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Automatic planning for functional lung avoidance radiotherapy based on function-guided beam angle selection and plan optimization.
Xiong, Tianyu; Zeng, Guangping; Chen, Zhi; Huang, Yu-Hua; Li, Bing; Zhou, Dejun; Liu, Xi; Sheng, Yang; Ren, Ge; Wu, Qingrong Jackie; Ge, Hong; Cai, Jing.
Afiliação
  • Xiong T; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Zeng G; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Chen Z; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Huang YH; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Li B; Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, People's Republic of China.
  • Zhou D; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Liu X; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Sheng Y; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States of America.
  • Ren G; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
  • Wu QJ; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States of America.
  • Ge H; Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, People's Republic of China.
  • Cai J; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China, People's Republic of China.
Phys Med Biol ; 69(15)2024 Jul 17.
Article em En | MEDLINE | ID: mdl-38959907
ABSTRACT
Objective.This study aims to develop a fully automatic planning framework for functional lung avoidance radiotherapy (AP-FLART).Approach.The AP-FLART integrates a dosimetric score-based beam angle selection method and a meta-optimization-based plan optimization method, both of which incorporate lung function information to guide dose redirection from high functional lung (HFL) to low functional lung (LFL). It is applicable to both contour-based FLART (cFLART) and voxel-based FLART (vFLART) optimization options. A cohort of 18 lung cancer patient cases underwent planning-CT and SPECT perfusion scans were collected. AP-FLART was applied to generate conventional RT (ConvRT), cFLART, and vFLART plans for all cases. We compared automatic against manual ConvRT plans as well as automatic ConvRT against FLART plans, to evaluate the effectiveness of AP-FLART. Ablation studies were performed to evaluate the contribution of function-guided beam angle selection and plan optimization to dose redirection.Main results.Automatic ConvRT plans generated by AP-FLART exhibited similar quality compared to manual counterparts. Furthermore, compared to automatic ConvRT plans, HFL mean dose,V20, andV5were significantly reduced by 1.13 Gy (p< .001), 2.01% (p< .001), and 6.66% (p< .001) respectively for cFLART plans. Besides, vFLART plans showed a decrease in lung functionally weighted mean dose by 0.64 Gy (p< .01),fV20by 0.90% (p= 0.099), andfV5by 5.07% (p< .01) respectively. Though inferior conformity was observed, all dose constraints were well satisfied. The ablation study results indicated that both function-guided beam angle selection and plan optimization significantly contributed to dose redirection.Significance.AP-FLART can effectively redirect doses from HFL to LFL without severely degrading conventional dose metrics, producing high-quality FLART plans. It has the potential to advance the research and clinical application of FLART by providing labor-free, consistent, and high-quality plans.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Automação / Planejamento da Radioterapia Assistida por Computador / Neoplasias Pulmonares Limite: Humans Idioma: En Revista: Phys Med Biol / Phys. med. biol / Physics in medicine and biology Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Automação / Planejamento da Radioterapia Assistida por Computador / Neoplasias Pulmonares Limite: Humans Idioma: En Revista: Phys Med Biol / Phys. med. biol / Physics in medicine and biology Ano de publicação: 2024 Tipo de documento: Article