{"title":"idh突变胶质瘤的先进影像学:诊断和治疗的准确性。","authors":"Onur Yildirim, Robert J Young","doi":"10.1016/bs.acr.2025.05.003","DOIUrl":null,"url":null,"abstract":"<p><p>Advancements in imaging techniques and analyses have evolved in parallel with advancements in precision oncology and the transformative changes in glioma diagnosis and management. This chapter explores the pivotal roles of modern qualitative and quantitative imaging in characterizing gliomas, particularly low-grade gliomas (LGGs). Key topics include the integration of standard imaging biomarkers (e.g., T2-FLAIR mismatch sign) and advanced imaging modalities (e.g., 2-hydroxyglutarate [2HG] spectroscopy, diffusion and perfusion imaging) into routine clinical practice. These approaches enhance diagnostic accuracy, facilitate treatment planning, and enable longitudinal monitoring of disease progression. Practical challenges, such as the logistical demands to implement tumor segmentation, variability in imaging acquisition and interpretation, and integration of imaging into decision-making discussions between physicians and patients, are also discussed. Additionally, the role of radiomics and artificial intelligence (AI) in refining tumor characterization and predicting treatment response is explored. The inclusion of emerging therapeutic strategies, including IDH inhibitors and AI-driven imaging tools, underscores this chapter's emphasis on precision-driven innovations. By synthesizing current research and clinical practices, this chapter provides a comprehensive framework for leveraging advanced imaging in glioma care. Improved imaging methodologies not only allow for earlier detection of disease progression but also offer insight into treatment response and resistance mechanisms. As imaging continues to evolve, its integration with molecular and computational tools will further refine personalized approaches in glioma management, ultimately contributing to better patient outcomes.</p>","PeriodicalId":94294,"journal":{"name":"Advances in cancer research","volume":"166 ","pages":"59-80"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advanced imaging of IDH-mutant gliomas: Precision in diagnosis and management.\",\"authors\":\"Onur Yildirim, Robert J Young\",\"doi\":\"10.1016/bs.acr.2025.05.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Advancements in imaging techniques and analyses have evolved in parallel with advancements in precision oncology and the transformative changes in glioma diagnosis and management. This chapter explores the pivotal roles of modern qualitative and quantitative imaging in characterizing gliomas, particularly low-grade gliomas (LGGs). Key topics include the integration of standard imaging biomarkers (e.g., T2-FLAIR mismatch sign) and advanced imaging modalities (e.g., 2-hydroxyglutarate [2HG] spectroscopy, diffusion and perfusion imaging) into routine clinical practice. These approaches enhance diagnostic accuracy, facilitate treatment planning, and enable longitudinal monitoring of disease progression. Practical challenges, such as the logistical demands to implement tumor segmentation, variability in imaging acquisition and interpretation, and integration of imaging into decision-making discussions between physicians and patients, are also discussed. Additionally, the role of radiomics and artificial intelligence (AI) in refining tumor characterization and predicting treatment response is explored. The inclusion of emerging therapeutic strategies, including IDH inhibitors and AI-driven imaging tools, underscores this chapter's emphasis on precision-driven innovations. By synthesizing current research and clinical practices, this chapter provides a comprehensive framework for leveraging advanced imaging in glioma care. Improved imaging methodologies not only allow for earlier detection of disease progression but also offer insight into treatment response and resistance mechanisms. As imaging continues to evolve, its integration with molecular and computational tools will further refine personalized approaches in glioma management, ultimately contributing to better patient outcomes.</p>\",\"PeriodicalId\":94294,\"journal\":{\"name\":\"Advances in cancer research\",\"volume\":\"166 \",\"pages\":\"59-80\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in cancer research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/bs.acr.2025.05.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/6/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in cancer research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/bs.acr.2025.05.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/18 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Advanced imaging of IDH-mutant gliomas: Precision in diagnosis and management.
Advancements in imaging techniques and analyses have evolved in parallel with advancements in precision oncology and the transformative changes in glioma diagnosis and management. This chapter explores the pivotal roles of modern qualitative and quantitative imaging in characterizing gliomas, particularly low-grade gliomas (LGGs). Key topics include the integration of standard imaging biomarkers (e.g., T2-FLAIR mismatch sign) and advanced imaging modalities (e.g., 2-hydroxyglutarate [2HG] spectroscopy, diffusion and perfusion imaging) into routine clinical practice. These approaches enhance diagnostic accuracy, facilitate treatment planning, and enable longitudinal monitoring of disease progression. Practical challenges, such as the logistical demands to implement tumor segmentation, variability in imaging acquisition and interpretation, and integration of imaging into decision-making discussions between physicians and patients, are also discussed. Additionally, the role of radiomics and artificial intelligence (AI) in refining tumor characterization and predicting treatment response is explored. The inclusion of emerging therapeutic strategies, including IDH inhibitors and AI-driven imaging tools, underscores this chapter's emphasis on precision-driven innovations. By synthesizing current research and clinical practices, this chapter provides a comprehensive framework for leveraging advanced imaging in glioma care. Improved imaging methodologies not only allow for earlier detection of disease progression but also offer insight into treatment response and resistance mechanisms. As imaging continues to evolve, its integration with molecular and computational tools will further refine personalized approaches in glioma management, ultimately contributing to better patient outcomes.