{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T01:42:56Z","timestamp":1790646176209,"version":"4.1.0"},"reference-count":28,"publisher":"IOP Publishing","issue":"14","license":[{"start":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T00:00:00Z","timestamp":1688515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T00:00:00Z","timestamp":1688515200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003246","name":"Dutch Research Council","doi-asserted-by":"crossref","award":["project no. 19484 (MEGAHERTZ)"],"award-info":[{"award-number":["project no. 19484 (MEGAHERTZ)"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"crossref"}]},{"name":"ITEA","award":["SIGNET project no. 20052"],"award-info":[{"award-number":["SIGNET project no. 20052"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2023,7,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    The high speed of cardiorespiratory motion introduces a unique challenge for cardiac stereotactic radio-ablation (STAR) treatments with the MR-linac. Such treatments require tracking myocardial landmarks with a maximum latency of 100 ms, which includes the acquisition of the required data. The aim of this study is to present a new method that allows to track myocardial landmarks from few readouts of MRI data, thereby achieving a latency sufficient for STAR treatments.\n                    <jats:italic>Approach.<\/jats:italic>\n                    We present a tracking framework that requires only few readouts of k-space data as input, which can be acquired at least an order of magnitude faster than MR-images. Combined with the real-time tracking speed of a probabilistic machine learning framework called Gaussian Processes, this allows to track myocardial landmarks with a sufficiently low latency for cardiac STAR guidance, including both the acquisition of required data, and the tracking inference.\n                    <jats:italic>Main results.<\/jats:italic>\n                    The framework is demonstrated in 2D on a motion phantom, and\n                    <jats:italic>in vivo<\/jats:italic>\n                    on volunteers and a ventricular tachycardia (arrhythmia) patient. Moreover, the feasibility of an extension to 3D was demonstrated by\n                    <jats:italic>in silico<\/jats:italic>\n                    3D experiments with a digital motion phantom. The framework was compared with template matching\u2014a reference, image-based, method\u2014and linear regression methods. Results indicate an order of magnitude lower total latency (&lt;10 ms) for the proposed framework in comparison with alternative methods. The root-mean-square-distances and mean end-point-distance with the reference tracking method was less than 0.8 mm for all experiments, showing excellent (sub-voxel) agreement.\n                    <jats:italic>Significance.<\/jats:italic>\n                    The high accuracy in combination with a total latency of less than 10 ms\u2014including data acquisition and processing\u2014make the proposed method a suitable candidate for tracking during STAR treatments. Additionally, the probabilistic nature of the Gaussian Processes also gives access to real-time prediction uncertainties, which could prove useful for real-time quality assurance during treatments.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ace023","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T18:43:21Z","timestamp":1687286601000},"page":"145001","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Real-time myocardial landmark tracking for MRI-guided cardiac radio-ablation using Gaussian Processes"],"prefix":"10.1088","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1558-1827","authenticated-orcid":false,"given":"Niek R F","family":"Huttinga","sequence":"first","affiliation":[{"name":"University Medical Center Utrecht"},{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4730-7635","authenticated-orcid":false,"given":"Osman","family":"Akdag","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9107-4627","authenticated-orcid":false,"given":"Martin F","family":"Fast","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9673-0793","authenticated-orcid":false,"given":"Joost J C","family":"Verhoeff","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2536-9384","authenticated-orcid":false,"given":"Firdaus A A","family":"Mohamed Hoesein","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5565-6889","authenticated-orcid":false,"given":"Cornelis A T","family":"van den Berg","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"},{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3276-4542","authenticated-orcid":false,"given":"Alessandro","family":"Sbrizzi","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"},{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4612-5509","authenticated-orcid":false,"given":"Stefano","family":"Mandija","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht"},{"name":"University Medical Center Utrecht"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2023,7,5]]},"reference":[{"key":"pmbace023bib1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.phro.2022.02.017","type":"journal-article","article-title":"Feasibility of cardiac-synchronized quantitative T1 and T2 mapping on a hybrid 1.5 Tesla magnetic resonance imaging and linear accelerator system","volume":"21","author":"Akdag","year":"2022b","journal-title":"Phys. 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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":"2023-02-17","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-06-20","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-07-05","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}