PT  - JOURNAL ARTICLE
AU  - Perreault, S.
AU  - Ramaswamy, V.
AU  - Achrol, A.S.
AU  - Chao, K.
AU  - Liu, T.T.
AU  - Shih, D.
AU  - Remke, M.
AU  - Schubert, S.
AU  - Bouffet, E.
AU  - Fisher, P.G.
AU  - Partap, S.
AU  - Vogel, H.
AU  - Taylor, M.D.
AU  - Cho, Y.J.
AU  - Yeom, K.W.
TI  - MRI Surrogates for Molecular Subgroups of Medulloblastoma
AID  - 10.3174/ajnr.A3990
DP  - 2014 May 15
TA  - American Journal of Neuroradiology
4099  - http://www.ajnr.org/content/early/2014/05/15/ajnr.A3990.short
4100  - http://www.ajnr.org/content/early/2014/05/15/ajnr.A3990.full
AB  - BACKGROUND AND PURPOSE: Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups. MATERIALS AND METHODS: All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (WNT, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes. RESULTS: Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), WNT tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%–100%), and SHH tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%–100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%–98%). When we used the MR imaging feature–based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort. CONCLUSIONS: Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing. Abbreviations CP/CPAcerebellar peduncle/cerebellopontine angle cisternFSLfMRI of the Brain Software LibrarySHHsonic hedgehogWNTwingless