title: Advanced MRI may complement histological diagnosis of lower  grade gliomas and help in predicting survival.
abstract: MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade.
authors.forename: Valeria
authors.initials: V
authors.lastname: Cuccarini
authors.forename: A
authors.initials: A
authors.lastname: Erbetta
authors.forename: M
authors.initials: M
authors.lastname: Farinotti
authors.forename: L
authors.initials: L
authors.lastname: Cuppini
authors.forename: F
authors.initials: F
authors.lastname: Ghielmetti
authors.forename: B
authors.initials: B
authors.lastname: Pollo
authors.forename: F
authors.initials: F
authors.lastname: Di Meco
authors.forename: M
authors.initials: M
authors.lastname: Grisoli
authors.forename: G
authors.initials: G
authors.lastname: Filippini
authors.forename: G
authors.initials: G
authors.lastname: Finocchiaro
authors.forename: M G
authors.initials: MG
authors.lastname: Bruzzone
authors.forename: M
authors.initials: M
authors.lastname: Eoli
mesh_terms: D000328:Adult; D001932:Brain Neoplasms / Q000401:mortality* / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D005260:Female; D005910:Glioma / Q000401:mortality* / Q000473:pathology*; D006801:Humans; D018810:Magnetic Resonance Angiography / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D060787:Neoplasm Grading / Q000379:methods*; D012680:Sensitivity and Specificity; D016019:Survival Analysis