{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T18:10:16Z","timestamp":1792692616614,"version":"4.5.0"},"reference-count":21,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"3","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>CT and MRI are synergistic in the information provided for neurosurgical planning. While obtaining both types of images lends unique data from each, doing so adds to cost and exposes patients to additional ionizing radiation after MRI has been performed. Cross-modal synthesis of high-resolution CT images from MRI sequences offers an appealing solution. The authors therefore sought to develop a deep learning conditional generative adversarial network (cGAN) which performs this synthesis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>Preoperative paired CT and contrast-enhanced MR images were collected for patients with meningioma, pituitary tumor, vestibular schwannoma, and cerebrovascular disease. CT and MR images were denoised, field corrected, and coregistered. MR images were fed to a cGAN that exported a \"synthetic\" CT scan. The accuracy of synthetic CT images was assessed objectively using the quantitative similarity metrics as well as by clinical features such as sella and internal auditory canal (IAC) dimensions and mastoid\/clinoid\/sphenoid aeration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>A total of 92,981 paired CT\/MR images obtained in 80 patients were used for training\/testing, and 10,068 paired images from 10 patients were used for external validation. Synthetic CT images reconstructed the bony skull base and convexity with relatively high accuracy. Measurements of the sella and IAC showed a median relative error between synthetic CT scans and ground truth images of 6%, with greater variability in IAC reconstruction compared with the sella. Aerations in the mastoid, clinoid, and sphenoid regions were generally captured, although there was heterogeneity in finer air cell septations. Performance varied based on pathology studied, with the highest limitation observed in evaluating meningiomas with intratumoral calcifications or calvarial invasion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>The generation of high-resolution CT scans from MR images through cGAN offers promise for a wide range of applications in cranial and spinal neurosurgery, especially as an adjunct for preoperative evaluation. Optimizing cGAN performance on specific anatomical regions may increase its clinical viability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3171\/2024.1.jns232196","type":"journal-article","created":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T20:40:51Z","timestamp":1712349651000},"page":"742-751","source":"Crossref","is-referenced-by-count":12,"title":["Generation and applications of synthetic computed tomography images for neurosurgical planning"],"prefix":"10.3171","volume":"141","author":[{"given":"Yiheng","family":"Tan","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"},{"name":"Department of Radiology, University Medical Center Groningen, University of Groningen, The Netherlands;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruchit V.","family":"Patel","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongming","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Computer Science, Guangdong University of Technology, Guangzhou, China; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinping","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Luo","sequence":"additional","affiliation":[{"name":"Radiology, Brigham and Women\u2019s Hospital, Harvard Medical School, Boston, Massachusetts;"},{"name":"Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenli","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhigang","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymond Y.","family":"Huang","sequence":"additional","affiliation":[{"name":"Radiology, Brigham and Women\u2019s Hospital, Harvard Medical School, Boston, Massachusetts;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haijun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenya Linda","family":"Bi","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shun","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Center for Pituitary Tumor Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;"},{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1754","reference":[{"issue":"1","key":"b1","series-title":"Nat Preceed","first-page":"1","article-title":"The history, development and impact of computed imaging in neurological diagnosis and neurosurgery: CT, MRI, and DTI","volume":"7","author":"Filler AG","year":"2010","unstructured":"Filler AG. 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MAGMA. 2022;35(3):449\u2013457."}],"container-title":["Journal of Neurosurgery"],"original-title":[],"link":[{"URL":"https:\/\/thejns.org\/view\/journals\/j-neurosurg\/141\/3\/article-p742.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/thejns.org\/downloadpdf\/journals\/j-neurosurg\/141\/3\/article-p742.xml","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/thejns.org\/downloadpdf\/journals\/j-neurosurg\/141\/3\/article-p742.xml","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T06:42:41Z","timestamp":1732603361000},"score":1,"resource":{"primary":{"URL":"https:\/\/thejns.org\/view\/journals\/j-neurosurg\/141\/3\/article-p742.xml"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,1]]},"references-count":21,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3171\/2024.1.jns232196","relation":{},"ISSN":["0022-3085","1933-0693"],"issn-type":[{"value":"0022-3085","type":"print"},{"value":"1933-0693","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,1]]}}}