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Title: SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality

Abstract

Purpose: Cranial SRS VMAT plans must have steep dose gradient around each target to reduce dose to normal brain. This study reports on the correlation between gradient index (GI=V50%/V100%), target size and target dose heterogeneity index (HI=PTV Dmax/prescription dose) for multi-lesion cranial SRS VMAT plans. Methods: VMAT plans for 10 cranial cases with 3 to 6 lesions (total 39 lesions) generated in Varian Eclipse V11.0.47 with a fine-tuned AAA beam model and 0.125 cm dose grid were analyzed. One or two iso centers were used depending on the spatial distribution of lesions. Two to nine coplanar and non-coplanar arcs were used per isocenter. Conformity index (CI= V100%/VPTV), HI, and GI were determined for each lesion. Dose to critical structures were recorded. Results: Lesion size ranged from 0.05–11.00 cm3. HI ranged from 1.2–1.4, CI ranged from 1.0–2.8 and GI from 3.1–8.4. Maximum dose to brainstem, chiasm, lenses, optic nerves and eyes ranged from 120–1946 cGy, 47–463 cGy, 9–121 cGy, 14–512 cGy, and 17–294 cGy, respectively. Brain minus PTV (Brain-PTV) V7Gy was in the range 1.1–6.5%, and Brain-PTV Dmean was in the range 94–324 cGy. Conclusion: This work shows that a GI < 5 can be achieved for lesions > 0.4cc. Formore » smaller lesions, GI increases rapidly. GI is lower when HI is increased. Based on this study, recommend HI is 1.4, and recommended GI is for volumes <0.1cc GI<9, 0.1–0.4cc GI<6, 0.4–0.1.0cc GI<5, and for volumes >1.0cc GI<4. CI is < 1.3 for all lesions except for targets < 0.1cc. Cranial SRS VMAT plans must be optimized to lower the GI to reduce the dose to normal brain tissue.« less

Authors:
; ; ; ; ; ; ; ;  [1]
  1. Memorial Sloan-Kettering Cancer Center, New York, NY (United States)
Publication Date:
OSTI Identifier:
22649177
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; BRAIN; RADIATION DOSES; RADIOTHERAPY; SPATIAL DISTRIBUTION

Citation Formats

Ballangrud, A, Kuo, L, Happersett, L, Lim, S, Li, X, Beal, K, Yamada, Y, LoSasso, T, and Mechalakos, J. SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality. United States: N. p., 2016. Web. doi:10.1118/1.4956798.
Ballangrud, A, Kuo, L, Happersett, L, Lim, S, Li, X, Beal, K, Yamada, Y, LoSasso, T, & Mechalakos, J. SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality. United States. doi:10.1118/1.4956798.
Ballangrud, A, Kuo, L, Happersett, L, Lim, S, Li, X, Beal, K, Yamada, Y, LoSasso, T, and Mechalakos, J. 2016. "SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality". United States. doi:10.1118/1.4956798.
@article{osti_22649177,
title = {SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality},
author = {Ballangrud, A and Kuo, L and Happersett, L and Lim, S and Li, X and Beal, K and Yamada, Y and LoSasso, T and Mechalakos, J},
abstractNote = {Purpose: Cranial SRS VMAT plans must have steep dose gradient around each target to reduce dose to normal brain. This study reports on the correlation between gradient index (GI=V50%/V100%), target size and target dose heterogeneity index (HI=PTV Dmax/prescription dose) for multi-lesion cranial SRS VMAT plans. Methods: VMAT plans for 10 cranial cases with 3 to 6 lesions (total 39 lesions) generated in Varian Eclipse V11.0.47 with a fine-tuned AAA beam model and 0.125 cm dose grid were analyzed. One or two iso centers were used depending on the spatial distribution of lesions. Two to nine coplanar and non-coplanar arcs were used per isocenter. Conformity index (CI= V100%/VPTV), HI, and GI were determined for each lesion. Dose to critical structures were recorded. Results: Lesion size ranged from 0.05–11.00 cm3. HI ranged from 1.2–1.4, CI ranged from 1.0–2.8 and GI from 3.1–8.4. Maximum dose to brainstem, chiasm, lenses, optic nerves and eyes ranged from 120–1946 cGy, 47–463 cGy, 9–121 cGy, 14–512 cGy, and 17–294 cGy, respectively. Brain minus PTV (Brain-PTV) V7Gy was in the range 1.1–6.5%, and Brain-PTV Dmean was in the range 94–324 cGy. Conclusion: This work shows that a GI < 5 can be achieved for lesions > 0.4cc. For smaller lesions, GI increases rapidly. GI is lower when HI is increased. Based on this study, recommend HI is 1.4, and recommended GI is for volumes <0.1cc GI<9, 0.1–0.4cc GI<6, 0.4–0.1.0cc GI<5, and for volumes >1.0cc GI<4. CI is < 1.3 for all lesions except for targets < 0.1cc. Cranial SRS VMAT plans must be optimized to lower the GI to reduce the dose to normal brain tissue.},
doi = {10.1118/1.4956798},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: Single-isocenter VMAT has been shown able to create high quality plans for complex intracranial multiple metastasis SRS cases. Linacs capable of the technique are typically outfitted with an MLC that consists of a combination of 5 mm and 10 mm leaves (standard) or 2.5 mm and 5 mm leaves (high-definition). In this study, we test the hypothesis that thinner collimator leaves are associated with improved plan quality. Methods: Ten multiple metastasis cases were identified and planned for VMAT SRS using a 10 MV flattening filter free beam. Plans were created for a standard (std) and a high-definition (HD) MLC.more » Published values for leaf transmission factor and dosimetric leaf gap were utilized. All other parameters were invariant. Conformity (plan and individual target), moderate isodose spill (V50%), and low isodose spill (mean brain dose) were selected for analysis. Results: Compared to standard MLC, HD-MLC improved overall plan conformity (median: Paddick CI-HD = 0.83, Paddick CI-std = 0.79; p = 0.004 and median: RTOG CI-HD =1.18, RTOG CI-std =1.24; p = 0.01 ), improved individual lesion conformity (median: Paddick CI-HD,i =0.77, Paddick CI-std,i =0.72; p < 0.001 and median: RTOG CI-HD,i = 1.28, RTOG CI-std,i =1.35; p < 0.001), improved moderate isodose spill (median: V50%-HD = 37.0 cc, V50%-std = 45.7 cc; p = 0.002), and improved low dose spill (median: dmean-HD = 2.90 Gy, dmean-std = 3.19 Gy; p = 0.002). Conclusion: For the single-isocenter VMAT SRS of multiple metastasis plans examined, use of HD-MLC modestly improved conformity, moderate isodose, and low isodose spill compared to standard MLC. However, in all cases we were able to generate clinically acceptable plans with the standard MLC. More work is need to further quantify the difference in cases with higher numbers of small targets and to better understand any potential clinical significance. This research was supported in part by Varian Medical Systems.« less
  • Purpose: Patient-specific quality assurance in volumetric modulated arc therapy (VMAT) brain stereotactic radiosurgery raises specific issues on dosimetric procedures, mainly represented by the small radiation fields associated with the lack of lateral electronic equilibrium, the need of small detectors and the high dose delivered. The purpose of the study is to compare three different dosimeters for pre-treatment QA. Methods: Nineteen patients (affected by neurinomas, brain metastases, and by meningiomas) were treated with VMAT plans computed on a Monte Carlo based TPS. Gafchromic films inside a slab phantom (GF), 3-D cylindrical phantom with two orthogonal diodes array (DA), and 3-D cylindricalmore » phantom with a single rotating ionization chambers array (ICA), have been evaluated. The dosimeters are, respectively, characterized by a spatial resolution of: 0.4 (in our method), 5 and 2.5 mm. For GF we used a double channel method for calibration and reading protocol; for DA and ICA we used the 3-D dose distributions reconstructed by the two software sold with the dosimeters. With the need of a common system for analyze different measuring approaches, we used an in-house software that analyze a single coronal plane in the middle of the phantoms and Gamma values (2% / 2 mm and 3% / 3 mm) were computed for all patients and dosimeters. Results: The percentage of points with gamma values less than one was: 95.7% for GF, 96.8% for DA and 95% for ICA, using 3%/3mm criteria, and 90.1% for GF, 92.4% for DA and 92% for ICA, using 2% / 2mm gamma criteria. Tstudent test p-values obtained by comparing the three datasets were not statistically significant for both gamma criteria. Conclusion: Gamma index analysis is not affected by different spatial resolution of the three dosimeters.« less
  • Purpose: IMPT plan design is highly dependent on planner’s experiences. VMAT plan design is relatively mature and can even be automated. The quality of IMPT plan designed by in-experienced planner could be inferior to that of VMAT plan designed by experienced planner or automatic planning software. Here we introduce a method for designing IMPT plan based on VMAT plan to ensure the IMPT plan be superior to IMRT/VMAT plan for majority clinical scenario. Methods: To design a new IMPT plan, a VMAT plan is first generated either by experienced planner or by in-house developed automatic planning system. An in-house developedmore » tool is used to generate the dose volume constrains for the IMPT plan as plan template to Eclipse TPS. The beam angles for IMPT plan are selected based on the preferred angles in the VMAT plan. IMPT plan is designed by importing the plan objectives generated from VMAT plan. Majority thoracic IMPT plans are designed using this plan approach in our center. In this work, a thoracic IMPT plan under RTOG 1308 protocol is selected to demonstrate the effectiveness and efficiency of this approach. The dosimetric indices of IMPT are compared with VMAT plan. Results: The PTV D95, lung V20, MLD, mean heart dose, esophagus D1, cord D1 are 70Gy, 31%, 17.8Gy, 25.5Gy, 73Gy, 45Gy for IMPT plan and 65.3Gy, 34%, 21.6Gy, 35Gy, 74Gy, 48Gy for VMAT plan. For majority cases, the high dose region of the normal tissue which is in proximity of PTV is comparable between IMPT and VMAT plan. The low dose region of the IMPT plan is significantly better than VMAT plan. Conclusion: Using the knowledge gained in VMAT plan design can help efficiently and effectively design high quality IMPT plan. The quality of IMPT plan can be controlled to ensure the superiority of IMPT plan compared to VMAT/IMRT plan.« less
  • Purpose: GPU has been employed to speed up VMAT optimizations from hours to minutes. However, its limited memory capacity makes it difficult to handle cases with a huge dose-deposition-coefficient (DDC) matrix, e.g. those with a large target size, multiple arcs, small beam angle intervals and/or small beamlet size. We propose multi-GPU-based VMAT optimization to solve this memory issue to make GPU-based VMAT more practical for clinical use. Methods: Our column-generation-based method generates apertures sequentially by iteratively searching for an optimal feasible aperture (referred as pricing problem, PP) and optimizing aperture intensities (referred as master problem, MP). The PP requires accessmore » to the large DDC matrix, which is implemented on a multi-GPU system. Each GPU stores a DDC sub-matrix corresponding to one fraction of beam angles and is only responsible for calculation related to those angles. Broadcast and parallel reduction schemes are adopted for inter-GPU data transfer. MP is a relatively small-scale problem and is implemented on one GPU. One headand- neck cancer case was used for test. Three different strategies for VMAT optimization on single GPU were also implemented for comparison: (S1) truncating DDC matrix to ignore its small value entries for optimization; (S2) transferring DDC matrix part by part to GPU during optimizations whenever needed; (S3) moving DDC matrix related calculation onto CPU. Results: Our multi-GPU-based implementation reaches a good plan within 1 minute. Although S1 was 10 seconds faster than our method, the obtained plan quality is worse. Both S2 and S3 handle the full DDC matrix and hence yield the same plan as in our method. However, the computation time is longer, namely 4 minutes and 30 minutes, respectively. Conclusion: Our multi-GPU-based VMAT optimization can effectively solve the limited memory issue with good plan quality and high efficiency, making GPUbased ultra-fast VMAT planning practical for real clinical use.« less
  • Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform tomore » solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.« less