V Rameh, U Löbel, F D'Arco, A Bhatia, K Mankad, T Y Poussaint, C A Alves
{"title":"Cortically Based Brain Tumors in Children: A Decision-Tree Approach in the Radiology Reading Room.","authors":"V Rameh, U Löbel, F D'Arco, A Bhatia, K Mankad, T Y Poussaint, C A Alves","doi":"10.3174/ajnr.A8477","DOIUrl":null,"url":null,"abstract":"<p><p>Cortically based brain tumors in children constitute a unique set of tumors with variably aggressive biologic behavior. Because radiologists play an integral role on the multidisciplinary medical team, a clinically useful and easy-to-follow flow chart for the differential diagnoses of these complex brain tumors is essential. This proposed algorithm tree provides the latest insights into the typical imaging characteristics and epidemiologic data that differentiate the tumor entities, taking into perspective the 2021 World Health Organization's classification and highlighting classic as well as newly identified pathologic subtypes by using current molecular understanding.</p>","PeriodicalId":93863,"journal":{"name":"AJNR. American journal of neuroradiology","volume":" ","pages":"11-23"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735440/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AJNR. American journal of neuroradiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3174/ajnr.A8477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cortically based brain tumors in children constitute a unique set of tumors with variably aggressive biologic behavior. Because radiologists play an integral role on the multidisciplinary medical team, a clinically useful and easy-to-follow flow chart for the differential diagnoses of these complex brain tumors is essential. This proposed algorithm tree provides the latest insights into the typical imaging characteristics and epidemiologic data that differentiate the tumor entities, taking into perspective the 2021 World Health Organization's classification and highlighting classic as well as newly identified pathologic subtypes by using current molecular understanding.