Intraoperative superb microvascular ultrasound imaging in glioma: novel quantitative analysis correlates with tumour grade.

Luke Dixon, Alistair Weld, Dolin Bhagawati, Neekhil Patel, Stamatia Giannarou, Matthew Grech-Sollars, Adrian Lim, Sophie Camp
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Abstract

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.

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胶质瘤术中超级微血管超声成像:与肿瘤分级相关的新型定量分析。
胶质瘤的准确分级对于指导治疗和预测预后至关重要。微血管增生是高级别胶质瘤的标志性特征,传统上需要对代表性组织进行有针对性的手术活检。超微血管成像(SMI)是一种新型的高分辨率多普勒超声技术,能独特地确定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、分形维度和熵。结果表明,高级别胶质瘤的血管复杂性和无序性明显增加,分形维度和熵增加,与侵袭性血管生成的已知组织病理学标志物相关。综合 ROC 模型达到了很高的准确度(AUC = 0.95),凸显了 SMI 作为无创诊断和预后工具的潜力。虽然还需要用更大的数据集进行进一步验证,但这项研究为神经胶质瘤管理中的SMI开辟了道路,为术中决策提供了支持,并为未来预后提供了信息。
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