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神经肿瘤学的现代化:影像学、液体活检和人工智能对诊断与治疗的影响

Modernizing Neuro-Oncology: The Impact of Imaging, Liquid Biopsies, and AI on Diagnosis and Treatment.

作者信息

Rafanan John, Ghani Nabih, Kazemeini Sarah, Nadeem-Tariq Ahmed, Shih Ryan, Vida Thomas A

机构信息

Department of Medical Education, Kirk Kerkorian School of Medicine at UNLV, 625 Shadow Lane, Las Vegas, NV 89106, USA.

出版信息

Int J Mol Sci. 2025 Jan 22;26(3):917. doi: 10.3390/ijms26030917.

Abstract

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemoradiotherapy, the prognosis for glioblastoma multiforme (GBM) and brain metastases remains poor, underscoring the need for innovative diagnostic strategies. This review highlights recent advancements in imaging techniques, liquid biopsies, and artificial intelligence (AI) applications addressing current diagnostic challenges. Advanced imaging techniques, including diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS), improve the differentiation of tumor progression from treatment-related changes. Additionally, novel positron emission tomography (PET) radiotracers, such as F-fluoropivalate, F-fluoroethyltyrosine, and F-fluluciclovine, facilitate metabolic profiling of high-grade gliomas. Liquid biopsy, a minimally invasive technique, enables real-time monitoring of biomarkers such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), circulating tumor cells (CTCs), and tumor-educated platelets (TEPs), enhancing diagnostic precision. AI-driven algorithms, such as convolutional neural networks, integrate diagnostic tools to improve accuracy, reduce interobserver variability, and accelerate clinical decision-making. These innovations advance personalized neuro-oncological care, offering new opportunities to improve outcomes for patients with central nervous system tumors. We advocate for future research integrating these tools into clinical workflows, addressing accessibility challenges, and standardizing methodologies to ensure broad applicability in neuro-oncology.

摘要

神经肿瘤学的进展已经改变了脑肿瘤的诊断和管理方式,脑肿瘤因其高死亡率和复杂的神经学影响而成为最具挑战性的恶性肿瘤之一。尽管手术以及放化疗取得了进展,但多形性胶质母细胞瘤(GBM)和脑转移瘤的预后仍然很差,这凸显了创新诊断策略的必要性。本综述重点介绍了成像技术、液体活检和人工智能(AI)应用方面的最新进展,这些进展应对了当前的诊断挑战。先进的成像技术,包括扩散张量成像(DTI)和磁共振波谱(MRS),改善了肿瘤进展与治疗相关变化的鉴别。此外,新型正电子发射断层扫描(PET)放射性示踪剂,如F-氟新戊酸、F-氟乙基酪氨酸和F-氟卢西克洛维,有助于对高级别胶质瘤进行代谢分析。液体活检是一种微创技术,能够实时监测生物标志物,如循环肿瘤DNA(ctDNA)、细胞外囊泡(EVs)、循环肿瘤细胞(CTCs)和肿瘤诱导血小板(TEPs),提高诊断精度。人工智能驱动的算法,如卷积神经网络,整合诊断工具以提高准确性,减少观察者间的差异,并加速临床决策。这些创新推动了个性化神经肿瘤护理的发展,为改善中枢神经系统肿瘤患者的治疗结果提供了新机会。我们倡导未来开展研究,将这些工具整合到临床工作流程中,解决可及性挑战,并规范方法,以确保其在神经肿瘤学中的广泛应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9d5/11817476/ae7ed88a5565/ijms-26-00917-g001.jpg

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