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