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DOE OSTI2014

MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based on an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

TU-C-17A-07: FusionARC Treatment with Adaptive Beam Selection Method

Purpose: Recently, a new treatment scheme, FusionARC, has been introduced to compensate for the pitfalls in single-arc VMAT planning. It basically allows for the static field treatment in selected locations, while the remaining is treated by single-rotational arc delivery. The important issue is how to choose the directions for static field treatment. This study presents an adaptive beam selection method to formulate fusionARC treatment scheme. Methods: The optimal plan for single-rotational arc treatment is obtained from two-step approach based on the reweighted total-variation (TV) minimization. To choose the directions for static field treatment with extra segments, a value of our proposed cost function at each field is computed on the new fluence-map, which adds an extra segment to the designated field location only. The cost function is defined as a summation of equivalent uniform dose (EUD) of all structures with the fluence-map, while assuming that the lower cost function value implies the enhancement of plan quality. Finally, the extra segments for static field treatment would be added to the selected directions with low cost function values. A prostate patient data was applied and evaluated with three different plans: conventional VMAT, fusionARC, and static IMRT. Results: The 7 field locations, corresponding to the lowest cost function values, are chosen to insert extra segment for step-and-shoot dose delivery. Our proposed fusionARC plan with the selected angles improves the dose sparing to the critical organs, relative to static IMRT and conventional VMAT plans. The dose conformity to the target is significantly enhanced at the small expense of treatment time, compared with VMAT plan. Its estimated treatment time, however, is still much faster than IMRT. Conclusion: The fusionARC treatment with adaptive beam selection method could improve the plan quality with insignificant damage in the treatment time, relative to the conventional VMAT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-G-BRF-09: Force- and Image-Adaptive Strategies for Robotised Placement of 4D Ultrasound Probes

Purpose: To allow continuous acquisition of high quality 4D ultrasound images for non-invasive live tracking of tumours for IGRT, image- and force-adaptive strategies for robotised placement of 4D ultrasound probes are developed and evaluated. Methods: The developed robotised ultrasound system is based on a 6-axes industrial robot (adept Viper s850) carrying a 4D ultrasound transducer with a mounted force-torque sensor. The force-adaptive placement strategies include probe position control using artificial potential fields and contact pressure regulation by a PD controller strategy. The basis for live target tracking is a continuous minimum contact pressure to ensure good image quality and high patient comfort. This contact pressure can be significantly disturbed by respiratory movements and has to be compensated. All measurements were performed on human subjects under realistic conditions. When performing cardiac ultrasound, rib- and lung shadows are a common source of interference and can disrupt the tracking. To ensure continuous tracking, these artefacts had to be detected to automatically realign the probe. The detection is realised by multiple algorithms based on entropy calculations as well as a determination of the image quality. Results: Through active contact pressure regulation it was possible to reduce the variance of the contact pressure by 89.79% despite respiratory motion of the chest. The results regarding the image processing clearly demonstrate the feasibility to detect image artefacts like rib shadows in real-time. Conclusion: In all cases, it was possible to stabilise the image quality by active contact pressure control and automatically detected image artefacts. This fact enables the possibility to compensate for such interferences by realigning the probe and thus continuously optimising the ultrasound images. This is a huge step towards fully automated transducer positioning and opens the possibility for stable target tracking in ultrasoundguided radiation therapy requiring contact pressure of 5–10 N. This work was supported by the Graduate School for Computing in Medicine and Life Sciences funded by Germany's Excellence Initiative [DFG GSC 235/1].

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Adaptive beamlet-based finite-size pencil beam dose calculation for independent verification of IMRT and VMAT

Purpose: The use of sophisticated dose calculation procedure in modern radiation therapy treatment planning is inevitable in order to account for complex treatment fields created by multileaf collimators (MLCs). As a consequence, independent volumetric dose verification is time consuming, which affects the efficiency of clinical workflow. In this study, the authors present an efficient adaptive beamlet-based finite-size pencil beam (AB-FSPB) dose calculation algorithm that minimizes the computational procedure while preserving the accuracy. Methods: The computational time of finite-size pencil beam (FSPB) algorithm is proportional to the number of infinitesimal and identical beamlets that constitute an arbitrary field shape. In AB-FSPB, dose distribution from each beamlet is mathematically modeled such that the sizes of beamlets to represent an arbitrary field shape no longer need to be infinitesimal nor identical. As a result, it is possible to represent an arbitrary field shape with combinations of different sized and minimal number of beamlets. In addition, the authors included the model parameters to consider MLC for its rounded edge and transmission. Results: Root mean square error (RMSE) between treatment planning system and conventional FSPB on a 10 × 10 cm{sup 2} square field using 10 × 10, 2.5 × 2.5, and 0.5 × 0.5 cm{sup 2} beamlet sizes were 4.90%, 3.19%, and 2.87%, respectively, compared with RMSE of 1.10%, 1.11%, and 1.14% for AB-FSPB. This finding holds true for a larger square field size of 25 × 25 cm{sup 2}, where RMSE for 25 × 25, 2.5 × 2.5, and 0.5 × 0.5 cm{sup 2} beamlet sizes were 5.41%, 4.76%, and 3.54% in FSPB, respectively, compared with RMSE of 0.86%, 0.83%, and 0.88% for AB-FSPB. It was found that AB-FSPB could successfully account for the MLC transmissions without major discrepancy. The algorithm was also graphical processing unit (GPU) compatible to maximize its computational speed. For an intensity modulated radiation therapy (∼12 segments) and a volumetric modulated arc therapy fields (∼90 control points) with a 3D grid size of 2.0 × 2.0 × 2.0 mm{sup 3}, dose was computed within 3–5 and 10–15 s timeframe, respectively. Conclusions: The authors have developed an efficient adaptive beamlet-based pencil beam dose calculation algorithm. The fast computation nature along with GPU compatibility has shown better performance than conventional FSPB. This enables the implementation of AB-FSPB in the clinical environment for independent volumetric dose verification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

An adaptive filtered back-projection for photoacoustic image reconstruction

Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing the correct signal strength of the absorbers. The reconstructed image of the second phantom further demonstrates the capability to form clear images of the spheres with sharp borders in the overlapping geometry. The smallest sphere is clearly visible and distinguishable, even though it is surrounded by two big spheres. In addition, image reconstructions were conducted with randomized noise added to the observed signals to mimic realistic experimental conditions. Conclusions: The authors have developed a new FBP algorithm that is capable for reconstructing high quality images with correct relative intensities and sharp borders for PAT. The results demonstrate that the weighting function serves as a precise ramp filter for processing the observed signals in the Fourier domain. In addition, this algorithm allows an adaptive determination of the cutoff frequency for the applied low pass filter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during plan optimization. Results: KBRT and original clinical plans were dosimetrically equivalent for parotid glands (mean/median doses), spinal cord, and brainstem (maximum doses). KBRT plans significantly reduced larynx median doses (21.5 ± 6.6 Gy to 17.9 ± 3.9 Gy), and oral cavity mean (32.3 ± 6.2 Gy to 28.9 ± 5.4 Gy) and median (28.7 ± 5.7 Gy to 23.2 ± 5.3 Gy) doses. Doses to ipsilateral parotid gland, larynx, oral cavity, and brainstem were lower or equivalent in the KBRT plans for the majority of cases. By contrast, KBRT plans generated without the dose warping and dose scaling steps were not significantly different from the clinical plans. Conclusions: Fast, semiautomatically generated HNC IMRT plans adapted from existing plans in a clinical database can be of equivalent or better quality than manually created plans. The reductions in OAR doses in the semiautomated plans, compared to the clinical plans, indicate that the proposed dose warping and scaling method shows promise in mitigating the impact of suboptimal clinical plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Proton dose calculation on scatter-corrected CBCT image: Feasibility study for adaptive proton therapy

Purpose: To demonstrate the feasibility of proton dose calculation on scatter-corrected cone-beam computed tomographic (CBCT) images for the purpose of adaptive proton therapy. Methods: CBCT projection images were acquired from anthropomorphic phantoms and a prostate patient using an on-board imaging system of an Elekta infinity linear accelerator. Two previously introduced techniques were used to correct the scattered x-rays in the raw projection images: uniform scatter correction (CBCT{sub us}) and a priori CT-based scatter correction (CBCT{sub ap}). CBCT images were reconstructed using a standard FDK algorithm and GPU-based reconstruction toolkit. Soft tissue ROI-based HU shifting was used to improve HU accuracy of the uncorrected CBCT images and CBCT{sub us}, while no HU change was applied to the CBCT{sub ap}. The degree of equivalence of the corrected CBCT images with respect to the reference CT image (CT{sub ref}) was evaluated by using angular profiles of water equivalent path length (WEPL) and passively scattered proton treatment plans. The CBCT{sub ap} was further evaluated in more realistic scenarios such as rectal filling and weight loss to assess the effect of mismatched prior information on the corrected images. Results: The uncorrected CBCT and CBCT{sub us} images demonstrated substantial WEPL discrepancies (7.3 ± 5.3 mm and 11.1 ± 6.6 mm, respectively) with respect to the CT{sub ref}, while the CBCT{sub ap} images showed substantially reduced WEPL errors (2.4 ± 2.0 mm). Similarly, the CBCT{sub ap}-based treatment plans demonstrated a high pass rate (96.0% ± 2.5% in 2 mm/2% criteria) in a 3D gamma analysis. Conclusions: A priori CT-based scatter correction technique was shown to be promising for adaptive proton therapy, as it achieved equivalent proton dose distributions and water equivalent path lengths compared to those of a reference CT in a selection of anthropomorphic phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-P-32: Adapting An MMLC to a Conventional Linac to Perform Stereotactic Applications

Purpose: Micro-MLCs minimizes beam scalloping effects caused by conventional-MLCs and facilitates conformal dynamic treatment delivery. But their effect on dosimetric parameters require careful investigations. Physical and dosimetric parameters and Linac mechanical stability with mMLC (net weight 30 Kg) attached to the gantry are to be investigated. Moreover, output study along with recommended jaws offsets are studied. Adaptation of an mMLC to our 16-years old conventional Linac is investigated in this work Methods: BrainLab mMLC (m3) mounted in a detachable chassis to the Philips SL-15 Linac (30kg). Gantry and collimator spoke shots measurements are made using a calibrated film in a solid phantom and compared with pin-point measurements. Leaf penumbra, transmission, leakage between the leaves, percentage depth dose (PDD) are measured using IBA pin-point ion chamber at 6 and 10 MV. For output measurements (using brass build-up cap), jaws are modified continuously regarding to m3-fields while output factor are compared with fixed jaws situation, while the mMLC leaf configuration is modified for different m3-fields Results: Mean transmission through leaves is 1.9±0.1% and mean leakage between leaves is 2.8±0.15%. Between opposing leaves abutting along the central beam-axis mean transmission is 15±3%, but it is reduced to 4.5±0.6% by moving the abutment position 4.5cm off-axis. The penumbra was sharper for m3 -fields than jaws-fields (maximum difference is 1.51±0.2%). m3-fields PDD show ∼3% variation from those of jaws-fields. m3-fields output factors show large variations (<4%) from Jaws defined fields. Output for m3-rectangular fields show slight variation in case of leaf-end&leaf-side as well as X-jaw&Y-jaw exchange. Circular m3-fields output factors shows close agreement with their corresponding square jaws-defined fields using 2mm Jaws offsets, If jaws are retracted to m3 limits, differences become <5%. Conclusion: BrainLab m3 is successfully adapted to our 16 old Philips-SL-15 Linac. Dosimetric properties should be taken into account for treatment planning considerations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-58: Comparison of Conformal Tracking Methods Using Initial, Adaptive and Preceding Image Frames for Image Registration

Purpose: Accounting for tumor motion during radiation therapy is important to ensure that the tumor receives the prescribed dose. Increasing the field size to account for this motion exposes the surrounding healthy tissues to unnecessary radiation. In contrast to using motion-encompassing techniques to treat moving tumors, conformal radiation therapy (RT) uses a smaller field to track the tumor and adapts the beam aperture according to the motion detected. This work investigates and compares the performance of three markerless, EPID based, optical flow methods to track tumor motion with conformal RT. Methods: Three techniques were used to track the motions of a 3D printed lung tumor programmed to move according to the tumor of seven lung cancer patients. These techniques utilized a multi-resolution optical flow algorithm as the core computation for image registration. The first method (DIR) registers the incoming images with an initial reference frame, while the second method (RFSF) uses an adaptive reference frame and the third method (CU) uses preceding image frames for registration. The patient traces and errors were evaluated for the seven patients. Results: The average position errors for all patient traces were 0.12 ± 0.33 mm, −0.05 ± 0.04 mm and −0.28 ± 0.44 mm for CU, DIR and RFSF method respectively. The position errors distributed within 1 standard deviation are 0.74 mm, 0.37 mm and 0.96 mm respectively. The CU and RFSF algorithms are sensitive to the characteristics of the patient trace and produce a wider distribution of errors amongst patients. Although the mean error for the DIR method is negatively biased (−0.05 mm) for all patients, it has the narrowest distribution of position error, which can be corrected using an offset calibration. Conclusion: Three techniques of image registration and position update were studied. Using direct comparison with an initial frame yields the best performance. The authors would like to thank Dr.YeLin Suh for making the Cyberknife dataset available to us. Scholarship funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and CancerCare Manitoba Foundation is acknowledged.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-77: Dose Tracking On An MR-Linac for Online QA and Plan Adaptation in Abdominal Organs

Recent developments made MRI-guided radiotherapy feasible. Simultaneously performed imaging during dose delivery reveals the influence of changes in anatomy not yet known at the planning stage. When targeting highly motile abdominal organs, respiratory gating is commonly employed in MRI and investigated in external beam radiotherapy to mitigate malicious motion effects. The purpose of the presented work is to investigate anatomy-adaptive dose reconstruction in the treatment of abdominalorgans using concurrent (duplex) gating of an integrated MRlinac modality.Using navigators, 3D-MR images were sampled during exhale phase, requiring 3s per axial volume (360×260×100mm{sup 3}, waterselective T1w-FFE). Deformation vector fields (DVF) were calculated for all imaging dynamics with respect to initial anatomy, yielding an estimation of anatomy changes over the time of a fraction. A pseudo-CT was generated from the outline of a reference MR image, assuming a water-filled body. Consecutively, a treatment was planned on a fictional kidney lesion and optimized simulating a 6MV linac in a 1.5T magnetic field. After delivery, using the DVF, the pseudo-CT was deformed and dose accumulated for every individual gating interval yielding the true accumulated dose on the dynamic anatomy during beam-on.Dose-volume parameters on the PTV show only moderate changes when incorporating motion, i.e. ΔD{sub 99} (GTV)=0.3Gy with D{sub 99} (GTV)=20Gy constraints. However, local differences in the PTV region showed underdosages as high as 2.7Gy and overdosages up to 1.4Gy as compared to the optimized dose on static anatomy.A dose reconstruction toolchain was successfully implemented and proved its potential in the duplex gated treatment of abdominal organs by means of an MR-linac modality. While primary dose constraints were not violated on the fictional test data, large deviations could be found locally, which are left unaccounted for in conventional treatments. Dose-tracking of both target structures and organs at risk using 3D MRI during treatment enables truly adaptive hypofractionated radiotherapy. 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-81: Adaptive Radiotherapy for IMRT Head & Neck Patient in AKUH

Purpose: In this study we proposed Adaptive radiotherapy for IMRT patients which will brought an additional dimension to the management of patients with H&N cancer in Aga Khan University Hospital. Methods: In this study 5 Head and Neck (H&N) patients plan where selected, who’s Re-CT were done during the course of their treatment, they were simulated with IMRT technique to learn the consequence of anatomical changes that may occur during the treatment, as they are more dramatic changes can occur as compare to conventional treatment. All the organ at risk were drawn according RTOG guidelines and doses were checked as per NCCN guidelines. Results: The reduction in size of Planning target volume (PTV) is more than 20% in all the cases which leads to 3 to 5 % overdose to normal tissues and Organ at Risk. Conclusion: Through this study we would like to emphasis the importance of Adaptive Radiotherapy practice in all IMRT (H&N) patients, although prospective studies are required with larger sample sizes to address the safety and the clinical effect of such approaches on patient outcome, also one need to develop protocols before implementation of this technique in practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-102: Performance Variations Among Clinically Available Deformable Image Registration Tools in Adaptive Radiotherapy: How Should We Evaluate and Interpret the Result?

Purpose: To evaluate the performance variations in commercial deformable image registration (DIR) tools for adaptive radiation therapy. Methods: Representative plans from three different anatomical sites, prostate, head-and-neck (HN) and cranial spinal irradiation (CSI) with L-spine boost, were included. Computerized deformed CT images were first generated using virtual DIR QA software (ImSimQA) for each case. The corresponding transformations served as the “reference”. Three commercial software packages MIMVista v5.5 and MIMMaestro v6.0, VelocityAI v2.6.2, and OnQ rts v2.1.15 were tested. The warped contours and doses were compared with the “reference” and among each other. Results: The performance in transferring contours was comparable among all three tools with an average DICE coefficient of 0.81 for all the organs. However, the performance of dose warping accuracy appeared to rely on the evaluation end points. Volume based DVH comparisons were not sensitive enough to illustrate all the detailed variations while isodose assessment on a slice-by-slice basis could be tedious. Point-based evaluation was over-sensitive by having up to 30% hot/cold-spot differences. If adapting the 3mm/3% gamma analysis into the evaluation of dose warping, all three algorithms presented a reasonable level of equivalency. One algorithm had over 10% of the voxels not meeting this criterion for the HN case while another showed disagreement for the CSI case. Conclusion: Overall, our results demonstrated that evaluation based only on the performance of contour transformation could not guarantee the accuracy in dose warping. However, the performance of dose warping accuracy relied on the evaluation methodologies. Nevertheless, as more DIR tools are available for clinical use, the performance could vary at certain degrees. A standard quality assurance criterion with clinical meaning should be established for DIR QA, similar to the gamma index concept, in the near future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-434: Fixed Margin Or Online Adaptation for Intermediate-Risk Prostate Stereotactic Body Radiation Therapy? A Dosimetric Study

Purpose: To investigate the choice of fixed margin or online adaptation when treating intermediate-risk prostate cancer including seminal vesicles (SV) using stereotactic body radiation therapy (SBRT). Methods: 9 prostate SBRT patients were retrospectively studied. All patients were implanted with fiducial markers in the prostate for daily localization and verification. Each patient had 5 pairs of pre-treatment and post-treatment cone-beam CT (CBCT) per protocol. SVs were contoured on planning CT and all CBCTs by one attending physician. Simultaneous integral boost (SIB) IMRT plans were developed to deliver 25Gy/5fx to the SV while delivering 37Gy/5fx to the prostate. A 3mm isotropic margin was added to the prostate while a 5 mm isotropic margin was used for the SV. The planning CT was registered to daily pre-treatment and post-treatment CBCT based on fiducial markers in the prostate to mimic online prostate localization; and the SV on daily CBCT was transferred to the CT structure set after the prostates were aligned. Daily pre-treatment and post-treatment SV dose coverage and the organ-at-risk (OAR) sparing were evaluated for the SIB regimen. At least 95% of the SV need to receive the prescription dose (5Gy per fraction). Results: For the total of 90 daily SVs analyzed (ten CBCTs for each of nine patients), only 45 daily SVs (50%) were able to meet the coverage that 95% of the SV received 25Gy. The OAR sparing performance was acceptable for most of the dosimetric constraints in low-risk prostate SBRT protocol with only two exceptions in bladder V100 (cc). Conclusion: A fixed 5mm margin for SV is not sufficient to provide consistent daily dose coverage due to SV’s substantial inter- and intra-fractional motion relative to the prostate. This finding calls for innovative strategies in margin design as well as online treatment adaptation. This work is partially supported a master research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-AB-303-01: A Feasibility Study for Dynamic Adaptive Therapy of Non-Small Cell Lung Cancer

Purpose: To compare plans for NSCLC optimized using Dynamic Adaptive Therapy (DAT) with conventional IMRT optimization. DAT adapts plans based on changes in the target volume by using dynamic programing techniques to consider expected changes into the optimization process. Information gathered during treatment, e.g. from CBCT, is incorporated into the optimization. Methods and materials: DAT is formulated using stochastic control formalism, which minimizes the total expected number of tumor cells at the end of a treatment course subject to uncertainty inherent in the tumor response and organs-at-risk (OAR) dose constraints. This formulation allows for non-stationary dose distribution as well as non-stationary fractional dose as needed to achieve a series of optimal plans that are conformal to tumor over time. Sixteen phantom cases with various sizes and locations of tumors, and OAR geometries were generated. Each case was planned with DAT and conventional IMRT (60Gy/30fx). Tumor volume change over time was obtained by using, daily MVCT-based, two-level cell population model. Monte Carlo simulations have been performed for each treatment course to account for uncertainty in tumor response. Same OAR dose constraints were applied for both methods. The frequency of plan modification was varied to 1, 2, 5 (weekly), and 29 (daily). The final average tumor dose and OAR doses have been compared to quantify the potential benefit of DAT. Results: The average tumor max, min, mean, and D95 resulted from DAT were 124.0–125.2%, 102.1–114.7%, 113.7–123.4%, and 102.0–115.9% (range dependent on the frequency of plan modification) of those from conventional IMRT. Cord max, esophagus max, lung mean, heart mean, and unspecified tissue D05 resulted from AT were 84–102.4%, 99.8–106.9%, 66.9–85.6%, 58.2–78.8%, and 85.2–94.0% of those from conventional IMRT. Conclusions: Significant tumor dose increase and OAR dose reduction, especially with parallel OAR with mean or dose-volume constraints, can be achieved using DAT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-AB-303-11: Predict Parotids Deformation Applying SIS Epidemiological Model in H&N Adaptive RT

Purpose: The aim is to investigate the use of epidemiological models to predict morphological variations in patients undergoing radiation therapy (RT). The susceptible-infected-susceptible (SIS) deterministic model was applied to simulate warping within a focused region of interest (ROI). Hypothesis is to consider each voxel like a single subject of the whole sample and to treat displacement vector fields like an infection. Methods: Using Raystation hybrid deformation algorithms and automatic re-contouring based on mesh grid, we post-processed 360 MVCT images of 12 H&N patients treated with Tomotherapy. Study focused on parotid glands, identified by literature and previous analysis, as ROI more susceptible to warping in H&N region. Susceptible (S) and infectious (I) cases were identified in voxels with inter-fraction movement respectively under and over a set threshold. IronPython scripting allowed to export positions and displacement data of surface voxels for every fraction. A MATLAB homemade toolbox was developed to model the SIS. Results: SIS model was validated simulating organ motion on QUASAR phantom. Applying model in patients, within a [0–1cm] range, a single voxel movement of 0.4cm was selected as displacement threshold. SIS indexes were evaluated by MATLAB simulations. Dynamic time warping algorithm was used to assess matching between model and parotids behavior days of treatments. The best fit of the model was obtained with contact rate of 7.89±0.94 and recovery rate of 2.36±0.21. Conclusion: SIS model can follow daily structures evolutions, making possible to compare warping conditions and highlighting challenges due to abnormal variation and set-up errors. By epidemiology approach, organ motion could be assessed and predicted not in terms of average of the whole ROI, but in a voxel-by-voxel deterministic trend. Identifying anatomical region subjected to variations, would be possible to focus clinic controls within a cohort of pre-selected patients eligible for adaptive RT. The research is partially co-funded by the Italian Research Grant: Dose warping methods for IGRT and Adaptive RT: dose accumulation based on organ motion and anatomical variations of the patients during radiation therapy treatments,MoH (GR-2010-2318757) and Tecnologie Avanzate S.r.l.(Italy)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-AB-BRA-09: Sensitivity of Plan Re-Optimization to Errors in Deformable Image Registration in Online Adaptive Image-Guided Radiation Therapy

Purpose: Online adaptive therapy (ART) relies on auto-contouring using deformable image registration (DIR). DIR’s inherent uncertainties require user intervention and manual edits while the patient is on the table. We investigated the dosimetric impact of DIR errors on the quality of re-optimized plans, and used the findings to establish regions for focusing manual edits to where DIR errors can Result in clinically relevant dose differences. Methods: Our clinical implementation of online adaptive MR-IGRT involves using DIR to transfer contours from CT to daily MR, followed by a physicians’ edits. The plan is then re-optimized to meet the organs at risk (OARs) constraints. Re-optimized abdomen and pelvis plans generated based on physician edited OARs were selected as the baseline for evaluation. Plans were then re-optimized on auto-deformed contours with manual edits limited to pre-defined uniform rings (0 to 5cm) around the PTV. A 0cm ring indicates that the auto-deformed OARs were used without editing. The magnitude of the variations caused by the non-deterministic optimizer was quantified by repeat re-optimizations on the same geometry to determine the mean and standard deviation (STD). For each re-optimized plan, various volumetric parameters for the PTV, the OARs were extracted along with DVH and isodose evaluation. A plan was deemed acceptable if the variation from the baseline plan was within one STD. Results: Initial results show that for abdomen and pancreas cases, a minimum of 5cm margin around the PTV is required for contour corrections, while for pelvic and liver cases a 2–3 cm margin is sufficient. Conclusion: Focusing manual contour edits to regions of dosimetric relevance can reduce contouring time in the online ART process while maintaining a clinically comparable plan. Future work will further refine the contouring region by evaluating the path along the beams, dose gradients near the target and OAR dose metrics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-AB-303-07: Computational Monitoring Framework of Four-Dimensional Dose Distributions During Treatment Time Based On a 2D/3D Registration with Adaptive Transformation Parameters in Lung Stereotactic Body Radiotherapy

Purpose: The aim of this study was to develop a computational framework for monitoring four-dimensional (4D) dose distributions during treatment time based on a 2D/3D registration with adaptive transformation parameters (ATPs) in lung stereotactic body radiotherapy (SBRT). Methods: The 4D dose distributions during the SBRT were calculated by applying a pencil beam convolution (PBC) algorithm to simulated 4D-computed tomography (CT) images during treatment time (hereinafter referred to as “treatment” 4D-CT images). The “treatment” 4D-CT images were derived by deforming 3D planning CT images by using transformation parameters so that 2D planning portal dose images (PDIs) can resemble 2D dynamic clinical PDIs in each frame, which were derived from electronic portal imaging device (EPID) images. The transformation parameters were optimized by the Levenberg- Marquardt (LM) algorithm. The optimized transformation parameters in a certain frame were adaptively employed as initial transformation parameters for optimization of the parameters in the consecutive frame. Gamma pass rates (3mm/3%) between dynamic clinical PDIs and dynamic “treatment” PDIs derived from the “treatment” 4D-CT images were measured for comparing the proposed frameworks without and with the ATPs. These proposed frameworks were applied to the EPID dynamic images (40 frames) of two patients with lung cancer, who underwent the SBRT. Results: Gamma pass rates without and with the ATPs were 83.01±4.42% and 89.31±3.18% on average, respectively (p<0.05). Moreover, percentage errors between prescribed doses and estimated doses at an isocenter by the proposed frameworks without and with the ATPs were 10.67±5.66% and 6.34±0.47% on average, respectively (p<0.05). Conclusion: The proposed framework with ATPs could be useful to ensure the quality of the SBRT by monitoring 4D dose distributions during treatment time.

60 APPLIED LIFE SCIENCES↗