Neuroimaging of pediatric infratentorial tumors and the value of diffusion-weighted imaging (DWI) in determining tumor grade

医学 有效扩散系数 分级(工程) 髓母细胞瘤 磁共振成像 核医学 曼惠特尼U检验 间变性星形细胞瘤 磁共振弥散成像 胶质瘤 放射科 活检 毛细胞星形细胞瘤 脑瘤 星形细胞瘤 病理 内科学 工程类 土木工程 癌症研究
作者
Kirthi Sathyakumar,Sunithi Mani,Gayatri Harshe Pathak,Krishna Prabhu,Ari G Chacko,Geeta Chacko
出处
期刊:Acta Radiologica [SAGE]
卷期号:62 (4): 533-540 被引量:7
标识
DOI:10.1177/0284185120933219
摘要

Background Diffusion-weighted imaging (DWI) provides information about the cellular density of tumors. This feature is useful in grading and identifying different tumor types. Purpose To assess the value of diffusion restriction and apparent diffusion coefficient (ADC) values in differentiating pediatric infratentorial tumors. Material and Methods This was a retrospective review of the magnetic resonance imaging (MRI) of 82 children (age range 1–16 years) with infratentorial tumors. Histopathological grading after surgical excision/biopsy was categorized as low grade (WHO grades I and II) (n = 31; 29 pilocytic astrocytomas, 2 ependymomas) and high grade (WHO grade III and IV) (n = 51; 40 medulloblastomas, 8 anaplastic ependymomas, 1 anaplastic astrocytoma, 2 atypical rhabdoid teratoid tumors [ATRT]). MRI features and ADC values were compared among tumor types and grades using a two-tailed t test, Mann–Whitney U test for continuous data and Chi-square test for categorical variables. Results Diffusion restriction and low ADC value was a feature of high-grade tumors ( P<0.001). The mean ADC values of the low-grade and high-grade tumors were 1.567 × 10 −3 mm 2 /s and 0.661 × 10 −3 mm 2 /s, respectively. Using 0.9 × 10 −3 mm 2 /s as the cut-off value, the sensitivity, specificity, positive and negative predictive values for differentiating the grades was 87%, 100%, 100%, and 81.8%, respectively. Significant differences were found between the mean ADC values of the individual tumor types ( P<0.05), except between medulloblastoma and ATRT. Conclusion ADC values and visual assessment of diffusion restriction are useful in tumor grading. The individual tumor types can be identified by an algorithmic approach, using DWI in conjunction with other described MRI features.
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