{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T12:12:10Z","timestamp":1776082330116,"version":"3.50.1"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T00:00:00Z","timestamp":1765843200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100023048","name":"International Council of Shopping Centers","doi-asserted-by":"publisher","award":["CN00000013 \\u2013 CUP I53C21000340006"],"award-info":[{"award-number":["CN00000013 \\u2013 CUP I53C21000340006"]}],"id":[{"id":"10.13039\/100023048","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004007","name":"Instituto Nazionale di Fisica Nucleare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004007","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","phiro.science","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physics and Imaging in Radiation Oncology"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.phro.2025.100893","type":"journal-article","created":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T00:33:02Z","timestamp":1765931582000},"page":"100893","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Optimizing thoracic synthetic computed tomography generation from magnetic resonance imaging: the role of Fourier transform and other key factors"],"prefix":"10.1016","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7225-3355","authenticated-orcid":false,"given":"Alessandro","family":"Bombini","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Vellini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Flaviovincenzo","family":"Quaranta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacopo","family":"Lenkowicz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sebastiano","family":"Menna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elisa","family":"Pilloni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Catucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"D\u2019Aviero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Claudio","family":"Votta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuditta","family":"Chiloiro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martina","family":"Iezzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Preziosi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessia","family":"Re","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Althea","family":"Boschetti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Floranna","family":"Mauro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sami","family":"Aburas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lana","family":"Smiljanic","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2361-9327","authenticated-orcid":false,"given":"Antonio","family":"Piras","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmela","family":"Di Dio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenzo","family":"Placidi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Boldrini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria Antonietta","family":"Gambacorta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gian Carlo","family":"Mattiucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Davide","family":"Cusumano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.phro.2025.100893_b0005","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.semradonc.2023.10.013","article-title":"MRI-guided adaptive radiation therapy","volume":"34","author":"Benitez","year":"2024","journal-title":"Semin Radiat Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0010","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.ejmp.2021.05.010","article-title":"Artificial intelligence in magnetic resonance guided radiotherapy: medical and physical considerations on state of art and future perspectives","volume":"85","author":"Cusumano","year":"2021","journal-title":"Phys Med"},{"key":"10.1016\/j.phro.2025.100893_b0015","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.ijrobp.2015.10.015","article-title":"Online magnetic resonance image guided adaptive radiation therapy: first clinical applications","volume":"94","author":"Acharya","year":"2016","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.phro.2025.100893_b0020","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.ijrobp.2019.06.2530","article-title":"A systematic review of the clinical implementation of pelvic magnetic resonance imaging-only planning for external beam radiation therapy","volume":"105","author":"Bird","year":"2019","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.phro.2025.100893_b0025","first-page":"28","article-title":"Current and future developments of synthetic computed tomography generation for radiotherapy. Phys Imaging","author":"van Elmpt","year":"2023","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0030","doi-asserted-by":"crossref","unstructured":"Isola P, Zhu J-Y, Zhou T, Efros AA. Image-to-image translation with conditional adversarial networks. 2018.","DOI":"10.1109\/CVPR.2017.632"},{"key":"10.1016\/j.phro.2025.100893_b0035","doi-asserted-by":"crossref","first-page":"6557","DOI":"10.1118\/1.4967480","article-title":"Dosimetric characterization of MRI-only treatment planning for brain tumors in atlas-based pseudo-CT images generated from standard T1-weighted MR images","volume":"43","author":"Demol","year":"2016","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2025.100893_b0040","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/s11547-019-01090-0","article-title":"On the accuracy of bulk synthetic CT for MR-guided online adaptive radiotherapy","volume":"125","author":"Cusumano","year":"2020","journal-title":"Radiol Med"},{"key":"10.1016\/j.phro.2025.100893_b0045","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.prro.2014.12.005","article-title":"Magnetic resonance imaging-based treatment planning for prostate cancer: use of population average tissue densities within the irradiated volume to improve plan accuracy","volume":"5","author":"Hu","year":"2015","journal-title":"Pract Radiat Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0050","first-page":"9","article-title":"Generation of synthetic CT images from MRI for treatment planning and patient positioning using a 3-channel U-net trained on sagittal images","author":"Gupta","year":"2019","journal-title":"Front Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0055","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1186\/s13014-023-02336-y","article-title":"Comparison of four synthetic CT generators for brain and prostate MR-only workflow in radiotherapy","volume":"18","author":"Autret","year":"2023","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0060","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.radonc.2020.11.027","article-title":"Multicentre, deep learning, synthetic-CT generation for ano-rectal MR-only radiotherapy treatment planning","volume":"156","author":"Bird","year":"2021","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0065","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1002\/mp.12155","article-title":"MR-based synthetic CT generation using a deep convolutional neural network method","volume":"44","author":"Han","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2025.100893_b0070","doi-asserted-by":"crossref","DOI":"10.1002\/acm2.13838","article-title":"Evaluation of MRI-only based online adaptive radiotherapy of abdominal region on MR-linac","volume":"24","author":"Nousiainen","year":"2023","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.phro.2025.100893_b0075","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.ejmp.2021.07.027","article-title":"Deep learning methods to generate synthetic CT from MRI in radiotherapy: a literature review","volume":"89","author":"Boulanger","year":"2021","journal-title":"Phys Med"},{"key":"10.1016\/j.phro.2025.100893_b0080","doi-asserted-by":"crossref","first-page":"689","DOI":"10.21037\/tlcr.2017.09.02","article-title":"Magnetic resonance imaging in precision radiation therapy for lung cancer","volume":"6","author":"Bainbridge","year":"2017","journal-title":"Transl Lung Cancer Res"},{"key":"10.1016\/j.phro.2025.100893_b0085","doi-asserted-by":"crossref","first-page":"3437","DOI":"10.1002\/mp.12267","article-title":"Technical note: is bulk electron density assignment appropriate for MRI-only based treatment planning for lung cancer?","volume":"44","author":"Prior","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2025.100893_b0090","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.ejmp.2018.08.007","article-title":"Experimental evaluation of the impact of low tesla transverse magnetic field on dose distribution in presence of tissue interfaces","volume":"53","author":"Cusumano","year":"2018","journal-title":"Phys Med"},{"key":"10.1016\/j.phro.2025.100893_b0095","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1088\/0031-9155\/50\/7\/002","article-title":"Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose increase at tissue-air interfaces in a lateral magnetic field due to returning electrons","volume":"50","author":"Raaijmakers","year":"2005","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.phro.2025.100893_b0100","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.radonc.2022.08.028","article-title":"A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases","volume":"176","author":"Lenkowicz","year":"2022","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0105","unstructured":"Guibas J, Mardani M, Li Z, Tao A, Anandkumar A, Catanzaro B. Adaptive Fourier neural operators: efficient token mixers for transformers. 2022. doi:10.48550\/arXiv.2111.13587."},{"key":"10.1016\/j.phro.2025.100893_b0110","doi-asserted-by":"crossref","first-page":"5828","DOI":"10.1118\/1.4930249","article-title":"Characterization of the onboard imaging unit for the first clinical magnetic resonance image guided radiation therapy system","volume":"42","author":"Hu","year":"2015","journal-title":"Med Phys"},{"key":"10.1016\/j.phro.2025.100893_b0115","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2024.110387","article-title":"Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy","volume":"198","author":"Villegas","year":"2024","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0120","unstructured":"Taylor J. Introduction to error analysis, the study of uncertainties in physical measurements, 2nd ed. 1997."},{"key":"10.1016\/j.phro.2025.100893_b0125","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2024.1294252","article-title":"Impact of bias field correction on 0.35 T pelvic MR images: evaluation on generative adversarial network-based OARs\u2019 auto-segmentation and visual grading assessment","volume":"14","author":"Vagni","year":"2024","journal-title":"Front Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0130","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.ejmp.2021.09.006","article-title":"Comparison of different deep learning architectures for synthetic CT generation from MR images","volume":"90","author":"Bahrami","year":"2021","journal-title":"Phys Med"},{"key":"10.1016\/j.phro.2025.100893_b0135","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.radonc.2020.10.018","article-title":"A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases","volume":"153","author":"Cusumano","year":"2020","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0140","article-title":"A deep learning algorithm to generate synthetic computed tomography images for brain treatments from 0.35 T magnetic resonance imaging","volume":"33","author":"Vellini","year":"2025","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.phro.2025.100893_b0145","doi-asserted-by":"crossref","DOI":"10.1002\/mp.18038","article-title":"A comprehensive comparative study of generative adversarial network architectures for synthetic computed tomography generation in the abdomen","volume":"52","author":"Lapaeva","year":"2025","journal-title":"Med Phys"}],"container-title":["Physics and Imaging in Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631625001988?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631625001988?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:36:56Z","timestamp":1776080216000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405631625001988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":29,"alternative-id":["S2405631625001988"],"URL":"https:\/\/doi.org\/10.1016\/j.phro.2025.100893","relation":{},"ISSN":["2405-6316"],"issn-type":[{"value":"2405-6316","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Optimizing thoracic synthetic computed tomography generation from magnetic resonance imaging: the role of Fourier transform and other key factors","name":"articletitle","label":"Article Title"},{"value":"Physics and Imaging in Radiation Oncology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.phro.2025.100893","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.","name":"copyright","label":"Copyright"}],"article-number":"100893"}}