title: MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.
abstract: OBJECTIVE
  To conduct a comprehensive analysis of radiologist-made assessments of glioblastoma (GBM) tumor size and composition by using a community-developed controlled terminology of magnetic resonance (MR) imaging visual features as they relate to genetic alterations, gene expression class, and patient survival.
  
  
  METHODS
  Because all study patients had been previously deidentified by the Cancer Genome Atlas (TCGA), a publicly available data set that contains no linkage to patient identifiers and that is HIPAA compliant, no institutional review board approval was required. Presurgical MR images of 75 patients with GBM with genetic data in the TCGA portal were rated by three neuroradiologists for size, location, and tumor morphology by using a standardized feature set. Interrater agreements were analyzed by using the Krippendorff α statistic and intraclass correlation coefficient. Associations between survival, tumor size, and morphology were determined by using multivariate Cox regression models; associations between imaging features and genomics were studied by using the Fisher exact test.
  
  
  RESULTS
  Interrater analysis showed significant agreement in terms of contrast material enhancement, nonenhancement, necrosis, edema, and size variables. Contrast-enhanced tumor volume and longest axis length of tumor were strongly associated with poor survival (respectively, hazard ratio: 8.84, P = .0253, and hazard ratio: 1.02, P = .00973), even after adjusting for Karnofsky performance score (P = .0208). Proneural class GBM had significantly lower levels of contrast enhancement (P = .02) than other subtypes, while mesenchymal GBM showed lower levels of nonenhanced tumor (P < .01).
  
  
  CONCLUSIONS
  This analysis demonstrates a method for consistent image feature annotation capable of reproducibly characterizing brain tumors; this study shows that radiologists' estimations of macroscopic imaging features can be combined with genetic alterations and gene expression subtypes to provide deeper insight to the underlying biologic properties of GBM subsets.
authors: Department of Biomedical Informatics, 36 Eagle Row, Room 572 PAIS, Emory University Hospital, Atlanta, GA 30322, USA. dgutman@emory.edu
authors: David A
authors: DA
authors: Gutman
authors: Lee A D
authors: LA
authors: Cooper
authors: Scott N
authors: SN
authors: Hwang
authors: Chad A
authors: CA
authors: Holder
authors: Jingjing
authors: J
authors: Gao
authors: Tarun D
authors: TD
authors: Aurora
authors: William D
authors: WD
authors: Dunn
authors: Lisa
authors: L
authors: Scarpace
authors: Tom
authors: T
authors: Mikkelsen
authors: Rajan
authors: R
authors: Jain
authors: Max
authors: M
authors: Wintermark
authors: Manal
authors: M
authors: Jilwan
authors: Prashant
authors: P
authors: Raghavan
authors: Erich
authors: E
authors: Huang
authors: Robert J
authors: RJ
authors: Clifford
authors: Pattanasak
authors: P
authors: Mongkolwat
authors: Vladimir
authors: V
authors: Kleper
authors: John
authors: J
authors: Freymann
authors: Justin
authors: J
authors: Kirby
authors: Pascal O
authors: PO
authors: Zinn
authors: Carlos S
authors: CS
authors: Moreno
authors: Carl
authors: C
authors: Jaffe
authors: Rivka
authors: R
authors: Colen
authors: Daniel L
authors: DL
authors: Rubin
authors: Joel
authors: J
authors: Saltz
authors: Adam
authors: A
authors: Flanders
authors: Daniel J
authors: DJ
authors: Brat
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001932:Brain Neoplasms / Q000235:genetics / Q000378:metabolism / Q000401:mortality* / Q000473:pathology*; D005260:Female; D015870:Gene Expression; D005909:Glioblastoma / Q000235:genetics / Q000378:metabolism* / Q000473:pathology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D015996:Survival Rate; D009626:Terminology as Topic
references: J Natl Cancer Inst. 1993 May 5;85(9):704-10
references: 8478956
references: J Neurosurg. 2010 Aug;113(2):286-92
references: 20302391
references: J Clin Oncol. 2010 Aug 20;28(24):3838-43
references: 20644085
references: AJNR Am J Neuroradiol. 2005 Nov-Dec;26(10):2466-74
references: 16286386
references: J Neurosurg. 2001 Aug;95(2):190-8
references: 11780887
references: Biol Psychiatry. 2009 Dec 15;66(12):1107-14
references: 19748078
references: PLoS One. 2011;6(10):e25451
references: 21998659
references: Summit Transl Bioinform. 2009 Mar 01;2009:106-10
references: 21347180
references: Proc Natl Acad Sci U S A. 2008 Apr 1;105(13):5213-8
references: 18362333
references: J Digit Imaging. 2010 Apr;23(2):217-25
references: 19294468
references: Acta Radiol. 2011 Nov 1;52(9):1052-60
references: 21969702
references: Cancer Cell. 2006 Mar;9(3):157-73
references: 16530701
references: N Engl J Med. 2005 Mar 10;352(10):987-96
references: 15758009
references: Cancer Res. 2011 Jun 15;71(12):4055-60
references: 21628493
references: Radiology. 2008 Oct;249(1):268-77
references: 18796682
references: Cancer. 1996 Mar 15;77(6):1161-6
references: 8635139
references: Cancer Cell. 2010 Jan 19;17(1):98-110
references: 20129251
references: Radiology. 2009 Dec;253(3):590-2
references: 19952021
references: J Neurooncol. 1996 Jan;27(1):65-73
references: 8699228