Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.
Purpose To evaluate whether radiomic feature-based magnetic resonance (MR) imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma with improved accuracy compared with that of established clinical and radiologic risk models. Materials and Methods Retrospective evaluation of data was approved by the local ethics committee and informed consent was waived. A total of 119 patients (allocated in a 2:1 ratio to a discovery [n = 79] or validation [n = 40] set) with newly diagnosed glioblastoma were subjected to radiomic feature extraction (12 190 features extracted, including first-order, volume, shape, and texture features) from the multiparametric (contrast material-enhanced T1-weighted and fluid-attenuated inversion-recovery imaging sequences) and multiregional (contrast-enhanced and unenhanced) tumor volumes. Radiomic features of patients in the discovery set were subjected to a supervised principal component (SPC) analysis to predict progression-free survival (PFS) and overall survival (OS) and were validated in the validation set. The performance of a Cox proportional hazards model with the SPC analysis predictor was assessed with C index and integrated Brier scores (IBS, lower scores indicating higher accuracy) and compared with Cox models based on clinical (age and Karnofsky performance score) and radiologic (Gaussian normalized relative cerebral blood volume and apparent diffusion coefficient) parameters. Results SPC analysis allowed stratification based on 11 features of patients in the discovery set into a low- or high-risk group for PFS (hazard ratio [HR], 2.43; P = .002) and OS (HR, 4.33; P < .001), and the results were validated successfully in the validation set for PFS (HR, 2.28; P = .032) and OS (HR, 3.45; P = .004). The performance of the SPC analysis (OS: IBS, 0.149; C index, 0.654; PFS: IBS, 0.138; C index, 0.611) was higher compared with that of the radiologic (OS: IBS, 0.175; C index, 0.603; PFS: IBS, 0.149; C index, 0.554) and clinical risk models (OS: IBS, 0.161, C index, 0.640; PFS: IBS, 0.139; C index, 0.599). The performance of the SPC analysis model was further improved when combined with clinical data (OS: IBS, 0.142; C index, 0.696; PFS: IBS, 0.132; C index, 0.637). Conclusion An 11-feature radiomic signature that allows prediction of survival and stratification of patients with newly diagnosed glioblastoma was identified, and improved performance compared with that of established clinical and radiologic risk models was demonstrated. (©) RSNA, 2016 Online supplemental material is available for this article.
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Philipp
P
Kickingereder
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Sina
S
Burth
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Antje
A
Wick
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Michael
M
Götz
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Oliver
O
Eidel
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Heinz-Peter
HP
Schlemmer
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Klaus H
KH
Maier-Hein
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Wolfgang
W
Wick
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Martin
M
Bendszus
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Alexander
A
Radbruch
From the Department of Neuroradiology (P.K., S.B., O.E., M.B., A.R., D.B.) and Neurology Clinic (A.W., W.W.), University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Medical Image Computing, Medical and Biological Informatics Division (M.G., K.H.M.H.), Department of Radiology (H.P.S., A.R., D.B.), and Clinical Neuro-oncology Cooperation Unit, German Cancer Consortium (DKTK) (W.W.), German Cancer Research Center (DKFZ), Heidelberg, Germany.
David
D
Bonekamp
D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003287:Contrast Media; D005260:Female; D005858:Germany; D005909:Glioblastoma / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008536:Meglumine; D009942:Organometallic Compounds; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment; D015996:Survival Rate; D047368:Tumor Burden
D003287:Contrast Media; D009942:Organometallic Compounds; D008536:Meglumine; C072417:gadoterate meglumine