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DOE OSTI2018

Superresolution Diffuse Optical Imaging by Localization of Fluorescence

The multiple scattering of light presents major challenges in realizing useful in vivo imaging at tissue depths of more than about one millimeter, where many answers to health questions lie. Visible through near-infrared photons can be readily and safely detected through centimeters of tissue; however, limited information is available for image formation. One strategy for obtaining images is to model the photon transport and a simple incoherent model is the diffusion equation approximation to the Boltzmann transport equation. Such an approach provides a prediction of the mean intensity of heavily scattered light and hence provides a forward model for optimization-based computational imaging. While diffuse optical imaging methods have received substantial attention, they remain restricted in terms of resolution because of the loss of high-spatial-frequency information that is associated with the multiple scattering of photons. Consequently, only relatively large inhomogeneities, such as tumors or organs in small animals, can be effectively resolved. We introduce a superresolution imaging approach based on point localization in a diffusion framework that enables over two orders of magnitude improvement in the spatial resolution of diffuse optical imaging. The method is demonstrated experimentally by localizing a fluorescent inhomogeneity in a highly scattering slab and characterizing the localization uncertainty. The approach allows imaging through centimeters of tissue with a resolution of tens of microns, thereby enabling cells or cell clusters to be resolved. More generally, this high-resolution imaging approach could be applied with any physical transport or wave model and hence to a broad class of physical problems. Finally, paired with a suitable optical contrast mechanism, as can be realized with targeted fluorescent molecules or genetically modified animals, superresolution diffuse imaging should open alternative dimensions for in vivo applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Sparsity-based photoacoustic image reconstruction with a linear array transducer and direct measurement of the forward model

Photoacoustic (PA) imaging is an emerging imaging technique for many clinical applications. One of the challenges posed by clinical translation is that imaging systems often rely on a finite-aperture transducer rather than a full tomography system. This results in imaging artifacts arising from an underdetermined reconstruction of the initial pressure distribution (IPD). Furthermore, clinical applications often require deep imaging, resulting in a low-signal-to-noise ratio for the acquired signal because of strong light attenuation in tissue. Conventional approaches to reconstruct the IPD, such as back projection and time-reversal, do not adequately suppress the artifacts and noise. We propose a sparsity-based optimization approach that improves the reconstruction of IPD in PA imaging with a linear array ultrasound transducer. In simulation studies, the forward model matrix was measured from k-Wave simulations, and the approach was applied to reconstruct simulated point objects and the Shepp–Logan phantom. The results were compared with the conventional back projection, time-reversal approach, frequency-domain reconstruction, and the iterative least-squares approaches. In experimental studies, the forward model of our imaging system is directly measured by scanning a graphite point source through the imaging field of view. Experimental images of graphite inclusions in tissue-mimicking phantoms are reconstructed and compared with the back projection and iterative least-squares approaches. Altogether these results show that our proposed optimization approach can leverage the sparsity of the PA images to improve the reconstruction of the IPD and outperform the existing popular reconstruction approaches.

47 OTHER INSTRUMENTATION↗

DOE OSTI2013

Radial differential interior tomography and its image reconstruction with differentiated backprojection and projection onto convex sets

Purpose: Interior tomography has been recognized as one of the most effective approaches in computed tomography (CT) to reduce radiation dose rendered to patients. In this work, the authors propose and evaluate an imaging method of radial differential interior tomography.Methods: In interior tomography, an x-ray beam is collimated to only irradiate the region of interest (ROI) with suspected lesions while the surrounding area/volume of normal tissues/organs is spared. In the proposed imaging method of radial differential interior tomography, the outcome is a ROI image that has gone through a radial differential filtering. The image reconstruction algorithm for the radial differential interior tomography is kept in the fashion of differentiated backprojection and projection onto convex sets, but the required a priori knowledge in a small round area becomes zero and may be more readily available in practice.Results: Using the projection data simulated by computer and acquired by CT scanner, the authors evaluate and verify the performance of the proposed radial differential interior tomography method and its associated image reconstruction algorithm. The preliminary results show that the proposed imaging method can generate an image that is the radial differentiation of a conventional tomographic image and is robust over noise that inevitably exist in practice.Conclusions: It is believed that the proposed imaging method may find its utility in advanced clinical applications wherein a ROI-based image processing and analysis is required for lesion visualization, characterization, and diagnosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstruction to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

SU-E-J-100: Reconstruction of Prompt Gamma Ray Three Dimensional SPECT Image From Boron Neutron Capture Therapy(BNCT)

Purpose: Purpose of paper is to confirm the feasibility of acquisition of three dimensional single photon emission computed tomography (SPECT) image from boron neutron capture therapy (BNCT) using Monte Carlo simulation. Methods: In case of simulation, the pixelated SPECT detector, collimator and phantom were simulated using Monte Carlo n particle extended (MCNPX) simulation tool. A thermal neutron source (<1 eV) was used to react with the boron uptake region (BUR) in the phantom. Each geometry had a spherical pattern, and three different BURs (A, B and C region, density: 2.08 g/cm3) were located in the middle of the brain phantom. The data from 128 projections for each sorting process were used to achieve image reconstruction. The ordered subset expectation maximization (OSEM) reconstruction algorithm was used to obtain a tomographic image with eight subsets and five iterations. The receiver operating characteristic (ROC) curve analysis was used to evaluate the geometric accuracy of reconstructed image. Results: The OSEM image was compared with the original phantom pattern image. The area under the curve (AUC) was calculated as the gross area under each ROC curve. The three calculated AUC values were 0.738 (A region), 0.623 (B region), and 0.817 (C region). The differences between length of centers of two boron regions and distance of maximum count points were 0.3 cm, 1.6 cm and 1.4 cm. Conclusion: The possibility of extracting a 3D BNCT SPECT image was confirmed using the Monte Carlo simulation and OSEM algorithm. The prospects for obtaining an actual BNCT SPECT image were estimated from the quality of the simulated image and the simulation conditions. When multiple tumor region should be treated using the BNCT, a reasonable model to determine how many useful images can be obtained from the SPECT could be provided to the BNCT facilities. This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies (ICT) and Future Planning (MSIP)(Grant No.200900420) and the Radiation Technology Research and Development program (Grant No.2013043498), Republic of Korea.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

SU-E-J-111: The Contouring Error of the Parotids Based On the CT and MRI Images in Radiotherapy Planning for Nasopharyngeal Carcinoma

Purpose: To analyze the variation of sketching the parotid for patients with nasopharyngeal carcinoma who underwent radiotherapy based on computed tomography (CT) and magnetic resonance(MR) images. Methods: 41 nasopharyngeal cancer patients were randomly selected. Each patient underwent MR and CT scanning. The Gross Tumor Volume and Organs at risk were contoured on both contrasted CT and T1-MR images. For each patient, one radiotherapist sketched the parotid on CT and MR images for 10 times, and 10 different radiotherapists were asked to sketching the parotid on CT and MR images only one time. The inter- and intra-observers volumes and outline variations were compared. Results: The volumes of parotid contoured by inter-observer on CT and MR images were 34.6±12.1cm{sup 3}(left),34.3±9.0cm{sup 3}(right) and 24.6±7.6cm{sup 3}(L),23.2±8.1cm{sup 3}(R); In the same way, for intra-observer on CT and MR images the volumes were 28.2±7.6cm{sup 3}(L),29.4±9.4cm{sup 3}(R) and 24.4±7.6cm{sup 3}(L),22.5±7.4cm{sup 3}(R), respectively. The variable ratios of volume on MR images were 4.7±0.7%(L),5.0±0.6%(R) for inter-observer and 2.3±0.4%(L),2.1±0.7%(R) for intra-observer. Similarly, The inter- and intra-observer ratios for contouring on CT images reached 18.0±4.8%(L),17.4±4.6%(R) and 6.3±1.5%(L),6.8±1.5%(R), respectively. Conclusion: Contouring the parotids on MR images was more accurate and reproducible than that on CT images.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-186: Acquiring and Assessing Upright CBCT Images for Future Treatment Planning

Purpose: To acquire upright CBCT images using the onboard imager of a Varian TrueBeam. An easy to implement upright imaging protocol could allow for widespread upright radiation therapy which would greatly benefit certain patients. These include thoracic cancer patients (because lung volume increases in a seated position) and patients who experience substantial discomfort during supine treatment. Methods: To acquire upright CBCT images, the gantry head remained stationary at 0 degrees with the KV imager arms extended to their lateral positions. Phantoms were placed upright at the end of the treatment couch. During a scan, the couch rotated from 270 to 90 degrees while continuous fluoroscopic projections were taken by the onboard imager. To extend the field-of-view, this sequence was performed twice: once with the KV detector longitudinally offset +14.5cm and once with it longitudinally offset −14.5cm. The resulting two image sets were stitched together before reconstruction. The imaging beam parameters were chosen to deliver a dose similar to that given during a simulation CT. Image quality was evaluated for spatial linearity, high and low contrast resolution, and HU linearity using CatPhan and anthropomorphic phantoms. A deformable registration technique was used to evaluate HU mapping from a simulation CT. Results: Spatial linearity and high contrast resolution were maintained in upright CBCT when compared to simulation CT. However, low contrast resolution and HU linearity degraded. Streak artifacts were caused by the limited 180 degree arc of the couch, and the stitching process created a sharp artifact at the center of the reconstruction. The deformable registration was robust in the HU mapping even with these artifacts and the loss of HU linearity. Conclusions: The image quality obtained from upright CBCT was sufficient for treatment planning. The success of this novel technique is an important step towards a future clinical protocol. This project was funded in part by Varian Medical Systems, Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-243: Possibility of Exposure Dose Reduction of Cone-Beam Computed Tomography in An Image Guided Patient Positioning System by Using Various Noise Suppression Filters

Purpose: To investigate the possibility of exposure dose reduction of the cone-beam computed tomography (CBCT) in an image guided patient positioning system by using 6 noise suppression filters. Methods: First, a reference dose (RD) and low-dose (LD)-CBCT (X-ray volume imaging system, Elekta Co.) images were acquired with a reference dose of 86.2 mGy (weighted CT dose index: CTDIw) and various low doses of 1.4 to 43.1 mGy, respectively. Second, an automated rigid registration for three axes was performed for estimating setup errors between a planning CT image and the LD-CBCT images, which were processed by 6 noise suppression filters, i.e., averaging filter (AF), median filter (MF), Gaussian filter (GF), bilateral filter (BF), edge preserving smoothing filter (EPF) and adaptive partial median filter (AMF). Third, residual errors representing the patient positioning accuracy were calculated as an Euclidean distance between the setup error vectors estimated using the LD-CBCT image and RD-CBCT image. Finally, the relationships between the residual error and CTDIw were obtained for 6 noise suppression filters, and then the CTDIw for LD-CBCT images processed by the noise suppression filters were measured at the same residual error, which was obtained with the RD-CBCT. This approach was applied to an anthropomorphic pelvic phantom and two cancer patients. Results: For the phantom, the exposure dose could be reduced from 61% (GF) to 78% (AMF) by applying the noise suppression filters to the CBCT images. The exposure dose in a prostate cancer case could be reduced from 8% (AF) to 61% (AMF), and the exposure dose in a lung cancer case could be reduced from 9% (AF) to 37% (AMF). Conclusion: Using noise suppression filters, particularly an adaptive partial median filter, could be feasible to decrease the additional exposure dose to patients in image guided patient positioning systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-244: Validation of a 6D-Robotic-Couch and Image Guidance Radiation Therapy (IGRT) System for Localization in World's First Single-Room Proton Therapy System

Purpose: The Mevion S250 proton therapy unit is equipped with a 6D-robotic couch and IGRT system (Verity). The patient alignment process allows corrections in six degrees of freedom: translation (x,y,z), pitch, roll, and yaw (θ,ϑ,ψ). Geometric accuracy of couch corrections and imaging vs. radiation isocenter coincidence were quantified before clinical implementation. Methods: A commercial phantom with sixteen 2mm tungsten BBs was rigidly couch-mounted and imaged with CT. Seventeen rigid translations/rotations of known magnitude were digitally applied to the original CT image using commercial software, validated with Varian OBI system. For each altered image, phantom was mounted on robotic couch in original position, then Verity 2D:2D match (PA-LLAT) was performed using DRRs from altered images. Corrections were recorded and applied, phantom was imaged a second time and residual corrections recorded. Physical measurements verified that applied couch corrections coincided with both physical couch shifts/rotations and known CT image translations/rotations. Additionally, image vs. radiation isocenter coicidence was quantified over couch treatment angles (±90° from setup position) using radiochromic film and an image-guided couch star-shot. Posterior-anterior and left-lateral kV radiographs were taken before each beam was delivered to verify imaging/radiation isocentricity. Results: Verity suggested couch corrections and known CT shifts/rotations agreed within ±1mm (average: Δ lat=0.5mm; Δ vert=0.4mm; Δ long=0.3mm) and ± 0.4° (average: Δ pitch=0.24° Δ roll=0.01°; Δ yaw=0.10°). Physical couch measurements and Verity applied corrections agreed within ± 1mm (average: Δlat=0.5mm; Δvert=0.4mm; Δlong=0.2mm) and ±0.2° (average: Δpitch=0.03°; Δ roll=0.04°; Δ yaw=0.04°). The directionality of all translations and rotations were qualitatively verified. The image vs. radiation isocenter coincidence was <1mm and radiation-isocenter precision was <1mm over the 180° of couch motion, as indicated by film analysis. Conclusion: The Verity IGRT software and 6D-couch combination on the Mevion S250 was verified as accurate within 1mm and 0.5°. This complies with the TG-142 standards for a stereotactic radiotherapy IGRT system. Rob Cessac is employed as Product Manager for Mevion Medical Systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

SU-E-T-225: It Is Necessary to Contouring the Brainstem On MRI Images in Radiotherapy of Head and Neck Cancer

Purpose: To analyze the error in contouring the brainstem for patients with head and neck cancer who underwent radiotherapy based on computed tomography (CT) and magnetic resonance (MR) images. Methods: 20 brain tumor and 17 nasopharyngeal cancer patients were randomly selected. Each patient underwent MR and CT scanning. For each patient, one observer contoured the brainstem on CT and MR images for 10 times, and 10 observers from five centers delineated the brainstem on CT and MR images only one time. The inter- and intra-observers volume and outline variations were compared. Results: The volumes of brainstem contoured by inter- and intra-observers on CT and MR images were similar (p>0.05). The reproducibility of contouring brainstem on MR images was better than that on CT images (p<0.05) for both inter- and intra-observer variability. The inter- and intra-observer for contouring on CT images reached mean values of 0.81±0.05 (p>0.05) and of 0.85±0.05 (p>0.05), respectively, while on MR images these respective values were 0.90±0.05 (p>0.05) and 0.92±0.04 (p>0.05). Conclusion: Contouring the brainstem on MR images was more accurate and reproducible than that on CT images. Precise information might be more helpful for protecting the brainstem radiation injury the patients whose lesion were closed to brainstem.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

Purpose: Traditionally, the assessment of X-ray tube output and detector positioning accuracy of on-board imagers (OBI) has been performed manually and subjectively with rulers and dosimeters, and typically takes hours to complete. In this study, we have designed a compact modular computational platform to automatically analyze OBI images acquired with in-house designed phantoms as an efficient and robust surrogate. Methods: The platform was developed as an integrated and automated image analysis-based platform using MATLAB for easy modification and maintenance. Given a set of images acquired with the in-house designed phantoms, the X-ray output accuracy was examined via cross-validation of the uniqueness and integration minimization of important image quality assessment metrics, while machine geometric and positioning accuracy were validated by utilizing pattern-recognition based image analysis techniques. Results: The platform input was a set of images of an in-house designed phantom. The total processing time is about 1–2 minutes. Based on the data acquired from three Varian Truebeam machines over the course of 3 months, the designed test validation strategy achieved higher accuracy than traditional methods. The kVp output accuracy can be verified within +/−2 kVp, the exposure accuracy within 2%, and exposure linearity with a coefficient of variation (CV) of 0.1. Sub-millimeter position accuracy was achieved for the lateral and longitudinal positioning tests, while vertical positioning accuracy within +/−2 mm was achieved. Conclusion: This new platform delivers to the radiotherapy field an automated, efficient, and stable image analysis-based procedure, for the first time, acting as a surrogate for traditional tests for LINAC OBI systems. It has great potential to facilitate OBI quality assurance (QA) with the assistance of advanced image processing techniques. In addition, it provides flexible integration of additional tests for expediting other OBI quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-215: Towards MR-Only Image Guided Identification of Calcifications and Brachytherapy Seeds: Application to Prostate and Breast LDR Implant Dosimetry

Purpose: To identify and analyze the appearance of calcifications and brachytherapy seeds on magnitude and phase MRI images and to investigate whether they can be distinguished from each other on corrected phase images for application to prostate and breast low dose rate (LDR) implant dosimetry. Methods: An agar-based gel phantom containing two LDR brachytherapy seeds (Advantage Pd-103, IsoAid, 0.8mm diameter, 4.5mm length) and two spherical calcifications (large: 7mm diameter and small: 4mm diameter) was constructed and imaged on a 3T Philips MR scanner using a 16-channel head coil and a susceptibility weighted imaging (SWI) sequence (2mm slices, 320mm FOV, TR/ TE= 26.5/5.3ms, 15 degree flip angle). The phase images were unwrapped and corrected using a 32×32, 2D Hanning high pass filter to remove background phase noise. Appearance of the seeds and calcifications was assessed visually and quantitatively using Osirix (http://www.osirix-viewer.com/). Results: As expected, calcifications and brachytherapy seeds appeared dark (hypointense) relative to the surrounding gel on the magnitude MRI images. The diameter of each seed without the surrounding artifact was measured to be 0.1 cm on the magnitude image, while diameters of 0.79 and 0.37 cm were measured for the larger and smaller calcifications, respectively. On the corrected phase images, the brachytherapy seeds and the calcifications appeared bright (hyperintense). The diameter of the seeds was larger on the phase images (0.17 cm) likely due to the dipole effect. Conclusion: MRI has the best soft tissue contrast for accurate organ delineation leading to most accurate implant dosimetry. This work demonstrated that phase images can potentially be useful in identifying brachytherapy seeds and calcifications in the prostate and breast due to their bright appearance, which helps in their visualization and quantification for accurate dosimetry using MR-only. Future work includes optimizing phase filters to best identify and delineate seeds and calcifications.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-216: A Sequence Independent Approach for Quantification of MR Image Deformations From Brachytherapy Applicators

Purpose: MRI is increasingly used as a single imaging modality for brachytherapy treatment planning. The presence of a brachytherapy applicator may cause distortions in the images, especially at higher field strengths. Our aim is to develop a procedure to quantify these distortions theoretically for any MR-sequence and to verify the estimated deformations for clinical sequences. Methods: Image distortions due to perturbation of the B0-field are proportional to the ratio of the induced frequency shift and the read-out bandwidth of the applied sequence. By reconstructing a frequency-shift map from the phase data from a multi-echo sequence, distortions can be calculated for any MR-sequence. Verification of this method for estimating distortions was performed by acquiring images with opposing read-out directions and consequently opposing distortions. The applicator shift can be determined by rigidly matching these images. Clinically, T2W-TSE-images are used for this purpose. For pre-clinical tests, EPI-sequences with narrow read-out bandwidth (19.5–47.5Hz), consequently large distortions, were added to the set of clinical MRsequences. To quantify deformations of the Utrecht Interstitial CT/MR applicator (Elekta Brachytherapy) on a Philips Ingenia 3T MRI, pre-clinical tests were performed in a phantom with the applicator in water, followed by clinical validation. Results: Deformations observed in the narrow bandwidth EPI-images were well predicted using the frequency-shift, the latter giving an overestimation up to 30%/up to 1 voxel. For clinically applied MR-sequences distortions were well below the voxel size. In patient setup distortions determined from the frequency-shift map were at sub-voxel level (<0.7mm). Using T2W-images larger distortions were found (1–2mm). This discrepancy was caused by patient movement between/during acquisition of the T2W-images with opposing read-out directions. Conclusion: Phantom experiments demonstrated the feasibility of a clinical procedure for quantification of MR-image distortions for any MR-sequence. In a clinical set-up the distortions from a Utrecht interstitial CT/MR applicator are sub-voxel level. This work was partially funded by Elekta Brachytherpy.

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-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↗

DOE OSTI2015

SU-F-303-02: Achieving 4D MRI in Regular Breathing Cycle with Extended Acquisition Time of Dynamic MR Images

Purpose: The purpose of this study is to develop a technique to obtain four-dimensional (4D) magnetic resonance (MR) images that are more representative of a patient’s typical breathing cycle by utilizing an extended acquisition time while minimizing the image artifacts. Methods: The 4D MR data were acquired with the balanced steady state free precession in two-dimensional sagittal plane of view. Each slice was acquired repeatedly for about 15 s, thereby obtaining multiple images at each of the 10 phases in the respiratory cycle. This improves the probability that at least one of the images were acquired at the desired phase during a regular breathing cycle. To create optimal 4D MR images, an iterative approach was used to identify the set of images that yielded the highest slice-to-slice similarity. To assess the effectiveness of the approach, the data set was truncated into periods of 7 s (50 time points), 11 s (75 time points) and the full 15 s (100 time points). The 4D MR images were then sorted with data of the three different acquisition periods for comparison. Results: In general, the 4D MR images sorted using data from longer acquisition periods showed less mismatched artifacts. In addition, the normalized cross correlation (NCC) between slices of a 4D volume increases with increased acquisition period. The average NCC was 0.791 from the 7 s period, 0.794 from the 11 s period and 0.796 from the 15 s period. Conclusion: Our preliminary study showed that extending the acquisition time with the proposed sorting technique can improve image quality and reduce artifact presence in the 4D MR images. Data acquisition over two breathing cycles is a good trade-off between artifact reduction and scan time. This research was partially funded by the the Center for Radiation Oncology Research from UT MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. We use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective motion assessment. Applications of these methods include motion assessment, identifying treatment windows for gating, and determining optimal margins for treatment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-EF-204-02: Hiigh Quality and Sub-MSv Cerebral CT Perfusion Imaging

Purpose: CT Perfusion (CTP) imaging is of great importance in acute ischemic stroke management due to its potential to detect hypoperfused yet salvageable tissue and distinguish it from definitely unsalvageable tissue. However, current CTP imaging suffers from poor image quality and high radiation dose (up to 5 mSv). The purpose of this work was to demonstrate that technical innovations such as Prior Image Constrained Compressed Sensing (PICCS) have the potential to address these challenges and achieve high quality and sub-mSv CTP imaging. Methods: (1) A spatial-temporal 4D cascaded system model was developed to indentify the bottlenecks in the current CTP technology; (2) A task-based framework was developed to optimize the CTP system parameters; (3) Guided by (1) and (2), PICCS was customized for the reconstruction of CTP source images. Digital anthropomorphic perfusion phantoms, animal studies, and preliminary human subject studies were used to validate and evaluate the potentials of using these innovations to advance the CTP technology. Results: The 4D cascaded model was validated in both phantom and canine stroke models. Based upon this cascaded model, it has been discovered that, as long as the spatial resolution and noise properties of the 4D source CT images are given, the 3D MTF and NPS of the final CTP maps can be analytically derived for a given set of processing methods and parameters. The cascaded model analysis also identified that the most critical technical factor in CTP is how to acquire and reconstruct high quality source images; it has very little to do with the denoising techniques often used after parametric perfusion calculations. This explained why PICCS resulted in a five-fold dose reduction or substantial improvement in image quality. Conclusion: Technical innovations generated promising results towards achieving high quality and sub-mSv CTP imaging for reliable and safe assessment of acute ischemic strokes. K. Li, K. Niu, Y. Wu: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗