Machine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study.

Akbari, Hamed; Bakas, Spyridon; Sako, Chiharu; Fathi Kazerooni, Anahita; Villanueva-Meyer, Javier; Garcia, Jose A; Mamourian, Elizabeth; Liu, Fang; Cao, Quy; Shinohara, Russell T; Baid, Ujjwal; Getka, Alexander; Pati, Sarthak; Singh, Ashish; Calabrese, Evan; Chang, Susan; Rudie, Jeffrey; Sotiras, Aristeidis; LaMontagne, Pamela; Marcus, Daniel S; Milchenko, Mikhail; Nazeri, Arash; Balana, Carmen; Capellades, Jaume; Puig, Josep; Badve, Chaitra; Barnholtz-Sloan, Jill S; Sloan, Andrew E; Vadmal, Vachan; Waite, Kristin; Ak, Murat; Colen, Rivka R; Park, Yae Won; Ahn, Sung Soo; Chang, Jong Hee; Choi, Yoon Seong; Lee, Seung-Koo; Alexander, Gregory S; Ali, Ayesha S; Dicker, Adam P; Flanders, Adam E; Liem, Spencer; Lombardo, Joseph; Shi, Wenyin; Shukla, Gaurav; Griffith, Brent; Poisson, Laila M; Rogers, Lisa R; Kotrotsou, Aikaterini; Booth, Thomas C; Jain, Rajan; Lee, Matthew; Mahajan, Abhishek; Chakravarti, Arnab; Palmer, Joshua D; DiCostanzo, Dominic; Fathallah-Shaykh, Hassan; Cepeda, Santiago; Santonocito, Orazio Santo; Di Stefano, Anna Luisa; Wiestler, Benedikt; Melhem, Elias R; Woodworth, Graeme F; Tiwari, Pallavi; Valdes, Pablo; Matsumoto, Yuji; Otani, Yoshihiro; Imoto, Ryoji; Aboian, Mariam; Koizumi, Shinichiro; Kurozumi, Kazuhiko; Kawakatsu, Toru; Alexander, Kimberley; Satgunaseelan, Laveniya; Rulseh, Aaron M; Bagley, Stephen J; Bilello, Michel; Binder, Zev A; Brem, Steven; Desai, Arati S; Lustig, Robert A; Maloney, Eileen; Prior, Timothy; Amankulor, Nduka; Nasrallah, Mac Lean P; O'Rourke, Donald M; Mohan, Suyash; Davatzikos, Christos

doi:10.1093/neuonc/noae260

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Professur für Neuroradiologie (Prof. Zimmer)

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Titel:: Machine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study.
Dokumenttyp:: Journal Article
Autor(en):: Akbari, Hamed; Bakas, Spyridon; Sako, Chiharu; Fathi Kazerooni, Anahita; Villanueva-Meyer, Javier; Garcia, Jose A; Mamourian, Elizabeth; Liu, Fang; Cao, Quy; Shinohara, Russell T; Baid, Ujjwal; Getka, Alexander; Pati, Sarthak; Singh, Ashish; Calabrese, Evan; Chang, Susan; Rudie, Jeffrey; Sotiras, Aristeidis; LaMontagne, Pamela; Marcus, Daniel S; Milchenko, Mikhail; Nazeri, Arash; Balana, Carmen; Capellades, Jaume; Puig, Josep; Badve, Chaitra; Barnholtz-Sloan, Jill S; Sloan, Andrew E; Vadmal, Vachan; Waite, Kristin; Ak, Murat; Colen, Rivka R; Park, Yae Won; Ahn, Sung Soo; Chang, Jong Hee; Choi, Yoon Seong; Lee, Seung-Koo; Alexander, Gregory S; Ali, Ayesha S; Dicker, Adam P; Flanders, Adam E; Liem, Spencer; Lombardo, Joseph; Shi, Wenyin; Shukla, Gaurav; Griffith, Brent; Poisson, Laila M; Rogers, Lisa R; Kotrotsou, Aikaterini; Booth, Thomas C; Jain, Rajan; Lee, Matthew; Mahajan, Abhishek; Chakravarti, Arnab; Palmer, Joshua D; DiCostanzo, Dominic; Fathallah-Shaykh, Hassan; Cepeda, Santiago; Santonocito, Orazio Santo; Di Stefano, Anna Luisa; Wiestler, Benedikt; Melhem, Elias R; Woodworth, Graeme F; Tiwari, Pallavi; Valdes, Pablo; Matsumoto, Yuji; Otani, Yoshihiro; Imoto, Ryoji; Aboian, Mariam; Koizumi, Shinichiro; Kurozumi, Kazuhiko; Kawakatsu, Toru; Alexander, Kimberley; Satgunaseelan, Laveniya; Rulseh, Aaron M; Bagley, Stephen J; Bilello, Michel; Binder, Zev A; Brem, Steven; Desai, Arati S; Lustig, Robert A; Maloney, Eileen; Prior, Timothy; Amankulor, Nduka; Nasrallah, Mac Lean P; O'Rourke, Donald M; Mohan, Suyash; Davatzikos, Christos «
Akbari, Hamed; Bakas, Spyridon; Sako, Chiharu; Fathi Kazerooni, Anahita; Villanueva-Meyer, Javier; Garcia, Jose A; Mamourian, Elizabeth; Liu, Fang; Cao, Quy; Shinohara, Russell T; Baid, Ujjwal; Getka, Alexander; Pati, Sarthak; Singh, Ashish; Calabrese, Evan; Chang, Susan; Rudie, Jeffrey; Sotiras, Aristeidis; LaMontagne, Pamela; Marcus, Daniel S; Milchenko, Mikhail; Nazeri, Arash; Balana, Carmen; Capellades, Jaume; Puig, Josep; Badve, Chaitra; Barnholtz-Sloan, Jill S; Sloan, Andrew E; Vadmal, Vac... »
Abstract:: BACKGROUND: Glioblastoma is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification. METHODS: We developed a highly reproducible, personalized prognostication and clinical subgrouping system using machine learning (ML) on routine clinical data, MRI, and molecular measures from 2,838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]). RESULTS: The ML model stratified patients into distinct prognostic subgroups with HRs between subgroups I-II and I-III of 1.62 (95%CI: 1.43-1.84, p<0.001) and 3.48 (95%CI: 2.94-4.11, p<0.001), respectively. Analysis of imaging features revealed several tumor properties contributing unique prognostic value, supporting the feasibility of a generalizable prognostic classification system in a diverse cohort. CONCLUSIONS: Our ML model demonstrates extensive reproducibility and online accessibility, utilizing routine imaging data rather than complex imaging protocols. This platform offers a unique approach for personalized patient management and clinical trial stratification in glioblastoma.
Zeitschriftentitel:: Neuro-oncol
Jahr:: 2024
Volltext / DOI:: doi:10.1093/neuonc/noae260
PubMed:: http://view.ncbi.nlm.nih.gov/pubmed/39665363
Print-ISSN:: 1522-8517
TUM Einrichtung:: Professur für AI for Image-Guided Diagnosis and Therapy (Prof. Wiestler); Professur für Neuroradiologie (Prof. Zimmer)
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