一种用于复杂4π放疗规划的超高性能并行(UHPP)框架。

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Qifan Xu, Qihui Lyu, Lu Jiang, Shusen Jing, Dan Ruan, Ke Sheng
{"title":"一种用于复杂4π放疗规划的超高性能并行(UHPP)框架。","authors":"Qifan Xu, Qihui Lyu, Lu Jiang, Shusen Jing, Dan Ruan, Ke Sheng","doi":"10.1088/1361-6560/adf2f2","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In radiotherapy, dose distribution conformity and compactness are critical to patient outcomes. Advanced techniques like 4π radiotherapy leverage non-coplanar beams for superior dosimetry by exploring additional degrees of freedom. However, 4π planning is computationally intensive due to large dose-loading matrices for candidate beams. This work presents an ultra-high performance parallel (UHPP) framework to accelerate high-dimensional treatment planning.&#xD;&#xD;Methods. For dose calculation, we developed: 1) A two-step TERMA computation module calculating the TERMA array once per beam, enabling reuse across convolution directions; 2) A synchronized dose calculation module based on collapsed-cone convolution superposition (CCCS), arranging rays in dedicated sequences to preserve thread efficiency and minimize memory access; 3) A scattering-based coordinate transformation mapping dose from beamlet to patient Cartesian coordinates, eliminating aliasing without atomic operations. The framework includes CCCS exponential kernel calculation for varying LINAC spectra. For beam orientation optimization, we employed fast iterative shrinkage-thresholding algorithm (FISTA) with group sparsity regularization, accelerated using cuSPARSE library on GPUs. We benchmarked against Monte Carlo (MC) simulations for dose accuracy and compared computational performance to state-of-the-art (SOTA) methods. Plan quality was evaluated across four approaches: UHPP, SOTA, clinical VMAT plans, and MC calculations based on UHPP plans.&#xD;&#xD;Results. Compared to MC simulations, UHPP achieved minimum 98% gamma passing rates under 1.5%/1.5mm criterion for water and slab phantoms, and average 97.35% and 92.18% under 3%/3mm criterion for pancreas and head-and-neck patients, respectively. UHPP delivered 8.86× and 6.99× speedups in dose calculation and plan optimization while maintaining comparable or superior plan quality. Both UHPP and SOTA consistently produced 4π plans outperforming clinical VMAT plans in organ-at-risk sparing and target coverage.&#xD;&#xD;Conclusion. The UHPP framework delivers high dose accuracy and substantial computational speedup without sacrificing 4π planning's dosimetric advantages, supporting practical adoption of advanced 4π radiotherapy in clinical workflows.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An ultra-high performance parallel (UHPP) framework for complex 4π radiotherapy planning.\",\"authors\":\"Qifan Xu, Qihui Lyu, Lu Jiang, Shusen Jing, Dan Ruan, Ke Sheng\",\"doi\":\"10.1088/1361-6560/adf2f2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>In radiotherapy, dose distribution conformity and compactness are critical to patient outcomes. Advanced techniques like 4π radiotherapy leverage non-coplanar beams for superior dosimetry by exploring additional degrees of freedom. However, 4π planning is computationally intensive due to large dose-loading matrices for candidate beams. This work presents an ultra-high performance parallel (UHPP) framework to accelerate high-dimensional treatment planning.&#xD;&#xD;Methods. For dose calculation, we developed: 1) A two-step TERMA computation module calculating the TERMA array once per beam, enabling reuse across convolution directions; 2) A synchronized dose calculation module based on collapsed-cone convolution superposition (CCCS), arranging rays in dedicated sequences to preserve thread efficiency and minimize memory access; 3) A scattering-based coordinate transformation mapping dose from beamlet to patient Cartesian coordinates, eliminating aliasing without atomic operations. The framework includes CCCS exponential kernel calculation for varying LINAC spectra. For beam orientation optimization, we employed fast iterative shrinkage-thresholding algorithm (FISTA) with group sparsity regularization, accelerated using cuSPARSE library on GPUs. We benchmarked against Monte Carlo (MC) simulations for dose accuracy and compared computational performance to state-of-the-art (SOTA) methods. Plan quality was evaluated across four approaches: UHPP, SOTA, clinical VMAT plans, and MC calculations based on UHPP plans.&#xD;&#xD;Results. Compared to MC simulations, UHPP achieved minimum 98% gamma passing rates under 1.5%/1.5mm criterion for water and slab phantoms, and average 97.35% and 92.18% under 3%/3mm criterion for pancreas and head-and-neck patients, respectively. UHPP delivered 8.86× and 6.99× speedups in dose calculation and plan optimization while maintaining comparable or superior plan quality. Both UHPP and SOTA consistently produced 4π plans outperforming clinical VMAT plans in organ-at-risk sparing and target coverage.&#xD;&#xD;Conclusion. The UHPP framework delivers high dose accuracy and substantial computational speedup without sacrificing 4π planning's dosimetric advantages, supporting practical adoption of advanced 4π radiotherapy in clinical workflows.</p>\",\"PeriodicalId\":20185,\"journal\":{\"name\":\"Physics in medicine and biology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics in medicine and biology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-6560/adf2f2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics in medicine and biology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1361-6560/adf2f2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

目的:在放射治疗中,剂量分布的一致性和紧凑性对患者的预后至关重要。先进的技术,如4π放射治疗利用非共面光束通过探索额外的自由度来进行卓越的剂量测定。然而,由于候选光束的大剂量载荷矩阵,4π规划是计算密集型的。这项工作提出了一个超高性能并行(UHPP)框架,以加速高维治疗计划。对于剂量计算,我们开发了:1)一个两步TERMA计算模块,每个波束计算一次TERMA阵列,实现跨卷积方向的重用;2)基于坍缩锥卷积叠加(CCCS)的同步剂量计算模块,将射线按专用序列排列,以保持线程效率并减少内存访问;3)一种基于散射的坐标变换,将剂量从波束映射到患者笛卡尔坐标,消除了混叠,无需原子操作。该框架包括CCCS指数核计算对不同的LINAC光谱。在波束方向优化方面,我们采用了群稀疏正则化的快速迭代收缩阈值算法(FISTA),在gpu上使用cuSPARSE库进行加速。我们对蒙特卡罗(MC)模拟剂量精度进行基准测试,并将计算性能与最先进的(SOTA)方法进行比较。通过四种方法评估计划质量:UHPP、SOTA、临床VMAT计划和基于UHPP计划的MC计算。与MC模拟相比,UHPP在1.5%/1.5mm标准下对水影和板影的伽玛通过率最低为98%,在3%/3mm标准下对胰腺和头颈部患者的平均伽玛通过率分别为97.35%和92.18%。UHPP在剂量计算和计划优化方面提供了8.86倍和6.99倍的加速,同时保持了相当或更好的计划质量。UHPP和SOTA一致产生的4π计划在保留危险器官和靶覆盖方面优于临床VMAT计划。UHPP框架在不牺牲4π计划的剂量学优势的情况下提供高剂量精度和大量计算速度,支持在临床工作流程中实际采用先进的4π放疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ultra-high performance parallel (UHPP) framework for complex 4π radiotherapy planning.

Purpose: In radiotherapy, dose distribution conformity and compactness are critical to patient outcomes. Advanced techniques like 4π radiotherapy leverage non-coplanar beams for superior dosimetry by exploring additional degrees of freedom. However, 4π planning is computationally intensive due to large dose-loading matrices for candidate beams. This work presents an ultra-high performance parallel (UHPP) framework to accelerate high-dimensional treatment planning. Methods. For dose calculation, we developed: 1) A two-step TERMA computation module calculating the TERMA array once per beam, enabling reuse across convolution directions; 2) A synchronized dose calculation module based on collapsed-cone convolution superposition (CCCS), arranging rays in dedicated sequences to preserve thread efficiency and minimize memory access; 3) A scattering-based coordinate transformation mapping dose from beamlet to patient Cartesian coordinates, eliminating aliasing without atomic operations. The framework includes CCCS exponential kernel calculation for varying LINAC spectra. For beam orientation optimization, we employed fast iterative shrinkage-thresholding algorithm (FISTA) with group sparsity regularization, accelerated using cuSPARSE library on GPUs. We benchmarked against Monte Carlo (MC) simulations for dose accuracy and compared computational performance to state-of-the-art (SOTA) methods. Plan quality was evaluated across four approaches: UHPP, SOTA, clinical VMAT plans, and MC calculations based on UHPP plans. Results. Compared to MC simulations, UHPP achieved minimum 98% gamma passing rates under 1.5%/1.5mm criterion for water and slab phantoms, and average 97.35% and 92.18% under 3%/3mm criterion for pancreas and head-and-neck patients, respectively. UHPP delivered 8.86× and 6.99× speedups in dose calculation and plan optimization while maintaining comparable or superior plan quality. Both UHPP and SOTA consistently produced 4π plans outperforming clinical VMAT plans in organ-at-risk sparing and target coverage. Conclusion. The UHPP framework delivers high dose accuracy and substantial computational speedup without sacrificing 4π planning's dosimetric advantages, supporting practical adoption of advanced 4π radiotherapy in clinical workflows.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信