Engineering topics

Wang, J

Publications and source records attributed to Wang, J.

At least 91 records · Page 5

DOE OSTI2015

SU-C-BRA-04: Use of Esophageal Wall Thickness in Evaluation of the Response to Chemoradiation Therapy for Esophageal Cancer

Purpose: To quantitatively evaluate the esophageal cancer response to chemoradiation therapy (CRT) by measuring the esophageal wall thickness in CT. Method: Two datasets were used in this study. The first dataset is composed of CT scans of 15 esophageal cancer patients and 15 normal controls. The second dataset is composed of 20 esophageal cancer patients who underwent PET/CT scans before (Pre-CRT) and after CRT (Post-CRT). We first segmented the esophagus using a multi-atlas-based algorithm. The esophageal wall thickness was then computed, on each slice, as the equivalent circle radius of the segmented esophagus excluding the lumen. To evaluate the changes of wall thickness, we computed the standard deviation (SD), coefficient of variation (COV, SD/Mean), and flatness [(Max–Min)/Mean] of wall thickness along the entire esophagus. Results: For the first dataset, the mean wall thickness of cancer patients and normal controls were 6.35 mm and 6.03 mm, respectively. The mean SD, COV, and flatness of the wall thickness were 2.59, 0.21, and 1.27 for the cancer patients and 1.99, 0.16, and 1.13 for normal controls. Statistically significant differences (p < 0.05) were identified in SD and flatness. For the second dataset, the mean wall thickness of pre-CRT and post-CRT patients was 7.13 mm and 6.84 mm, respectively. The mean SD, COV, and flatness were 1.81, 0.26, and 1.06 for pre-CRT and 1.69, 0.26, and 1.06 for post-CRT. Statistically significant difference was not identified for these measurements. Current results are based on the entire esophagus. We believe significant differences between pre- and post-CRT scans could be obtained, if we conduct the measurements at tumor sites. Conclusion: Results show thicker wall thickness in pre-CRT scans and differences in wall thickness changes between normal and abnormal esophagus. This demonstrated the potential of esophageal wall thickness as a marker in the tumor CRT response evaluation. This work was supported in part by the National Cancer Institute Grant R01CA172638.

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DOE OSTI2015

SU-D-BRA-04: Fractal Dimension Analysis of Edge-Detected Rectal Cancer CTs for Outcome Prediction

Purpose: To extract the fractal dimension features from edge-detected rectal cancer CTs, and to examine the predictability of fractal dimensions to outcomes of primary rectal cancer patients. Methods: Ninety-seven rectal cancer patients treated with neo-adjuvant chemoradiation were enrolled in this study. CT images were obtained before chemoradiotherapy. The primary lesions of the rectal cancer were delineated by experienced radiation oncologists. These images were extracted and filtered by six different Laplacian of Gaussian (LoG) filters with different filter values (0.5–3.0: from fine to coarse) to achieve primary lesions in different anatomical scales. Edges of the original images were found at zero-crossings of the filtered images. Three different fractal dimensions (box-counting dimension, Minkowski dimension, mass dimension) were calculated upon the image slice with the largest cross-section of the primary lesion. The significance of these fractal dimensions in survival, recurrence and metastasis were examined by Student’s t-test. Results: For a follow-up time of two years, 18 of 97 patients had experienced recurrence, 24 had metastasis, and 18 were dead. Minkowski dimensions under large filter values (2.0, 2.5, 3.0) were significantly larger (p=0.014, 0.006, 0.015) in patients with recurrence than those without. For metastasis, only box-counting dimensions under a single filter value (2.5) showed differences (p=0.016) between patients with and without. For overall survival, box-counting dimensions (filter values = 0.5, 1.0, 1.5), Minkowski dimensions (filter values = 0.5, 1.5, 2.0, 2,5) and mass dimensions (filter values = 1.5, 2.0) were all significant (p<0.05). Conclusion: It is feasible to extract shape information by edge detection and fractal dimensions analysis in neo-adjuvant rectal cancer patients. This information can be used to prognosis prediction.

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DOE OSTI2015

SU-D-207-04: GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method

Purpose: Due to the limited number of projections at each phase, the image quality of a four-dimensional cone-beam CT (4D-CBCT) is often degraded, which decreases the accuracy of subsequent motion modeling. One of the promising methods is the simultaneous motion estimation and image reconstruction (SMEIR) approach. The objective of this work is to enhance the computational speed of the SMEIR algorithm using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the tetrahedral mesh based on the features of a reference phase 4D-CBCT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. After the mesh generation, the updated motion model and other phases of 4D-CBCT can be obtained by matching the 4D-CBCT projection images at each phase with the corresponding forward projections of the deformed reference phase of 4D-CBCT. The entire process of this 4D-CBCT reconstruction method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its tremendous parallel computing ability. Results: A 4D XCAT digital phantom was used to test the proposed mesh-based image reconstruction algorithm. The image Result shows both bone structures and inside of the lung are well-preserved and the tumor position can be well captured. Compared to the previous voxel-based CPU implementation of SMEIR, the proposed method is about 157 times faster for reconstructing a 10 -phase 4D-CBCT with dimension 256×256×150. Conclusion: The GPU-based parallel 4D CBCT reconstruction method uses the feature-based mesh for estimating motion model and demonstrates equivalent image Result with previous voxel-based SMEIR approach, with significantly improved computational speed.

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DOE OSTI2015

SU-E-I-01: Iterative CBCT Reconstruction with a Feature-Preserving Penalty

Purpose: Low-dose CBCT is desired in various clinical applications. Iterative image reconstruction algorithms have shown advantages in suppressing noise in low-dose CBCT. However, due to the smoothness constraint enforced during the reconstruction process, edges may be blurred and image features may lose in the reconstructed image. In this work, we proposed a new penalty design to preserve image features in the image reconstructed by iterative algorithms. Methods: Low-dose CBCT is reconstructed by minimizing the penalized weighted least-squares (PWLS) objective function. Binary Robust Independent Elementary Features (BRIEF) of the image were integrated into the penalty of PWLS. BRIEF is a general purpose point descriptor that can be used to identify important features of an image. In this work, BRIEF distance of two neighboring pixels was used to weigh the smoothing parameter in PWLS. For pixels of large BRIEF distance, weaker smooth constraint will be enforced. Image features will be better preserved through such a design. The performance of the PWLS algorithm with BRIEF penalty was evaluated by a CatPhan 600 phantom. Results: The image quality reconstructed by the proposed PWLS-BRIEF algorithm is superior to that by the conventional PWLS method and the standard FDK method. At matched noise level, edges in PWLS-BRIEF reconstructed image are better preserved. Conclusion: This study demonstrated that the proposed PWLS-BRIEF algorithm has great potential on preserving image features in low-dose CBCT.

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DOE OSTI2015

SU-E-I-08: Investigation of Deconvolution Methods for Blocker-Based CBCT Scatter Estimation

Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used to recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.

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DOE OSTI2015

SU-E-J-83: CBCT Based Rectum and Bladder Dose Tracking in the Prostate Radiotherapy

Purpose: The aim of this study is to monitor the volume changes of bladder and rectum and evaluate the dosimetric changes of bladder and rectum using daily cone-beam CT for prostate radiotherapy. Methods: The data of this study were obtained from 12 patients, totally 222 CBCTs. All the volume of the bladder and the rectum on the CBCT were normalized to the bladder and the rectum on their own original CT to monitory the volume changes. To evaluate dose delivered to the OARs, volumes that receive 70Gy (V70Gy), 60Gy, 50Gy, 40Gy and 30Gy are calculated for the bladder and the rectum, V20Gy and V10Gy for rectum additionally. And the deviation of the mean dose to the bladder and the rectum are also chosen as the evaluation parameter. Linear regression analysis was performed to identify the mean dose change of the volume change using SPSS 19. Results: The results show that the variances of the normalize volume of the bladder and the rectum are 0.15–0.58 and 0.13–0.50. The variances of V70Gy, V60Gy, V50Gy, V40Gy and V30Gy of bladder are bigger than rectum for 11 patients. The linear regression analysis indicated a negative correlation between the volume and the mean dose of the bladder (p < 0.05). A 10% increase in bladder volume will cause 5.1% (±4.3%) reduction in mean dose. Conclusion: The bladder volume change is more significant than that for rectum for the prostate cancer patient. The volume changes of rectum are not significant except air gap in the rectum. Bladder volume varies will cause significant dose change. The bladder volume monitoring before fractional treatment delivery would be crucial for accuracy dose delivery.

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DOE OSTI2015

SU-E-J-154: Image Quality Assessment of Contrast-Enhanced 4D-CT for Pancreatic Adenocarcinoma in Radiotherapy Simulation

Purpose: This study presents quantitative and qualitative assessment of the image qualities in contrast-enhanced (CE) 3D-CT, 4D-CT and CE 4D-CT to identify feasibility for replacing the clinical standard simulation with a single CE 4D-CT for pancreatic adenocarcinoma (PDA) in radiotherapy simulation. Methods: Ten PDA patients were enrolled and underwent three CT scans: a clinical standard pair of CE 3D-CT immediately followed by a 4D-CT, and a CE 4D-CT one week later. Physicians qualitatively evaluated the general image quality and regional vessel definitions and gave a score from 1 to 5. Next, physicians delineated the contours of the tumor (T) and the normal pancreatic parenchyma (P) on the three CTs (CE 3D-CT, 50% phase for 4D-CT and CE 4D-CT), then high density areas were automatically removed by thresholding at 500 HU and morphological operations. The pancreatic tumor contrast-to-noise ratio (CNR), signal-tonoise ratio (SNR) and conspicuity (C, absolute difference of mean enhancement levels in P and T) were computed to quantitatively assess image quality. The Wilcoxon rank sum test was used to compare these quantities. Results: In qualitative evaluations, CE 3D-CT and CE 4D-CT scored equivalently (4.4±0.4 and 4.3±0.4) and both were significantly better than 4D-CT (3.1±0.6). In quantitative evaluations, the C values were higher in CE 4D-CT (28±19 HU, p=0.19 and 0.17) than the clinical standard pair of CE 3D-CT and 4D-CT (17±12 and 16±17 HU, p=0.65). In CE 3D-CT and CE 4D-CT, mean CNR (1.8±1.4 and 1.8±1.7, p=0.94) and mean SNR (5.8±2.6 and 5.5±3.2, p=0.71) both were higher than 4D-CT (CNR: 1.1±1.3, p<0.3; SNR: 3.3±2.1, p<0.1). The absolute enhancement levels for T and P were higher in CE 4D-CT (87, 82 HU) than in CE 3D-CT (60, 56) and 4DCT (53, 70). Conclusions: The individually optimized CE 4D-CT is feasible and achieved comparable image qualities to the clinical standard simulation. This study was supported in part by Philips Healthcare.

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DOE OSTI2015

SU-E-J-205: Dose Distribution Differences Caused by System Related Geometric Distortion in MRI-Guided Radiation Treatment System

Purpose: MRI has superb soft tissue contrast but is also known for geometric distortions. The concerns and uncertainty about MRI’s geometric distortion have contributed to the hesitation of using only MRI for simulation in radiation therapy. There are two major categories of geometric distortion in MRI; system related and patient related. In this presentation, we studied the impact of system-related geometric distortion on dose distribution in a digital body phantom under an MR-Linac environment. Methods: Residual geometric distortion (after built-in geometric correction) was modeled based on phantom measurements of the system-related geometric distortions of a MRI scanner of a combined MR guided Radiation Therapy (MRgRT) system. A digital oval shaped phantom (40×25 cm) as well as one ellipsoid shaped tumor volume was created to simulate a simplified human body. The simulated tumor volume was positioned at several locations between the isocenter and the body surface. CT numbers in HUs that approximate soft tissue and tumor were assigned to the respective regions in the digital phantom. To study the effect of geometric distortion caused by system imperfections, an IMRT plan was optimized with the distorted image set with the B field. Dose distributions were re-calculated on the undistorted image set with the B field (as in MR-Linac). Results: The maximum discrepancies in both body contour and tumor boundary was less than 2 mm, which leads to small dose distribution change. For the target in the center, coverage was reduced from 98.8% (with distortion) to 98.2%; for the other peripheral target coverage was reduced from 98.4% to 95.9%. Conclusion: System related geometric distortions over the 40×25 area were within 2mm and the resulted dosimetric effects were minor for the two tumor locations in the phantom. Patient study will be needed for further investigation. The authors received a corporate research grant from Elekta.

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DOE OSTI2015

SU-E-J-214: MR Protocol Development to Visualize Sirius MRI Markers in Prostate Brachytherapy Patients for MR-Based Post-Implant Dosimetry

Purpose: The current CT-based post-implant dosimetry allows precise seed localization but limited anatomical delineation. Switching to MR-based post-implant dosimetry is confounded by imprecise seed localization. One approach is to place positive-contrast markers (Sirius) adjacent to the negative-contrast seeds. This patient study aims to assess the utility of a 3D fast spoiled gradient-recalled echo (FSPGR) sequence to visualize Sirius markers for post-implant dosimetry. Methods: MRI images were acquired in prostate implant patients (n=10) on Day 0 (day-of-implant) and Day 30. The post-implant MR protocol consisted of 3D T2-weighted fast-spin-echo (FSE), T2-weighted 2D-FSE (axial) and T1-weighted 2D-FSE (axial/sagittal/coronal). We incorporated a 3D-FSPGR sequence into the post-implant MR protocol to visualize the Sirius markers. Patients were scanned with different number-of-excitations (6, 8, 10), field-of-view (10cm, 14cm, 18cm), slice thickness (1mm, 0.8mm), flip angle (14 degrees, 20 degrees), bandwidth (122.070 Hz/pixel, 325.508 Hz/pixel, 390.625 Hz/pixel), phase encoding steps (160, 192, 224, 256), frequency-encoding direction (right/left, anterior/posterior), echo-time type (minimum-full, out-of-phase), field strength (1.5T, 3T), contrast (with, without), scanner vendor (Siemens, GE), coil (endorectal-coil only, endorectal-and-torso-coil, torsocoil only), endorectal-coil filling (30cc, 50cc) and endorectal-coil filling type (air, perfluorocarbon [PFC]). For post-implant dosimetric evaluation with greater anatomical detail, 3D-FSE images were fused with 3D-FSPGR images. For comparison with CT-based post-implant dosimetry, CT images were fused with 3D-FSPGR images. Results: The 3D-FSPGR sequence facilitated visualization of markers in patients. Marker visualization helped distinguish signal voids as seeds versus needle tracks for more definitive MR-based post-implant dosimetry. On the CT-MR fused images, the distance between the seed on CT to MR images was 3.2±1.6mm in patients with no endorectal coil, 2.3±0.8mm in patients with 30cc-PFC-filled endorectal-coil and 5.0±1.8mm in patients with 50cc-PFC-filled endorectal-coil. Conclusion: An MR protocol to visualize positive-contrast Sirius markers to assist in the identification of negative-contrast seeds was demonstrated. S Frank is a co-founder of C4 Imaging LLC, the manufacturer of the MRI markers.

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DOE OSTI2015

SU-E-J-220: Assessment of MRI Geometric Distortion in Head and Neck Cancer Patients Scanned in Immobilized Radiation Treatment Position

Purpose: Uncertainties about geometric distortion have somewhat hindered MRI simulation in radiation therapy. Most of the geometric distortion studies were performed with phantom measurements but another major aspect of MR distortion is patient related. We studied the geometric distortion in patient images by comparing their MRI scans with the corresponding CT, using CT as the non-distorted gold standard. Methods: Ten H&N cancer patients were imaged with MRI as part of a prospective IRB approved study. All patients had their treatment planning CT done on the same day or within one week of the MRI. MR Images were acquired with a T2 SE sequence (1×1×2.5mm voxel size) in the same immobilization position as in the CT scans. MRI to CT rigid registration was then done and geometric distortion comparison was done by measuring the corresponding anatomical landmarks on both the MRI and the CT images by two observers. Several skin to skin (9 landmarks), bone to bone (8 landmarks), and soft tissue (3 landmarks) were measured at specific levels in horizontal and vertical planes of both scans. Results: The mean distortion for all landmark measurements in all scans was 1.8±1.9mm. For each patient 11 measurements were done in the horizontal plane while 9 were done in the vertical plane. The measured geometric distortion were significantly lower in the horizontal axis compared to the vertical axis (1.3±0.16 mm vs 2.2±0.19 mm, respectively, P=0.003*). The magnitude of distortion was lower in the bone to bone landmarks compared to the combined soft tissue and skin to skin landmarks (1.2±0.19 mm vs 2.3±0.17 mm, P=0.0006*). The mean distortion measured by observer one was not significantly different compared toobserver 2 (2.3 vs 2.4 mm, P=0.4). Conclusion: MRI geometric distortions were quantified in H&N patients with mean error of less than 2 mm. JW received a corporate sponsored research grant from Elekta.

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DOE OSTI2015

SU-E-J-225: CEST Imaging in Head and Neck Cancer Patients

Purpose: Chemical Exchange Saturation Transfer (CEST) imaging is an MRI technique enables the detection and imaging of metabolically active compounds in vivo. It has been used to differentiate tumor types and metabolic characteristics. Unlike PET/CT,CEST imaging does not use isotopes so it can be used on patient repeatedly. This study is to report the preliminary results of CEST imaging in Head and Neck cancer (HNC) patients. Methods: A CEST imaging sequence and the post-processing software was developed on a 3T clinical MRI scanner. Ten patients with Human papilloma virus positive oropharyngeal cancer were imaged in their immobilized treatment position. A 5 mm slice CEST image was acquired (128×128, FOV=20∼24cm) to encompass the maximum dimension of tumor. Twenty-nine off-set frequencies (from −7.8ppm to +7.8 ppm) were acquired to obtain the Z-spectrum. Asymmetry analysis was used to extract the CEST contrasts. ROI at the tumor, node and surrounding tissues were measured. Results: CEST images were successfully acquired and Zspectrum asymmetry analysis demonstrated clear CEST contrasts in tumor as well as the surrounding tissues. 3∼5% CEST contrast in the range of 1 to 4 ppm was noted in tumor as well as grossly involved nodes. Injection of glucose produced a marked increase of CEST contrast in tumor region (∼10%). Motion and pulsation artifacts tend to smear the CEST contrast, making the interpretation of the image contrast difficult. Field nonuniformity, pulsation in blood vesicle and susceptibility artifacts caused by air cavities were also problematic for CEST imaging. Conclusion: We have demonstrated successful CEST acquisition and Z-spectrum reconstruction on HNC patients with a clinical scanner. MRI acquisition in immobilized treatment position is critical for image quality as well as the success of CEST image acquisition. CEST images provide novel contrast of metabolites in HNC and present great potential in the pre- and post-treatment assessment of patients undergoing radiation therapy.

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DOE OSTI2015

SU-E-J-254: Evaluating the Role of Mid-Treatment and Post-Treatment FDG-PET/CT in Predicting Progression-Free Survival and Distant Metastasis of Anal Cancer Patients Treated with Chemoradiotherapy

Purpose: To evaluate the role of mid-treatment and post-treatment FDG-PET/CT in predicting progression-free survival (PFS) and distant metastasis (DM) of anal cancer patients treated with chemoradiotherapy (CRT). Methods: 17 anal cancer patients treated with CRT were retrospectively studied. The median prescription dose was 56 Gy (range, 50–62.5 Gy). All patients underwent FDG-PET/CT scans before and after CRT. 16 of the 17 patients had an additional FDG-PET/CT image at 3–5 weeks into the treatment (denoted as mid-treatment FDG-PET/CT). 750 features were extracted from these three sets of scans, which included both traditional PET/CT measures (SUVmax, SUVpeak, tumor diameters, etc.) and spatialtemporal PET/CT features (comprehensively quantify a tumor’s FDG uptake intensity and distribution, spatial variation (texture), geometric property and their temporal changes relative to baseline). 26 clinical parameters (age, gender, TNM stage, histology, GTV dose, etc.) were also analyzed. Advanced analytics including methods to select an optimal set of predictors and a model selection engine, which identifies the most accurate machine learning algorithm for predictive analysis was developed. Results: Comparing baseline + mid-treatment PET/CT set to baseline + posttreatment PET/CT set, 14 predictors were selected from each feature group. Same three clinical parameters (tumor size, T stage and whether 5-FU was held during any cycle of chemotherapy) and two traditional measures (pre- CRT SUVmin and SUVmedian) were selected by both predictor groups. Different mix of spatial-temporal PET/CT features was selected. Using the 14 predictors and Naive Bayes, mid-treatment PET/CT set achieved 87.5% accuracy (2 PFS patients misclassified, all local recurrence and DM patients correctly classified). Post-treatment PET/CT set achieved 94.0% accuracy (all PFS and DM patients correctly predicted, 1 local recurrence patient misclassified) with logistic regression, neural network or support vector machine model. Conclusion: Applying radiomics approach to either midtreatment or post-treatment PET/CT could achieve high accuracy in predicting anal cancer treatment outcomes. This work was supported in part by the National Cancer Institute Grant R01CA172638.

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DOE OSTI2015

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered images were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction.

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DOE OSTI2015

SU-E-J-260: Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy

Purpose: To identify the effective quantitative image features (radiomics features) for prediction of response, survival, recurrence and metastasis of hepatocellular carcinoma (HCC) in radiotherapy. Methods: Multiphase contrast enhanced liver CT images were acquired in 16 patients with HCC on pre and post radiation therapy (RT). In this study, arterial phase CT images were selected to analyze the effectiveness of image features for the prediction of treatment outcome of HCC to RT. Response evaluated by RECIST criteria, survival, local recurrence (LR), distant metastasis (DM) and liver metastasis (LM) were examined. A radiation oncologist manually delineated the tumor and normal liver on pre and post CT scans, respectively. Quantitative image features were extracted to characterize the intensity distribution (n=8), spatial patterns (texture, n=36), and shape (n=16) of the tumor and liver, respectively. Moreover, differences between pre and post image features were calculated (n=120). A total of 360 features were extracted and then analyzed by unpaired student’s t-test to rank the effectiveness of features for the prediction of response. Results: The five most effective features were selected for prediction of each outcome. Significant predictors for tumor response and survival are changes in tumor shape (Second Major Axes Length, p= 0.002; Eccentricity, p=0.0002), for LR, liver texture (Standard Deviation (SD) of High Grey Level Run Emphasis and SD of Entropy, both p=0.005) on pre and post CT images, for DM, tumor texture (SD of Entropy, p=0.01) on pre CT image and for LM, liver (Mean of Cluster Shade, p=0.004) and tumor texture (SD of Entropy, p=0.006) on pre CT image. Intensity distribution features were not significant (p>0.09). Conclusion: Quantitative CT image features were found to be potential predictors of the five endpoints of HCC in RT. This work was supported in part by the National Cancer Institute Grant R01CA172638.

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DOE OSTI2015

SU-E-J-270: Repeated 18F-FDG PET/CTs Based Feature Analysis for the Predication of Anal Cancer Recurrence

Purpose: To identify PET/CT based imaging predictors of anal cancer recurrence and evaluate baseline vs. mid-treatment vs. post-treatment PET/CT scans in the tumor recurrence prediction. Methods: FDG-PET/CT scans were obtained at baseline, during chemoradiotherapy (CRT, midtreatment), and after CRT (post-treatment) in 17 patients of anal cancer. Four patients had tumor recurrence. For each patient, the mid-treatment and post-treatment scans were respectively aligned to the baseline scan by a rigid registration followed by a deformable registration. PET/CT image features were computed within the manually delineated tumor volume of each scan to characterize the intensity histogram, spatial patterns (texture), and shape of the tumors, as well as the changes of these features resulting from CRT. A total of 335 image features were extracted. An Exact Logistic Regression model was employed to analyze these PET/CT image features in order to identify potential predictors for tumor recurrence. Results: Eleven potential predictors of cancer recurrence were identified with p < 0.10, including five shape features, five statistical texture features, and one CT intensity histogram feature. Six features were indentified from posttreatment scans, 3 from mid-treatment scans, and 2 from baseline scans. These features indicated that there were differences in shape, intensity, and spatial pattern between tumors with and without recurrence. Recurrent tumors tended to have more compact shape (higher roundness and lower elongation) and larger intensity difference between baseline and follow-up scans, compared to non-recurrent tumors. Conclusion: PET/CT based anal cancer recurrence predictors were identified. The post-CRT PET/CT is the most important scan for the prediction of cancer recurrence. The baseline and mid-CRT PET/CT also showed value in the prediction and would be more useful for the predication of tumor recurrence in early stage of CRT. This work was supported in part by the National Cancer Institute Grant R01CA172638.

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SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss or gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.

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SU-E-T-59: A Novel Multi-Beam Dynamic IMRT with Fixed-Jaw Technique for Left Breast Cancer Patients with Regional Lymph Nodes Radiotherapy

Purpose: This study was to investigate the dosimetric benefit of a novel intensity modulated radiation therapy (IMRT) technique for irradiating the left breast and regional lymph node (RLN). Methods: The breast and RLN (internal mammary node and periclavicular node) and normal tissue were contoured for 16 consecutive left-sided breast cancer patients previously treated with RT after lumpectomy. Nine equi-spaced fields IMRT (9 -field IMRT), tangential multi-beam IMRT (tangential-IMRT) and IMRT with fixed-jaw technique (FJT-IMRT) were developed and compared with three-dimensional conformal RT (3DCRT). Prescribed dose was 50 Gy in 25 fractions. Dose distributions and dose volume histograms were used to evaluate plans. Results: All IMRTs achieved similar target coverage and substantially reduced heart V30 and V20 compared to the 3DCRT. The average heart mean dose had different changes, which were 9.0Gy for 9-field IMRT, 5.7Gy for tangential-IMRT and 4.2Gy for FJT-IMRT. For the contralateral lung and breast, the 9-field IMRT has the highest mean dose; and the FJT-IMRT and tangential-IMRT had similar lower value. For the thyroid, both 9-field IMRT and FJT-IMRT had similar V30 (20% and 22%) and were significantly lower than that of 3DCRT (34%) and tangential-IMRT (46%). Moreover, the thyroid mean dose of FJT-IMRT is the lowest. For cervical esophagus and humeral head, the FJT-IMRT also had the best sparing. Conclusion: All 9-field IMRT, tangential-IMRT and FJT-IMRT had superiority for targets coverage and substantially reduced the heart volume of high dose irradiation. The FJT-IMRT showed advantages of avoiding the contralateral breast and lung irradiation and decreasing the thyroid, humeral head and cervical esophagus radiation dose at the expense of a slight monitor units (MUs) increasing.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-287: Dose Verification On the Variation of Target Volume and Organ at Risk in Preradiation Chemotherapy IMRT for Nasopharyngeal Cancer

Purpose: To quantify the target volume and organ at risk of nasopharyngeal carcinoma (NPC) patients with preradiation chemotherapy based on CT scanned during intensity-modulated radiotherapy (IMRT), and recalculate the dose distribution. Methods: Seven patients with NPC and preradiation chemotherapy, treated with IMRT (35 to 37 fractions) were reviewed. Repeat CT scanning was required to all of the patients during the radiotherapy, and the number of repeat CTs varies from 2 to 6. The plan CT and repeat CT were generated by different CT scanner. To ensure crespectively on the same IMPT plan. The real dose distribution was calculated by deformable registration and weighted method in Raystation (v 4.5.1). The fraction of each dose is based on radiotherapy record. The volumetric and dose differences among these images were calculated for nascIpharyngeal tumor and retro-pharyngeal lymph nodes (GTV-NX), neck lymph nodes(GTV-ND), and parotid glands. Results: The volume variation in GTV-NX from CT1 to CT2 was 1.15±3.79%, and in GTV-LN −0.23±4.93%. The volume variation in left parotid from CT1 to CT2 was −6.79±11.91%, and in right parotid −3.92±8.80%. In patient 2, the left parotid volume were decreased remarkably, as a Result, the V30 and V40 of it were increased as well. Conclusion: The target volume of patients with NPC varied lightly during IMRT. It shows that preradiation chemotherapy can control the target volume variation and perform a good dose repeatability. Also, the decreasing volume of parotid in some patient might increase the dose of it, which might course potential complications.

60 APPLIED LIFE SCIENCES↗