{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T04:29:14Z","timestamp":1790483354223,"version":"4.1.0"},"reference-count":58,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2012,12,18]],"date-time":"2012-12-18T00:00:00Z","timestamp":1355788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2015,9,1]],"date-time":"2015-09-01T00:00:00Z","timestamp":1441065600000},"content-version":"tdm","delay-in-days":987,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01\u2010CA\u2010127444"],"award-info":[{"award-number":["R01\u2010CA\u2010127444"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01-CA-127444"],"award-info":[{"award-number":["R01-CA-127444"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aip.org"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2013,1]]},"abstract":"<jats:sec><jats:title><jats:bold>Purpose:<\/jats:bold><\/jats:title><jats:p>Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (&lt;10 mm diameter) during surgery presents a major challenge that is likely to increase as more early\u2010stage disease is detected incidentally and in low\u2010dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT\u2010fluoroscopy), the authors propose the use of intraoperative cone\u2010beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video\u2010assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy.<\/jats:p><\/jats:sec><jats:sec><jats:title><jats:bold>Methods:<\/jats:bold><\/jats:title><jats:p>The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model\u2010driven stage followed by a finer image\u2010driven stage. The model\u2010driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image\u2010driven stage. The image\u2010driven stage employs an intensity\u2010corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT\u2010guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross\u2010correlation. Variations of the algorithm were investigated to study the behavior of the model\u2010 and image\u2010driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process.<\/jats:p><\/jats:sec><jats:sec><jats:title><jats:bold>Results:<\/jats:bold><\/jats:title><jats:p>The combined model\u2010 and image\u2010driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (\u223c3\u20135 mm within the target wedge) and critical structure avoidance (\u223c1\u20132 mm). The model\u2010driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image\u2010driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed.<\/jats:p><\/jats:sec><jats:sec><jats:title><jats:bold>Conclusions:<\/jats:bold><\/jats:title><jats:p>The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within \u223c1\u20132 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes<jats:italic>in vivo<\/jats:italic> testing, optimization of workflow, and integration with a CBCT image guidance system.<\/jats:p><\/jats:sec>","DOI":"10.1118\/1.4767757","type":"journal-article","created":{"date-parts":[[2012,12,18]],"date-time":"2012-12-18T23:55:59Z","timestamp":1355874959000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":35,"title":["Deformable registration of the inflated and deflated lung in cone\u2010beam CT\u2010guided thoracic surgery: Initial investigation of a combined model\u2010 and image\u2010driven approach"],"prefix":"10.1002","volume":"40","author":[{"given":"Ali","family":"Uneri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sajendra","family":"Nithiananthan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Schafer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshito","family":"Otake","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. 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