Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer

•Developed a novel algorithm to predict anatomical evolutions during radiotherapy.•Incorporated potential tumor shrinkages into optimization of predictive planning.•Demonstrated improvement in therapeutic ratio with a study of 60 lung patients.•Fully integrable to clinical workflow for facilitation...

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Veröffentlicht in:	Radiotherapy and oncology 2022-04, Vol.169, p.57-63
Hauptverfasser:	Lee, Donghoon, Hu, Yu-chi, Kuo, Licheng, Alam, Sadegh, Yorke, Ellen, Li, Anyi, Rimner, Andreas, Zhang, Pengpeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive radiotherapy Deep Learning Humans Lung - pathology Lung Neoplasms - diagnostic imaging Lung Neoplasms - pathology Lung Neoplasms - radiotherapy Lung tumor Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted - methods Radiotherapy, Intensity-Modulated Time series
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