{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T22:11:59Z","timestamp":1791756719867,"version":"4.3.4"},"reference-count":45,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,12,6]],"date-time":"2023-12-06T00:00:00Z","timestamp":1701820800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Image\u2010guided radiation\u2010therapy (IGRT)\u2010based robotic radiosurgery using magnetic resonance imaging (MRI)\u2010only simulation could allow for improved target definition with highly conformal radiotherapy treatments. Fiducial marker (FM)\u2010based alignment is used with robotic radiosurgery treatments of sites such as the prostate because it aids in accurate target localization. Synthetic CT (sCT) images are generated in the MRI\u2010only workflow but FMs used for IGRT appear as signal voids in MRIs and do not appear in MR\u2010generated sCTs, hindering the ability to use sCTs for fiducial\u2010based IGRT.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>In this study we evaluate the fiducial tracking accuracy for a novel artificial fiducial insertion method in sCT images that allows for fiducial marker tracking in robotic radiosurgery, using MRI\u2010only simulation imaging (MRI\u2010only workflow).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Artificial fiducial markers were inserted into sCT images at the site of the real marker implantation as visible in MRI. Two phantoms were used in this study. A custom anthropomorphic pelvis phantom was designed to validate the tracking accuracy for a variety of artificial fiducials in an MRI\u2010only workflow. A head phantom containing a hidden target and orthogonal film pair inserts was used to perform end\u2010to\u2010end tests of artificial fiducial configurations inserted in sCT images. The setup and end\u2010to\u2010end targeting accuracy of the MRI\u2010only workflow were compared to the computed tomography (CT)\u2010based standard. Each phantom had six FMs implanted with a minimum spacing of 2\u00a0cm. For each phantom a bulk\u2010density sCT was generated, and artificial FMs were inserted at the implantation location. Several methods of FM insertion were tested including: (1) replacing HU with a fixed value (10000HU) (voxel\u2010burned); (2) using a representative fiducial image derived from a linear combination of fiducial templates (composite\u2010fiducial); (3) computationally simulating FM signal voids using a digital phantom containing FMs and inserting the corresponding signal void into sCT images (simulated\u2010fiducial). All tests were performed on a CyberKnife system (Accuray, Sunnyvale, CA). Treatment plans and digital\u2010reconstructed\u2010radiographs were generated from the original CT and sCTs with embedded fiducials and used to align the phantom on the treatment couch. Differences in the initial phantom alignment (3D translations\/rotations) and tracking parameters between CT\u2010based plans and sCT\u2010based plans were analyzed. End\u2010to\u2010end plans for both scenarios were generated and analyzed following our clinical protocol.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>For all plans, the fiducial tracking algorithm was able to identify the fiducial locations. The mean FM\u2010extraction uncertainty for the composite and simulated FMs was below 48% for fiducials in both the anthropomorphic pelvis and end\u2010to\u2010end phantoms, which is below the 70% treatment uncertainty threshold. The total targeting error was within tolerance (&lt;0.95\u00a0mm) for end\u2010to\u2010end tests of sCT images with the composite and head\u2010on simulated FMs (0.26, 0.44, and 0.35\u00a0mm for the composite fiducial in sCT, head\u2010on simulated fiducial in sCT, and fiducials in original CT, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>MRI\u2010only simulation for robotic radiosurgery could potentially improve treatment accuracy and reduce planning margins. Our study has shown that using a composite\u2010derived or simulated FM in conjunction with sCT images, MRI\u2010only workflow can provide clinically acceptable setup accuracy in line with CT\u2010based standards for FM\u2010based robotic radiosurgery.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16857","type":"journal-article","created":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T02:20:08Z","timestamp":1701915608000},"page":"31-41","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["End\u2010to\u2010end validation of fiducial tracking accuracy in robotic radiosurgery using MRI\u2010only simulation imaging"],"prefix":"10.1002","volume":"51","author":[{"given":"Kamal","family":"Singhrao","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Brigham and Women's Hospital Dana\u2010Farber Cancer Institute and Harvard Medical School  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Zubair","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University of California  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomi","family":"Nano","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University of California  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica E.","family":"Scholey","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University of California  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Descovich","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University of California  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,12,6]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/60\/22\/R323"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014\u2010014\u20100309\u20100"},{"key":"e_1_2_8_4_1","unstructured":"Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation optimization and quality assurance\u2014Glide\u2010Hurst \u2010 2021 \u2010 Medical Physics\u2014Wiley Online Library. 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