Illuminating radiogenomic signatures in pediatric-type diffuse gliomas: insights into molecular, clinical, and imaging correlations. Part I: high-grade group.

IF 4.8 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Ryo Kurokawa, Akifumi Hagiwara, Daiju Ueda, Rintaro Ito, Tsukasa Saida, Maya Honda, Kentaro Nishioka, Akihiko Sakata, Masahiro Yanagawa, Koji Takumi, Seitaro Oda, Satoru Ide, Keitaro Sofue, Shunsuke Sugawara, Tadashi Watabe, Kenji Hirata, Mariko Kawamura, Mami Iima, Shinji Naganawa
{"title":"Illuminating radiogenomic signatures in pediatric-type diffuse gliomas: insights into molecular, clinical, and imaging correlations. Part I: high-grade group.","authors":"Ryo Kurokawa, Akifumi Hagiwara, Daiju Ueda, Rintaro Ito, Tsukasa Saida, Maya Honda, Kentaro Nishioka, Akihiko Sakata, Masahiro Yanagawa, Koji Takumi, Seitaro Oda, Satoru Ide, Keitaro Sofue, Shunsuke Sugawara, Tadashi Watabe, Kenji Hirata, Mariko Kawamura, Mami Iima, Shinji Naganawa","doi":"10.1007/s11547-025-02078-9","DOIUrl":null,"url":null,"abstract":"<p><p>Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiologia Medica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11547-025-02078-9","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.

阐明小儿型弥漫性胶质瘤的放射基因组特征:对分子、临床和影像学相关性的见解。第一部分:高档组。
分子遗传学的最新进展彻底改变了2021年世界卫生组织中枢神经系统肿瘤分类中的儿科型高级别胶质瘤的分类。本文综述了目前关于以下四种肿瘤类型的证据:弥漫性中线胶质瘤,H3 k27改变;弥漫性半球胶质瘤,H3 g34突变体;弥漫性小儿型高级别胶质瘤,h3 -野生型和idh -野生型;以及婴儿型半球胶质瘤。我们对2025年1月之前发表的文章进行了全面的文献检索。对于每种肿瘤类型,我们分析了典型的临床表现、分子改变、传统和先进的磁共振成像特征、放射-分子相关性以及当前的治疗方法。新兴的放射基因组学方法利用人工智能,包括放射组学和深度学习,在识别与分子特征相关的成像生物标志物方面显示出希望。这篇综述强调了整合放射学和分子数据对于准确诊断和治疗计划的重要性,同时承认当前方法的局限性和需要在更大的队列中进行前瞻性验证。了解这些相关性对于推进针对这些挑战性肿瘤的个性化治疗策略至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Radiologia Medica
Radiologia Medica 医学-核医学
CiteScore
14.10
自引率
7.90%
发文量
133
审稿时长
4-8 weeks
期刊介绍: Felice Perussia founded La radiologia medica in 1914. It is a peer-reviewed journal and serves as the official journal of the Italian Society of Medical and Interventional Radiology (SIRM). The primary purpose of the journal is to disseminate information related to Radiology, especially advancements in diagnostic imaging and related disciplines. La radiologia medica welcomes original research on both fundamental and clinical aspects of modern radiology, with a particular focus on diagnostic and interventional imaging techniques. It also covers topics such as radiotherapy, nuclear medicine, radiobiology, health physics, and artificial intelligence in the context of clinical implications. The journal includes various types of contributions such as original articles, review articles, editorials, short reports, and letters to the editor. With an esteemed Editorial Board and a selection of insightful reports, the journal is an indispensable resource for radiologists and professionals in related fields. Ultimately, La radiologia medica aims to serve as a platform for international collaboration and knowledge sharing within the radiological community.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信