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However, the role of connectome architecture in shaping morphological alterations and identifying atrophy epicenters remains unclear. Furthermore, individualized modeling of atrophy epicenters and their potential clinical applications have not been well established. This study aims to explore how gray matter atrophy correlates with normal connectome architecture, identify potential atrophy epicenters, and employ individualized modeling approach to evaluate the impact of different epicenter patterns on surgical outcomes in patients with\n                      <jats:styled-content style=\"fixed-case\">TLE<\/jats:styled-content>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This study utilized anatomic\n                      <jats:styled-content style=\"fixed-case\">MRI<\/jats:styled-content>\n                      data from 126 refractory\n                      <jats:styled-content style=\"fixed-case\">TLE<\/jats:styled-content>\n                      patients who underwent anterior temporal lobectomy and 60 healthy controls (\n                      <jats:styled-content style=\"fixed-case\">HCs<\/jats:styled-content>\n                      ), along with normative functional and structural connectome data, to investigate the relationship between gray matter volume (\n                      <jats:styled-content style=\"fixed-case\">GMV<\/jats:styled-content>\n                      ) changes and functional or structural connectivity. Two models were employed to identify atrophy epicenters: a data\u2010driven approach evaluating nodal and neighbor atrophy rankings, and a network diffusion model (\n                      <jats:styled-content style=\"fixed-case\">NDM<\/jats:styled-content>\n                      ) simulating the spread of pathology from different seed regions. K\u2010means clustering was applied in patient\u2010tailored modeling to uncover distinct epicenter subtypes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Our findings indicate that the pattern of gray matter atrophy in\n                      <jats:styled-content style=\"fixed-case\">TLE<\/jats:styled-content>\n                      is constrained primarily by structural connectivity rather than by functional connectivity. Using the structural connectome, we pinpointed the hippocampus and adjacent temporo\u2010limbic regions as key atrophy epicenters. The patient\u2010tailored modeling revealed significant variability in epicenter distribution, allowing us to categorize them into two distinct subtypes. Notably, patients in subtype 2, with epicenters localized to the ipsilateral temporal pole and medial temporal lobe, exhibited significantly higher seizure\u2010free rates compared to patients in subtype 1, whose epicenters situated in frontocentral regions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Significance<\/jats:title>\n                    <jats:p>\n                      These findings highlight the central role of structural connectivity in shaping\n                      <jats:styled-content style=\"fixed-case\">TLE<\/jats:styled-content>\n                      \u2010related morphological changes. Individualized epicenter modeling may enhance surgical decisions and improve prognostic stratification in\n                      <jats:styled-content style=\"fixed-case\">TLE<\/jats:styled-content>\n                      management.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/epi.18343","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T07:04:39Z","timestamp":1741676679000},"page":"2053-2065","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Connectome architecture for gray matter atrophy and surgical outcomes in temporal lobe epilepsy"],"prefix":"10.1111","volume":"66","author":[{"given":"Qiuxing","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Neurology, West China Hospital Sichuan University  Chengdu Sichuan 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