{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T23:19:55Z","timestamp":1786231195256,"version":"build-2736575974"},"reference-count":41,"publisher":"IOP Publishing","issue":"9","license":[{"start":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T00:00:00Z","timestamp":1556755200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T00:00:00Z","timestamp":1556755200000},"content-version":"tdm","delay-in-days":1,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01-EB-017226"],"award-info":[{"award-number":["R01-EB-017226"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2019,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Percutaneous screw fixation in pelvic trauma surgery is a challenging procedure that often requires long fluoroscopic exposure times and trial-and-error insertion attempts along narrow bone corridors of the pelvis. We report a method to automatically plan surgical trajectories using preoperative CT and assist device placement by augmenting the fluoroscopic scene with planned trajectories.<\/jats:p>\n                  <jats:p>A pelvic shape atlas was formed from 40 CT images and used to construct a statistical shape model (SSM). Each member of the atlas included expert definition of volumetric regions representing safe trajectory within bone corridors for fixating 10 common fracture patterns. Patient-specific planning is obtained by mapping the SSM to the (un-segmented) patient CT via active shape model (ASM) registration and free-form deformation (FFD), and the resulting transformation is used to transfer the atlas trajectory volumes to the patient CT. Fluoroscopic images acquired during K-wire placement are in turn augmented with projection of the planned trajectories via 3D\u20132D registration. Registration performance was evaluated via leave-one-out cross-validation over the 40-member atlas, computing the root mean square error (RMSE) in pelvic surface alignment (volumetric registration error), the positive predicted value (PPV) of volumetric trajectories within bone corridors (safety of the automatically planned trajectories), and the distance between trajectories within the planned volume and the bone cortex (absence of breach). A cadaver study was conducted in which K-wires were placed under fluoroscopic guidance to validate 3D\u20132D registration accuracy and evaluate the potential utility of augmented fluoroscopy with planned trajectories.<\/jats:p>\n                  <jats:p>The leave-one-out cross-validation achieved surface RMSE of 2.2\u2009\u2009\u00b1\u2009\u20090.3\u2009mm after ASM registration and 1.8\u2009\u2009\u00b1\u2009\u20090.2\u2009mm after FFD refinement. Automatically determined surgical plans conformed within bone corridors with PPV\u2009\u2009&gt;\u2009\u200990% and centerline trajectory within 3\u20135\u2009mm of the bone cortex. 3D\u20132D registration in the cadaver study achieved 0.3\u2009\u2009\u00b1\u2009\u20090.8\u2009mm accuracy (in-plane translation) and\u2009\u2009&lt;4\u00b0 accuracy (in-plane rotation). Fluoroscopic images augmented with planning data exhibited\u2009\u2009&gt;90% conformance of volumetric planning data overlay within bone, and all centerline trajectories were within safe corridors.<\/jats:p>\n                  <jats:p>The approach yields a method for both automatic planning of pelvic fracture fixation and augmentation of fluoroscopy for improved surgical precision and safety. The method does not require segmentation of the patient CT, operates without additional hardware (e.g. tracking systems), and is consistent with common workflow in fluoroscopically guided procedures. The approach has the potential to reduce operating time and radiation dose by minimizing trial-and-error attempts in percutaneous screw placement.<\/jats:p>","DOI":"10.1088\/1361-6560\/ab1456","type":"journal-article","created":{"date-parts":[[2019,3,28]],"date-time":"2019-03-28T18:30:19Z","timestamp":1553797819000},"page":"095022","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":39,"title":["Atlas-based automatic planning and 3D\u20132D fluoroscopic guidance in pelvic trauma surgery"],"prefix":"10.1088","volume":"64","author":[{"given":"R","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3419-1805","authenticated-orcid":false,"given":"A","family":"Uneri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T","family":"De Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M","family":"Ketcha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J","family":"Goerres","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S","family":"Vogt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G","family":"Kleinszig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G","family":"Osgood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J H","family":"Siewerdsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2019,5,2]]},"reference":[{"key":"pmbab1456bib001","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1016\/j.neuroimage.2009.02.018","type":"journal-article","article-title":"Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy","volume":"46","author":"Aljabar","year":"2009","journal-title":"NeuroImage"},{"key":"pmbab1456bib002","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.1109\/TMI.2009.2014372","type":"journal-article","article-title":"Combination strategies in multi-atlas image segmentation: application to brain MR data","volume":"28","author":"Artaechevarria","year":"2009","journal-title":"IEEE Trans. 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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":"2018-12-05","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2019-03-28","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2019-05-02","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}