Dixon Luke, Weld Alistair, Bhagawati Dolin, Patel Neekhil, Giannarou Stamatia, Grech-Sollars Matthew, Lim Adrian, Camp Sophie
medRxiv. 2024 Dec 8:2024.12.07.24318636. doi: 10.1101/2024.12.07.24318636.
Accurate grading of gliomas is critical to guide therapy and predict prognosis. The presence of microvascular proliferation is a hallmark feature of high grade gliomas which traditionally requires targeted surgical biopsy of representative tissue. Superb microvascular imaging (SMI) is a novel high resolution Doppler ultrasound technique which can uniquely define the microvascular architecture of whole tumours. We examined both qualitative and quantitative vascular features of gliomas captured with SMI, analysing flow signal density, vessel number, branching points, curvature, vessel angle deviation, fractal dimension, and entropy. Results indicate that high-grade gliomas exhibit significantly greater vascular complexity and disorganisation, with increased fractal dimension and entropy, correlating with known histopathological markers of aggressive angiogenesis. The integrated ROC model achieved high accuracy (AUC = 0.95), highlighting SMI's potential as a non-invasive diagnostic and prognostic tool. While further validation with larger datasets is required, this study opens avenues for SMI in glioma management, supporting intraoperative decision-making and informing future prognosis.
准确分级胶质瘤对于指导治疗和预测预后至关重要。微血管增殖的存在是高级别胶质瘤的一个标志性特征,传统上这需要对代表性组织进行靶向手术活检。超微血管成像(SMI)是一种新型高分辨率多普勒超声技术,它能够独特地定义整个肿瘤的微血管结构。我们研究了用SMI捕获的胶质瘤的定性和定量血管特征,分析了血流信号密度、血管数量、分支点、曲率、血管角度偏差、分形维数和熵。结果表明,高级别胶质瘤表现出显著更高的血管复杂性和紊乱性,分形维数和熵增加,与侵袭性血管生成的已知组织病理学标志物相关。综合ROC模型具有较高的准确性(AUC = 0.95),突出了SMI作为一种非侵入性诊断和预后工具的潜力。虽然需要用更大的数据集进行进一步验证,但这项研究为SMI在胶质瘤管理中的应用开辟了道路,支持术中决策并为未来预后提供信息。