Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine.
Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine.
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DOI：
10.3390/cancers13235921
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发表时间：
2021-11-25
期刊：
影响因子：
5.2
通讯作者：
Nasrallah MP
中科院分区：
文献类型：
--
作者：
Fathi Kazerooni A;Bagley SJ;Akbari H;Saxena S;Bagheri S;Guo J;Chawla S;Nabavizadeh A;Mohan S;Bakas S;Davatzikos C;Nasrallah MP
放射组学和放射基因组学为高级别胶质瘤生物学以及胶质瘤对标准疗法的反应行为提供了新的见解。在这篇文章中，我们提供了神经肿瘤学，神经病理学和放射组学在提供更准确的诊断中的作用的计算观点，鉴定，和高级别胶质瘤患者的监测，以及放射组学在临床实践中的潜在应用，总体目标是推进精准医学，以实现最佳的患者护理。与医学成像相结合的机器学习（ML）通过放射组学和放射基因组学为高级别胶质瘤的精确诊断引入了新的视角。这为表征用于预测患者生存、肿瘤复发和基因组学的非侵入性和体内生物标志物带来了希望，从而鼓励针对个性化需求的治疗。基于术前多参数磁共振成像（MP-MRI）扫描的肿瘤浸润表征可以预测未来肿瘤复发的位点，从而有助于规划患者的治疗过程，例如优化切除范围以及辐射的剂量和靶区域。肿瘤基因组学的成像特征可以帮助识别受益于某些靶向治疗的患者。神经胶质瘤的分子特性和预测其随时间和治疗的变化将允许优化治疗。在这篇文章中，我们提供了神经肿瘤学，神经病理学和放射组学和放射基因组学的承诺，允许个性化治疗胶质瘤患者的计算观点，并讨论了这些方法在多机构临床试验中的挑战和局限性，并建议减轻问题和未来的方向。
Radiomics and radiogenomics offer new insight into high-grade glioma biology, as well as into glioma behavior in response to standard therapies. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the role of radiomics in providing more accurate diagnoses, prognostication, and surveillance of patients with high-grade glioma, and on the potential application of radiomics in clinical practice, with the overarching goal of advancing precision medicine for optimal patient care. Machine learning (ML) integrated with medical imaging has introduced new perspectives in precision diagnostics of high-grade gliomas, through radiomics and radiogenomics. This has raised hopes for characterizing noninvasive and in vivo biomarkers for prediction of patient survival, tumor recurrence, and genomics and therefore encouraging treatments tailored to individualized needs. Characterization of tumor infiltration based on pre-operative multi-parametric magnetic resonance imaging (MP-MRI) scans may allow prediction of the loci of future tumor recurrence and thereby aid in planning the course of treatment for the patients, such as optimizing the extent of resection and the dose and target area of radiation. Imaging signatures of tumor genomics can help in identifying the patients who benefit from certain targeted therapies. Specifying molecular properties of gliomas and prediction of their changes over time and with treatment would allow optimization of treatment. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the promise of radiomics and radiogenomics for allowing personalized treatments of patients with gliomas and discuss the challenges and limitations of these methods in multi-institutional clinical trials and suggestions to mitigate the issues and the future directions.
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影响因子：
19.7
作者：
Bae, Sohi;Choi, Yoon Seong;Lee, Seung-Koo
通讯作者：
Lee, Seung-Koo
影响因子：
2.5
作者：
Davatzikos, Christos;Sotiras, Aristeidis;Kontos, Despina
通讯作者：
Kontos, Despina
影响因子：
4.4
作者：
Clark, Kenneth;Vendt, Bruce;Prior, Fred
通讯作者：
Prior, Fred
DOI：
10.1002/jmri.27908
发表时间：
2022-03
期刊：
Journal of magnetic resonance imaging : JMRI
影响因子：
--
作者：
Bashyam VM;Doshi J;Erus G;Srinivasan D;Abdulkadir A;Singh A;Habes M;Fan Y;Masters CL;Maruff P;Zhuo C;Völzke H;Johnson SC;Fripp J;Koutsouleris N;Satterthwaite TD;Wolf DH;Gur RE;Gur RC;Morris JC;Albert MS;Grabe HJ;Resnick SM;Bryan NR;Wittfeld K;Bülow R;Wolk DA;Shou H;Nasrallah IM;Davatzikos C;iSTAGING and PHENOM consortia
通讯作者：
iSTAGING and PHENOM consortia
影响因子：
11.5
作者：
Beig, Niha;Bera, Kaustav;Tiwari, Pallavi
通讯作者：
Tiwari, Pallavi