Results for “Plan” — Page 58

DOE OSTI2015

MO-G-304-01: FEATURED PRESENTATION: Expanding the Knowledge Base for Data-Driven Treatment Planning: Incorporating Patient Outcome Models

Purpose: To extend the capabilities of knowledge-based treatment planning beyond simple dose queries by incorporating validated patient outcome models. Methods: From an analytic, relational database of 684 head and neck cancer patients, 372 patients were identified having dose data for both left and right parotid glands as well as baseline and follow-up xerostomia assessments. For each existing patient, knowledge-based treatment planning was simulated for by querying the dose-volume histograms and geometric shape relationships (overlap volume histograms) for all other patients. Dose predictions were captured at normalized volume thresholds (NVT) of 0%, 10%, 20, 30%, 40%, 50%, and 85% and were compared with the actual achieved doses using the Wilcoxon signed-rank test. Next, a logistic regression model was used to predict the maximum severity of xerostomia up to three months following radiotherapy. Baseline xerostomia scores were subtracted from follow-up assessments and were also included in the model. The relative risks from predicted doses and actual doses were computed and compared. Results: The predicted doses for both parotid glands were significantly less than the achieved doses (p < 0.0001), with differences ranging from 830 cGy ± 1270 cGy (0% NVT) to 1673 cGy ± 1197 cGy (30% NVT). The modelled risk of xerostomia ranged from 54% to 64% for achieved doses and from 33% to 51% for the dose predictions. Relative risks varied from 1.24 to 1.87, with maximum relative risk occurring at 85% NVT. Conclusions: Data-driven generation of treatment planning objectives without consideration of the underlying normal tissue complication probability may Result in inferior plans, even if quality metrics indicate otherwise. Inclusion of complication models in knowledge-based treatment planning is necessary in order to close the feedback loop between radiotherapy treatments and patient outcomes. Future work includes advancing and validating complication models in the context of knowledge-based treatment planning. This work is supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-BRD-01: Quantifying the Effectiveness of the Physics Pre-Treatment Plan Review for Detecting Errors in Radiation Therapy

Purpose: Physics pre-treatment plan review is crucial to safe radiation oncology treatments. Studies show that most errors originate in treatment planning, which underscores the importance of physics plan review. As a QA measure the physics review is of fundamental importance and is central to the profession of medical physics. However, little is known about its effectiveness. More hard data are needed. The purpose of this study was to quantify the effectiveness of physics review with the goal of improving it. Methods: This study analyzed 315 “potentially serious” near-miss incidents within an institutional incident learning system collected over a two-year period. 139 of these originated prior to physics review and were found at the review or after. Incidents were classified as events that: 1)were detected by physics review, 2)could have been detected (but were not), and 3)could not have been detected. Category 1 and 2 events were classified by which specific check (within physics review) detected or could have detected the event. Results: Of the 139 analyzed events, 73/139 (53%) were detected or could have been detected by the physics review; although, 42/73 (58%) were not actually detected. 45/73 (62%) errors originated in treatment planning, making physics review the first step in the workflow that could detect the error. Two specific physics checks were particularly effective (combined effectiveness of >20%): verifying DRRs (8/73) and verifying isocenter (7/73). Software-based plan checking systems were evaluated and found to have potential effectiveness of 40%. Given current data structures, software implementations of some tests such as isocenter verification check would be challenging. Conclusion: Physics plan review is a key safety measure and can detect majority of reported events. However, a majority of events that potentially could have been detected were NOT detected in this study, indicating the need to improve the performance of physics review.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Validation of a novel robot-assisted 3DUS system for real-time planning and guidance of breast interstitial HDR brachytherapy

Purpose: In current clinical practice, there is no integrated 3D ultrasound (3DUS) guidance system clinically available for breast brachytherapy. In this study, the authors present a novel robot-assisted 3DUS system for real-time planning and guidance of breast interstitial high dose rate (HDR) brachytherapy treatment. Methods: For this work, a new computer controlled robotic 3DUS system was built to perform a hybrid motion scan, which is a combination of a 6 cm linear translation with a 30° rotation at both ends. The new 3DUS scanner was designed to fit on a modified Kuske assembly, keeping the current template grid configuration but modifying the frame to allow the mounting of the 3DUS system at several positions. A finer grid was also tested. A user interface was developed to perform image reconstruction, semiautomatic segmentation of the surgical bed as well as catheter reconstruction and tracking. A 3D string phantom was used to validate the geometric accuracy of the reconstruction. The volumetric accuracy of the system was validated with phantoms using magnetic resonance imaging (MRI) and computed tomography (CT) images. In order to accurately determine whether 3DUS can effectively replace CT for treatment planning, the authors have compared the 3DUS catheter reconstruction to the one obtained from CT images. In addition, in agarose-based phantoms, an end-to-end procedure was performed by executing six independent complete procedures with both 14 and 16 catheters, and for both standard and finer Kuske grids. Finally, in phantoms, five end-to-end procedures were performed with the final CT planning for the validation of 3DUS preplanning. Results: The 3DUS acquisition time is approximately 10 s. A paired Student t-test showed that there was no statistical significant difference between known and measured values of string separations in each direction. Both MRI and CT volume measurements were not statistically different from 3DUS volume (Student t-test: p > 0.05) and they were significantly correlated to 3DUS measurement (Pearson test: MRI p < 0.05 and CT p < 0.001). The mean angular separation distance between catheter trajectories segmented from 3DUS and CT images was 0.42° ± 0.24°, while the maximum and mean trajectory separations were 0.51 ± 0.19 and 0.37 ± 0.17 mm, respectively. Overall, the new finer grid has performed significantly better in terms of dosimetric indices. The planning target volume dosimetric indices were not found statistically different between 3DUS and CT planning (Student t-test, p > 0.05). Both the skin and the pectoral muscle dosimetric indices were within ABS guidelines. Conclusions: A novel robot-assisted 3DUS system was designed and validated. To their knowledge, this is the first system capable of performing real-time guidance and planning of breast multicatheter HDR brachytherapy treatments. Future investigation will test the feasibility of using the system in the clinic and for permanent breast brachytherapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-63: Abdominal Diameter Changes in Children During Volumetric Modulated Arc Therapy (VMAT): Is Re-Planning Needed?

Purpose: To investigate the dosimetric impact of daily changes in patient’s diameter, due to weight gain/loss and air in the bowel, based on CBCT information during radiotherapy treatment of pediatric abdominal tumors. Methods: 10 pediatric patients with neuroblastoma (n=6) and Wilms’ (n=4) tumors were included. Available CBCTs were affinely registered to the planning CT for daily set-up variations corrections. A density override approach assigning air-density to the random air pockets and water-density to the remaining anatomy was used to determine the CBCT and CT dose. Clinical VMAT plans, with a PTV prescribed dose ranging between (14.4- 36) Gy, were re-optimized on the density override CT and re-calculated on each CBCT. Dose-volume statistics of the PTV and kidneys, delineated on each CBCT, were used to compare the daily and cumulative CBCT dose with the reference CT dose. Results: The average patient diameter variation was (0.5 ± 0.7) cm (maximum daily difference of 2.3 cm). The average PTV mean dose difference (MDD) between the CT and the cumulative CBCT plans was (0.1 ± 1.1) % (maximum daily MDD of 2%). A reduction in target coverage up to 3% and 7% was observed for the cumulative and daily CBCT plans, respectively. The average kidneys’ cumulative MDD was (−2.7 ± 3.6) % (maximum daily MDD of −12%), corresponding to an overdosage. Conclusion: Due to patient’s diameter changes, a target underdosage was assessed. Given the high local tumor control of neuroblastoma and Wilms’ diseases, the need of re-planning might be discarded. However, the assessed kidneys overdosage could represent a problem when the normal tissue tolerance is reached. The necessity of re-planning should then be considered to reduce the risk of long-term renal complications. Due to the poor softtissue contrast on CBCT, MRI-guidance is required to obtain a better assessment of the accumulated dose on the remaining OARs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-114: On-Treatment Imagereconstruction Using Transit Images of Treatment Beams Through Patient and Thosethrough Planning CT Images

Purpose: To reconstruct patient images at the time of radiation delivery using measured transit images of treatment beams through patient and calculated transit images through planning CT images. Methods: We hypothesize that the ratio of the measured transit images to the calculated images may provide changed amounts of the patient image between times of planning CT and treatment. To test, we have devised lung phantoms with a tumor object (3-cm diameter) placed at iso-center (simulating planning CT) and off-center by 1 cm (simulating treatment). CT images of the two phantoms were acquired; the image of the off-centered phantom, unavailable clinically, represents the reference on-treatment image in the image quality of planning CT. Cine-transit images through the two phantoms were also acquired in EPID from a non-modulated 6 MV beam when the gantry was rotated 360 degrees; the image through the centered phantom simulates calculated image. While the current study is a feasibility study, in reality our computational EPID model can be applicable in providing accurate transit image from MC simulation. Changed MV HU values were reconstructed from the ratio between two EPID projection data, converted to KV HU values, and added to the planning CT, thereby reconstructing the on-treatment image of the patient limited to the irradiated region of the phantom. Results: The reconstructed image was compared with the reference image. Except for local HU differences>200 as a maximum, excellent agreement was found. The average difference across the entire image was 16.2 HU. Conclusion: We have demonstrated the feasibility of a method of reconstructing on-treatment images of a patient using EPID image and planning CT images. Further studies will include resolving the local HU differences and investigation on the dosimetry impact of the reconstructed image.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-186: A Treatment Planning Study of Normal Tissue Sparing with Robustness Optimized IMPT, 4Pi IMRT, and VMAT for Head and Neck Cases

Purpose: We performed a retrospective dosimetric comparison study between the robustness optimized Intensity Modulated Proton Therapy (RO-IMPT), volumetric-modulated arc therapy (VMAT), and the non-coplanar 4? intensity modulated radiation therapy (IMRT). These methods represent the most advanced radiation treatment methods clinically available. We compare their dosimetric performance for head and neck cancer treatments with special focus on the OAR sparing near the tumor volumes. Methods: A total of 11 head and neck cases, which include 10 recurrent cases and one bilateral case, were selected for the study. Different dose levels were prescribed to tumor target depending on disease and location. Three treatment plans were created on commercial TPS systems for a novel noncoplanar 4π method (20 beams), VMAT, and RO-IMPT technique (maximum 4 fields). The maximum patient positioning error was set to 3 mm and the maximum proton range uncertainty was set to 3% for the robustness optimization. Line dose profiles were investigated for OARs close to tumor volumes. Results: All three techniques achieved 98% coverage of the CTV target and most photon plans had less than 110% of the hot spots. The RO-IMPT plans show superior tumor dose homogeneity than 4? and VMAT plans. Although RO-IMPT has greater R50 dose spillage to the surrounding normal tissue than 4π and VMAT, the RO-IMPT plans demonstrate better or comparable OAR (parotid, mandible, carotid, oral cavity, pharynx, and etc.) sparing for structures closely abutting tumor targets. Conclusion: The RO-IMPT’s ability of OAR sparing is benchmarked against the C-arm linac based non-coplanar 4π technique and the standard VMAT method. RO-IMPT consistently shows better or comparable OAR sparing even for tissue structures closely abutting treatment target volume. RO-IMPT further reduces treatment uncertainty associated with proton therapy and delivers robust treatment plans to both unilateral and bilateral head and neck cancer patients with desirable treatment time.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-336: A Quick Auto-Planning (QAP) Method for Patient Intensity Modulated Radiotherapy (IMRT)

Purpose: The aim of this study is to develop a quick auto-planning system that permits fast patient IMRT planning with conformal dose to the target without manual field alignment and time-consuming dose distribution optimization. Methods: The planning target volume (PTV) of the source and the target patient were projected to the iso-center plane in certain beameye- view directions to derive the 2D projected shapes. Assuming the target interior was isotropic for each beam direction boundary analysis under polar coordinate was performed to map the source shape boundary to the target shape boundary to derive the source-to-target shape mapping function. The derived shape mapping function was used to morph the source beam aperture to the target beam aperture over all segments in each beam direction. The target beam weights were re-calculated to deliver the same dose to the reference point (iso-center) as the source beam did in the source plan. The approach was tested on two rectum patients (one source patient and one target patient). Results: The IMRT planning time by QAP was 5 seconds on a laptop computer. The dose volume histograms and the dose distribution showed the target patient had the similar PTV dose coverage and OAR dose sparing with the source patient. Conclusion: The QAP system can instantly and automatically finish the IMRT planning without dose optimization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm

Background: Commercial treatment planning system Pinnacle3 (Philips, Fitchburg, WI, USA) employs a convolution-superposition algorithm for volumetric-modulated arc radiotherapy (VMAT) optimization and dose calculation. Study of Monte Carlo (MC) dose recalculation of VMAT plans for advanced-stage nasopharyngeal cancers (NPC) is currently limited. Methods: Twenty-nine VMAT prescribed 70Gy, 60Gy, and 54Gy to the planning target volumes (PTVs) were included. These clinical plans achieved with a CS dose engine on Pinnacle3 v9.0 were recalculated by the Monaco TPS v5.0 (Elekta, Maryland Heights, MO, USA) with a XVMC-based MC dose engine. The MC virtual source model was built using the same measurement beam dataset as for the Pinnacle beam model. All MC recalculation were based on absorbed dose to medium in medium (Dm,m). Differences in dose constraint parameters per our institution protocol (Supplementary Table 1) were analyzed. Results: Only differences in maximum dose to left brachial plexus, left temporal lobe and PTV54Gy were found to be statistically insignificant (p> 0.05). Dosimetric differences of other tumor targets and normal organs are found in supplementary Table 1. Generally, doses outside the PTV in the normal organs are lower with MC than with CS. This is also true in the PTV54-70Gy doses but higher dose in the nasal cavity near the bone interfaces is consistently predicted by MC, possibly due to the increased backscattering of short-range scattered photons and the secondary electrons that is not properly modeled by the CS. The straight shoulders of the PTV dose volume histograms (DVH) initially resulted from the CS optimization are merely preserved after MC recalculation. Conclusion: Significant dosimetric differences in VMAT NPC plans were observed between CS and MC calculations. Adjustments of the planning dose constraints to incorporate the physics differences from conventional CS algorithm should be made when VMAT optimization is carried out directly with MC dose engine.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-378: Evaluation of Dose-Volume Variability and Parameters Between Prostate IMRT and VMAT Plans

Purpose: This study compared the rectal dose-volume consistency, equivalent uniform dose (EUD) and normal tissue complication probability (NTCP) in prostate intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Methods: For forty prostate IMRT and fifty VMAT patients treated using the same dose prescription (78 Gy/39 fraction) and dose-volume criteria in inverse planning optimization, the rectal EUD and NTCP were calculated for each patient. The rectal dose-volume consistency, showing the variability of dose-volume histogram (DVH) among patients, was defined and calculated based on the deviation between the mean and corresponding rectal DVH. Results: From both the prostate IMRT and VMAT plans, the rectal EUD and NTCP were found decreasing with the rectal volume. The decrease rates for the IMRT plans (EUD = 0.47 × 10{sup −3} Gy cm{sup −3} and NTCP = 3.94 × 10{sup −2} % cm{sup −3}) were higher than those for the VMAT (EUD = 0.28 × 10{sup −3} Gy cm{sup −3} and NTCP = 2.61 × 10{sup −2} % cm{sup −3}). In addition, the dependences of the rectal EUD and NTCP on the dose-volume consistency were found very similar between the prostate IMRT and VMAT plans. This shows that both delivery techniques have similar variations of the rectal EUD and NTCP on the dose-volume consistency. Conclusion: Dependences of the dose-volume consistency on the rectal EUD and NTCP were compared between the prostate IMRT and VMAT plans. It is concluded that both rectal EUD and NTCP decreased with an increase of the rectal volume. The variation rates of the rectal EUD and NTCP on the rectal volume were higher for the IMRT plans than VMAT. However, variations of the rectal dose-volume consistency on the rectal EUD and NTCP were found not significant for both delivery techniques.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-625: Optimal Treatment Planning Strategy Among Arc Arrangements for Prostate SBRT with VMAT Technique

Purpose: The purpose of this study is to determine the optimal treatment planning strategy among the different arc arrangements for prostate stereotactic body radiotherapy (SBRT) plans with volumetric modulated arc therapy (VMAT). Methods: Ten patients with prostate cancer were selected. The SBRT-VMAT plans for each patient were generated with single-full (181° to 179°; 1FA), single-partial (240° to 120°; 1PA), double-full (181° to 179° and 179° to 181°; 2FA), and double-partial (240° to 120° and 120° to 240°; 2PA) arc arrangements. The prescription dose was 42.7 Gy in 7 fractions. Dose distribution was calculated using a 10-MV flattening-filter-free beam and the Acuros XB algorithm. Dosimetric parameters of target volume and organs at risk (OARs) were evaluated from cumulative dose-volume histograms on prostate SBRT-VMAT plans between single-arc (1FA and 1PA) and double-arc (2FA and 2PA) arrangements. Results: All plans using four arc arrangements were highly conformal with conformity index (CI)<1.05 and conformation number (CN)=0.91, and the doses to target volume were homogeneous (homogeneity index (HI)= 0.09 0.12). Pertaining to the dose to the OARs, there were significant differences in the rectum, left and right femoral head doses while having no difference in the bladder dose. The partial-arc (1PA and 2PA) had relatively high reductions for the mean rectum dose compared to full-arc (1FA and 2FA). The near-to-maximum dose (D2%) and mean dose of the left and right femoral head were always lower on prostate SBRT-VMAT plan using the full-arc, when compared to the partial-arc arrangement. Conclusion: This study confirmed that prostate SBRT-VMAT using 1PA was feasible fast delivery time and produced equivalent target coverage and better rectum sparing, although the D2% and mean dose of the left and right femoral head increased slightly. Therefore, the results of this study suggest that the use of 1PA is an attractive choice for delivering prostate SBRT-VMAT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-D-BRC-04: Multiple-Criteria Optimization Planning

Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-D-BRC-00: In Memoriam of Jan Van De Geijn: Knowledge-Based Planning

Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-D-BRC-02: Auto-Planning

Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-D-BRC-03: Knowledge-Based Planning

Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-202-05: Identifying Treatment Planning System Errors in IROC-H Phantom Irradiations

Purpose: Treatment Planning System (TPS) errors can affect large numbers of cancer patients receiving radiation therapy. Using an independent recalculation system, the Imaging and Radiation Oncology Core-Houston (IROC-H) can identify institutions that have not sufficiently modelled their linear accelerators in their TPS model. Methods: Linear accelerator point measurement data from IROC-H’s site visits was aggregated and analyzed from over 30 linear accelerator models. Dosimetrically similar models were combined to create “classes”. The class data was used to construct customized beam models in an independent treatment dose verification system (TVS). Approximately 200 head and neck phantom plans from 2012 to 2015 were recalculated using this TVS. Comparison of plan accuracy was evaluated by comparing the measured dose to the institution’s TPS dose as well as the TVS dose. In cases where the TVS was more accurate than the institution by an average of >2%, the institution was identified as having a non-negligible TPS error. Results: Of the ∼200 recalculated plans, the average improvement using the TVS was ∼0.1%; i.e. the recalculation, on average, slightly outperformed the institution’s TPS. Of all the recalculated phantoms, 20% were identified as having a non-negligible TPS error. Fourteen plans failed current IROC-H criteria; the average TVS improvement of the failing plans was ∼3% and 57% were found to have non-negligible TPS errors. Conclusion: IROC-H has developed an independent recalculation system to identify institutions that have considerable TPS errors. A large number of institutions were found to have non-negligible TPS errors. Even institutions that passed IROC-H criteria could be identified as having a TPS error. Resolution of such errors would improve dose delivery for a large number of IROC-H phantoms and ultimately, patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-H-209-00: Planning and Delivering HDR APBI Treatments

Learnings Objectives: Although brachytherapy is the oldest form of radiation therapy, the rapid advancement of the methods of dose calculation, treatment planning and treatment delivery pushes us to keep updating our knowledge and experience to new procedures all the time. Our purpose is to present the newest applicators used in Accelerated Partial Breast Irradiation (APBI) and the techniques of using them for a maximum effective treatment. Our objective will be to get the user familiar with the Savi, Contura and ML Mammosite from the detailed description and measurements to cavity eval and choice or size, to acceptance tests and use of each. At the end of the session the attendants will be able to assist at the scanning of the patient for the first treatment, decide on the proper localization and immobilization devices, import the scans in the treatment planning system, perform the structure segmentation, reconstruct the catheters and develop a treatment plan using inverse planning (IPSA) or volume optimization. The attendant should be able to evaluate the quality of a treatment plan according to the ABS protocols and B39 after this session. Our goal is that all the attendants to gain knowledge of all the quality assurance procedures required to be performed prior to a treatment, at the beginning of a treatment day, weekly, monthly and annualy on the remote afterloader, the treatment planning system and the secondary check system. We will provide tips for a consistent treatment delivery of the 10 fractions in a BID (twice daily) regimen.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-CD-206-05: Machine-Learning Based Segmentation of Organs at Risks for Head and Neck Radiotherapy Planning

Purpose: Accurate and efficient delineation of tumor target and organs-at-risks is essential for the success of radiotherapy. In reality, despite of decades of intense research efforts, auto-segmentation has not yet become clinical practice. In this study, we present, for the first time, a deep learning-based classification algorithm for autonomous segmentation in head and neck (HaN) treatment planning. Methods: Fifteen HN datasets of CT, MR and PET images with manual annotation of organs-at-risk (OARs) including spinal cord, brainstem, optic nerves, chiasm, eyes, mandible, tongue, parotid glands were collected and saved in a library of plans. We also have ten super-resolution MR images of the tongue area, where the genioglossus and inferior longitudinalis tongue muscles are defined as organs of interest. We applied the concepts of random forest- and deep learning-based object classification for automated image annotation with the aim of using machine learning to facilitate head and neck radiotherapy planning process. In this new paradigm of segmentation, random forests were used for landmark-assisted segmentation of super-resolution MR images. Alternatively to auto-segmentation with random forest-based landmark detection, deep convolutional neural networks were developed for voxel-wise segmentation of OARs in single and multi-modal images. The network consisted of three pairs of convolution and pooing layer, one RuLU layer and a softmax layer. Results: We present a comprehensive study on using machine learning concepts for auto-segmentation of OARs and tongue muscles for the HaN radiotherapy planning. An accuracy of 81.8% in terms of Dice coefficient was achieved for segmentation of genioglossus and inferior longitudinalis tongue muscles. Preliminary results of OARs regimentation also indicate that deep-learning afforded an unprecedented opportunities to improve the accuracy and robustness of radiotherapy planning. Conclusion: A novel machine learning framework has been developed for image annotation and structure segmentation. Our results indicate the great potential of deep learning in radiotherapy treatment planning.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Y-12 Groundwater Protection Program Groundwater And Surface Water Sampling And Analysis Plan For Calendar Year 2012

This plan provides a description of the groundwater and surface water quality monitoring activities planned for calendar year (CY) 2012 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) that will be managed by the Y-12 Groundwater Protection Program (GWPP). Groundwater and surface water monitoring performed by the GWPP during CY 2012 is in accordance with the following goals: (1) to protect the worker, the public, and the environment; (2) to maintain surveillance of existing and potential groundwater contamination sources; (3) to provide for the early detection of groundwater contamination and determine the quality of groundwater and surface water where contaminants are most likely to migrate beyond the Oak Ridge Reservation property line; (4) to identify and characterize long-term trends in groundwater quality at Y-12; and (5) to provide data to support decisions concerning the management and protection of groundwater resources. Groundwater and surface water monitoring will be performed in three hydrogeologic regimes at Y-12: the Bear Creek Hydrogeologic Regime (Bear Creek Regime), the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek and East Fork regimes are located in Bear Creek Valley and the Chestnut Ridge Regime is located south of Y-12 (Figure A.1). Additional surface water monitoring will be performed north of Pine Ridge along the boundary of the Oak Ridge Reservation. Modifications to the CY 2012 monitoring program may be necessary during implementation. Changes in programmatic requirements may alter the analytes specified for selected monitoring wells or may add or remove wells from the planned monitoring network. Each modification to the monitoring program will be approved by the Y-12 GWPP manager and documented as an addendum to this sampling and analysis plan. The following sections of this report provide details regarding the CY 2012 groundwater and surface water monitoring activities. Section 2 describes the monitoring locations in each regime and the processes used to select the sampling locations. A description of the field measurements and laboratory analytes is provided in Section 3. Sample collection methods and procedures are described in Section 4, and Section 5 lists the documents cited for more detailed operational and technical information. The narrative sections of the report reference several appendices. Figures (maps and diagrams) and tables (excluding a data summary table presented in Section 4) are in Appendix A and Appendix B, respectively. Groundwater Monitoring Schedules (when issued throughout CY 2012) will be inserted in Appendix C, and addenda to this plan (if issued) will be inserted in Appendix D. Laboratory requirements (bottle lists, holding times, etc.) are provided in Appendix E, and an approved Waste Management Plan is provided in Appendix F.

54 ENVIRONMENTAL SCIENCES↗