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The Mann\u2013Whitney\n                      <jats:italic>U<\/jats:italic>\n                      test compared the intratumoral susceptibility signals (ITSS) grade across molecular markers, with ITSS defined as fine linear or dot-like low signal areas on SWI. Predictive efficacy was assessed using receiver operating characteristic (ROC) analysis and multivariate logistic regression models. Path analysis evaluated the relationships between ITSS grade and molecular markers.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Gliomas with high ITSS grade showed higher histological grade, Ki-67 LI, and TERT mutation rates compared to those with low ITSS grade, mostly being wild-type gliomas. ITSS grade predicted the histological grade, Ki-67 LI, and TERT status (area under the ROC curve = 0.769\u20120.817). Multivariate logistic regression analysis identified Ki-67 LI and TERT status as independent predictors of high ITSS grade. Path analysis indicated direct effects of Ki-67 LI and TERT mutation on ITSS grade, and an indirect effect of IDH1 mutation on ITSS grade mediated through Ki-67 LI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>7-T SWI-derived ITSS grade predicts histologic grade, Ki-67 LI, and TERT promoter mutation status in gliomas. Ki-67 LI and TERT mutation exert relatively independent effects on ITSS grade and allow reverse inference of their status from SWI, whereas IDH1 mutation influences ITSS grade indirectly via Ki-67 LI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Relevance statement<\/jats:title>\n                    <jats:p>\n                      This study establishes a connection between preoperative imaging and molecular glioma pathology via 7-T SWI. It helps to reveal the\n                      <jats:italic>in vivo<\/jats:italic>\n                      characteristics of pathology and promotes collaboration among radiologists, pathologists, and clinicians, which a great clinical potential.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>A 7-T susceptibility-weighted MRI\u2013based intratumoral susceptibility signal (ITSS) grading system enables precise detection of glioma microbleeds and neovascularization.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>7-T susceptibility-weighted MRI\u2013derived ITSS grade noninvasively predicts histologic grade, Ki-67 labeling index, and telomerase reverse transcriptase (TERT) promoter mutation status in gliomas.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Path analysis suggested that molecular markers relate to ITSS grade through distinct pathways, with Ki-67 and TERT exerting direct effects and isocitrate dehydrogenase 1 influencing ITSS grade indirectly.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1186\/s41747-026-00696-0","type":"journal-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T10:20:52Z","timestamp":1775125252000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["7-T MRI intratumoral susceptibility signals reflect biomarker status in gliomas"],"prefix":"10.1186","volume":"10","author":[{"given":"Fengwei","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zilong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suyi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaodong","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiafei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhentao","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiming","family":"Zhen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6829-9067","authenticated-orcid":false,"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,2]]},"reference":[{"key":"696_CR1","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","volume":"23","author":"DN Louis","year":"2021","unstructured":"Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. 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