Perreault S, Ramaswamy V, Achrol A S, Chao K, Liu T T, Shih D, Remke M, Schubert S, Bouffet E, Fisher P G, Partap S, Vogel H, Taylor M D, Cho Y J, Yeom K W
From the Department of Neurology (S. Perreault, S.S., P.G.F., S. Partap, Y.J.C.), Division of Child NeurologyDivision of Child Neurology (S. Perreault), Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada.
Division of Neurosurgery (V.R., D.S., M.R., M.D.T.)Labatt Brain Tumour Research Centre (V.R., D.S., M.R., E.B., M.D.T.)Department of Laboratory Medicine and Pathobiology (V.S., D.S., M.R., M.D.T.), University of Toronto, Toronto, Ontario, Canada.
AJNR Am J Neuroradiol. 2014 Jul;35(7):1263-9. doi: 10.3174/ajnr.A3990. Epub 2014 May 15.
Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups.
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.
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.
Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.
最近确定的髓母细胞瘤分子亚组显示出改善风险分层的潜力。我们假设不同的磁共振成像（MR）特征可以预测这些亚组。
在一家机构诊断为髓母细胞瘤的所有患者，均有治疗前MR成像和手术组织，作为发现队列（n = 47）。3名盲法神经放射科医生评估MR成像特征。对肿瘤组织进行基于NanoString的分析，将肿瘤分为4个已确定的分子亚组（无翼型、音猬因子型、3组和4组）。来自独立机构的第二个儿童髓母细胞瘤队列（n = 52）用于验证预测分子亚型的MR成像特征。
发现队列中的逻辑回归分析显示肿瘤位置（P <.001）和强化模式（P =.001）是髓母细胞瘤亚组的重要预测因素。立体特异性计算分析证实，3组和4组肿瘤在中线第四脑室内占主导（100%，P =.007），无翼型肿瘤定位于小脑脚/小脑脑桥角池，阳性预测值为100%（95%CI，30% - 100%），音猬因子型肿瘤发生于小脑半球，阳性预测值为100%（95%CI，59% - 100%）。中线4组肿瘤表现为轻度/无强化，阳性预测值为91%（95%CI，59% - 98%）。当我们使用基于MR成像特征的回归模型时，发现队列中66%的髓母细胞瘤被正确预测，验证队列中为65%。
肿瘤位置和强化模式可预测儿童髓母细胞瘤的分子亚组，并可能潜在地作为基因组检测的替代指标。
