles J Alpuche , Pistorius S
Published: November 2011

Purpose: The aim of this study was to investigate the distribution of single coherent scatter of a flat panel based first generation breast CT system using computer simulations. Methods: The phantom, beam and detector were Monte Carlo simulated using the Easy Particle Propagation user code. The breast was simulated using a 50/50 cylindrical breast phantom with a diameter of 14 cm and a height of 10.5 cm. The number of incident photons was set to result in a dose of 4 mGy for a 3D breast scan of 288 projections. The beam and detector were translated across the phantom in steps of 0.1 cm for one projection. In order to improve the signal to noise ratio (SNR) from coherent scatter, a ring integration was performed such that signal from pixels whose centers were at distances r (with r being the distance from the center of the detector) were summed. Ring widths of 50 microns, 250 microns, 500 microns and 1 mm were probed. Detector phantom separations (DPS) of 1 cm and 11 cm were also investigated. Results: A DPS of 11 cm provides more CS than any type of contaminating scatter in the desired momentum transfer (MT) range. A ring width of 1 mm provides a ring width with the best SNR while keeping the necessary MT resolution to theoretically resolve glandular tissue and carcinoma. The total number of CS photons per ring can vary by as much as 30% for beams that go through different thicknesses of the phantom. Conclusions: We have implemented and validated a simulation of flat panel based first generation CT of the breast. The detector phantom separation and the different ways of reading the signal on the detector affect the magnitude of coherent scatter and, consequently, its application for imaging.
SU‐E‐I‐164: Maternal Magnetocardiographic Interference Cancellation Using Splined Independent Component Subtraction
Authors: YU S , Wakai R
Published: November 2011

Purpose: Signal distortion is commonly observed when using independent component analysis (ICA) to remove maternal cardiac interference from the fetal magnetocardiogram(fMCG). This can be seen even in the most conservative case where only the independent components dominated by maternal interference are subtracted from the raw signal, a procedure we refer to as independent component subtraction (ICS). Distortion occurs when the subspaces of the fetal and maternal signals have appreciable overlap. To overcome this problem, we propose a new method for reducing the signal distortion. Methods: we employed splining to remove the fetal signal from the maternal source component. The maternal source components were downsampled and then interpolated to their original sampling rate using a cubic spline. The splined maternal source components were projected back onto the magnetic field measurement space and then subtracted from the raw signal. The method was evaluated using data from 24 subjects. We compared the results of conventional, i.e. unsplined, ICS with our method, splined ICS, using matched filtering as a reference. Correlation and subjective assessment of the P‐wave and QRS complex were used to assess the performance. Results: Using ICS, we found that the P‐wave was adversely affected in 7 of 24 (29%) subjects, all having correlations less than 0.8. Splined ICS showed negligible distortion and improved the signal fidelity to some extent in all patients. We also demonstrate that maternal T‐wave interference can be problematic when the fetal and maternal heartbeats are synchronous. In these instances, splined ICS is more effective than matched filtering. Conclusions: Splined ICS overcomes the problem of ICA signal distortion that has limited its utility for assessment of fetal rhythm. The method is very simple to implement and is suitable for routine processing of fMCG recordings. NIH grant R01 HL63174.
SU‐E‐I‐166: Investigation and Development of Point‐Based Image Reconstruction Algorithm Capable of Handling Non‐Rigid Motion
Authors: Klyuzhin I , Sossi V
Published: November 2011

Purpose: To evaluate PET image reconstruction algorithm capable of handling moving, deformable objects, particularly unrestrained conscious rodents. Methods: The proposed point‐based image reconstruction algorithm is based on 2D filtered back‐projection. Reconstruction took place in 2D virtual space filled with dimensionless sampling points. During the backprojection, points acted as spatial count bins, accumulating values of the backprojected LORs. To correct for motion, sampling points in the image space were moved in accord with the scanned object. Thus, motion correction and deformation correction were performed via image bin repositioning. After the backprojection step, images of activity distributions were obtained by fitting a smooth surface over the sampling points. Results: To evaluate the performance of the image reconstruction algorithm, stationary and moving NEMA image quality phantoms were scanned on Siemens Focus 120 microPET scanner, and data was reconstructed using conventional 2D filtered back‐projection and point‐based algorithms. Images obtained using two reconstruction algorithms were in remarkable quantitative agreement, with deviations mostly in the background and on the order of few percent. The location of points during reconstruction had little influence as long as Nyquist sampling criteria was satisfied. For the point‐ based reconstruction, motion‐corrected images preserved quantification and demonstrated good performance in removing the motion artifact. The SNR of motion‐corrected images also improved compared with shorter but motion‐free frames. Conclusions: It had been demonstrated that point reconstruction can provide accurate, quantitative PET images. As opposed to voxels, points can be moved freely relative to one another. By moving points during the backprojection process, almost any kind of deformation can be taken into account. Plans for the future include further method development of the method to enable full 3D list‐mode reconstruction, which could ultimately lead to unrestrained conscious rodent imaging.
SU‐E‐I‐167: Impact of Peak SUV Definition on Quantification of Treatment Response
Authors: Vanderhoek M , Perlman S , Jeraj R
Published: November 2011

Purpose: PET‐based treatment response assessment typically measures the change in SUVmax, which is adversely affected by noise. SUVpeak has been recommended as a more robust alternative, but currently its associated region‐of‐interest (ROIpeak) is not uniquely defined. We investigated the impact of different ROIpeak definitions on quantification of SUVpeak and tumor response. Methods: Seventeen patients with solid malignancies were treated with an anti‐proliferative, molecular targeted agent. Using the cellular proliferation marker [F‐18]FLT, whole‐body PET/CT scans were acquired at baseline and during treatment. Lesions with highest FLT uptake (∼2/patient) were segmented on PET images and tumor response was assessed via the relative change in SUVpeak. For each tumor, 24 different SUVpeak and response values were determined by changing ROIpeak shape, size, and location. Within each tumor, variation of the 24 values was measured using range, coefficient of variation (CV) for SUVpeak, and standard deviation (SD) for response. For each ROIpeak definition, population average SUVpeak and response were determined over all tumors. Results: Substantial variation in both SUVpeak and response resulted from changing the ROIpeak definition. Intra‐tumor SUVpeak variation (CV: 17%) and response variation (SD: 9%) ranged as far as 50% from the mean. Population average SUVpeak variation (CV: 14%) ranged as far as 30% from the mean but population average tumor response variation (SD: 2%) ranged only 3% from the mean. Size of ROIpeak caused more variation in SUVpeak and response than location or shape of ROIpeak. Conclusion: Quantification of individual tumor response using SUVpeak is highly sensitive to ROIpeak definition, which can significantly impact the use of SUVpeak for treatment response assessment. However, population average response is robust to ROIpeak definition. Standardization of SUVpeak is crucial for consistent assessment of treatment response. Clinical trials are necessary to compare the efficacy of SUVpeak and SUVmax for quantification of response to therapy.
SU‐E‐I‐172: Fast Computation of High Resolution LOR‐Based 3D OSEM PET Algorithm Using the GPU Device
Authors: Nassiri M , Després P , Hissoiny S , Carrier J
Published: November 2011

Purpose: The line‐of‐response OSEM (LOR‐OSEM) algorithm allows a PET image reconstruction from sinograms without any data compression(span=1, mashing=1). The main objective of this work is to accelerate the computation of this algorithm for modern PET scanners such as the Philips Gemini GXL by its implementation on modern GPU devices.Methods: We implemented the LOR‐OSEM algorithm on the NVIDIA Tesla 2050 GPU. The implementation incorporates the attenuation and normalization correction in the sensitivity matrix as weight factors (ANW‐LOR‐OSEM algorithm). The system matrices are built on‐the‐fly by using the multi‐ray Siddon algorithm. We used 3 rays per detector pair in the tangential direction and 2 rays in the axial direction. To reduce this computation time, the symmetries of the scanner were exploited. This implementation was validated using Monte Carlo simulated data with the GATE package.Results: The reconstruction was computed for a 188×188×57 array (FOV=376 mm, 2×2×3.15 mm̂3 voxel size) and for a 144×144×57 array (FOV=576 mm, 4×4×3.15 mm̂3 voxel size). If the sinograms are pre‐corrected for attenuation and detector efficiency, and if the projection data matrix which depends only of the scanner geometry is pre‐calculated, the time to compute the LOR‐OSEM algorithm for 10 subsets, 1 iteration and 112 million coincidences is 30.5 seconds for the 188×188×57 array and 29.4 seconds for the 144×144×57 array. This time is 73.4 seconds for the 188×188×57 array and 72.7 seconds for the 144×144×57 array for the ANW‐LOR‐OSEM algorithm Conclusions: The LOR‐OSEM algorithm was successfully implemented on a Tesla C2050 GPU, including the calculation of the sensitivity matrix, for a PET system that has 85 million LORs. The reported reconstruction times are compatible with a clinical use. The NVIDIA Tesla GPU appears to be a low‐cost, high‐ performance solution for advanced PET reconstruction such as real time 4D gated reconstruction.
SU‐E‐J‐49: Evaluation of Deformable Image Co‐Registration in Adaptive Dose Painting by Numbers for Head and Neck Cancer
Authors: Berwouts D , Olteanu A , De Neve W , Vercauteren T , De Gersem W , Madani I
Published: November 2011

Purpose: To evaluate the accuracy of automated contour deformation for head‐and‐neck cancer in adaptive treatment. Methods: Data from 13 head‐and‐neck patients in a phase I trial for adaptive treatment were used. Adaptation was based on [18F]FDG‐PET‐guided dose painting by numbers (DPBN) plans. Each patient had two DPBN plans based on: (i) a pretreatment PET/CT scan and (ii) a during‐treatment PET/CT scan acquired after 8 fractions. Contours manually drawn on the pretreatment CT scan were deformed using commercial deformable image registration software onto the during‐treatment CT scan. Deformed contours of regions of interest (ROIdef) were visually inspected by an experienced radiation oncologist and, if necessary, adjusted (ROIdef_ad) and both sets of contours were compared to manually redrawn ROIs (ROIm) using Jaccard (JI) and overlap indices (OI). ROI indices and volumes were compared for all contour sets used a paired t‐test and one‐way ANOVA pairwise comparison, respectively. Results: Almost all deformed ROIs in all patients required adjustment after visual inspection. The largest adjustments were made in GTVs when substantial tumor regression occured, e.g., ROIdef=9.2 cm3 vs. ROIdef_ad=2.2 cm3 vs. ROIm=2.1 cm3. The swallowing structures were the most frequently adjusted ROIs. The mandible was the most acurately propagated ROI requiring little or no adaptation: JI=0.7 and OI=0.8. The upper esophageal sphincter was the worst propagated ROI: JI=0.3 and OI=0.3 for the ROIdef, JI=0.5 and OI=0.6 for the ROIdef_ad. Despite the variation in indices, there was no statistically significant difference between ROIdef, ROIdef_ad and ROIm volumes. Generating ROIm took 4–6 hours, generating ROIdef took a few minutes and generating ROIdef_ad took less than 2 hours. Conclusions: Deformable image co‐registration followed by visual inspection does require adjustment of most deformed ROIs. Nevertheless, fast automatic ROI propagation followed by user‐driven adjustments appears to be more efficient than labor intensive de‐novo re‐contouring.
SU‐E‐J‐52: The Automated Detection and Scoring Algorithm for Bladder Transitional Cell Carcinoma Screening with PLZ4 Coated Beads
Authors: Li B , Bao S , Chen Q
Published: November 2011

Purpose: One cyclic peptide named PLZ4 was identified that could selectively bind to bladder cancer cell lines and all of the 5 primary bladder cancer cells from human patients, but not to normal urothelial cells, cell mixtures from normal bladder specimens, fibroblasts, and blood cells. Beads coated with PLZ4 will have cancer cells bound on it when used for screen. It is labor intensive for human to read microscope images to make a diagnosis. A computer algorithm is developed to automate the segmentation and analysis. Methods: The computer algorithm has to complete two tasks. First, segment the image to isolate individual beads. Secondly, analysis each bead to determine whether it have cell binding. Various image processing algorithms were applied to pre‐process the image. A flood‐fill algorithm was used to isolate individual beads from background. A rejection mechanism was setup to throw away regions that are mis‐registered as beads to make the algorithm robust. The gradient magnitude of the image was used for deciding whether cell attachment exists. The regions around the edge and inside of the bead were analyzed. Scoring function was setup based on the training data. Results: The algorithm performed well in segmenting individual beads even when a lot of the beads are touching each other. Only about 1% of the beads failed to get detected. The algorithm assigns proper confidence level for cell attachment that is generally agreed by human. The result is improvable when more training data is provided. Conclusions: The automated detection and scoring algorithm for bladder transitional cell carcinoma screening with PLZ4 coated beads is promising for automatic imaging detection during diagnosis and follow‐up/surveillance of noninvasive and advanced bladder cancer.
SU‐E‐J‐54: Evaluation of a Toolkit for Automatic Deformable Registration and Segmentation of Treatment Images in Clinical Prostate Cancer IGRT Applications
Authors: Xu Z , Chaney E , Kress A , Tracton G , Foskey M , Lian J , Chang S
Published: November 2011

Purpose: High quality IGRT is only practical when robust tools are available for accurate and fast deformable registration and segmentation of the treatment images. We have implemented such a toolkit for the male pelvis using a class of statistically trainable deformable models (SDMs) of anatomical structures, called medial representations (m‐reps). The aim of this study is to evaluate its capabilities and performance in clinical prostate cancer IGRT applications. Methods: An image collection for prostate cancer patients treated with IGRT using a CT‐on‐Rails (CTORs) system was studied retrospectively with this toolkit to determine the actual delivered dose throughout the treatment course. The patient‐specific planning models of the male pelvic organs, including the prostate, bladder, rectum, and femoral heads, were constructed via user‐guided autosegmentation of the planning CT. The planning CT was then automatically registered to the CTORs images via a rigid‐body, soft‐tissue‐based registration method. The planning models were then transformed into initialized treatment models to segment the CTORs images. The essential tissue‐voxel correspondence across treatment images was established by this model‐based segmentation process. The dose delivered to the same tissue elements can, therefore, be accumulated for adaptive planning and/or outcome assessment. Results: Preliminary results show that the m‐rep‐based planning image segmentations are clinically acceptable to the physicians and can be readily constructed from the planning CT with nominal user guidance. The automatic image registration with the treatment‐day image, occasionally followed by manual refinement, also considered acceptable by clinical staff. Treatment image segmentation with intrinsic tissue‐voxel correspondence used substantially less time (5 ± 1.3 minutes) in comparison to manual contouring. Conclusions: Our clinic‐oriented toolkit is effective in segmentation of treatment images of the male pelvis. Application for dose accumulation and adaptive IGRT is in progress.

This work has been conducted in collaboration with Morphormics, Inc. with grant support from NCI R44 CA119571.
SU‐E‐J‐56: Statistical Modeling for Quantitative Evaluation of Automatic Anatomy Segmentation in Radiotherapy
Authors: Yang J , Zhang L , Zhang Y , Dong L
Published: November 2011

Purpose: To quantitatively evaluate automatic anatomy segmentation for radiotherapy using a statistical model that can account for the observer variations and to provide a graphical visualization of the segmentation performance. Methods: We proposed to use the binary statistical behavior of voxel overlap to evaluate the performance of segmentation. A statistical model parameterized on a Beta distribution was built upon the observations of the volume overlap between the automatic segmentation and the manual reference contours. A statistical performance profile (SPP) was estimated from the model using the generalized maximum likelihood approach. The SPP defined the probability density function characterizing the distribution of performance values. This method was applied to evaluating auto‐contour propagation for 10 head‐and‐neck cancer patients with a total of 122 daily CT scans. One physician contoured the parotid glands on each daily CT from scratch and modified from deformed contours automatically propagated from the planning CT using a deformable image registration method. Results: The SPP curves characterizing the overlap between deformed contours and manual contours for both parotids showed a mean performance of 0.71 with standard deviation of 0.07. They also showed that the probability of performance value above 0.90 is almost 0. This demonstrated the high intra‐observer variations in contouring head‐and‐neck patients. The SPP curves for the modified contours showed a high performance for both parotids, with mean value around 0.98 and standard deviation of 0.05. The probability of performance value above 0.99 was around 80%. This indicated that the auto‐propagated contours matched well with the physicianˈs judgment. On the other hand, it confirmed that the intra‐observer variations in the manual reference contours had a great impact on the evaluation. Conclusions: We developed a statistical modeling method for evaluating automatic segmentation. The method can quantify the impact of observer variations and graphically visualize the segmentation performance.
SU‐E‐J‐60: GPU Accelerated DRR Computation with Scatter
Authors: Vidal F , Folkerts M , Freud N , Jiang S
Published: November 2011

Purpose: We propose a fast software library implemented on graphics processing unit (GPU) to compute digitally reconstructed radiographs (DRRs). It takes into account first order Compton scattering. Methods: The simulation is based on the evaluation of the Beer‐Lambert law and of the Klein‐Nishina equation. The algorithm is fully determinist and has been fully implemented on GPU to achieve clinically acceptable efficiency. A full resolution simulation is performed for primary radiation. A much lower image resolution is used for Compton scattering as it adds a low frequency pattern over the projection image. Each voxel of the CT dataset is considered as a secondary source. The number of photons that reach each voxel is evaluated. Then, for each secondary source, a projection image is computed and integrated in the final image. The photon energy between each secondary source and each pixel is also computed. An interlaced sampling mode is also proposed to further reduce the computation time without sacrificing numerical accuracy. Finally, the speed and accuracy are assessed.Results: We show that the computations can be fully implemented on the GPU with an original under‐sampling method to produce clinically acceptable results. For example, a simulation can be achieved in less than 7 seconds whilst the maximum relative error remains below 5% and the average relative error below 1.4%. At full resolution, a speed‐up by factor ∼12X is achieved for the GPU implementation with our interlaced‐mode by comparison with our multi‐threaded CPU implementation using 8 threads in parallel Conclusions: DRR calculation with scatter is computationally intensive. The use of GPU can achieve clinically acceptable efficiency. A Compton fluence map can be computed in a few seconds using under‐sampling, whilst keeping numerical inaccuracies relatively low. This work can be used for CBCT reconstruction to reduce scatter artifacts.
SU‐E‐J‐61: Investigation of Retrospective 4D‐CT Reconstruction Strategies to Improve the Image Quality for IGRT Planning and Verification of Moving Targets
Authors: Gaede S , Peat E , Taylor J
Published: November 2011

Purpose: To quantify the dependence of helical‐based 4D‐CT image quality on pitch and to identify plausible correction techniques without increasing mAs.Methods: A commercial respiratory motion quality assurance phantom was imaged using a clinical, helical‐based 4D‐CT protocol on a Philips Big Bore 16‐slice CT scanner (Philips Medical Systems, Cleveland, USA). Scans with identical parameters were repeated under various conditions including breathing period, motion amplitude, pitch, and mAs. Scans were retrospectively reconstructed into ten equal phases (4D phases) of one breathing period. Reconstructed phases were used to generate an average image of all ten phases (avg‐IP) used as a non‐gated planning CT and a subset average of the 30–60% phases (subset‐IP) used as the respiratory‐gated planning CT. Raw data from each scan was also used to reconstruct a low‐pitch helical CT scan call the Untagged Average CT (Untagged‐IP). Analysis of axial slices involved the placement of identical regions of interest (ROIˈs) on predetermined slice locations for moving and static components of the phantom. The average standard deviation (noise) was computed over several ROIˈs for each component.Results: The reconstructed individual 4D‐CT phases, avg‐IP, and subset‐IP demonstrated a strong increase in noise as pitch decreased. Both the avg‐IP and subset‐IP improved over any single phase of the 4D set for all breath rates. The noise in the untagged‐IP was independent of pitch for all breath rates and was consistently lower than the avg‐IP or any phase of the 4D‐CT dataset Conclusions: Decreasing pitch for a helical‐based 4D‐CT scan degrades image quality. Two specific reconstruction techniques that can help compensate for image degradation are, the untagged‐IP for non‐gated cases and the subset‐IP for gated cases. Both techniques can overcome the pitfalls of using a single respiratory phase without increasing mAs.
SU‐E‐J‐64: Margins for Single‐Fraction Treatments: Stereotactic Radiosurgery Brain Cases
Authors: Zhang Q , Chan M , Burman C , Amols H , Ling C , Mageras G
Published: November 2011

Purpose: To determine the appropriate margin expansion from clinical target volume (CTV) to planning target volume (PTV) for single‐fraction stereotactic radiosurgery (SRS). Setting a proper margin is crucial for delivering the right dose to the CTV and sparing of organs at risk. Methods: Whereas in conventional fractionated treatment a Gaussian function is used to represent systemic errors, for single‐fraction treatment with a specific machine, the delta function is more appropriate. As input to the function, we measured the differences between image isocenter and radiation isocenter for a Varian Trilogy linac over a period of six weeks. To approximate the residual setup errors for a population of patients, we adopted a Gaussian function with different standard deviation. A phenomenological formula for calculating the CTV‐PTV margin for single‐fraction SRS brain cases is proposed. For 95% success (CTV received prescribed dose) of patientsˈ treatments, the margin for a single‐fraction treatment is obtained which is a function of standard deviation of the residual setup errors and system errors. Results: The differences between the image isocenter and radiation isocenter remain constant to within sub‐ millimeter during the typical treatment period of six weeks. This confirms our assumption on the system errors distribution as being a delta function and machine‐specific. This definition is especially important for a single‐fraction treatment. Our study found that human factors could also attribute to the reduction of the margin of CTV‐PTV in addition to stability of the treatment machine. Conclusions: A margin formula is proposed for the SRS brain case that attempts to help physicists determine the proper margin of CTV‐ PTV. This margin derivation could also extend for multi‐fraction cases because the system errors do not change from time to time unless system upgrades.

R01‐CA126993
SU‐E‐J‐69: An Anomaly Detector for Radiotherapy Quality Assurance Using Machine Learning
Authors: El Naqa I
Published: November 2011

Purpose: To investigate a new approach and automated quality assurance (QA) tool for detecting radiotherapy errors using machine learning. The proposed datamining approach utilizes anomaly detection based on one‐class estimation to overcome computational challenges of detecting rare events encountered in currently existing techniques. Methods: The proposed anomaly detection approach captures regions in the input space of radiotherapy data where the safe class probability density lives and estimate errors as outliers that reside outside this support region. To model nonlinear support regions, we used a support vector machine (SVM) formalism, in which the QA data is mapped into higher dimensional space using kernel functions to achieve maximal separability and is denoted QA‐SVM detector. We demonstrated our method using forty‐three treatments plans from patients who received stereotactic body radiation therapy (SBRT) for lung cancer. Results: Features related to monitor units, beam energies, number of beams, number of fractions, in addition to V20 were extracted from the DICOM files and used to train the QA‐SVM detector. Using principle component analysis, 5 features were selected and used subsequently. For testing, we used a combination of cases that were considered “safe” with class label “+1” and simulated cases, which were considered “risky” with class label “‐1“. A radial basis function was used as kernel and false positive limit was set at 10%. Our preliminary results indicate a training accuracy of 84% on cross‐validation and testing accuracy of 80% with 100% positive predictive value and 80% negative predictive value. Conclusions: We presented a new approach and tool based on machine learning to overcome the problem of direct modeling of QA errors and rare events in radiotherapy. The tool will be very valuable for automated QA and safety management for patients who undergo radiotherapy treatment.
SU‐E‐J‐70: Computerized Treatment Plan Integrity Verification Using ‘Read‐Only’ Scripting
Authors: Moore K L , Yang D
Published: November 2011

Purpose: Currently Philipsˈ Pinnacle treatment planning system (TPS) is the only commercial TPS with the ability to encode sequences of internal command messages into ‘scripts’ which can be executed by the user within the TPS itself, although other vendors will be incorporating this functionality into future releases. The purpose of this work was to evaluate the use of ‘read‐only’ scripting to improve the safety and quality of the radiotherapy treatment planning process. Methods: ‘Read‐only’ scripting is defined to be routines, called from within a TPS, that do not modify any state of the treatment plan but do allow access to primary data elements, e.g. imaging data, contours, beams, dose grid, and dose volume histograms. A suite of analysis and safeguard scripts were developed using a combination of Pinnacle scripts and Perl routines which accomplish a myriad of clinical goals, including backup of irreplaceable treatment planning information, enforcing naming conventions of contours and beams, checks of the technical integrity of IMRT plans, and standardizing the evaluation of treatment plans. Version control of clinical scripts ensures the integrity and safe usage of the routines themselves. Results: Backup scripts have highlighted edits of tumor volume contours, as well as providing the ability to restore the lost data. Formerly common errors in IMRT planning, such as the creation of fields with in‐field MLC abutments or couch/gantry collisions, have been all but eliminated. Report scripts presenting quantitative dosimetric information to clinicians have reduced the time expended in evaluating the clinical acceptability of treatment plans. Finally, ongoing process improvement studies have been facilitated by the active storage of aggregate planning data. Conclusions: While ‘read‐only’ scripting does not give clinicians the ability to modify elements of the treatment plan, this functionality can be used to ensure a safer and more consistent treatment planning process.
SU‐E‐J‐76: MR Diffusion Tensor Imaging Application in Assessing Cognitive Impairment in Children After Cranial Proton Irradiation
Authors: Grosshans D , Curtis W , Zhu X , Palmer M , Amsbaugh M , Kumar A , Wang J
Published: November 2011

Purpose: Magnetic resonance diffusion tensor imaging (DTI) changes may predict for cognitive impairment following cranial irradiation. We sought to assess temporal changes in white matter integrity in children with brain tumors treated with proton therapy (PT) using DTI. Methods: Six patients with low grade gliomas who had been treated with proton therapy were included. Pre‐therapy as well as the follow‐up scans (including DTI) were registered. DTI parameters were calculated and studied for changes immediately after therapy and over time. Results: In the peri‐tumoral regions which had received irradiation, FA value decreased after treatment while ADC increased over time. Within the tumor region, FA demonstrated a trend of steady increase while ADC decreased over time. Conclusions: Changes in DTI parameters were found in brain regions corresponding to higher radiation doses. In contrast, normal areas spared from excess radiation displayed no change over time. This supports the use of proton therapy for young patients. Future studies will assess patients treated with photon therapy and seek to correlate changes in imaging with cognitive outcomes.
SU‐E‐J‐81: MR‐Based Prostate Radiotherapy Treatment Planning: An Investigation of the Dosimetric Consequences of Distortion Correction
Authors: Baldwin L , Pervez N , Wachowicz K , Fallone B
Published: November 2011

Purpose: To quantify the effect of geometric distortions on patient dosimetry for MR‐based radiotherapy treatment planning (MR‐RTP) and to evaluate the clinical importance of distortion correction. Methods and Materials: Ten prostate patients underwent MR imaging in the standard treatment position. Axial MR images (MRIs) were segmented for bone and tissue, bulk electron densities were assigned, and images were corrected for machine‐ and patient‐related image distortion. Intensity modulated plans (IMRT) were developed for each patient and dose distributions were calculated on both the original and corrected images. The effect of MR distortion correction on both target and organ at risk (OAR) dosimetry was studied. Results: Maximum and mean image distortion for all patients was 5.4 mm and 1.4 mm, respectively. Distortions near the target and OARs were considerably less. The minimum dose received by the planning target volume (PTV) was most affected by distortion correction and changed, on average, by −0.3% for IMRT plans. Changes in mean and maximum PTV dose were smaller and dose volume histograms (DVHs) were insignificantly altered. Conclusions: For the combination of the MR scanner and imaging sequence, distortion correction has no impact on prostate plan dosimetry when patients are properly positioned within the magnet. MR‐RTP will be further studied but appears to be clinically viable for prostate patients.
SU‐E‐J‐88: Correction of Arterial Input Function Distortion for DCE MRI Assessment of Hepatic Perfusion Response to Radiation Therapy
Authors: Wang H , Cao Y
Published: November 2011

Purpose: To develop a post‐processing method for correction of arterial input function (AIF) distortion in T1‐weighted dynamic contrast enhanced (DCE) imaging used for perfusion quantification of the liver. Methods: The T2* effect at 3T can suppress the first‐pass peak of AIF sampled from aorta in DCE‐MRI acquisition due to high concentration of Gd‐DTPA during the first pass. To correct the distorted AIF, the first pass of AIF is modeled as a smooth function with a single peak by minimizing the least squares error in fitting the dual‐input single compartment kinetic model of the liver. Spline is used to interpolate data points from knot points. The method was evaluated by simulated data with different degrees of saturation in the first pass of AIF, and applied to DCE‐MRI of the liver in 12 patients. Hepatic perfusion estimated from original and corrected AIFs were compared.Results: The simulation shows that AIF saturation causes systemically errors in hepatic perfusion quantification. The AIF correction significantly improves perfusion measurement for a variety of degrees of saturation and image noise. In the DCE‐MRI of the 12 patients, there is an average of 35% saturation in the peak of AIF compared with corrected ones. The corrected AIF improves hepatic arterial perfusion by −20% and portal venous perfusion by 24%. Conclusions: The proposed method can correct saturation in the first pass of AIF due to the T2* effect at high‐concentration of Gd‐DTPA, and improve hepatic perfusion quantification. This approach might have the potential for evaluation of liver response to treatment in the patients with hepatic cancers.The work is supported in part by PO1CA59827 and RO1CA132834.
SU‐E‐J‐92: Dosimetric Evaluation of Treatment Delivery for Lung SBRT Using Respiratory Gated PET and In‐Treatment Imaging
Authors: Yue Y , Aristophanous M , Rottmann J , Killoran J , Yap J , Chen A , Berbeco R
Published: November 2011

Purpose: Imaging of lung cancer with 4D PET has recently received much attention in oncology diagnosis and staging. Independently studies have also shown the feasibility of dosimetric evaluation of delivery efficacy of lung stereotactic body radiotherapy (SBRT) using an EPID in cine mode. We propose a novel method to evaluate treatment delivery by quantifying dose deposited in the residual tumor using 4D PET and in‐treatment imaging. Methods: A two‐step dosimetric evaluation of treatment delivery for lung SBRT is proposed. First, delivered dose is calculated by motion‐corrected fluence. Megavoltage images are recorded throughout treatment delivery, and tumor positions are tracked using a multi‐template tracking algorithm for all fields and fractions. The delivered fluence is obtained by convolving the tracked tumor positions with the planned fluence. Utilizing the convolved fluence, the 3D delivered dose is obtained. Second, treatment delivery is evaluated utilizing a post‐therapy 4D PET scan. High FDG uptake regions are segmented as sites of residual disease at each phase of 4D PET images. Residual structures are then fused with the planning CT using regional image registration. Relying on the pre‐computed delivered dose, dose volume histograms (DVHs) are obtained for the residual structures. Results: We validated the method using clinical data acquired from lung SBRT treatments. The planned and delivered DVHs were compared and verified on the target volume. The delivered dose to the residual tumor was calculated for each phase of 4D PET. For a patient with large tumor motion (1 cm), 10% deviation from prescription dose is observed at inhale phase of breathing. Conclusions: Dose delivered to residual disease provides critical evidence for evaluation of the efficacy of treatment delivery. 4D PET has a potential impact on dosimetric evaluation for lung cancer treatment.
SU‐E‐J‐95: Evaluation of Repeat Respiratory Gated PET Scans for the Assessment of Treatment Effectiveness
Authors: Aristophanous M , Yue Y , Killoran J , Yap J , Dauten A , Chen A , Berbeco R
Published: November 2011

Purpose: Gated (4D) PET/CT scans have been shown to be effective in recovering the signal lost due to respiratory motion. Ungated (3D) and 4D FDG‐PET scans obtained pre and post radiation therapy (RT) for lung cancer were compared to examine the role of 4D PET in assessing FDG uptake changes due to therapy. Methods: Sequential 3D and 4D FDG‐PET/CT scans were acquired approximately two weeks before (pre‐RT) and one month after (post‐RT) treatment for patients receiving definitive RT for lung cancer. Targeted lesions were identified for each patient, and a region of interest (ROI) was defined for each lesion on the 3D and each of the five phases of the 4D pre‐RT scans. The ROIs were generated using a 40% of the maximum standardized uptake value (SUV) threshold, and the maximum SUV for each lesion from the pre—RT scans was recorded. Pre‐RT ROIs were then used to locate the areas of the original FDG uptake on the post‐RT scans using rigid registration. A post‐RT ROI was generated, and the maximum post‐RT SUV was recorded. Results: Sixteen lesions were identified and analyzed for twelve patients. Comparison of pre‐RT to post‐RT 3D PET scans showed a median SUV decrease of 62% (range 36–89%), while comparison of pre‐RT to post‐RT 4D PET scans showed a median SUV decrease of 67% (range 30–89%). The mean difference between the SUV change on 3D versus 4D scans was 4.9% (range 0–15%, p=.07), and the highest quartile had an absolute difference greater than 9% in SUV change.Conclusion: When assessing SUV changes with PET scans done pre and post‐RT, a substantial proportion of lesions had showed differences of over 9% in measurement of SUV change when comparing 3D PET to 4D PET. Such differences could potentially influence classification of PET‐based response assessment.
SU‐E‐J‐96: Prognostic Value of Automatically Segmented Lung Volumes during Chemotherapy for Patients with Mesothelioma
Authors: Labby Z , Sensakovic W , Nowak A , Kindler H , Armato S
Published: November 2011

Purpose: To assess the prognostic significance of changes in segmented lung volume, a physiological correlate of tumor volume changes, during the course of chemotherapy for patients with mesothelioma. Methods: Serial chest CT scans were collected during the course of platinum‐based chemotherapy for 64 patients with confirmed unilateral mesothelioma between 2002 and 2010. Lung volumes for each scan were calculated using an automated segmentation technique, the results of which were manually reviewed for accuracy prior to volume calculation. Diseased (ipsilateral) lung volumes were normalized by the respective contralateral lung volumes to account for differences in respiratory phase between the scans of each patient. Lung volume trajectories were modeled as the difference between normalized ipsilateral lung volumes at baseline and first therapy follow‐up imaging time points (median span: 35 days). Correlation between volume changes and overall survival from diagnosis was assessed using the Log‐Rank test and Cox Proportional Hazards modeling. Results: Between baseline CT and first follow‐up CT, the geometric mean of lung volume trajectories indicated a 6% increase in ipsilateral lung volume (and, by logical extension, a corresponding decrease in tumor volume). When discretized as lung volume gain versus volume loss, patients experiencing volume loss (n=21) had a median survival of 12.6 months, whereas patients with lung volume gain (n=43) had a median survival of 17.9 months (Log‐Rank p=0.0028). As a continuous numerical parameter, lung volume trajectory was a significant imaging biomarker of patient prognosis (p=0.0044) in a multivariate model including histology, a known prognostic covariate. Conclusions: Analysis of lung volume trajectories during the course of chemotherapy for patients with unilateral mesothelioma indicates that increases in lung volume are significantly associated with prolonged patient survival. This work motivates future investigations of lung volume as a therapy response metric, since changes in lung and tumor volumes are physiologically correlated.
SU‐E‐J‐97: Predictive and Prognostic Clinical Values of 18F‐FDG PET Based Measurements in Locally Advanced Esophageal Cancer Are Not Improved by Partial Volume Effects Correction
Authors: Hatt M , Le Pogam A , Visvikis D , Pradier O , Cheze‐Le Rest C
Published: November 2011

Purpose: We have previously demonstrated that functional tumor volume (TV) and Total Lesion Glycolysis (TLG=TV×SUVmean) measured on pretreatment 18F‐FDG PET scans were significant predictors of response and prognostic factors of survival, whereas SUV measurements were not. The objective of this study was to investigate the impact of partial volume effects (PVE) correction (PVC) on this clinical value. Methods: 50 patients with esophageal cancer treated with concomitant radiochemotherapy were retrospectively analyzed. 18F‐FDG PET baseline scans were corrected for PVE with iterative deconvolution with wavelet‐based denoising. Tumors were subsequently delineated using the Fuzzy Locally Adaptive Bayesian (FLAB) algorithm on both original and corrected images. Maximum and peak SUV, TV, mean SUV, and TLG were extracted and compared. The value of each parameter (with or without PVC) was investigated using Kruskal‐Wallis tests regarding response and Kaplan‐Meier curves regarding survival. Results: Whereas PVC had a significant quantitative impact on the absolute values of each parameter (up to more than 100% for SUVmax), the respective clinical value was not significantly modified whether for overall survival or response to therapy. No significant improvement was observed after PVC for the already established significant predictive and prognostic value of TV and TLG. Similarly, the non significant predictive and prognostic value of the various SUV measurements was not improved by PVC and was even lowered in some cases. Conclusions: PVC did not modify significantly the previously established clinical value of tumor volume or TLG. In addition, the limited value of SUV measurements in this context may therefore not be explained by the lack of PVC since PVC did not improve their clinical value and in most cases it even lowered it.