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Med. Biol."],"published-print":{"date-parts":[[2026,5,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Cardiotoxicity is a devastating complication of thoracic radiotherapy. However, current practice ignores the radiosensitivities and complex motion trajectories of individual substructures. Current imaging protocols in radiotherapy are insufficient to decouple and quantify cardiac motion, limiting substructure-specific motion considerations in treatment planning. We propose a 5D-MRI workflow for comprehensive substructure-specific motion analysis.\n                    <jats:italic>Approach.<\/jats:italic>\n                    Our 5D-MRI workflow was implemented in 10 healthy subjects (23\u201365 years) and two patients with lung cancer (67\u201369 years), with iterative reconstruction at end-exhale\/inhale and active-exhale\/inhale for end-systole\/diastole. For motion assessment, proximal coronary arteries, chambers, great vessels, and cardiac valves\/nodes were contoured across all images and verified. Centroid\/bounding box excursion was calculated for cardiac, respiratory, and hysteresis motion. Distance metrics were tested for statistical independence across substructure pairings. Three thoracic radiotherapy plans were retrospectively analyzed using volunteer-derived internal organ-at-risk volumes (IRVs). Cardiac substructure motion was compared between volunteer and patient cohorts.\n                    <jats:italic>Main results.<\/jats:italic>\n                    5D-MRI images were successfully acquired and contoured for all volunteers. Cardiac motion exceeded 1 cm for right-heart substructures and was greatest for the right coronary artery. Respiratory motion was largest for the inferior vena cava\/left ventricle. Respiratory hysteresis was generally &lt;5 mm but &gt;5 mm for some subjects. For cardiac motion, statistically significant differences were observed between coronary arteries\/chambers\/great vessels and between right\/left-sided substructures. Respiratory motion differed significantly between the heart base\/apex. For three plans, D\n                    <jats:sub>0.03cc<\/jats:sub>\n                    increased by up to 21.5 Gy across volunteer-derived cardiorespiratory IRVs. Patients\u2019 right-heart motion ranged from 7\u201319 mm, yet left-heart motion varied due to tumor location.\n                    <jats:italic>Significance.<\/jats:italic>\n                    Our 5D-MRI workflow successfully decouples cardiorespiratory motion in a \u223c5 min free-breathing acquisition. Cardiac motion was &gt;5 mm for coronary arteries\/chambers, while respiratory motion was &gt;5 mm for all substructures. Statistically significant differences were observed between cardiac substructures for cardiac and respiratory motion. The interplay between tumor location and motion magnitude affected substructure dose.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ae5752","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T22:53:34Z","timestamp":1774479214000},"page":"095007","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Deducing cardiorespiratory motion of cardiac substructures using a novel 5D-MRI workflow for radiotherapy"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2915-7970","authenticated-orcid":true,"given":"Chase","family":"Ruff","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tarun","family":"Naren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Wieben","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prashant","family":"Nagpal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin","family":"Johnson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiwei","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3279-6931","authenticated-orcid":true,"given":"Thomas","family":"Grist","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Baschnagel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7989-4382","authenticated-orcid":true,"given":"Carri","family":"Glide-Hurst","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2026,4,29]]},"reference":[{"key":"pmbae5752bib1","doi-asserted-by":"publisher","first-page":"3515","DOI":"10.1088\/0031-9155\/52\/12\/012","type":"journal-article","article-title":"Phase and amplitude binning for 4D-CT imaging","volume":"52","author":"Abdelnour","year":"2007","journal-title":"Phys. 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