{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T05:40:54Z","timestamp":1789105254761,"version":"build-2803163510"},"reference-count":27,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T00:00:00Z","timestamp":1668643200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To propose a novel magnetic field dose calculation method based on transformation from pencil beam (PB) to Monte Carlo (MC) distribution for MRI\u2010Linac online treatment planning.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The novel magnetic field dose calculation algorithm was established by a PB dose engine and a magnetic field with tissue inhomogeneity influence correction network. The correction network was constructed with a Res\u2010UNet framework, including residual modules and an encoding\u2013decoding path, by inputting three\u2010dimensional PB dose and patient electron density map, and outputting transformed dose distribution. The influences of magnetic fields and tissue heterogeneity were considered and corrected simultaneously in the correction model. A total of 110 clinically treated static beam IMRT plans were collected, including plans for brain, head\u2010and\u2010neck, lung, and rectum cases. A total of 90 cases were used and enhanced to train and validate the model, and the other 20 cases were for test. By comparing the proposed pipeline\u2010generated dose distribution with original input PB dose and corresponding MC dose, the feasibility and effectiveness of the method was evaluated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Results on both beam dose and plan dose accuracy comparisons on all investigated four tumor sites show great consistency between the cross\u2010dose\u2010engine transformation generations and the MC results, with averaged plan mean absolute error of 0.90%\u00a0\u00b1\u00a00.13% for the voxel\u2010wise dose difference and 98.33%\u00a0\u00b1\u00a01.07% gamma passing rate at the 2%\/2\u00a0mm criteria. The whole PB calculation and transformation process can be completed within second.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We have successfully developed a fast novel magnetic field dose calculation pipeline based on transformation from PB distribution to MC distribution for MRI\u2010Linac online treatment planning.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16077","type":"journal-article","created":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T06:54:28Z","timestamp":1667890468000},"page":"2429-2437","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Cross\u2010engine transformation\u2010based fast dose calculation for MRI\u2010Linac online treatment planning"],"prefix":"10.1002","volume":"50","author":[{"given":"Ting","family":"Song","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering Southern Medical University  Guangzhou Guangdong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linghong","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering Southern Medical University  Guangzhou Guangdong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongbao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Sun Yat\u2010sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou Guangdong 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