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Oncol."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To evaluate the accuracy and efficiency of Artificial-Intelligence (AI) segmentation in Total Marrow Irradiation (TMI) including contours throughout the head and neck (H&amp;amp;N), thorax, abdomen, and pelvis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>An AI segmentation software was clinically introduced for total body contouring in TMI including 27 organs at risk (OARs) and 4 planning target volumes (PTVs). This work compares the clinically utilized contours to the AI-TMI contours for 21 patients. Structure and image dicom data was used to generate comparisons including volumetric, spatial, and dosimetric variations between the AI- and human-edited contour sets. Conventional volume and surface measures including the S\u00f8rensen\u2013Dice coefficient (Dice) and the 95<jats:sup>th<\/jats:sup>% Hausdorff Distance (HD95) were used, and novel efficiency metrics were introduced. The clinical efficiency gains were estimated by the percentage of the AI-contour-surface within 1mm of the clinical contour surface. An unedited AI-contour has an efficiency gain=100%, an AI-contour with 70% of its surface&amp;lt;1mm from a clinical contour has an efficiency gain of 70%. The dosimetric deviations were estimated from the clinical dose distribution to compute the dose volume histogram (DVH) for all structures.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 467 contours were compared in the 21 patients. In PTVs, contour surfaces deviated by &amp;gt;1mm in 38.6% \u00b1 23.1% of structures, an average efficiency gain of 61.4%. Deviations &amp;gt;5mm were detected in 12.0% \u00b1 21.3% of the PTV contours. In OARs, deviations &amp;gt;1mm were detected in 24.4% \u00b1 27.1% of the structure surfaces and &amp;gt;5mm in 7.2% \u00b1 18.0%; an average clinical efficiency gain of 75.6%. In H&amp;amp;N OARs, efficiency gains ranged from 42% in optic chiasm to 100% in eyes (unedited in all cases). In thorax, average efficiency gains were &amp;gt;80% in spinal cord, heart, and both lungs. Efficiency gains ranged from 60-70% in spleen, stomach, rectum, and bowel and 75-84% in liver, kidney, and bladder. DVH differences exceeded 0.05 in 109\/467 curves at any dose level. The most common 5%-DVH variations were in esophagus (86%), rectum (48%), and PTVs (22%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>AI auto-segmentation software offers a powerful solution for enhanced efficiency in TMI treatment planning. Whole body segmentation including PTVs and normal organs was successful based on spatial and dosimetric comparison.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fonc.2022.970425","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T05:19:18Z","timestamp":1661836758000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Auto-segmentation for total marrow irradiation"],"prefix":"10.3389","volume":"12","author":[{"given":"William 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