Planning Contours Research Articles

Feasibility of creating a daily adaptive plan using automatic DIR-created target and OARs contours in patients with prostate cancer magnetic-resonance-guided adaptive radiotherapy.

The purpose of this study was to evaluate the feasibility of treatment plans for prostate cancer with magnetic resonance (MR)-guided online adaptive radiotherapy, which are generated using deformable image registration (DIR)-created contours of the targets and organs. Totally, 150 fractions from 30 prostate cancer patients implanted with a hydrogel spacer and treated with the MR-Linac were studied. Reference treatment plans that satisfied all institutional dose constraints were initially created on planning MRI. The adaptive treatment plans were created on daily MRI based on the reference plan using the DIR-created contours, ensuring all dose constraints were met. Subsequently, a clinician manually created reference contours for each daily MRI. Finally, the dose volume histogram indices of the plan generated with DIR-created contours were re-evaluated with clinician created contours. The evaluated contours included the bladder wall, rectum wall, sigmoid, small bowel and planning target volume (PTV) for dose prescription. The PTV for dose prescription met the dose constraints in all fractions. The bladder and rectum walls met the dose constraint of maximum dose (D0.03 cc) in all fractions. Five patients failed to meet the sigmoid and small bowel dose constraints, with the largest deviation being 13.3% exceedance at D2 cc in the small bowel added 3mm margin. This study suggests that most treatment plans created without modifying the DIR-created contours are clinically viable. However, dislodgements of the small bowel and sigmoid may exceed the extent of DIR propagation from the reference plan contours, and it is recommended that these contours be verified.

Underground Parking Layout Generation Based on the WaveFunctionCollapse Algorithm

During the design process, architectural layout configuration is subject to complex constraints such as site conditions and design requirements, resulting in limited design efficiency. This research aims to provide architects with an effective design tool that can generate reference-worthy underground parking layout solutions based on the given site information. In this research, we extract spatial modules from underground parking layouts, and transform the design constraints into adjacency rules based on the analysis of the configuration process for underground parking layout, then develop a generation and optimization model of the underground parking layout based on the WaveFunctionCollapse algorithm (WFC) and Multi-objective Optimization (MOO), and verify the effectiveness of the model through experiments. The results show that with given plan contour and entrance/exit locations as inputs, the model can efficiently generate architectural layout solutions that meet the design objectives.

Prior knowledge based deep learning auto-segmentation in magnetic resonance imaging-guided radiotherapy of prostate cancer

Background and purposeAutomation is desirable for organ segmentation in radiotherapy. This study compared deep learning methods for auto-segmentation of organs-at-risk (OARs) and clinical target volume (CTV) in prostate cancer patients undergoing fractionated magnetic resonance (MR)-guided adaptive radiation therapy. Models predicting dense displacement fields (DDFMs) between planning and fraction images were compared to patient-specific (PSM) and baseline (BM) segmentation models. Materials and methodsA dataset of 92 patients with planning and fraction MR images (MRIs) from two institutions were used. DDFMs were trained to predict dense displacement fields (DDFs) between the planning and fraction images, which were subsequently used to propagate the planning contours of the bladder, rectum, and CTV to the daily MRI. The training was performed either with true planning-fraction image pairs or with planning images and their counterparts deformed by known DDFs. The BMs were trained on 53 planning images, while to generate PSMs, the BMs were fine-tuned using the planning image of a given single patient. The evaluation included Dice similarity coefficient (DSC), the average (HDavg) and the 95th percentile (HD95) Hausdorff distance (HD). ResultsThe DDFMs with DSCs for bladder/rectum of 0.76/0.76 performed worse than PSMs (0.91/0.90) and BMs (0.89/0.88). The same trend was observed for HDs. For CTV, DDFM and PSM performed similarly yielding DSCs of 0.87 and 0.84, respectively. ConclusionsDDFMs were found suitable for CTV delineation after rigid alignment. However, for OARs they were outperformed by PSMs, as they predicted only limited deformations even in the presence of substantial anatomical changes.

Outcomes Specific to Spinal Metastases with Paraspinal Disease Extension Following Spine Stereotactic Body Radiotherapy

Spinal metastases with paraspinal disease (PD) extension are known to have worse outcomes following stereotactic body radiotherapy (SBRT). Characteristics of the PD itself have not been investigated to determine the impact on outcomes such as local control, which is the purpose of this study. We retrospectively reviewed those patients who had SBRT for spinal metastases with PD disease, identified from a prospectively maintained database. Spinal metastases previously irradiated or surgical resected were excluded. The extent of PD was classified as involving the rib, neuroforamina, and muscle invasion. The gross tumor volume of PD (GTV_PD) and the clinical target volume of PD (CTV_PD) were segregated from the bony compartments based on the treatment plan contours. The outcomes of interest included the cumulative risk of local failure (LF), re-irradiation rates (ReRT), and overall survival (OS). LF and ReRT were estimated for each treated sites using the competing risk model (death as the competing risk), while OS was evaluated per patient using the Kaplan Meier method. A total of 86 patients with 96 spinal metastases sites with PD were included. Of the 96 treated sites, 65% (62/96), 29% (28/96) and 6% (6/96) of PD spanned 1, 2, and 3 vertebral levels respectively. The median follow-up was 12.4months (range: 0.6-100months). The 6- and 12-month OS for the cohort was 81% and 51%, respectively. 33/86 (38%) patients had radioresistant cancer (gastrointestinal, renal cell carcinoma, thyroid, sarcoma, or melanoma). Involvement of rib, neuroforamina and muscle invasion were observed in 39% (37/96), 65% (62/96) and 21% (20/96) of the treated sites, respectively. Epidural disease was present in 57% (55/96) of treated sites. The median GTV_PD volume was 7cc (range: 0.3-114cc), and the median CTV_PD volume was 24cc (range: 0.4-248cc). The prescribed doses were 24 Gy/2 fractions (fx) (80%), 28 Gy/2 fx (10%) and 30 Gy/4 fx (10%). There were 84 treated sites with at least one post-treatment MRI available for LF assessment. The crude LF risk was 32% (27/84), and the 6- and 12-month cumulative LF rates were 12% and 28%, respectively. There was a trend towards an increased risk of LF when PD involved the rib (35% vs 24% at 1 year respectively, P = 0.07) and muscle (67% vs 20% at 1 year respectively; P = 0.06), but no difference in LF for neuroforamina involvement (26% vs 34% at 1 year respectively, P = 0.5). There were no differences in LF based on cancer radioresistance (P = 0.6), GTV_PD volume (P = 0.3) or CTV_PD volume (P = 0.4). Of the 96 treated sites, 14% (14/96) were re-irradiated (9 with repeat SBRT and 5 with conventional EBRT) at a median of 15 months (range: 4.7-59 months) post initial SBRT. The cumulative incidence of ReRT at 6- and 12-months were 1.2% and 7.3%, respectively. PD involving adjacent rib and muscle may be associated with worse LF following SBRT. Further expansion of the cohort and dosimetric analyses are ongoing.

Material and construction solutions in the construction of civil defence shelters

An analysis is presented of the use of material and construction solutions used in construction, mainly residential, for the construction of OC (civil defence) shelters.The article presents procedures for designing reinforced concrete structures that make it possible to properly determine the load capacity of critical sections. In the present work, a study of the deformation stability of a zone of reinforced concrete sections that is subjected to compression is used. Computational methods based on Drucker's postulate were used to solve the problem. The proposed approach enables the determination of the values of ultimate and failure strains based on the analysis of the loading path of a reinforced concrete section.Generally, shelters built into residential buildings are analysed, intended to be constructed in the rooms of the basement floor. A reduced need for ancillary space, the basement room, is observed. Garage functions are located on the basement floor. The plan contours of the basement are often larger than those of the ground floor. It is possible to design a shelter for the residents of the building, which ensures the greatest efficiency in its use. It is desirable to maintain uniform material and construction solutions while maintaining technological and organisational solutions during the erection of the entire building.The paper indicates the possibility of using some of the material and structural solutions of the housing construction in the realisation of OC shelters built into the basement floor. The construction of free-standing shelters was not analysed separately, but the proposals presented in the paper can also be applied to the type of OC shelters. Some results of the analysis of the adaptation of material and structural solutions of the housing construction to the needs of OC shelters construction will be presented during the symposium.It is advisable to develop models for the construction of OC shelters using contemporary technologies used in the construction industry.Useful tool can be the proposed scheme for improving activities based on the EFQM model.

The role of adaptive planning in margin-reduced, MRI-guided stereotactic body radiotherapy to the prostate bed following radical prostatectomy: Post-hoc analysis of a phase II clinical trial

Background and purposeWe examined the interfractional variations of clinical target volumes (CTVs), planning target volumes (PTVs), and organs-at-risk (OARs) in patients receiving MRI-guided stereotactic body radiotherapy (SBRT) to the prostate bed and evaluated the potential role of adaptive planning. Materials and Methods31 patients received 30–34 Gy in five fractions to the prostate bed on a phase II clinical trial. OARs, CTVs, and PTVs were retrospectively contoured on daily pretreatment MRIs (n = 155). Geometric comparisons were made between initial planning contours and daily pretreatment contours. Predicted treatment plans for each fraction were evaluated using the following constraints: CTV V95%>93%, PTV V95%>90%, bladder Dmax < 36.7 Gy, bladder V32.5 Gy < 35%, rectum Dmax < 36.7 Gy, rectum V27.5 Gy < 45%, rectum 32.5 Gy < 30%, and rectal wall V24Gy < 50%. Adaptive planning was simulated for all fractions that failed to meet these criteria. Plans were then re-evaluated. ResultsMedian change in volume was 0.48% for CTV, −24.5% for bladder, and 6.95% for rectum. Median DSC was 0.89 for CTV, 0.79 for bladder, and 0.76 for rectum. 145/155 fractions (93.5%) met CTV V95%>93%. 75/155 fractions (48.4%) failed at least one OAR dose constraint. Overall, 83/155 fractions (53.5%) met criteria for adapting planning. This affected 24/31 patients (77.4%). Following adaptive planning, all fractions met CTV V95%>93% and PTV V95%>90% and 120/155 fractions (77.4%) met all OAR constraints. ConclusionDue to significant interfractional variations in anatomy, a majority of fractions failed to meet both target volume and OAR constraints. However, adaptive planning was effective in overcoming these anatomic changes. Adaptive planning should be routinely considered in prostate bed SBRT.

Research on deposition toolpath planning and laser head Z-axis rising height setting for directed energy deposition

In this study, the biggest goal was using laser directed energy deposition (L-DED) process to fabricate a solid blade part. In the process of CAD modeling, a blade model was built by sweeping a blade cross-section and twisting 10° simultaneously, which made it to have overhanging and tilting features. So, to select an appropriate deposition toolpath was the most important thing. The deposition toolpath in this study was decomposed into contour and field toolpaths. First of all, a cuboid part model of which the geometry was simpler was created to test toolpath planning approaches. The results recommended to use “Fixed rising height per layer with proper laser head rising height (Z-offset setting)” or “Spiral” approaches to plan contour toolpaths. For field toolpaths, “Reciprocating zigzag” planning approach was suggested and it needed to adjust the cladding angle to fit the cross-section of the parts. According to the test results of cuboid part fabrications, the contour of the target blade part was successfully manufactured with a 50% Z-offset setting and the spiral toolpath. The solid blade fabrication was also finished with a fixed rising height per layer with a 50% Z-offset setting and 45° reciprocating zigzag toolpath. In addition, the relationship between the Z-offset setting and the dilution was investigated through experiments. A conjecture that a height shrinkage of an old layer caused by thermal deformation is equal to the single-layer deposition dilution was proposed. Based on this conjecture, users can improve L-DED deposition results by setting the Z-offset as “the product of single-track height and the degree of shrinkage of an old layer height.” By combining the predictive value of dilution surface fitting model with the conjecture, it can be easier to get better LDED deposition quality.

Dosimetric Implications of Margin-Reduced MRI-Guided Stereotactic Body Radiotherapy to the Prostate Bed Following Radical Prostatectomy: Post-Hoc Analysis of a Phase II Study

<h3>Purpose/Objective(s)</h3> Due to the highly deformable and mobile nature of the target volume and adjacent organs at risk (OARs), generous planning target volume (PTV) margins have historically been used in the context of radiotherapy after radical prostatectomy. MRI-guided radiotherapy systems have improved on-board imaging capabilities and the ability to perform automatic beam holds based on pre-specified structures. Herein, we evaluate the dosimetric implications of interfraction variations in the clinical target volumes (CTV) and OARs in patients receiving margin-reduced MRI-guided stereotactic body radiotherapy (SBRT) to the prostate bed. <h3>Materials/Methods</h3> 31 consecutive patients received MRI-guided SBRT to the prostate bed (30 – 34 Gy in 5 fractions) without adaptive planning on a phase II study. The OAR volumes, CTV, and PTV (created using a 3 mm isotropic expansion of the CTV) were retrospectively contoured on on-board 0.35T MRIs obtained prior to each fraction (n=155). Geometric comparisons were made between the initial planning contours and the 5 daily contours for each patient using change in volume and Dice similarity coefficient (DSC) calculations. Coverage of the CTV and PTV was assessed (CTV V95% >93% and PTV V95% >90%), as were bladder and rectal dose constraints (Bladder Dmax <36.7 Gy, Bladder V32.5 Gy <35%, Rectum Dmax <36.7 Gy, Rectum V27.5 Gy <45%, Rectum 32.5 Gy <30%, and Rectal Wall V24 <50%). <h3>Results</h3> The median change in volume was -24.5% (interquartile range [IQR], -35.5 – -2.2%) for the bladder, 6.95% (IQR, -6.94 – 23.0%) for the rectum, -0.2% (IQR, -8.3 – 8.7%) for the rectal wall, 0.48% (IQR, -3.87 – 7.6%) for the CTV, and -0.48% (IQR, -5.12 – 6.53%) for the PTV. The median DSC was 0.79 (IQR, 0.73 – 0.84) for the bladder, 0.76 (IQR, 0.69 – 0.81) for the rectum, 0.35 (IQR, 0.28 – 0.44) for the rectal wall, 0.89 (IQR, 0.83 – 0.93) for the CTV, and 0.90 (IQR, 0.87 – 0.95) for the PTV. 145/155 fractions (93.5%) met the CTV V95% >93% target and 134/155 fractions (86.5%) met both the CTV V95% >93% and PTV V95% >90% targets. When calculated over 5 cumulative fractions, 29/31 patients (93.5%) met the CTV goal of V95% >93%. 62/155 fractions (40%) failed at least one OAR constraint. The mean number of fractions per patient that failed at least one OAR constraint was 2/5 (median, 1; range, 0 – 5). <h3>Conclusion</h3> With MRI-guidance, a reduction of the PTV margin to 3 mm isotropically allows for adequate CTV coverage in over 90% of patients without the need for adaptive planning. However, OAR constraints are not met in 40% of delivered fractions despite meeting all dose constraints at the time of treatment planning. Online dose prediction and, if indicated, adaptive radiotherapy can optimize this to allow for improved OAR protection and potentially allow for further reductions in the PTV expansion while maintaining adequate CTV coverage.

Prospective Analysis of a Deep Learning Auto-Contouring Model for Definitive Radiation of Localized Prostate Cancer

<h3>Purpose/Objective(s)</h3> To analyze the prospective use of a deep learning auto contouring model for patients with localized prostate cancer with or without insertion of a radiopaque hydrogel spacer. <h3>Materials/Methods</h3> The model was initially trained with patients from an academic center. It was implemented for prospective clinical use at a satellite center by three experienced radiation oncologists. The model auto contours prostate, proximal seminal vesicles (SVs), bladder, rectum, femurs, penile bulb and spacer (when existing). The auto contours (ACs) were reviewed and edited by treating physician. The ACs were compared to the approved planning contours (PCs) for the initial 23 patients to evaluate the extent of physician editing required. Each AC was compared to the final PC by one physician using a qualitative 4-point system: 1 (minor discrepancy with significant efficiency gain), 2 (moderate discrepancy with substantial gain), 3 (significant discrepancy with meaningful gain), and 4 (rejected for gross error or no efficiency gain). A composite score was calculated by averaging the score of each structure. A Turing test was performed to see if the physician can differentiate AC vs. PC. Quantitatively, the geometric differences between each AC and PC were analyzed using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). <h3>Results</h3> As shown in Table 1, the mean score was ≤1.4 for all structures except for SVs, and 1.26 for the composite, indicating overall significant efficiency gain. In 97.8% of cases, the ACs led to an efficiency gain. While the passing rate of the Turing test was not high, the failure was frequently due to very minor differences. The DSC was close to 1 for femurs, bladder and spacer, and >0.9 for prostate and rectum. The MDA was <2 mm for all structures except SVs. All quantitative measures except for the SVs were within the tolerance recommended by AAPM TG 132 (DSC ≥ 0.8, MDA ≤ 3 mm). On average, treating physicians estimated 17 minutes were saved for each patient. <h3>Conclusion</h3> Overall, the model can accurately auto contour targets, organs, and spacer with significant efficiency gain. A majority of ACs qualitatively evaluated by a physician had only mild discrepancies. Quantitative analysis demonstrated ACs for most organs had only minor geometric differences, unlikely to result in any significant dose-volume impact.

Magnetic Resonance Image Guided Adaptive Radiation Therapy: Clinical Applications in the Pediatric and Adolescent and Young Adult Population

<h3>Purpose/Objective(s)</h3> To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiotherapy in the pediatric, adolescent and young adult (AYA) population. <h3>Materials/Methods</h3> All pediatric (age < 18) and AYA patients (age < 30), treated on an MR linear accelerator (MRL) from 2019 to 2021 were enrolled onto a prospective registry. The system is used with a related treatment planning system which employs a Monte Carlo dose calculation algorithm to account for effects of the magnetic field on the dose distribution. Step-and-Shoot intensity-modulated radiation treatment (IMRT) plans were generated for all Unity patients with a dose grid of 3 mm and a statistical uncertainty of ≤ 1% per plan. CT and MR images were obtained for each patient for initial radiation treatment planning. Daily treatment setup consisted of a volumetric MRI scan followed by rigid registration used to evaluate the agreement between the reference plan contours and daily shifts in internal anatomy. If necessary, based on evaluation of the daily anatomy, online recontouring and plan re-optimization was performed. <h3>Results</h3> A total of 14 pediatric and AYA patients have been treated. The median patient age is 13 years (range: 14 mo -27 yrs). Four patients were ≤ 8 years old. Reasons for treatment on the MRL were improved visualization of the primary tumor, re-irradiation in a critical area, and need for daily adaptive replanning to minimize dose to critical structures The clinical applications of MR-guided radiotherapy included Ewing sarcoma (primary and metastatic, n = 3), recurrent diffuse intrinsic pontine glioma (DIPG, n = 2), nasopharyngeal carcinoma (n = 1), clival chordoma (n = 1), primitive neuroectodermal tumor of the pancreas (n = 1), recurrent gluteo-sacral germ cell tumor (n = 1), Wilms tumor with unresectable IVC thrombus (n = 1), C-spine ependymoma (n = 1), and posterior fossa ependymoma (n = 1). Only one child (age 14 mo. with Wilms tumor required anesthesia. One AYA patient with Ewing sarcoma of C1 could not complete the treatment course due to pain related to longer treatment times and was transferred to a conventional linear accelerator. No patient experienced treatment interruptions or unexpected toxicity. Reasons for plan adaptation included changes in stomach and small bowel anatomy, target shape change on a near-daily basis, critical location adjacent to the brainstem, and manipulation of hot spots near the spinal cord. <h3>Conclusion</h3> Radiotherapy on the MRL was well-tolerated by pediatric and AYA patients. There was no increased use of anesthesia outside of our usual practice. Significant dosimetric advantages were seen for patients with tumors in critical locations such as adjacent to or involving the brainstem, spinal cord or near abdominal organs that change shape and location daily.

Training and Validation of Deep Learning-Based Auto-Segmentation Models for Lung Stereotactic Ablative Radiotherapy Using Retrospective Radiotherapy Planning Contours.

PurposeDeep learning-based auto-segmented contour (DC) models require high quality data for their development, and previous studies have typically used prospectively produced contours, which can be resource intensive and time consuming to obtain. The aim of this study was to investigate the feasibility of using retrospective peer-reviewed radiotherapy planning contours in the training and evaluation of DC models for lung stereotactic ablative radiotherapy (SABR).MethodsUsing commercial deep learning-based auto-segmentation software, DC models for lung SABR organs at risk (OAR) and gross tumor volume (GTV) were trained using a deep convolutional neural network and a median of 105 contours per structure model obtained from 160 publicly available CT scans and 50 peer-reviewed SABR planning 4D-CT scans from center A. DCs were generated for 50 additional planning CT scans from center A and 50 from center B, and compared with the clinical contours (CC) using the Dice Similarity Coefficient (DSC) and 95% Hausdorff distance (HD).ResultsComparing DCs to CCs, the mean DSC and 95% HD were 0.93 and 2.85mm for aorta, 0.81 and 3.32mm for esophagus, 0.95 and 5.09mm for heart, 0.98 and 2.99mm for bilateral lung, 0.52 and 7.08mm for bilateral brachial plexus, 0.82 and 4.23mm for proximal bronchial tree, 0.90 and 1.62mm for spinal cord, 0.91 and 2.27mm for trachea, and 0.71 and 5.23mm for GTV. DC to CC comparisons of center A and center B were similar for all OAR structures.ConclusionsThe DCs developed with retrospective peer-reviewed treatment contours approximated CCs for the majority of OARs, including on an external dataset. DCs for structures with more variability tended to be less accurate and likely require using a larger number of training cases or novel training approaches to improve performance. Developing DC models from existing radiotherapy planning contours appears feasible and warrants further clinical workflow testing.

Fuzzy judgment of edge features under dynamic constraints in pedestrian tracking

In order to improve the pedestrian tracking and recognition ability, it is required to conduct fuzzy judgment to edge features. Therefore, a fuzzy judgment method of edge features under dynamic constraints in pedestrian tracking based on local motion planning and edge contour segmentation was proposed. In this method, a geometry mesh area model for pedestrian tracking and recognition was constructed, and the fuzzy dynamic feature segmentation method was adopted to reconstruct dynamic edge feature points in pedestrian tracking to extract the greyscale pixel set under dynamic constraints in pedestrian tracking. The simulation results show that in pedestrian tracking and recognition, this method has strong fuzzy judgment ability of edge features and can provide results with error below 10 mm and relatively stable fluctuation, so this method can provide relatively high recognition accuracy and good robustness.

Quality Assurance Peer Review for Radiotherapy for Haematological Malignancies

AimsTo assess the impact of weekly scheduled peer review of radiotherapy planning contours for definitive treatment of haematological malignancies based on rates of recommended changes. Materials and methodsAnalysis of a prospective database of contour-based peer review at weekly scheduled meetings for patients undergoing definitive radiotherapy for haematological malignancies at a single large cancer centre between January and December 2018. Recommended changes were prospectively classified as involving the gross tumour volume (GTV), clinical target volume (CTV), planning target volume (PTV), organs at risk or dose fractionation. A univariate analysis was carried out to explore the associations between recommended changes and disease, treatment characteristics and consultant experience. ResultsIn total, 158/171 (92%) of all cases of haematological malignancy undergoing definitive radiotherapy were prospectively peer reviewed over a 12-month period. Overall, 26/158 (16.5%) changes were recommended within the peer review meetings. This included a total of 27 contour changes (GTV, CTV or PTV) in 25 patients. An increase in CTV was the most common change, occurring in 20/158 (12.7%) cases. One dose-fractionation change was recommended. Additional advice regarding planning technique/set-up was documented in 5/158 (3.2%) patients. There were no significant associations between rates of recommended change and disease type, stage, prior chemotherapy, first line versus refractory/relapse, anatomical site, radiotherapy technique or consultant experience. ConclusionsWeekly contour-based peer review meetings resulted in a high rate of recommended changes. Compliance was high. Peer review was potentially beneficial for all disease and treatment characteristics and for any degree of clinician experience.

Improved Volumetric Modulated Arc Therapy Field Junctions Using In Silico Base Plans: Application to Craniospinal Irradiation

IntroductionField junctions present a major challenge for planning craniospinal irradiation (CSI) using volumetric modulated arc therapy (VMAT). In this study, the feasibility of using in silico base dose distributions for planning junctioned VMAT fields for CSI is assessed. MethodsAn in-house computer program was created to generate strategic base plans with controlled linear dose gradients across the junction. The algorithm was generalized to allow user-defined parameters such as number of junctions and junction length. In silico base plans were used to optimize junctioned VMAT CSI plans for a pediatric case and an adult case. Throughout optimization, dose to the eyes, kidneys, lungs, heart, and liver were minimized. Final plan quality was evaluated using the percent of planning target volume receiving at least 95% prescription dose (V95%), homogeneity index, and conformity number. Final plan robustness to setup error was evaluated using changes in near-minimum, median, and near-maximum doses defined as the most exposed 98%, 50%, and 2% of the planning target volume (D98%, D50%, D2%) within the junction region before and after setup errors of ±3, ±5, and ±7 mm in the craniocaudal direction. ResultsThe program generated ideal in silico dose distributions that were compatible with a commercial treatment planning system for use as base doses during VMAT optimization. VMAT plans, that were optimized with the in silico base plans, had complementary linear dose profiles across the junction. Final pediatric and adult VMAT CSI plans both had V95% ≥98.1% and 98.1%, homogeneity index: 0.09 and 0.10, and conformity number: 0.86, 0.84, respectively. In addition, dose to surrounding organs at risk was acceptably low for both cases. For ±3 mm setup errors, small variations in the junction dose were recorded with ΔD98% ≤2.3%, ΔD50% ≤2.3%, and ΔD2% ≤2.8%. ConclusionsThis is the first demonstration of junctioned VMAT field optimization with a controlled linear dose gradient across the junction without the use of any extra planning contours. Planning junctioned VMAT using in silico base plans is feasible and capable of generating high-quality plans that are robust to clinically expected setup variations.

NCO-14PRE-TREATMENT HIPPOCAMPAL VOLUME PREDICTS NEUROCOGNITIVE FUNCTION (NCF) FOR PATIENTS TREATED WITH HIPPOCAMPAL AVOIDANCE WHOLE BRAIN RADIOTHERAPY (HA-WBRT) FOR BRAIN METASTASES: SECONDARY ANALYSIS OF NRG ONCOLOGY/RTOG 0933

BACKGROUND: RTOG 0933 demonstrated reduced risk of NCF decline in patients with brain metastases treated with HA-WBRT versus historical controls treated with standard WBRT. Hippocampal volume (HV) derived from high resolution MRI (HR-MRI) is an established predictor of NCF in Alzheimer's disease. We assessed associations of HV with NCF of patients enrolled on RTOG 0933. METHODS: HV (-Left, -Right, -Total) was calculated from (1) the submitted treatment structure file and (2) independent processing of baseline HR-MRI with validated software (FreeSurfer, FS). HV was correlated with baseline and 4 month NCF scores (Hopkins Verbal Learning Test-Revised (HVLT-R) Total Recall (TR), Immediate Recognition (IR), and Delayed Recall (DR)) using Pearson correlation. Comparisons between deteriorated and non-deteriorated patients were made using Wilcoxon. RESULTS: 39 of the 42 evaluable patients for the RTOG 0933 primary endpoint had hippocampal contours. All 42 had HR-MRIs, but only 21 were processable by FS due to scan quality. HVs from FS were larger than plan contours (median HV-Total 7.2 vs. 5.5 cc), though were significantly correlated (ρ = 0.68, p = 0.001). Larger FS HV-Total and HV-Right were significantly correlated with improved baseline HVLT-R TR (ρ = 0.46/p = 0.04, ρ = 0.51/p = 0.02, respectively) and DR (ρ = 0.46/p = 0.04, ρ = 0.49/p = 0.03, respectively) but not IR. Plan contour HV was not correlated with baseline HVLT-R though there was a trend for HV-Left with 4 month HVLT-R TR (ρ = 0.29/p = 0.07). There were no significant associations between HV and HVLT deterioration or change from baseline to 4 months. CONCLUSIONS: Baseline HV calculated from automatic segmentation of the hippocampus is significantly associated with baseline NCF. HV is not correlated with deterioration in NCF, though analysis is limited by few events and analyzable patients. The importance of HV will be explored further in two developing NRG trials. This project was supported by grants U10CA21661, U10CA180868, U10CA180822, U10CA37422 and UG1CA189867 from the National Cancer Institute (NCI).

Quantification of Organ Volume Changes and Impact of Interfraction Motion on Planning Contours Using Deformable Image Registration for Head and Neck Radiation Therapy

Quantification of Organ Volume Changes and Impact of Interfraction Motion on Planning Contours Using Deformable Image Registration for Head and Neck Radiation Therapy

Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences.

To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.

SU‐E‐T‐637: Proton Aperture Quality Assurance Using Computed Tomography

Purpose:To develop an automated algorithm for aperture quality assurance for double scattering proton radiotherapy.Methods:Anterior‐Posterior scout images were acquired on a CT scanner for five brass apertures (2 large, 3 small) with 120 kVp and 10mA. A semi‐automated algorithm was developed for the QA process. The input includes a user selecting the scout image and the associated patient plan, field and aperture size. The program automatically thresholds the scout image. Next, a connectivity algorithm is used to determine the points associated with the central shape to obtain the contour. To compare with the plan contour, the program converts the detected and plan contours into polar coordinates, interpolates the data to a 1 degree spaced grid, and determines the differences in radial distance at each grid point.Results:The mean and maximum difference and the percentage of points with distance differences less than 1.25 mm (due to the divergent cut of the aperture) between the detected and plan field aperture contours were obtained. A repeatability coefficient was derived based on repeated scanning and processing of three of the apertures. The mean difference for five apertures was 0.44 +/−0.08 mm. The maximum difference in distance was 1.2 +/−0.23 mm for all apertures. The Repeatability Coefficient was +/−0.038 mm, indicating the technique is highly repeatable. The mean percent of points with distance less than 1.25 mm was 97.41 +/−0.35%.Conclusion:Automated CT scout image based proton aperture QA is feasible, saves time, and provides a quantitative metric for proton patient specific aperture QA.

TH‐EF‐BRB‐06: Intensity Modulated Imaging?: Clinical Workflow for Fluence Field Modulated CT On a TomoTherapy System

Purpose:This work presents a new approach that uses the multi leaf collimator present on TomoTherapy devices to modulate the imaging beam. This allows for targeted imaging in which only regions of clinical importance for IGRT (patient positioning confirmation) receive a high level of image quality. This allows the total imaging dose to decrease, especially for healthy tissue.Methods:A clinical TomoTherapy machine was programmed to deliver imaging dose such that small pre‐defined volumes of interest (VOI) received relatively higher levels of image quality with respect to surrounding regions. Four different size ROIs were placed at varying distances from isocenter. The noise and mean CT number were compared between VOI and un‐modulated scans. Dose distributions were generated using a treatment planning dose calculator. A clinically feasible workflow was developed to implement this technique that used treatment planning contours to define VOI positions.Results:The VOI‐FFMCT technique produced an image noise within 5% of an unmodulated scan for all size VOIs. The VOI technique required a total imaging dose of 0.61, 0.69, 0.60, and 0.50 times the “full dose” acquisition dose for VOI sizes/locations of 10/13/10/6 cm in diameter and located 0/2/5/6 cm from isocenter respectively. Mean CT numbers for the VOI scans were within 1% of the unmodulated case.Conclusion:This approach, which combines state‐of‐the‐art radiation therapy fluence control with a novel imaging approach has been implemented on a clinical system with no hardware or software changes. A clinically feasible method for implementing this technique was developed which requires no additional user input relative to the current procedures in our clinic. The method allows physicians to choose between: (1) better image quality at no dose penalty or (2) equal image quality while reducing dose levels relative to today's standard of care.Research grants from GE HealthCare and TomoTherapy.

SU‐E‐J‐116: Uncertainties Associated with Dose Summation of High‐Dose Rate Brachytherapy and Intensity Modulated Radiotherapy for Gynecological Cases

Purpose:Determining the cumulative dose distribution (CDD) for gynecological patients treated with both high‐dose rate (HDR) brachytherapy and intensity‐modulated radiotherapy (IMRT) is challenging. The purpose of this work is to study the uncertainty of performing this with a structure‐guided deformable (SGD) approach in Velocity.Methods:For SGD, the Hounsfield units inside specified contours are overridden to set uniform values. Deformable image registration (DIR) is the run on these process images, which forces the DIR to focus on these contour boundaries. 18 gynecological cancer patients were used in this study. The original bladder and rectum planning contours for these patients were used to drive the SGD. A second set of contours were made of the bladder by the same person with the intent of carefully making them completely consistent with each other. This second set was utilized to evaluate the spatial accuracy of the SGD. The determined spatial accuracy was then multiplied by the local dose gradient to determine a dose uncertainty associated with the SGD dose warping. The normal tissue complication probability (NTCP) was then calculated for each dose volume histogram (DVH) that included four different probabilistic uncertainties associated with the spatial errors (e.g., 68.3% and 95.4%).Results:The NTCPs for each DVH (e.g., NTCP_−95.4%, NTCP_−68.3%, NTCP_68.3%, NTCP_95.4%) differed amongst patients. All patients had an NTCP_−95.4% close to 0%, while NTCP_95.4% ranged from 0.67% to 100%. Nine patients had an NTCP_−95.4% less than 50% while the remaining nine patients had NTCP_95.4% greater than 50%.Conclusion:The uncertainty associated with this CDD technique renders a large NTCP uncertainty. Thus, it is currently not practical for clinical use. The two ways to improve this would be to use more precise contours to drive the SGD and to use a more accurate DIR algorithm.