{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T18:08:12Z","timestamp":1791914892457,"version":"4.3.4"},"reference-count":26,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      Medical imaging is crucial in modern radiotherapy, aiding diagnosis, treatment planning, and monitoring. The development of synthetic imaging techniques, particularly synthetic computed tomography (sCT), continues to attract interest in radiotherapy. The\n                      <jats:italic>SynthRAD2025<\/jats:italic>\n                      dataset and the accompanying SynthRAD2025 Grand Challenge aim to stimulate advancements in synthetic CT generation algorithms by providing a platform for comprehensive evaluation and benchmarking of synthetic CT generation algorithms based on cone\u2010beam CTs (CBCT) and magnetic resonance images (MRI).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Acquisition and validation methods<\/jats:title>\n                    <jats:p>The dataset comprises 2362 cases, including 890 MRI\u2010CT pairs and 1472 CBCT\u2010CT pairs of head\u2010and\u2010neck, thoracic, and abdominal cancer patients treated at five European university medical centers [UMC Groningen, UMC Utrecht, Radboud UMC (Netherlands), LMU University Hospital Munich, and University Hospital of Cologne (Germany)]. Images were acquired using a wide range of acquisition protocols and scanners. Pre\u2010processing, including rigid and deformable image registration methods, was performed to ensure high\u2010quality image datasets and alignment between modalities. Extensive quality assurance was performed to validate image consistency and usability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data format and usage notes<\/jats:title>\n                    <jats:p>\n                      All imaging data is provided using the MetaImage (.mha) file format, ensuring compatibility with common medical image processing tools. Metadata, including acquisition parameters and registration details, is available in structured comma\u2010separated value (CSV) files. To ensure dataset integrity,\n                      <jats:italic>SynthRAD2025<\/jats:italic>\n                      is split into training (65%), validation (10%), and test (25%) sets. The dataset is accessible through\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/doi.org\/10.5281\/zenodo.14918088\">https:\/\/doi.org\/10.5281\/zenodo.14918088<\/jats:ext-link>\n                      under the\n                      <jats:italic>SynthRAD2025<\/jats:italic>\n                      collection.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Potential applications<\/jats:title>\n                    <jats:p>\n                      This dataset enables benchmarking and development of synthetic imaging techniques for radiotherapy applications. Potential use cases include sCT generation for MRI\u2010only and MR\u2010guided photon and proton radiotherapy, CBCT\u2010based dose calculations, and adaptive radiotherapy workflows. By incorporating data from diverse acquisition settings,\n                      <jats:italic>SynthRAD2025<\/jats:italic>\n                      supports the advancement of robust and generalizable image synthesis algorithms for clinical implementation, ultimately promoting personalized cancer care and improving adaptive radiotherapy workflows.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.17981","type":"journal-article","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T05:08:19Z","timestamp":1752642499000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["SynthRAD2025 Grand Challenge dataset: Generating synthetic CTs for radiotherapy from head to abdomen"],"prefix":"10.1002","volume":"52","author":[{"given":"Adrian","family":"Thummerer","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology LMU University Hospital  LMU Munich Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erik","family":"van der Bijl","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Radboud University Medical Center  Nijmegen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arthur Jr","family":"Galapon","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Kamp","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Cyberknife Center University Hospital of Cologne  Cologne Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Savenije","sequence":"additional","affiliation":[{"name":"Department of Radiotherapy University Medical Center Utrecht  Utrecht The Netherlands"},{"name":"Computational Imaging Group for MR Diagnostics &amp; Therapy University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Muijs","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shafak","family":"Aluwini","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roel J. 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M.","family":"Steenbakkers","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie","family":"Beuel","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Cyberknife Center University Hospital of Cologne  Cologne Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martijn PW","family":"Intven","sequence":"additional","affiliation":[{"name":"Department of Radiotherapy University Medical Center Utrecht  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes A.","family":"Langendijk","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Both","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University Medical Center Groningen University of Groningen  Groningen The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanie","family":"Corradini","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology LMU University Hospital  LMU Munich Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Viktor","family":"Rogowski","sequence":"additional","affiliation":[{"name":"Radiation Physics, Department of Hematology, Oncology, and Radiation Physics Sk\u00e5ne University Hospital  Lund Sweden"},{"name":"Medical Radiation Physics, Department of Clinical Sciences Lund Lund University  Lund Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maarten","family":"Terpstra","sequence":"additional","affiliation":[{"name":"Department of Radiotherapy University Medical Center Utrecht  Utrecht The Netherlands"},{"name":"Computational Imaging Group for MR Diagnostics &amp; 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