Abstract：
Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. Large and complex amounts of data from liquid biopsy can be simplified by machine learning using various algorithms. By using this technique, we can diagnose brain tumours and differentiate low versus highgrade glioma and true progression from pseudo-progression. The potential of liquid biopsy in brain tumours has not been extensively studied, but it has a bright future in the coming years. Here, we present a literature review on the role of machine learning in liquid biopsy of brain tumours.
摘要：
液体活检具有多种益处，并广泛用于肿瘤学的其他领域，但迄今为止，它在神经肿瘤学中的作用有限。多种肿瘤来源的材料，如循环肿瘤细胞（CTC），肿瘤培养的血小板（TEP），无细胞DNA（cfDNA），循环肿瘤DNA（ctDNA），在CSF中研究miRNA，血液（血浆，血清）或尿液。可以通过使用各种算法的机器学习来简化来自液体活检的大量复杂数据。通过使用这种技术，我们可以诊断脑肿瘤，并区分低度和高度胶质瘤以及真实进展和假性进展。液体活检在脑肿瘤中的潜力尚未得到广泛研究，但它在未来几年有一个光明的未来。这里,我们对机器学习在脑肿瘤液体活检中的作用进行了文献综述。
