{"id":8389,"date":"2025-12-03T10:56:59","date_gmt":"2025-12-03T15:56:59","guid":{"rendered":"https:\/\/www.med.unc.edu\/radiology\/?p=8389"},"modified":"2025-12-03T10:56:59","modified_gmt":"2025-12-03T15:56:59","slug":"unc-radiology-researchers-harness-ai-to-overcome-long-standing-barriers-in-mapping-human-brain-circuitry","status":"publish","type":"post","link":"https:\/\/www.med.unc.edu\/radiology\/2025\/12\/unc-radiology-researchers-harness-ai-to-overcome-long-standing-barriers-in-mapping-human-brain-circuitry\/","title":{"rendered":"UNC Radiology Researchers Harness AI to Overcome Long-Standing Barriers in Mapping Human Brain Circuitry"},"content":{"rendered":"

Chapel Hill, N.C.<\/strong>\u00a0\u2014 A research team led by the University of North Carolina at Chapel Hill has unveiled a transformative new approach to mapping the brain\u2019s white matter pathways\u2014one that eliminates the need for diffusion MRI (dMRI), long considered essential for tractography.<\/p>\n

Published in\u00a0Nature Communications<\/em><\/a>, the study introduces\u00a0Anatomy-to-Tract Mapping (ATM)<\/strong>, a deep learning framework capable of reconstructing full white matter bundles using only standard T1-weighted structural MRI. This innovation could greatly expand access to high-quality brain connectivity mapping in both research and clinical settings, where diffusion imaging is often limited or unavailable.<\/p>\n

Traditionally, dMRI tractography relies on the propagation of streamlines guided by local fiber orientation estimates\u2014an approach that struggles in regions where multiple fiber populations cross, bend, or converge. High-quality diffusion data is also difficult to acquire, making robust tractography inaccessible for many clinical environments.<\/p>\n

ATM bypasses these challenges by learning the relationship between anatomical MRI features and known white matter pathways, generating anatomically plausible, subject-specific streamlines conditioned directly on a patient\u2019s structural MRI. The result: accurate reconstructions of 30 major white matter bundles\u2014without using any diffusion data.<\/p>\n

Notably, ATM performed well even on low-field and low-resolution clinical MRI scans, highlighting potential for real-world deployment in settings with limited imaging resources.<\/p>\n

The authors note that ATM marks a significant conceptual shift: the possibility that large-scale brain anatomy may contain more information about underlying white matter architecture than previously recognized. By leveraging structural MRI\u2014a fast, widely available, and distortion-free modality\u2014ATM opens the door to more accessible, individualized brain mapping.<\/p>\n

Future developments aim to integrate additional imaging contrasts, refine streamline quality, and adapt the method for atypical or pathological brain anatomies. As a flexible generative framework, ATM may ultimately support hybrid models that blend structural and diffusion data for even more powerful tractography.<\/p>\n

The study was supported by the National Institutes of Health.<\/p>\n

For more information, please contact:
\nPew-Thian Yap, PhD<\/strong>
\nDepartment of Radiology, UNC Chapel Hill<\/p>\n","protected":false},"excerpt":{"rendered":"

Chapel Hill, N.C.\u00a0\u2014 A research team led by the University of North Carolina at Chapel Hill has unveiled a transformative new approach to mapping the brain\u2019s white matter pathways\u2014one that eliminates the need for diffusion MRI (dMRI), long considered essential for tractography. Published in\u00a0Nature Communications, the study introduces\u00a0Anatomy-to-Tract Mapping (ATM), a deep learning framework capable … Read more<\/a><\/p>\n","protected":false},"author":83776,"featured_media":8390,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"layout":"","cellInformation":"","apiCallInformation":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[83,91,92],"tags":[],"class_list":["post-8389","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-department-news","category-homepage-news","category-in-the-news","odd"],"acf":[],"featured_image":"https:\/\/www.med.unc.edu\/radiology\/wp-content\/uploads\/sites\/1384\/2025\/12\/41467_2025_66615_Author.jpeg","featured_image_medium":"https:\/\/www.med.unc.edu\/radiology\/wp-content\/uploads\/sites\/1384\/2025\/12\/41467_2025_66615_Author-300x228.jpeg","featured_image_medium_large":"https:\/\/www.med.unc.edu\/radiology\/wp-content\/uploads\/sites\/1384\/2025\/12\/41467_2025_66615_Author.jpeg","featured_image_large":"https:\/\/www.med.unc.edu\/radiology\/wp-content\/uploads\/sites\/1384\/2025\/12\/41467_2025_66615_Author.jpeg","featured_image_thumbnail":"https:\/\/www.med.unc.edu\/radiology\/wp-content\/uploads\/sites\/1384\/2025\/12\/41467_2025_66615_Author-150x150.jpeg","featured_image_alt":"Colorful mapping of the brain.","category_details":[{"name":"Department News","link":"https:\/\/www.med.unc.edu\/radiology\/category\/department-news\/"},{"name":"Homepage News","link":"https:\/\/www.med.unc.edu\/radiology\/category\/homepage-news\/"},{"name":"IN THE NEWS","link":"https:\/\/www.med.unc.edu\/radiology\/category\/department-news\/in-the-news\/"}],"tag_details":[],"_links_to":[],"_links_to_target":[],"_links":{"self":[{"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/posts\/8389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/users\/83776"}],"replies":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/comments?post=8389"}],"version-history":[{"count":1,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/posts\/8389\/revisions"}],"predecessor-version":[{"id":8391,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/posts\/8389\/revisions\/8391"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/media\/8390"}],"wp:attachment":[{"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/media?parent=8389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/categories?post=8389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.med.unc.edu\/radiology\/wp-json\/wp\/v2\/tags?post=8389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}