title: Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.
abstract: OBJECTIVE
  Despite 90 % of glioblastoma (GBM) recurrences occurring in the peritumoral brain zone (PBZ), its contribution in patient survival is poorly understood. The current study leverages computerized texture (i.e. radiomic) analysis to evaluate the efficacy of PBZ features from pre-operative MRI in predicting long- (>18 months) versus short-term (<7 months) survival in GBM.
  
  
  METHODS
  Sixty-five patient examinations (29 short-term, 36 long-term) with gadolinium-contrast T1w, FLAIR and T2wsequences from the Cancer Imaging Archive were employed. An expert manually segmented each study as: enhancing lesion, PBZ and tumour necrosis. 402 radiomic features (capturing co-occurrence, grey-level dependence and directional gradients) were obtained for each region. Evaluation was performed using threefold cross-validation, such that a subset of studies was used to select the most predictive features, and the remaining subset was used to evaluate their efficacy in predicting survival.
  
  
  RESULTS
  A subset of ten radiomic 'peritumoral' MRI features, suggestive of intensity heterogeneity and textural patterns, was found to be predictive of survival (p = 1.47 × 10-5) as compared to features from enhancing tumour, necrotic regions and known clinical factors.
  
  
  CONCLUSIONS
  Our preliminary analysis suggests that radiomic features from the PBZ on routine pre-operative MRI may be predictive of long- versus short-term survival in GBM.
  
  
  CONCLUSIONS
  • Radiomic features from peritumoral regions can capture glioblastoma heterogeneity to predict outcome. • Peritumoral radiomics along with clinical factors are highly predictive of glioblastoma outcome. • Identifying prognostic markers can assist in making personalized therapy decisions in glioblastoma.
authors: Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA.
authors: Prateek
authors: P
authors: Prasanna
authors: Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA.
authors: Jay
authors: J
authors: Patel
authors: Case Western Reserve School of Medicine, University Hospitals Case Medical Center, 11100 Euclid Ave, Cleveland, OH, 44106, USA.
authors: Sasan
authors: S
authors: Partovi
authors: Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA.
authors: Anant
authors: A
authors: Madabhushi
authors: Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA. pxt130@case.edu.
authors: Pallavi
authors: http://orcid.org/0000-0001-9477-4856
authors: P
authors: Tiwari
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000000981:diagnostic imaging*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000401:mortality; D005260:Female; D005909:Glioblastoma / Q000000981:diagnostic imaging* / Q000401:mortality; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000453:epidemiology; D011379:Prognosis; D015203:Reproducibility of Results; D018570:Risk Assessment; D015996:Survival Rate; D055815:Young Adult
keywords: Glioblastoma multiforme; Peritumoral; Radiomics; Survival; Texture