1
|
Panda S, Swamidas J, Chopra S, Mangaj A, Fogliata A, Kupelian P, Agarwal JP, Cozzi L. Treatment planning comparison of volumetric modulated arc therapy employing a dual-layer stacked multi-leaf collimator and helical tomotherapy for cervix uteri. Radiat Oncol 2020; 15:22. [PMID: 32000832 PMCID: PMC6990476 DOI: 10.1186/s13014-020-1473-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 01/19/2020] [Indexed: 12/26/2022] Open
Abstract
Purpose To ascertain the dosimetric performance of a new delivery system (the Halcyon system, H) equipped with dual-layer stacked multi-leaf collimator (MLC) for risk-adapted targets in cervix uteri cancer patients compared to another ring-based system in clinical operation (Helical Tomotherapy, HT). Methods Twenty patients were retrospectively included in a treatment planning study (10 with positive lymph nodes and 10 without). The dose prescription (45Gy to the primary tumour volume and a simultaneously integrated boost up to 55Gy for the positive patients) and the clinical planning objectives were defined consistently as recommended by an ongoing multicentric clinical trial. Halcyon plans were optimised for the volumetric modulated arc therapy. The plan comparison was performed employing the quantitative analysis of the dose-volume histograms. Results The coverage of the primary and nodal target volumes was comparable for both techniques and both subsets of patients. The primary planning target volume (PTV) receiving at least 95% of the prescription isodose ranged from 97.2 ± 1.1% (node-negative) to 99.1 ± 1.2% (node-positive) for H and from 96.5 ± 1.9% (node-negative) to 98.3 ± 0.9% (node-positive) for HT. The uncertainty is expressed at one standard deviation from the cohort of patient per each group. For the nodal clinical target volumes, the dose received by 98% of the planning target volume ranged 55.5 ± 0.1 to 56.0 ± 0.8Gy for H and HT, respectively. The only significant and potentially relevant differences were observed for the bowels. In this case, V40Gy resulted 226.3 ± 35.9 and 186.9 ± 115.9 cm3 for the node-positive and node-negative patients respectively for Halcyon. The corresponding findings for HT were: 258.9 ± 60.5 and 224.9 ± 102.2 cm3. On the contrary, V15Gy resulted 1279.7 ± 296.5 and 1557.2 ± 359.9 cm3 for HT and H respectively for node-positive and 1010.8 ± 320.9 versus 1203.8 ± 332.8 cm3 for node-negative. Conclusion This retrospective treatment planning study, based on the dose constraints derived from the Embrace II study protocol, suggested the essential equivalence between Halcyon based and Helical Tomotherapy based plans for the intensity-modulated rotational treatment of cervix uteri cancer. Different levels of sparing were observed for the bowels with H better protecting in the high-dose region and HT in the mid-low dose regions. The clinical impact of these differences should be further addressed.
Collapse
|
2
|
Neylon J, Min Y, Kupelian P, Low DA, Santhanam A. Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations. Int J Comput Assist Radiol Surg 2016; 12:669-680. [PMID: 27558385 DOI: 10.1007/s11548-016-1473-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 08/12/2016] [Indexed: 10/21/2022]
Abstract
PURPOSE In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. METHODS An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. RESULTS The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. CONCLUSIONS The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.
Collapse
|
3
|
Santhanam A, Min Y, Beron P, Agazaryan N, Kupelian P, Low D. SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework. Med Phys 2016. [DOI: 10.1118/1.4955617] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
4
|
Ruan D, Shao W, Wong J, Veruttipong D, Steinberg M, Low D, Kupelian P. SU-F-T-102: Automatic Curation for a Scalable Registry Using Machine Learning. Med Phys 2016. [DOI: 10.1118/1.4956238] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
5
|
Yang L, Low D, Lee P, Ruan D, Chin R, Kaprealian T, Kamrava M, Kupelian P, Beron P, Steinberg M, Chen A, Agazaryan N, Ray S, Qi X. SU-F-J-181: An Alternative Patient Alignment Tool On TomoTherapy: The First In- Human Megavoltage-Topogram Acquisition. Med Phys 2016. [DOI: 10.1118/1.4956089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
6
|
Neylon J, Sheng K, Yu V, Chen Q, Low DA, Kupelian P, Santhanam A. A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures. Med Phys 2015; 41:101711. [PMID: 25281950 DOI: 10.1118/1.4895822] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. METHODS The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy into a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. RESULTS The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. CONCLUSIONS The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.
Collapse
|
7
|
Ruan D, Shao W, Low D, Kupelian P, Qi SX. SU-E-T-01: (In)dependence of Plan Quality On Treatment Modalities and Target-To-Critical Structure Geometry for Brain Tumor. Med Phys 2015. [DOI: 10.1118/1.4924362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
8
|
Qi S, Kishan A, Alexander S, Lee P, Selch M, Kupelian P, Steiberg M, Low D. SU-F-BRB-13: Correlation of Improved Target and Organ-At-Risk Dosimetric Quantities and Clinical Outcomes for Helical Tomotherapy Treated Mesothelioma. Med Phys 2015. [DOI: 10.1118/1.4925208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
9
|
Yu V, Nguyen D, Tran A, Ruan D, Cao M, Kaprealian T, Kupelian P, Low D, Sheng K. TU-CD-304-05: 4Ï€ Non-Coplanar Radiotherapy: From Mathematical Modeling to Clinical Implementation. Med Phys 2015. [DOI: 10.1118/1.4925574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
10
|
Santhanam A, Min Y, Kupelian P, Low D. TH-AB-204-04: On the Feasibility of a Multi-3D Kinect V2 Camera System for Monitoring Radiation Therapy Treatment Setup and Improving Patient Safety. Med Phys 2015. [DOI: 10.1118/1.4926171] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
11
|
Neylon J, Kupelian P, Santhanam A. WE-AB-BRA-10: Systematic Assessment of a Novel Image Similarity Parameterization Metric for Fully Automated Quantification of Deformable Image Registration Accuracy. Med Phys 2015. [DOI: 10.1118/1.4925863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
12
|
Yu V, Nguyen D, Pajonk F, Kaprealian T, Kupelian P, Steinberg M, Low D, Sheng K. SU-D-BRB-06: Treating Glioblastoma Multiforme (GBM) as a Chronic Disease: Implication of Temporal-Spatial Dose Fractionation Optimization Including Cancer Stem Cell Dynamics. Med Phys 2015. [DOI: 10.1118/1.4923879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
13
|
Neylon J, Qi X, Sheng K, Staton R, Pukala J, Manon R, Low DA, Kupelian P, Santhanam A. A GPU based high-resolution multilevel biomechanical head and neck model for validating deformable image registration. Med Phys 2014; 42:232-43. [PMID: 25563263 DOI: 10.1118/1.4903504] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
14
|
Levin-Epstein R, Wang J, Tenn S, Selch M, De Salles A, Pouratian N, McCloskey S, Kupelian P, Steinberg M, Yang I, Beron P, Kaprealian T. Stereotactic Radiation Therapy Demonstrates Improved Tumor Control Versus Whole Brain Radiation Therapy in Breast Cancer Brain Metastasis for All Receptor Subtypes. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
15
|
Kamrava M, Joshua S, Park S, Swamy U, Fallon J, Banerjee R, Kupelian P, Demanes D. Clinical Outcomes of High-Dose-Rate Interstitial Gynecologic Brachytherapy for Primary Locally Advanced Cervical Cancer. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
16
|
Santhanam A, John N, Staton R, Qi X, Kupelian P. A Systematic Assessment of Head and Neck Deformable Image Registration Using High Resolution Biomechanical Models. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
17
|
Kang J, Selch M, Kupelian P, Cloughesy T, Lee P. High-Dose Radiation to the Subventricular Zone Does Not Alter the Patterns of Recurrence in GB. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
18
|
Gomez C, Xu X, Qi X, Wang P, Kupelian P, Steinberg M, King C. Dosimetric Parameters Predict Quality of Life Outcomes for Patients Receiving Stereotactic Body Radiation Therapy for Prostate Cancer. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
19
|
Rwigema J, Nguyen D, Heron D, Chen A, Lee P, Vargo J, Low D, Huq M, Steinberg M, Kupelian P, Sheng K. 4π Non-Coplanar Stereotactic Body Radiation Therapy (SBRT) for Head and Neck Cancer: Potential to Improve Local Control and Late Toxicity. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
20
|
Qi X, Pajonk F, Low D, Kupelian P, McCloskey S, Sheng K. Radioresistance of the Breast Tumor is Highly Correlated to Its Level of Cancer Stem Cell. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
21
|
Sheng K, Gou S, Kupelian P, Kamrava M, Low D, Steinberg M. Detecting Prostate Focal Lesions in CT Images. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.2444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
22
|
Nguyen D, Rwigema J, Yu V, Kaprealian T, Kupelian P, Selch M, Low D, Sheng K. Feasibility of Extreme Dose Escalation for Glioblastoma Multiforme Using 4π Radiation Therapy. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.527] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
23
|
Wallner P, Kupelian P, Erickson B, Alektiar K. Promises and Pitfalls: Development of a National Brachytherapy Registry. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
24
|
Qi S, Neylon J, Chen A, Low D, Kupelian P, Steinberg M, Santhanam A. SU-E-J-127: Real-Time Dosimetric Assessment for Adaptive Head-And-Neck Treatment Via A GPU-Based Deformable Image Registration Framework. Med Phys 2014. [DOI: 10.1118/1.4888179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
25
|
Yu V, Nguyen D, Kupelian P, Kaprealian T, Selch M, Low D, Pajonk F, Sheng K. SU-C-BRE-03: Dual Compartment Mathematical Modeling of Glioblastoma Multiforme (GBM). Med Phys 2014. [DOI: 10.1118/1.4889709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|