Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA.
School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Brain. 2023 Apr 19;146(4):1281-1298. doi: 10.1093/brain/awac450.
Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.
胶质母细胞瘤是最具侵袭性的成人原发性脑肿瘤。胶质母细胞瘤患者的中位生存期仍约为 15 个月，5 年生存率<10%。目前的治疗选择有限，自 2011 年以来，标准治疗方案基本保持不变。在过去十年中，已经研究了多种不同的治疗方案，但收效甚微。由于胶质母细胞瘤肿瘤高度异质性和侵袭性，目前的治疗策略几乎不可避免地会导致肿瘤复发。此外，胶质母细胞瘤患者面临的另一个挑战是如何区分肿瘤进展和治疗效果，尤其是在临床中依赖常规诊断成像技术时。由于治疗后效果的外观相似，常规成像在早期或及时识别肿瘤进展的特异性较差。在这里，我们简要描述了目前在评估和早期预测治疗反应以及早期检测肿瘤进展或复发方面的现状和挑战。我们还总结和讨论了一些先进方法的研究，如定量成像、液体生物标志物发现和机器智能，这些方法具有很大的潜力，可以帮助监测这种恶性肿瘤的治疗，并对治疗反应进行早期预测，这可能会在精准医学时代彻底改变传统的检测方法。
