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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.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality

Purpose: To develop a quantitative decision making metric for automatically detecting irregular breathing using a large patient population that received phase-sorted 4DCT. Methods: This study employed two patient cohorts. Cohort#1 contained 256 patients who received a phasesorted 4DCT. Cohort#2 contained 86 patients who received three weekly phase-sorted 4DCT scans. A previously published technique used a single abdominal surrogate to calculate the ratio of extreme inhalation tidal volume to normal inhalation tidal volume, referred to as the κ metric. Since a single surrogate is standard for phase-sorted 4DCT in radiation oncology clinical practice, tidal volume was not quantified. Without tidal volume, the absolute κ metric could not be determined, so a relative κ (κrel) metric was defined based on the measured surrogate amplitude instead of tidal volume. Receiver operator characteristic (ROC) curves were used to quantitatively determine the optimal cutoff value (jk) and efficiency cutoff value (τk) of κrel to automatically identify irregular breathing that would reduce the image quality of phase-sorted 4DCT. Discriminatory accuracy (area under the ROC curve) of κrel was calculated by a trapezoidal numeric integration technique. Results: The discriminatory accuracy of ?rel was found to be 0.746. The key values of jk and tk were calculated to be 1.45 and 1.72 respectively. For values of ?rel such that jk≤κrel≤τk, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of κrel held consistent over 3 weeks for 73% of the patients in cohort#3. Conclusion: The decision making metric, ?rel, was shown to be an accurate classifier of irregular breathing patients in a large patient population. This work provided an automatic quantitative decision making metric to quickly and accurately assess the extent to which irregular breathing is occurring during phase-sorted 4DCT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-159: Analysis of Total Imaging Uncertainty in Respiratory-Gated Radiotherapy

Purpose: In respiratory-gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory-gated radiotherapy. Methods: Two factors of imaging uncertainties related to respiratory-gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X-ray image was acquired for image-guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X-ray image. The total imaging uncertainty was analyzed from these two factors. Results: In the CT image, the uncertainty between the target and cylindrical marker’s actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm. Conclusion: The total imaging uncertainty in respiratory-gated radiotherapy was clinically acceptable. However, an internal margin should be added to account for the total imaging uncertainty.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-167: Dosimetric Consequences From Minimal Displacements in APBI with SAVI Applicators

Purpose: To determine the importance of providing proper solid immobilization in every fraction of treatment in APBI with brachytherapy. Methods: 125 patients treated with APBI brachytherapy with SAVI applicators at SFRO Boca Raton, from 2013–2015 were considered for this retrospective study. The CT scans of each patient, which were taken before each treatment, were imported in to the Oncentra treatment planning system. Then they were compared with the initial CT scan which was used for the initial plan. Deviation in displacements in reference to ribs and skin surface was measured and dosimetric evaluations respective to the initial image were performed. Results: Small deviations in displacements were observed from the SAVI applicator to the ribs and the skin surface. Dosimetric evaluations revealed, very small changes in the inter-fractionation position make significant differences in the maximum dose to critical organs. Additionally, the volume of the cavity also changed between fractions. As a Result, the maximum dose manifested variance between 10% and 32% in ribs and skin surface respectively. Conclusion: It appears that taking a CT scan before each treatment is necessary to minimize the risk of delivering undesired high doses to the critical organs. This study indicates, in 30% of the cases re-planning was necessary between treatments. We conclude that, treatment planning teams should evaluate the placement of the device by analyzing the CT images before each treatment and they must be prepared for re-planning if needed. This study also reveals the urgent need of improving the immobilization methods with APBI when treating with the SAVI applicator.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-170: Dosimetric Consequences of Uncorrected Rotational Setup Errors During Stereotactic Body Radiation Therapy (SBRT) Treatment of Pancreatic Cancers

Purpose: To explore the dosimetric consequences of uncorrected rotational setup errors during SBRT for pancreatic cancer patients. Methods: This was a retrospective study utilizing data from ten (n=10) previously treated SBRT pancreas patients. For each original planning CT, we applied rotational transformations to derive additional CT images representative of possible rotational setup errors. This resulted in 6 different sets of rotational combinations, creating a total of 60 CT planning images. The patients’ clinical dosimetric plans were then applied to their corresponding rotated CT images. The 6 rotation sets encompassed a 3, 2 and 1-degree rotation in each rotational direction and a 3-degree in just the pitch, a 3-degree in just the yaw and a 3-degree in just the roll. After the dosimetric plan was applied to the rotated CT images, the resulting plan was then evaluated and compared with the clinical plan for tumor coverage and normal tissue sparing. Results: PTV coverage, defined here by V33 throughout all of the patients’ clinical plans, ranged from 92–98%. After an n degree rotation in each rotational direction that range decreased to 68–87%, 85–92%, and 88– 94% for n=3, 2 and 1 respectively. Normal tissue sparing defined here by the proximal stomach V15 throughout all of the patients’ clinical plans ranged from 0–8.9 cc. After an n degree rotation in each rotational direction that range increased to 0–17 cc, 0–12 cc, and 0–10 cc for n=3, 2, and 1 respectively. Conclusion: For pancreatic SBRT, small rotational setup errors in the pitch, yaw and roll direction on average caused under dosage to PTV and over dosage to proximal normal tissue. The 1-degree rotation was on average the least detrimental to the normal tissue and the coverage of the PTV. The 3-degree yaw created on average the lowest increase in volume coverage to normal tissue. This research was sponsored by the AAPM Education Council through the AAPM Education and Research Fund for the AAPM Summer Undergraduate Fellowship Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-189: Determination of Markerless Lung Tumor Position in Real Time: A Feasibility Study Using a Novel Tomo-Cinegraphy Imaging

Purpose: A Tomo-Cinegraphy (TC) is a method to generate a series of temporal tomographic images from projection images of the on-board imager (OBI) while gantry is moving. It is to test if this technique is useful to determine a lung tumor position during treatments. Methods: Tomographic image via background subtraction, TIBS uses a priori anatomical information from a previous CT scan to isolate a SOI from a planar kV image by factoring out the attenuations by tissues outside the SOI (background). This idea was extended to a TC, which enables to generate tomographic images of same geometry from the projection of different gantry angles and different breathing phases. Projection images of a lung patient for CBCT acquisition are used to generate TC images. A region of interest (ROI) is selected around a tumor adding 2cm margins. Center of mass (COM) of the ROI is traced to determine tumor position for every projection images. Results: Tumor is visible in the TC images while the OBI projections are not. The coordinates of the COMs represent the temporal tumor positions. While, it is not possible to trace the tumor motion using the projection images. A source of time delay is the time to acquire projection images, which is always less than a second. Conclusion: TC allows tracking the tumor positions without fiducial markers in real time for some lung patients, if the projection images are acquired during treatments. Partially supported by NIH R01CA133539.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-209: Geometric Distortion at 3T in a Commercial 4D MRI-Compatible Phantom

Purpose: There are very few commercial 4D phantoms that are marketed as MRI compatible. We are evaluating one such commercial phantom, made to be used with an MRI-Linear accelerator. The focus of this work is to characterize the geometric distortions produced in this phantom at 3T using 3 clinical MR pulse sequences. Methods: The CIRS MRI-Linac Dynamic Phantom (CIRSTM) under investigation in this study consists of a softwaredriven moving tumour volume within a thorax phantom body and enables dose accumulation by placing a dosimeter within the tumour volume. Our initial investigation is to evaluate the phantom in static mode prior to examining its 4D capability. The water-filled thorax phantom was scanned using a wide-bore Philips 3T Achieva MRI scanner employing a Thoracic xl coil and clinical 2D T1W FFE, 2D T1W TSE and 3D T1W TFE pulse sequences. Each of the MR image sets was rigidly fused with a reference CT image of the phantom employing a rigid registration with 6 degrees of freedom. Geometric distortions between the MR and CT image sets were measured in 3 dimensions at selected points along the periphery of the distortion grid embedded within the phantom body (11.5, 7.5 and 3 cm laterally, ant/post and sup/inf of magnetic isocenter respectively). Results: The maximal measured geometric distortions between the MR and reference CT points of interest were 0.9, 1.8 and 1.3 mm in the lateral, anteriorposterior and cranio-caudal directions, respectively. For all 3 spatial dimensions, the maximal distortions occurred for the FFE pulse sequence. Maximal distortions for the 2D FFE, 2D TSE and 3D TFE sequences were 1, 0.7 and 1.8 mm, respectively. Conclusion: Our initial static investigation of this phantom shows minimal geometric distortions at 3T along the periphery of the embedded grid. CIRS has provided us with a phantom at no charge for evaluation at 3 Tesla.

60 APPLIED LIFE SCIENCES↗
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.

60 APPLIED LIFE SCIENCES↗
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.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-224: Using UTE and T1 Weighted Spin Echo Pulse Sequences for MR-Only Treatment Planning; Phantom Study

Purpose: Investigating a new approach in MRI based treatment planning using the combination of (Ultrashort Echo Time) UTE and T1 weighted spin echo pulse sequences to delineate air, bone and water (soft tissues) in generating pseudo CT images comparable with CT. Methods: A gel phantom containing chicken bones, ping pang balls filled with distilled water and air bubbles, was made. It scanned with MRI using UTE and 2D T1W SE pulse sequences with (in plane resolution= 0.53mm, slice thickness= 2 mm) and CT with (in plane resolution= 0.5 mm and slice thickness= 0.75mm) as a ground truth for geometrical accuracy. The UTE and T1W SE images were registered with CT using mutual information registration algorithm provided by Philips Pinnacle treatment planning system. The phantom boundaries were detected using Canny edge detection algorithm for CT, and MR images. The bone, air bubbles and water in ping pong balls were segmented from CT images using threshold 300HU, - 950HU and 0HU, respectively. These tissue inserts were automatically segmented from combined UTE and T1W SE images using edge detection and relative intensity histograms of the phantom. The obtained segmentations of air, bone and water inserts were evaluated with those obtained from CT. Results: Bone and air can be clearly differentiated in UTE images comparable to CT. Combining UTE and T1W SE images successfully segmented the air, bone and water. The maximum segmentation differences from combine MRI images (UTE and T1W SE) and CT are within 1.3 mm, 1.1mm for bone, air, respectively. The geometric distortion of UTE sequence is small less than 1 pixel (0.53 mm) of MR image resolution. Conclusion: Our approach indicates that MRI can be used solely for treatment planning and its quality is comparable with CT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-230: Evaluation of ViewRay 0.35 T MRI Normal Structure Segmentation

Purpose: In order to take advantage of the high resolution soft tissue imaging available in MR images, we investigated 3D images obtained with the low field 0.35 T MR in ViewRay to serve as an alternative to CT scans for radiotherapy treatment planning. In these images, normal and target structure delineation can be visualized. Assessment is based upon comparison with the CT images and the ability to produce comparable contours. Methods: Routine radiation oncology CT scans were acquired on five patients. Contours of brain, brainstem, esophagus, heart, lungs, spinal cord, and the external body were drawn. The same five patients were then scanned on the ViewRay TrueFISP-based imaging pulse sequence. The same organs were selected on the MR images and compared to those from the CT scan. Physical volume and the Dice Similarity Coefficient (DSC) were used to assess the contours from the two systems. Image quality stability was quantitatively ensured throughout the study following the recommendations of the ACR MR accreditation procedure. Results: The highest DSC of 0.985, 0.863, and 0.843 were observed for brain, lungs, and heart respectively. On the other hand, the brainstem, spinal cord, and esophagus had the lowest DSC. Volume agreement was most satisfied for the heart (within 5%) and the brain (within 2%). Contour volume for the brainstem and lung (a widely dynamic organ) varied the most (27% and 19%). Conclusion: The DSC and volume measurements suggest that the results obtained from ViewRay images are quantitatively consistent and comparable to those obtained from CT scans for the brain, heart, and lungs. MR images from ViewRay are well-suited for treatment planning and for adaptive MRI-guided radiotherapy. The physical data from 0.35 T MR imaging is consistent with our geometrical understanding of normal structures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-234: Application of a Breathing Motion Model to ViewRay Cine MR Images

Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determine motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-237: Real-Time 3D Anatomy Estimation From Undersampled MR Acquisitions

Recent developments made MRI guided radiotherapy feasible. Performing simultaneous imaging during fractions can provide information about changing anatomy by means of deformable image registration for either immediate plan adaptations or accurate dose accumulation on the changing anatomy. In 3D MRI, however, acquisition time is considerable and scales with resolution. Furthermore, intra-scan motion degrades image quality.In this work, we investigate the sensitivity of registration quality on imageresolution: potentially, by employing spatial undersampling, the acquisition timeof MR images for the purpose of deformable image registration can be reducedsignificantly.On a volunteer, 3D-MR imaging data was sampled in a navigator-gated manner, acquiring one axial volume (360×260×100mm{sup 3}) per 3s during exhale phase. A T1-weighted FFE sequence was used with an acquired voxel size of (2.5mm{sup 3}) for a duration of 17min. Deformation vector fields were evaluated for 100 imaging cycles with respect to the initial anatomy using deformable image registration based on optical flow. Subsequently, the imaging data was downsampled by a factor of 2, simulating a fourfold acquisition speed. Displacements of the downsampled volumes were then calculated by the same process.In kidneyliver boundaries and the region around stomach/duodenum, prominent organ drifts could be observed in both the original and the downsampled imaging data. An increasing displacement of approximately 2mm was observed for the kidney, while an area around the stomach showed sudden displacements of 4mm. Comparison of the motile points over time showed high reproducibility between the displacements of high-resolution and downsampled volumes: over a 17min acquisition, the componentwise RMS error was not more than 0.38mm.Based on the synthetic experiments, 3D nonrigid image registration shows little sensitivity to image resolution and the displacement information is preserved even when halving the resolution. This can be employed to greatly reduce image acquisition times for interventional applications in real-time. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.

60 APPLIED LIFE SCIENCES↗
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.

60 APPLIED LIFE SCIENCES↗
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.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-261: The Importance of Appropriate Image Preprocessing to Augment the Information of Radiomics Image Features

Purpose: To investigate how different image preprocessing techniques, their parameters, and the different boundary handling techniques can augment the information of features and improve feature’s differentiating capability. Methods: Twenty-seven NSCLC patients with a solid tumor volume and no visually obvious necrotic regions in the simulation CT images were identified. Fourteen of these patients had a necrotic region visible in their pre-treatment PET images (necrosis group), and thirteen had no visible necrotic region in the pre-treatment PET images (non-necrosis group). We investigated how image preprocessing can impact the ability of radiomics image features extracted from the CT to differentiate between two groups. It is expected the histogram in the necrosis group is more negatively skewed, and the uniformity from the necrosis group is less. Therefore, we analyzed two first order features, skewness and uniformity, on the image inside the GTV in the intensity range [−20HU, 180HU] under the combination of several image preprocessing techniques: (1) applying the isotropic Gaussian or anisotropic diffusion smoothing filter with a range of parameter(Gaussian smoothing: size=11, sigma=0:0.1:2.3; anisotropic smoothing: iteration=4, kappa=0:10:110); (2) applying the boundaryadapted Laplacian filter; and (3) applying the adaptive upper threshold for the intensity range. A 2-tailed T-test was used to evaluate the differentiating capability of CT features on pre-treatment PT necrosis. Result: Without any preprocessing, no differences in either skewness or uniformity were observed between two groups. After applying appropriate Gaussian filters (sigma>=1.3) or anisotropic filters(kappa >=60) with the adaptive upper threshold, skewness was significantly more negative in the necrosis group(p<0.05). By applying the boundary-adapted Laplacian filtering after the appropriate Gaussian filters (0.5 <=sigma<=1.1) or anisotropic filters(20<=kappa <=50), the uniformity was significantly lower in the necrosis group (p<0.05). Conclusion: Appropriate selection of image preprocessing techniques allows radiomics features to extract more useful information and thereby improve prediction models based on these features.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-265: Feasibility Study of Texture Analysis for Prognosis of Local Tumor Recurrence Within 5-Years for Pharyngeal-Laryngeal Carcinoma Patients Received Radiotherapy Treatment

Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were received two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image features, sensitivity of tumor segmentation variations, and effect of image filtering.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

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.

60 APPLIED LIFE SCIENCES↗