Fellows’ Journal Club
July 2014
(1 of 3)
These authors seek to establish the imaging features that would allow classification of medulloblastomas according to their genetic attributes. In nearly 100 tumors they found that groups 3 and 4 occurred predominantly in the fourth ventricle, wingless ones were located in the cerebellar peduncles or CPA region, and sonic hedgehog tumors were present in cerebellar hemispheres. Midline group 4 tumors showed minimal contrast enhancement. Thus, tumor location and contrast-enhancement patterns may be predictive of the molecular subtypes of medulloblastoma.
Abstract
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 (wingless, 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), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%–100%), and sonic hedgehog 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.
