{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T12:45:18Z","timestamp":1786193118753,"version":"build-2736575974"},"reference-count":19,"publisher":"IOP Publishing","issue":"16","license":[{"start":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T00:00:00Z","timestamp":1597363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T00:00:00Z","timestamp":1597363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"National Institutes of Health (NIH)\/National Institute for Dental and Craniofacial Research","award":["1R01DE025248-01\/R56DE025248-01"],"award-info":[{"award-number":["1R01DE025248-01\/R56DE025248-01"]}]},{"name":"NIH\/NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program","award":["1R01CA218148-01"],"award-info":[{"award-number":["1R01CA218148-01"]}]},{"DOI":"10.13039\/100012287","name":"Andrew Sabin Family Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100012287","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Cancer center Support Grant Radiation Oncology\/Cancer Imaging Program Seed Grant","award":["5P30CA016672"],"award-info":[{"award-number":["5P30CA016672"]}]},{"DOI":"10.13039\/100011676","name":"Elekta AB","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100011676","id-type":"DOI","asserted-by":"crossref"}]},{"name":"NIH\/National Cancer Institute (NCI) Head and Neck Specialized Programs of Research Excellence (SPORE) Developmental Research Program Award","award":["P50CA097007-10"],"award-info":[{"award-number":["P50CA097007-10"]}]},{"name":"Pau l Calabresi Clinical Oncology Program Award","award":["K12 CA088084-06"],"award-info":[{"award-number":["K12 CA088084-06"]}]},{"name":"RaySearch Laboratories"},{"name":"National Science Foundation (NSF), Division of Mathematical Sciences, Joint NIH\/NSF Initiative on Quantitative Approaches to Biomedical Big Data (QuBBD) Grant","award":["NSF 1557679"],"award-info":[{"award-number":["NSF 1557679"]}]},{"name":"NIH\/NCI CCSG","award":["Grant P30CA016672"],"award-info":[{"award-number":["Grant P30CA016672"]}]},{"name":"Helen Black Image Guided Cancer Therapy Fund"},{"name":"NIH Big Data to Knowledge (BD2K) Program of the National Cancer Institute (NCI) Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science Award","award":["1R01CA214825-01"],"award-info":[{"award-number":["1R01CA214825-01"]}]},{"name":"Image Guided Cancer Therapy Research Program at The University of Texas MD Anderson Cancer Center"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2020,8,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Purpose.<\/jats:italic>\n                    Early animal studies suggest that parotid gland (PG) toxicity prediction could be improved by an accurate estimation of the radiation dose to sub-regions of the PG. Translation to clinical investigation requires voxel-level dose accumulation in this organ that responds volumetrically throughout treatment. To date, deformable image registration (DIR) has been evaluated for the PG using only surface alignment. We sought to develop and evaluate an advanced DIR technique capable of modeling these complex PG volume changes over the course of radiation therapy.\n                    <jats:italic>Materials and methods.<\/jats:italic>\n                    Planning and mid-treatment magnetic resonance images from 19 patients and computed tomography images from nine patients who underwent radiation therapy for head and neck cancer were retrospectively evaluated. A finite element model (FEM)-based DIR algorithm was applied between the corresponding pairs of images, based on boundary conditions on the PG surfaces only (Morfeus-spatial). To investigate an anticipated improvement in accuracy, we added a population model-based thermal expansion coefficient to simulate the dose distribution effect on the volume change inside the glands (Morfeus-spatialDose). The model accuracy was quantified using target registration error for magnetic resonance images, where corresponding anatomical landmarks could be identified. The potential clinical impact was evaluated using differences in mean dose, median dose, D98, and D50 of the PGs.\n                    <jats:italic>Results.<\/jats:italic>\n                    In the magnetic resonance images, the mean (\u00b1standard deviation) target registration error significantly reduced by 0.25 \u00b1 0.38 mm (p = 0.01) when using Morfeus-spatialDose instead of Morfeus-spatial. In the computed tomography images, differences in the mean dose, median dose, D98, and D50 of the PGs reached 2.9 \u00b1 0.8, 3.8, 4.1, and 3.8 Gy, respectively, between Morfeus-spatial and Morfeus-spatialDose.\n                    <jats:italic>Conclusion.<\/jats:italic>\n                    Differences between Morfeus-spatial and Morfeus-spatialDose may be impactful when considering high-dose gradients of radiation in the PGs. The proposed DIR model can allow more accurate PG alignment than the standard model and improve dose estimation and toxicity prediction modeling.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ab8bf1","type":"journal-article","created":{"date-parts":[[2020,4,22]],"date-time":"2020-04-22T18:15:28Z","timestamp":1587579328000},"page":"165017","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Biomechanical modeling of radiation dose-induced volumetric changes of the parotid glands for deformable image registration"],"prefix":"10.1088","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7531-1263","authenticated-orcid":false,"given":"Molly M","family":"McCulloch","sequence":"first","affiliation":[{"name":"The University of Texas MD Anderson Cancer Center"},{"name":"School of Medicine, Oregon Health and Science 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2019-12-23","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2020-04-22","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2020-08-14","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}