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Chen, H

Publications and source records attributed to Chen, H.

At least 55 records · Page 3

SU-F-BRA-07: Dosimetric Verification of the Valencia Skin Applicator Using Gafchromic EBT3 Film

Purpose: The Valencia applicators have recently been introduced for HDR treatment of small and shallow superficial skin lesions (< 20 mm diameter and 3-mm depth). Per AAPM TG 56, any HDR applicator internal dimensions must be verified prior to clinical use. However radiographic and tomographic imaging to validate the Valencia applicators is impractical due to the Tungsten alloy housing and flattening filter. In this study, we propose to use EBT3 film to indirectly confirm the physical integrity of the Valencia applicators. Methods: Treatment plans were created using the Oncentra MasterPlan TPS v4.5 for the H2 (20-mm dia.) and H3 (30-mm dia.) Valencia Applicators. A virtual CT phantom (2-mm slice thickness) was created with one source position in water. The published effective depth method was used for each applicator to delivery 500 cGy to a 3-mm depth using the TG-43 formalism. Film measurements (n=3) at 3-mm depth and vertical plane in solid water were performed for each applicator to verify the prescribed dose calculated by the TPS. Percent depth dose curves and off-axis profiles (phantom surface and 3-mm depth) were measured and compared to published data. Films were analyzed using an in-house written program and RIT113 v6 software. Film calibration was performed per TG-55 protocol using the Ir-192 source with NIST-traceable calibration. Results: The prescription absolute dose difference was 1% for the Valencia H2 applicator and 4% for the Valencia H3 applicator. The measured percent depth dose curves and off-axis dose profiles measured for the H2 and H2 Valencia applicators are in excellent agreement with the Granero et al. Monte Carlo results{sup 1}. Conclusion: Gafchromic EBT3 film can be used to indirectly verify the internal components of special HDR skin applicators constructed from high Z materials.{sup 1}Granero et al. “Design and evaluation of a HDR skin applicator with flattening filter”, Med. Phys. 35(2), 495–503, 2008.

60 APPLIED LIFE SCIENCES↗

MO-AB-BRA-10: Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging

Purpose: In cancer therapy, utilizing FDG-18 PET image-based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster-Shafer theory (DST) based approach, evidential low-dimensional transformation with feature selection (ELT-FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics. Methods: First, a specific loss function with sparse penalty was developed to learn an adaptive low-rank distance metric for representing the dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low-dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1-norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K-nearest-neighbor (EK- NN) classifier to predict treatment outcome. Results: Twenty-five patients with stage II–III non-small-cell lung cancer and thirty-six patients with esophageal squamous cell carcinomas treated with chemo-radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave-one-out cross-validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT-FS leads to higher prediction accuracy for the training and testing sets both for lung-cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal-cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT-FS also provides superior class separation in both test data sets. Conclusion: A novel DST- based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK-NN classifier.

60 APPLIED LIFE SCIENCES↗

TU-EF-204-10: A Preliminary Study Evaluating Calculation Variations of Local Noise Power Spectra for CT Simulation in Radiation Therapy

Purpose: Local noise power spectrum (NPS) properties are significantly affected by calculation variables and CT acquisition and reconstruction parameters, but a thoughtful analysis of these effects is absent. In this study, we performed a complete analysis of the effects of calculation and imaging parameters on the NPS. Methods: The uniformity module of a Catphan phantom was scanned with a Philips Brilliance 64-slice CT simulator using various scanning protocols. Images were reconstructed using both FBP and iDose4 reconstruction algorithms. From these images, local NPS were calculated for regions of interest (ROI) of varying locations and sizes, using four image background removal methods. Additionally, using a predetermined ground truth, NPS calculation accuracy for various calculation parameters was compared for computer simulated ROIs. A complete analysis of the effects of calculation, acquisition, and reconstruction parameters on the NPS was conducted. Results: The local NPS varied with ROI size and image background removal method, particularly at low spatial frequencies. The image subtraction method was the most accurate according to the computer simulation study, and was also the most effective at removing low frequency background components in the acquired data. However, first-order polynomial fitting using residual sum of squares and principle component analysis provided comparable accuracy under certain situations. Similar general trends were observed when comparing the NPS for FBP to that of iDose4 while varying other calculation and scanning parameters. However, while iDose4 reduces the noise magnitude compared to FBP, this reduction is spatial-frequency dependent, further affecting NPS variations at low spatial frequencies. Conclusion: The local NPS varies significantly depending on calculation parameters, image acquisition parameters, and reconstruction techniques. Appropriate local NPS calculation should be performed to capture spatial variations of noise; calculation methodology should be selected with consideration of image reconstruction effects and the desired purpose of CT simulation for radiotherapy tasks.

60 APPLIED LIFE SCIENCES↗

WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first time allows to automatically identify the H&N upper airway and quantify in-treatment H&N internal motion in real-time. This approach can be applied to track other structures’ motion, and provide guidance on patient-specific prediction of intra-/inter-fractional structure displacements.

60 APPLIED LIFE SCIENCES↗

SU-F-BRF-09: A Non-Rigid Point Matching Method for Accurate Bladder Dose Summation in Cervical Cancer HDR Brachytherapy

Purpose: To propose and validate a deformable point matching scheme for surface deformation to facilitate accurate bladder dose summation for fractionated HDR cervical cancer treatment. Method: A deformable point matching scheme based on the thin plate spline robust point matching (TPSRPM) algorithm is proposed for bladder surface registration. The surface of bladders segmented from fractional CT images is extracted and discretized with triangular surface mesh. Deformation between the two bladder surfaces are obtained by matching the two meshes' vertices via the TPS-RPM algorithm, and the deformation vector fields (DVFs) characteristic of this deformation is estimated by B-spline approximation. Numerically, the algorithm is quantitatively compared with the Demons algorithm using five clinical cervical cancer cases by several metrics: vertex-to-vertex distance (VVD), Hausdorff distance (HD), percent error (PE), and conformity index (CI). Experimentally, the algorithm is validated on a balloon phantom with 12 surface fiducial markers. The balloon is inflated with different amount of water, and the displacement of fiducial markers is benchmarked as ground truth to study TPS-RPM calculated DVFs' accuracy. Results: In numerical evaluation, the mean VVD is 3.7(±2.0) mm after Demons, and 1.3(±0.9) mm after TPS-RPM. The mean HD is 14.4 mm after Demons, and 5.3mm after TPS-RPM. The mean PE is 101.7% after Demons and decreases to 18.7% after TPS-RPM. The mean CI is 0.63 after Demons, and increases to 0.90 after TPS-RPM. In the phantom study, the mean Euclidean distance of the fiducials is 7.4±3.0mm and 4.2±1.8mm after Demons and TPS-RPM, respectively. Conclusions: The bladder wall deformation is more accurate using the feature-based TPS-RPM algorithm than the intensity-based Demons algorithm, indicating that TPS-RPM has the potential for accurate bladder dose deformation and dose summation for multi-fractional cervical HDR brachytherapy. This work is supported in part by the National Natural ScienceFoundation of China (no 30970866 and no 81301940)

60 APPLIED LIFE SCIENCES↗

SU-F-18C-02: Evaluations of the Noise Power Spectrum of a CT Iterative Reconstruction Technique for Radiation Therapy

Purpose: To quantitatively assess the noise power spectrum (NPS) of the new, commercially released CT iterative reconstruction technique, iDose{sup 4} from Philips, to compare it with filtered back-projection techniques (FBP), and to provide clinical practice suggestions for radiation therapy. Methods: A uniform phantom was CT imaged with 120kVp tube potential over a range of mAs (250-3333). The image sets were reconstructed using two reconstruction algorithms (FBP and iDose{sup 4} with noise reduction levels 1, 3, and 6) and three reconstruction filters (standard B, smooth A, and sharp C), after which NPS variations were analyzed and compared on region of interest (ROI) sizes (16×16 to 128×128 pixels), ROI radii (0–65 mm), reconstruction algorithms, reconstruction filters, and mAs. Results: The NPS magnitude and shape depended considerably on ROI size and location for both reconstruction algorithms. Regional noise variance became more stationary as ROI size decreased, minimizing NPS artifacts. The optimal 32×32-pixel ROI size balanced the trade-off between stationary noise and adequate sampling. NPS artifacts were greatest at the center of reconstruction space and decreased with increasing ROI distance from the center. The optimal ROI position was located near the phantom's radial midpoint (∼40mm). For sharper filters, the NPS magnitude and the maximum magnitude frequency increased. Higher dose scans yielded lower NPS magnitudes for both reconstruction algorithms and all filters. Compared to FBP, the iDose{sup 4} algorithm reduced the NPS magnitude while preferentially reducing noise at mid-range spatial frequencies, altering noise texture. This reduction was more significant with increasing iDose{sup 4} noise reduction level. Conclusion: Compared to pixel standard deviation, NPS has greater clinical potential for task-based image quality assessment, describing both the magnitude and spatial frequency characteristics of image noise. While iDose{sup 4} reduces the NPS magnitude more dramatically than FBP, further studies are needed to assess the impacts of noise texture alteration on its clinical usage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

MO-C-17A-11: A Segmentation and Point Matching Enhanced Deformable Image Registration Method for Dose Accumulation Between HDR CT Images

Purpose: To propose and validate a novel and accurate deformable image registration (DIR) scheme to facilitate dose accumulation among treatment fractions of high-dose-rate (HDR) gynecological brachytherapy. Method: We have developed a method to adapt DIR algorithms to gynecologic anatomies with HDR applicators by incorporating a segmentation step and a point-matching step into an existing DIR framework. In the segmentation step, random walks algorithm is used to accurately segment and remove the applicator region (AR) in the HDR CT image. A semi-automatic seed point generation approach is developed to obtain the incremented foreground and background point sets to feed the random walks algorithm. In the subsequent point-matching step, a feature-based thin-plate spline-robust point matching (TPS-RPM) algorithm is employed for AR surface point matching. With the resulting mapping, a DVF characteristic of the deformation between the two AR surfaces is generated by B-spline approximation, which serves as the initial DVF for the following Demons DIR between the two AR-free HDR CT images. Finally, the calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. Results: The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative results as well as the visual inspection of the DIR indicate that our proposed method can suppress the interference of the applicator with the DIR algorithm, and accurately register HDR CT images as well as deform and add interfractional HDR doses. Conclusions: We have developed a novel and robust DIR scheme that can perform registration between HDR gynecological CT images and yield accurate registration results. This new DIR scheme has potential for accurate interfractional HDR dose accumulation. This work is supported in part by the National Natural ScienceFoundation of China (no 30970866 and no 81301940)

60 APPLIED LIFE SCIENCES↗

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TU-C-17A-04: BEST IN PHYSICS (THERAPY) - A Supervised Framework for Automatic Contour Assessment for Radiotherapy Planning of Head- Neck Cancer

Purpose: Precise contour delineation of tumor targets and critical structures from CT simulations is essential for accurate radiotherapy (RT) treatment planning. However, manual and automatic delineation processes can be error prone due to limitations in imaging techniques and individual anatomic variability. Tedious and laborious manual verification is hence needed. This study develops a general framework for automatically assessing RT contours for head-neck cancer patients using geometric attribute distribution models (GADMs). Methods: Geometric attributes (centroid and volume) were computed from physician-approved RT contours of 29 head-neck patients. Considering anatomical correlation between neighboring structures, the GADM for each attribute was trained to characterize intra- and interpatient structure variations using principal component analysis. Each trained GADM was scalable and deformable, but constrained by the principal attribute variations of the training contours. A new hierarchical model adaptation algorithm was utilized to assess the RT contour correctness for a given patient. Receiver operating characteristic (ROC) curves were employed to evaluate and tune system parameters for the training models. Results: Experiments utilizing training and non-training data sets with simulated contouring errors were conducted to validate the framework performance. Promising assessment results of contour normality/abnormality for the training contour-based data were achieved with excellent accuracy (0.99), precision (0.99), recall (0.83), and F-score (0.97), while corresponding values of 0.84, 0.96, 0.83, and 0.9 were achieved for the non-training data. Furthermore, the areas under the ROC curves were above 0.9, validating the accuracy of this test. Conclusion: The proposed framework can reliably identify contour normality/abnormality based upon intra- and inter-structure constraints derived from clinically-approved contours. It also allows physicians to analytically determine the system parameters to fit various clinic requirements (e.g. as-low-as-possible false positives). It has great potential for improving RT work flow. More geometric attributes and training sets will be investigated to improve framework performance in the future.

60 APPLIED LIFE SCIENCES↗

WE-A-BRF-01: Dual-Energy CT Imaging in Diagnostic Imaging and Radiation Therapy

The quantification accuracy of dual-energy imaging is influenced by the fundamentals of x-ray physics, system geometry, data acquisition hardware/protocol, system calibration, and image processing technique. This symposium will provide updates on the following advanced application areas: Mammography. Volumetric breast density techniques based on standard mammograms require estimation of breast thickness, which is difficult to accurately measure. By comparison, calculation of breast density using dual energy mammography does not require measurement of breast thickness. Dual energy mammography has been implemented using both energy integrating flat panel detectors in conjunction with beam energy switching and energy resolved photon counting detectors. These techniques have been optimized using simulation studies and validated using physical phantoms and postmortem breasts. Chemical decomposition was used as the gold standard for volumetric breast density measurement in postmortem breasts. Breast density measurements have also been compared with results from four-category BI-RADS density rankings, standard image thresholding and Fuzzy k-mean clustering techniques. These studies indicate that dual energy mammography can be used to accurately measure volumetric breast density. Cardiovascular CT. The predicative accuracy of risk models for recurrent stroke and cardiac arrest depends heavily on accurate differentiation of thrombus or calcium from iodine in left atrial appendage or coronary arteries. The amount of energy separation is constrained by image noise; therefore, optimal kVp, beam filtration, and balanced flux are essential for the quantification accuracy of iodine and calcium. The basis materials are combined linearly to generate monochromatic energy images, where CT# accuracy and CNR are energy dependent. With optimal monochromatic energy, the mean iodine concentration for the thrombus, circulatory stasis, and control groups are significantly different. Risk classification based on calcium scores shows excellent agreement with classification on the basis of conventional coronary artery calcium scoring. These studies demonstrate dual-energy cardiovascular CT can potentially be a noninvasive and sensitive modality in high risk patients. On-board KV/MV Imaging. To enhance soft tissue contrast and reduce metal artifacts, we have developed a dual-energy CBCT technique and a novel on-board kV/MV imaging technique based on hardware available on modern linear accelerators. We have also evaluated the feasibility of these two techniques in various phantom studies. Optimal techniques (energy, beam filtration, # of overlapping projections, etc) have been investigated with unique calibration procedures, which leads to successful decomposition of imaged material into acrylic-aluminum basis material pair. This enables the synthesis of virtual monochromatic (VM) CBCT images that demonstrate much less beam hardening, significantly reduced metal artifacts, and/or higher soft tissue CNR compared to single-energy CBCT. Adaptive Radiation Therapy. DECT could actually contribute to the area of Dose-Guided Radiation Therapy (or Adaptive Therapy). The application of DECT imaging using 80kV and 140 kV combinations could potentially increase the image quality by reducing the bone or high density material artifacts and also increase the soft tissue contrast by a light contrast agent. The result of this higher contrast / quality images is beneficial for deformable image registration / segmentation algorithm to improve its accuracy hence to make adaptive therapy less time consuming in its recontouring process. The real time re-planning prior to per treatment fraction could become more realistic with this improvement especially in hypofractional SBRT cases. Learning Objectives: Learn recent developments of dual-energy imaging in diagnosis and radiation therapy; Understand the unique clinical problem and required quantification accuracy in each application; Understand the different approaches to optimize dual-energy imaging techniques for different applications.

60 APPLIED LIFE SCIENCES↗

SU-D-19A-07: Dosimetric Comparison of HDR Plesiotherapy and Electron Beam Therapy for Superficial Lesions

Purpose: Large superficial (skin, soft tissue sarcoma) lesions located on curved areas are hard to treat with electrons. The Freiburg Flap (Nucletron, Netherlands) is a flexible mesh style surface which can be easily shaped to fit curved surfaces for reproducible HDR fraction delivery. To understand the fundamental dosimetric differences, a dosimetric comparison was made between HDR plesiotherapy (Freiburg applicator for lesions over 4cm) and external electron beam radiotherapy over cases with varying target curvature (both stylized and clinical cases). Methods: Four stylized cases with variable complexity were created using artificial DICOM axial CT slices and RT structures (a square and three curved structures on a 4.5cm radius cylinder). They were planned using Oncentra v4.3 and exported to Pinnacle v9.6 for electrons planning. The HDR source dwell positions were optimized for the best coverage of the targets using graphical optimization. Electron treatment plans were created in Pinnacle using the same CT and RT structures of three HDR cases with surface lesions previously treated with the Freiburg flap. The En face electron plans used 6-12 MeV electrons and 0.5–1 cm bolus was added to increase surface dose. The electron plans were prescribed to an isodose line to conform to the target. Results: For all lesions, the average target dose coverage was similar (D90ave of 100% for HDR vs 101% for electrons). For lesions with high curvature, the HDR coverage was better (D90 102% vs D90 97% for electron). For all cases, adjacent structures high dose region was lower for HDR than electrons (D1cc 100% for HDR vs D1cc 111% for electrons). Conclusion: HDR plesiotherapy offers excellent target conformity for superficial targets similar to electrons. However, for lesions with complex curved surfaces, HDR has the advantage to achieve better dose distributions using graphical optimization to spare adjacent normal tissue while maximizing target coverage.

60 APPLIED LIFE SCIENCES↗

SU-E-T-68: Clinical Implementation of Total Skin Electron Beam Therapy: A New- York Presbyterian Hospital Experience

Purpose: Total skin electron beam therapy (TSET) is used in the treatment of rare skin diseases such as mycosis fungoides, the most common type of cutaneous T-cell lymphoma. We report our experience with clinical implementation of TSET. Methods: A modified six-dual-field irradiation technique was chosen to deliver TSET. A Varian Trilogy linear accelerator with a nominal 6 MeV beam using high dose rate total skin electron mode (HDTSe) was employed. The recommendations of AAPM task group report 23 were followed for the commissioning. An acrylic plate (energy degrader) of 3.2 mm depth was mounted on the HDTSe applicator. The nominal source to skin distance was set at 450 cm. The optimum tilt angle of the gantry was determined using NACP-02 ionization chamber embedded in certified therapy grade solid water. Percent depth dose measurements were performed using ionization chamber and radiochromic films embedded in solid water and anthropomorphic phantom. For absolute dose measurements, TG-51 formalism was employed. The dose distribution on the entire skin was measured by irradiating the anthropomorphic phantom, with TLDs attached, mimicking the real treatment. Results: The 3.2 mm acrylic plate mounted on the HDTSe applicator degraded the energy of the electron beam to 4.1 MeV in the treatment plane, located at an SSD of 450 cm. The optimum tilt angle was found to be ±20°. A single-dual field had a longitudinal uniformity, measured at a depth of dose maximum, of ±7% over a length of about 200 cm. For the entire treatment the multiplication factor was found to be 2.86. On the surface of the phantom, the dose varied from 108% to 93% of the prescription dose. Conclusion: We have successfully commissioned TSET meeting the guidelines of the TG report 23, and treated our first patient on February 25, 2014.

07 ISOTOPE AND RADIATION SOURCES↗