Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report.

Autor: Huijben EMC; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Terpstra ML; Radiotherapy Department, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Imaging Group for MR Diagnostics & Therapy, University Medical Center Utrecht, Utrecht, The Netherlands., Galapon AJ; Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Pai S; Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands., Thummerer A; Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany., Koopmans P; Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands., Afonso M; Wageningen University & Research, Wageningen Plant Research, Wageningen, The Netherlands., van Eijnatten M; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Gurney-Champion O; Department of Radiology and Nuclear Medicine, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands., Chen Z; School of Biomedical Engineering, Southern Medical University, Guangzhou, China., Zhang Y; School of Biomedical Engineering, Southern Medical University, Guangzhou, China., Zheng K; School of Biomedical Engineering, Southern Medical University, Guangzhou, China., Li C; School of Biomedical Engineering, Southern Medical University, Guangzhou, China., Pang H; School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China., Ye C; School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China., Wang R; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China., Song T; Fudan University, Shanghai, China., Fan F; Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany., Qiu J; Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany., Huang Y; Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany., Ha J; Indiana University, Bloomington, USA., Sung Park J; Indiana University, Bloomington, USA., Alain-Beaudoin A; Advanced Development Engineering, Elekta Ltd, Montreal, Canada., Bériault S; Advanced Development Engineering, Elekta Ltd, Montreal, Canada., Yu P; Infervision Medical Technology Co., Ltd. Beijing, China., Guo H; Department of Biomedical Engineering, Shantou University, China., Huang Z; Department of Biomedical Engineering, Shantou University, China., Li G; Independent researchers., Zhang X; Independent researchers., Fan Y; Department of Computer Science, Vanderbilt University, Nashville, USA., Liu H; Department of Computer Science, Vanderbilt University, Nashville, USA., Xin B; Australian e-Health Research Centre, CSIRO, Herston, Queensland, Australia., Nicolson A; Australian e-Health Research Centre, CSIRO, Herston, Queensland, Australia., Zhong L; Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA., Deng Z; Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA., Müller-Franzes G; University Hospital Aachen, Aachen, Germany., Khader F; University Hospital Aachen, Aachen, Germany., Li X; Center for Proton Therapy, Paul Scherrer Institut, Villigen, Switzerland; Department of Computer Science, ETH Zurich, Zurich, Switzerland., Zhang Y; Center for Proton Therapy, Paul Scherrer Institut, Villigen, Switzerland; Department of Computer Science, ETH Zurich, Zurich, Switzerland., Hémon C; University Rennes 1, CLCC Eugène Marquis, INSERM, LTSI, Rennes, France., Boussot V; University Rennes 1, CLCC Eugène Marquis, INSERM, LTSI, Rennes, France., Zhang Z; Subtle Medical, Shanghai, China., Wang L; Subtle Medical, Shanghai, China., Bai L; MedMind Technology Co. Ltd., Beijing, China., Wang S; MedMind Technology Co. Ltd., Beijing, China., Mus D; MRI Guidance BV, Utrecht, The Netherlands., Kooiman B; MRI Guidance BV, Utrecht, The Netherlands., Sargeant CAH; Division of Cancer Sciences, The University of Manchester, United Kingdom., Henderson EGA; Division of Cancer Sciences, The University of Manchester, United Kingdom., Kondo S; Muroran Institute of Technology, Hokkaido, Japan., Kasai S; Niigata University of Health and Welfare, Niigata, Japan., Karimzadeh R; Image Analysis, Computational Modelling and Geometry, University of Copenhagen, Denmark., Ibragimov B; Image Analysis, Computational Modelling and Geometry, University of Copenhagen, Denmark., Helfer T; IACS, Stony Brook University, NY, USA., Dafflon J; Data Science and Sharing Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, USA; Machine Learning Team, Functional Magnetic Resonance Imaging Facility National Institute of Mental Health, Bethesda, USA., Chen Z; Shenying Medical Technology (Shenzhen) Co., Ltd., Shenzhen, Guangdong, China., Wang E; Shenying Medical Technology (Shenzhen) Co., Ltd., Shenzhen, Guangdong, China., Perko Z; Delft University of Technology, Faculty of Applied Sciences, Department of Radiation Science and Technology, Delft, The Netherlands., Maspero M; Radiotherapy Department, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Imaging Group for MR Diagnostics & Therapy, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: m.maspero@umcutrecht.nl.
Jazyk: angličtina
Zdroj: Medical image analysis [Med Image Anal] 2024 Oct; Vol. 97, pp. 103276. Date of Electronic Publication: 2024 Jul 17.
DOI: 10.1016/j.media.2024.103276
Abstrakt: Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning. Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans. The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT. SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Matteo Maspero reports financial support was provided by EWUU alliance. Manya Afonso, Maureen van Eijnatten reports financial support was provided by EWUU alliance. Runqi Wang, Tao Song, Zhihao Zhang, Long Wang reports a relationship with Subtle Medical that includes: employment. Alexandra Alain-Beaudoin, Silvain Bériault reports a relationship with Elekta Ltd that includes: employment. Alexandra Alain-Beaudoin, Silvain Beriault has patent pending to Elekta Ltd. Pengxin Yu reports a relationship with Infervision Medical Technology Co., Ltd that includes: employment. Gengwan Li, Xueru Zhang reports a relationship with Canon Medical Systems Corporation that includes: employment. Lujia Zhong, Zhiwei Deng reports financial support was provided by University of Southern California. Valentin Boussot reports financial support was provided by French National Research Agency. Valentin Boussot reports financial support was provided by Rennes Métropole. Cédric Hémon reports financial support was provided by Elekta AB. Cédric Hémon reports financial support was provided by CominLabs. Valentin Boussot reports a relationship with University of Rennes that includes: employment. Cédric Hémon reports a relationship with University of Rennes that includes: employment. Cédric Hémon reports a relationship with Centre Eugène Marquis that includes: employment. Lu Bai, Shaobin Wang reports a relationship with MedMind Technology Co. Ltd that includes: employment. Lu Bai and Shaobing Wang had adopted some training ideas from Du Yi who is a staff in Institute of Medical Technology, Peking University Health Science Center, Beijing, China Derk Mus, Bram Kooiman reports a relationship with MRI Guidance BV that includes: employment. Chelsea Sargeant reports a relationship with Elekta AB that includes: funding grants and travel reimbursement. Edward Henderson reports a relationship with Manchester Cancer Research Centre that includes: funding grants and travel reimbursement. Zijie Chen, Enpei Wang reports a relationship with Shenying Medical Technology (Shenzhen) Co., Ltd that includes: employment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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