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DOE OSTI2014

SU-E-J-59: Effective Adaptive DMLC Gated Radiotherapy with OAR Sparing

Purpose: Patient respiratory motion degrades the effectiveness of cancer radiation treatment. Advanced respiratory gating delivers radiation dose accurately yet with elongated treatment time. The goal of this research is to propose a novel adaptive dMLC dynamic gating with high delivery efficiency and precision. Methods: The dose delivery of dMLC is aided by simultaneous tracking of tumor and organ at risk (OAR). The leaf opening/closing will follow the motion trajectory of the tumor while sparing the OAR. The treatment beam turns on only when there is no overlapping between OAR and tumor in BEV. A variety of evaluation metrics were considered and calculated, including duty cycle, beam toggling rate, and direct irradiation avoidance to OAR, under various combinations of different tumor margins and the distance between the centers of the tumor and OAR in BEV (expressed as dx). Results: Retrospective simulation was performed to investigate the feasibility and superiority of this technique using four groups of synchronized tumor and OAR motion data. The simulation results indicate that the tumor and OAR motion patterns and their relative positions are the dominant influential factors. The duty cycle can be greater than 96.71% yet can be as low as 6.69% depending different motion groups. This proposed technique provides good OAR protection, especially for such cases with low duty cycle for which as high as 77.71% maximal direct irradiation to OAR can be spared. Increasing dx improves the duty cycle (treatment efficiency) and provides better OAR volume sparing, whereas, that of the tumor margins has the opposite influence. Conclusion: This real-time adaptive dMLC gated radiation treatment with synchronous tumor and OAR tracking has inherent accurate dose delivery to tumor with reduced treatment time. In addition, the OAR protection capability make it an outstanding potential treatment strategy for mobile tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-124: FDG PET Metrics Analysis in the Context of An Adaptive PET Protocol for Node Positive Gynecologic Cancer Patients

Purpose: To compare PET extracted metrics and investigate the role of a gradient-based PET segmentation tool, PET Edge (MIM Software Inc., Cleveland, OH), in the context of an adaptive PET protocol for node positive gynecologic cancer patients. Methods: An IRB approved protocol enrolled women with gynecological, PET visible malignancies. A PET-CT was obtained for treatment planning prescribed to 45–50.4Gy with a 55– 70Gy boost to the PET positive nodes. An intra-treatment PET-CT was obtained between 30–36Gy, and all volumes re-contoured. Standard uptake values (SUVmax, SUVmean, SUVmedian) and GTV volumes were extracted from the clinician contoured GTVs on the pre- and intra-treament PET-CT for primaries and nodes and compared with a two tailed Wilcoxon signed-rank test. The differences between primary and node GTV volumes contoured in the treatment planning system and those volumes generated using PET Edge were also investigated. Bland-Altman plots were used to describe significant differences between the two contouring methods. Results: Thirteen women were enrolled in this study. The median baseline/intra-treatment primary (SUVmax, mean, median) were (30.5, 9.09, 7.83)/( 16.6, 4.35, 3.74), and nodes were (20.1, 4.64, 3.93)/( 6.78, 3.13, 3.26). The p values were all < 0.001. The clinical contours were all larger than the PET Edge generated ones, with mean difference of +20.6 ml for primary, and +23.5 ml for nodes. The Bland-Altman revealed changes between clinician/PET Edge contours to be mostly within the margins of the coefficient of variability. However, there was a proportional trend, i.e. the larger the GTV, the larger the clinical contours as compared to PET Edge contours. Conclusion: Primary and node SUV values taken from the intratreament PET-CT can be used to assess the disease response and to design an adaptive plan. The PET Edge tool can streamline the contouring process and lead to smaller, less user-dependent contours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-151: Dosimetric Evaluation of DIR Mapped Contours for Image Guided Adaptive Radiotherapy with 4D Cone-Beam CT

Purpose: To estimate dosimetric errors resulting from using contours deformably mapped from planning CT to 4D cone beam CT (CBCT) images for image-guided adaptive radiotherapy of locally advanced non-small cell lung cancer (NSCLC). Methods: Ten locally advanced non-small cell lung cancer (NSCLC) patients underwent one planning 4D fan-beam CT (4DFBCT) and weekly 4DCBCT scans. Multiple physicians delineated the gross tumor volume (GTV) and normal structures in planning CT images and only GTV in CBCT images. Manual contours were mapped from planning CT to CBCTs using small deformation, inverse consistent linear elastic (SICLE) algorithm for two scans in each patient. Two physicians reviewed and rated the DIR-mapped (auto) and manual GTV contours as clinically acceptable (CA), clinically acceptable after minor modification (CAMM) and unacceptable (CU). Mapped normal structures were visually inspected and corrected if necessary, and used to override tissue density for dose calculation. CTV (6mm expansion of GTV) and PTV (5mm expansion of CTV) were created. VMAT plans were generated using the DIR-mapped contours to deliver 66 Gy in 33 fractions with 95% and 100% coverage (V66) to PTV and CTV, respectively. Plan evaluation for V66 was based on manual PTV and CTV contours. Results: Mean PTV V66 was 84% (range 75% – 95%) and mean CTV V66 was 97% (range 93% – 100%) for CAMM scored plans (12 plans); and was 90% (range 80% – 95%) and 99% (range 95% – 100%) for CA scored plans (7 plans). The difference in V66 between CAMM and CA was significant for PTV (p = 0.03) and approached significance for CTV (p = 0.07). Conclusion: The quality of DIR-mapped contours directly impacted the plan quality for 4DCBCT-based adaptation. Larger safety margins may be needed when planning with auto contours for IGART with 4DCBCT images. Reseach was supported by NIH P01CA116602.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation method overcomes an important hurdle to the clinical implementation of online adaptive radiotherapy. Partial funding for this work was provided by Accuray Incorporated as part of a research collaboration with Erasmus MC Cancer Institute.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-245: Is Off-Line Adaptive Radiotherapy Sufficient for Head and Neck Cancer with IGRT?

Purpose: Radiation doses delivered to patients with head and neck cancer (HN) may deviate from the planned doses because of variations in patient setup and anatomy. This study was to evaluate whether off-line Adaptive Radiotherapy (ART) is sufficient. Methods: Ten HN patients, who received IMRT under daily imaging guidance using CT-on-rail/KV-CBCT, were randomly selected for this study. For each patient, the daily treatment setup was corrected with translational only directions. Sixty weekly verification CTs were retrospectively analyzed. On these weekly verification CTs, the tumor volumes and OAR contours were manually delineated by a physician. With the treatment iso-center placed on the verification CTs, according to the recorded clinical shifts, the treatment beams from the original IMRT plans were then applied to these CTs to calculate the delivered doses. The electron density of the planning CTs and weekly CTs were overridden to 1 g/cm3. Results: Among 60 fractions, D99 of the CTVs in 4 fractions decreased more than 5% of the planned doses. The maximum dose of the spinal cord exceeded 10% of the planned values in 2 fractions. A close examination indicated that the dose discrepancy in these 6 fractions was due to patient rotations, especially shoulder rotations. After registering these 6 CTs with the planning CT allowing six degree of freedoms, the maximum rotations around 3 axes were > 1.5° for these fractions. With rotation setup errors removed, 4 out of 10 patients still required off-line ART to accommodate anatomical changes. Conclusion: A significant shoulder rotations were observed in 10% fractions, requiring patient re-setup. Off-line ART alone is not sufficient to correct for random variations of patient position, although ART is effective to adapt to patients' gradual anatomic changes. Re-setup or on-line ART may be considered for patients with large deviations detected early by daily IGRT images. The study is supported in part by Siemens Medical Solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-254: Utility of Pinnacle Dynamic Planning Module Utilizing Deformable Image Registration in Adaptive Radiotherapy

Purpose For certain highly conformal treatment techniques, changes in patient anatomy due to weight loss and/or tumor shrinkage can result in significant changes in dose distribution. Recently, the Pinnacle treatment planning system added a Dynamic Planning module utilizing Deformable Image Registration (DIR). The objective of this study was to evaluate the effectiveness of this software in adapting to altered anatomy and adjusting treatment plans to account for it. Methods We simulated significant tumor response by changing patient thickness and altered chin positions using a commercially-available head and neck (H and N) phantom. In addition, we studied 23 CT image sets of fifteen (15) patients with H and N tumors and eight (8) patients with prostate cancer. In each case, we applied deformable image registration through Dynamic Planning module of our Pinnacle Treatment Planning System. The dose distribution of the original CT image set was compared to the newly computed dose without altering any treatment parameter. Result was a dose if we did not adjust the plan to reflect anatomical changes. Results For the H and N phantom, a tumor response of up to 3.5 cm was correctly deformed by the Pinnacle Dynamic module. Recomputed isodose contours on new anatomies were within 1 mm of the expected distribution. The Pinnacle system configuration allowed dose computations resulting from original plans on new anatomies without leaving the planning system. Original and new doses were available side-by-side with both CT image sets. Based on DIR, about 75% of H and N patients (11/15) required a re-plan using new anatomy. Among prostate patients, the DIR predicted near-correct bladder volume in 62% of the patients (5/8). Conclusions The Dynamic Planning module of the Pinnacle system proved to be an accurate and useful tool in our ability to adapt to changes in patient anatomy during a course of radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-267: Weekly Volumetric and Dosimetric Changes in Adaptive Conformal Radiotherapy of Non-Small-Cell-Lung Cancer Using 4D CT and Gating

Purpose: This study was to evaluate the significance of weekly imageguided patient setup and to assess the volumetric and dosimetric changes in no-small-cell-lung cancer (NSCLC) patients treated with adaptive conformal radiotherapy (CRT). Methods: 9 NSCLC patients treated with 3D CRT underwent 4D CT-on-rail every five fractions. ITV was generated from three phases of the 4DCT (the end of exhalation, 25% before and after the end of exhalation). The margin of ITV to PTV is 5mm. 6 weekly CTs were acquired for each patient. The weekly CTs were fused with the planning CT by vertebrae. The couch shift was recorded for each weekly CT to evaluate the setup error. The gross tumor volumes (GTVs) were contoured on weekly CT images by a physician. Beams from the original plans were applied to weekly CTs to calculate the delivered doses. All patients underwent replanning after 20 fractions. Results: Among the total 54 CTs, the average setup error was 2.0± 1.7, 2.6± 2.1, 2.7± 2.2 mm in X, Y, and Z direction, respectively. The average volume of the primary GTV was reduced from 42.45 cc to 22.78 cc (47.04%) after 6 weeks. The maximal volume regression occurred between 15 and 20 fractions. Adaptive radiation therapy (ART) reduced the V20 and V5 of the lung by 33.5% and 16.89%, respectively. ART also reduced Dmean and D1/3 of the heart by 31.7% and 32.32%, respectively. Dmax of the spinal cord did not vary much during the treatment course. Conclusion: 5 mm margin is sufficient for 4D weekly CTguided radiotherapy in lung cancer. Tumor regression was observed in the majority of patients. ART significantly reduced the OARs dose. Our preliminary results indicated that an off-line ART approach is appropriate in clinical practice.

60 APPLIED LIFE SCIENCES↗
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↗