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Strategies for enhancing delivery efficiency on MR-Linac: A dosimetric study and historical plan review.

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Title: Strategies for enhancing delivery efficiency on MR-Linac: A dosimetric study and historical plan review.
Authors: Zhang Y; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Tang S; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Kabat C; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Visak J; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Chiu T; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Li R; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Jiang S; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA., Lin MH; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.
Source: Journal of applied clinical medical physics [J Appl Clin Med Phys] 2026 May; Vol. 27 (5), pp. e70638.
Publication Type: Journal Article
Journal Info: Publisher: Wiley on behalf of American Association of Physicists in Medicine Country of Publication: United States NLM ID: 101089176 Publication Model: Print Cited Medium: Internet ISSN: 1526-9914 (Electronic) Linking ISSN: 15269914 NLM ISO Abbreviation: J Appl Clin Med Phys Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Zhang+Y%22">Zhang Y</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Tang+S%22">Tang S</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Kabat+C%22">Kabat C</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Visak+J%22">Visak J</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Chiu+T%22">Chiu T</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Li+R%22">Li R</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Jiang+S%22">Jiang S</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Lin+MH%22">Lin MH</searchLink>; Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas, USA.
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        Value: 10.1002/acm2.70638
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      – TitleFull: Strategies for enhancing delivery efficiency on MR-Linac: A dosimetric study and historical plan review.
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            – D: 01
              M: 05
              Text: 2026 May
              Type: published
              Y: 2026
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