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While recent data suggest that necrotic tissue plays an active role in glioblastoma growth, the prognostic relevance of necrosis imaging remains understudied. This study evaluated necrotic tissue on MRI to identify a prognostic morphological signature and characterize its underlying biological characteristics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>82 patients with glioblastoma imaged after chemoradiation were retrospectively analyzed. A combination of two shape features (volume density and surface-to-volume ratio) was used to define prognostic necrosis phenotypes (low- vs. high-risk). The association between necrosis phenotypes and survival was tested with log-rank and multivariable Cox models adjusting for other prognostic variables. Diffusion, perfusion, and pH-weighted MRI were used to biologically characterize the two groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The low-risk necrosis phenotype was more compact (not spatially dispersed), with smoother margins and fewer fragmentations. Patients with this phenotype had an almost three-fold lower hazard of death (HR: 0.35,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.001), which was confirmed after adjusting for tumor volume, MGMT status, age, and Karnofsky performance score (KPS) (HR: 0.29,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.001). Low-risk necrosis was characterized by greater necrosis volume and necrosis proportion, fewer isolated clusters, lower perfusion values, and higher oxygen extraction values.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The necrosis morphology bears prognostic information in post-chemoradiation glioblastoma and exhibits distinct biological features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Are quantitative MRI-derived necrosis phenotypes associated with survival in post-chemoradiation glioblastoma?<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>The low-risk necrosis phenotype, derived from two quantitative necrosis features, is independently associated with patient survival and reflects distinct perfusion characteristics<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Quantitative assessment of necrosis morphology from routine MRI may complement established prognostic factors and enable improved risk stratification of patients with glioblastoma after chemoradiation<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-026-12862-4","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T18:00:56Z","timestamp":1790704856000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Imaging patterns of necrosis after treatment with chemoradiation are prognostic for survival in glioblastoma"],"prefix":"10.1007","author":[{"given":"Johanna","family":"Heugenhauser","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Sanvito","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingwen","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irina","family":"Kryukov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catalina","family":"Raymond","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashley","family":"Teraishi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phioanh L.","family":"Nghiemphu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Albert","family":"Lai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert M.","family":"Prins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David A.","family":"Nathanson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy F.","family":"Cloughesy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2764-6640","authenticated-orcid":false,"given":"Benjamin M.","family":"Ellingson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"12862_CR1","doi-asserted-by":"publisher","first-page":"vi1","DOI":"10.1093\/neuonc\/noae145","volume":"26","author":"M Price","year":"2024","unstructured":"Price M, Ballard C, Benedetti J et al (2024) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2017\u20132021. 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Ellingson.","order":1,"name":"Ethics","label":"Guarantor","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Benjamin M. Ellingson is a paid consultant and advisor for Alpheus Medical, Inc., Autem Therapeutics, Carthera, Chimerix Inc., Ellipses Pharma, Erasca, Global Coalition for Adaptive Research (GCAR), Imaging Endpoints, Medicenna, Medscape\/WebMD, MeritCRO, Monteris, Neosoma, Nerviano Medical Sciences, Nuvation Bio, Orbus Therapeutics, Sagimet Biosciences, Sapience Therapeutics, Servier Pharmaceuticals, SonALAsense, Sumitomo Dainippon Pharma Oncology, Telix, Third Rock Ventures, and Voiant. Benjamin M. Ellingson has received grant funding from Siemens. Timothy F. Cloughesy is cofounder, major stock holder, consultant and board member of Katmai Pharmaceuticals, member of the board for the 501c3 Global Coalition for Adaptive Research, holds stock option of Notable Labs, holds stock in Chimerix and receives milestone payments and possible future royalties, member of the scientific advisory board for Break Through Cancer, member of the scientific advisory board for Cure Brain Cancer Foundation, has provided paid consulting services to GCAR; Gan & Lee; BrainStorm; Katmai; Sapience; Inovio; Vigeo Therapeutics; DNATrix; Tyme; SDP; Novartis; Roche; Kintara; Bayer; Merck; Boehinger Ingelheim; VBL; Amgen; Kiyatec; Odonate Therapeutics QED; Medefield; Pascal Biosciences; Bayer; Tocagen; Karyopharm; GW Pharma; Abbvie; VBI; Deciphera; VBL; Agios; Genocea; Celgene; Puma; Lilly; BMS; Cortice; Wellcome Trust; Novocure; Novogen; Boston Biomedical; Sunovion; Human Longevity; Insys; ProNai; Pfizer; Notable labs; Medqia Trizel; Medscape and has contracts with UCLA for the Brain Tumor Program with Oncovir; Merck; Oncoceutics; Novartis; Amgen; Abbvie; DNAtrix; Beigene; BMS; AstraZeneca; Kazia; Agios; Boston Biomedical; Deciphera; Tocagen; Orbus; Karyopharm.","order":2,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"No complex statistical methods were necessary for this paper.","order":3,"name":"Ethics","label":"Statistics and biometry","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"All patients gave written informed consent to be included in the database used in this study.","order":4,"name":"Ethics","label":"Informed consent","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The collection and analysis of clinical and imaging data for this research were approved by the UCLA institutional review board under the identification number IRB#19-002084.","order":5,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We analyzed a patient cohort that was previously reported in another article (\n                      \n                      ) with substantially different aims and scope.","order":6,"name":"Ethics","label":"Study subjects or cohorts overlap","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"order":7,"name":"Ethics","label":"Methodology","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}}]}}