Dedhia Mehek, Germano Isabelle M
Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Cancers (Basel). 2025 May 6;17(9):1582. doi: 10.3390/cancers17091582.
Gliomas are the most prevalent and aggressive form of primary brain tumors. The clinical challenge in managing patients with this disease revolves around the difficulty of diagnosis, both at onset and during treatment, and the scarcity of prognostic outcome indicators. Radiomics involves the extraction of quantitative features from medical images with the help of artificial intelligence, positioning it as a promising tool to be integrated into the care of glioma patients. Using data from 52 studies and 12,482 patients over two years, this review explores how radiomics can enhance the initial diagnosis of gliomas, especially helping to differentiate treatment stages that may be difficult for the human eye to do otherwise. Radiomics has also been able to identify patient-specific tumor molecular signatures for targeted treatments without the need for invasive surgical biopsy. Such an approach could lead to earlier interventions and more precise individualized therapies that are tailored to each patient. Additionally, it could be integrated into clinical practice to improve longitudinal diagnosis during treatment and predict tumor recurrence. Finally, radiomics has the potential to predict clinical outcomes, helping both patients and providers set realistic expectations. While this field is continuously evolving, future research should conduct such studies in larger, multi-institutional cohorts to enhance generalizability and applicability in clinical practice and focus on combining radiomics with other modalities to improve its predictive accuracy and clinical utility.
神经胶质瘤是原发性脑肿瘤中最常见且侵袭性最强的类型。对患有这种疾病的患者进行治疗时面临的临床挑战主要围绕诊断的困难，包括发病时和治疗期间，以及预后结果指标的匮乏。放射组学涉及借助人工智能从医学图像中提取定量特征，使其成为有望整合到神经胶质瘤患者护理中的工具。本综述利用两年内来自52项研究和12482名患者的数据，探讨了放射组学如何增强神经胶质瘤的初始诊断，特别是有助于区分人眼难以做到的治疗阶段。放射组学还能够识别患者特异性的肿瘤分子特征，用于靶向治疗而无需进行侵入性手术活检。这种方法可以实现更早的干预以及为每个患者量身定制的更精确的个性化治疗。此外，它可以整合到临床实践中，以改善治疗期间的纵向诊断并预测肿瘤复发。最后，放射组学有潜力预测临床结果，帮助患者和医疗人员树立现实的预期。虽然该领域在不断发展，但未来的研究应在更大规模的多机构队列中开展此类研究，以提高其在临床实践中的普遍性和适用性，并专注于将放射组学与其他方法相结合，以提高其预测准确性和临床实用性。
