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多层自适应新生血管内术中定量 (MANIOQ)。

Multi-layered adaptive neoangiogenesis Intra-Operative quantification (MANIOQ).

机构信息

UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.

UMR 1253, iBrain and the CHRU de Tours, Neurosurgical Department, Indre et Loire, Tours, France.

出版信息

J Cereb Blood Flow Metab. 2023 Sep;43(9):1557-1570. doi: 10.1177/0271678X231170504. Epub 2023 Apr 18.

Abstract

Quantification of vascularization volume can provide valuable information for diagnosis and prognosis in vascular pathologies. It can be adapted to inform the surgical management of gliomas, aggressive brain tumors characterized by exuberant sprouting of new blood vessels (neoangiogenesis). Filtered ultrafast Doppler data can provide two main parameters: vascularization index (VI) and fractional moving blood volume (FMBV) that clinically reflect tumor micro vascularization. Current protocols lack robust, automatic, and repeatable filtering methods. We present a filtrating method called Multi-layered Adaptive Neoangiogenesis Intra-Operative Quantification (MANIOQ). First, an adaptive clutter filtering is implemented, based on singular value decomposition (SVD) and hierarchical clustering. Second a method for noise equalization is applied, based on the subtraction of a weighted noise profile. Finally, an analysis of the periphery of the B-mode hyper signal area allows to measure the vascular infiltration extent of the brain tumors. Ninety ultrasound acquisitions were processed from 23 patients. Compared to reference methods in the literature, MANIOQ provides a more robust tissue filtering, and noise equalization allows for the first time to keep axial and lateral gain compensation (TGC and LGC). MANIOQ opens the way to an intra-operative clinical analysis of gliomas micro vascularization.

摘要

血管化体积的量化可以为血管病变的诊断和预后提供有价值的信息。它可以适应于胶质瘤的手术管理,胶质瘤是一种以新血管(新生血管生成)过度发芽为特征的侵袭性脑肿瘤。过滤的超快多谱勒数据可以提供两个主要参数:血管化指数(VI)和分数运动血液体积(FMBV),这两个参数在临床上反映了肿瘤微血管化。目前的方案缺乏强大、自动和可重复的过滤方法。我们提出了一种称为多层自适应新生血管术中量化(MANIOQ)的过滤方法。首先,基于奇异值分解(SVD)和层次聚类实现自适应杂波过滤。其次,应用了一种基于加权噪声轮廓减法的噪声均衡方法。最后,对 B 模式高信号区域的外围进行分析,以测量脑肿瘤的血管浸润程度。对 23 名患者的 90 次超声采集进行了处理。与文献中的参考方法相比,MANIOQ 提供了更强大的组织过滤,噪声均衡允许首次保持轴向和侧向增益补偿(TGC 和 LGC)。MANIOQ 为胶质瘤微血管化的术中临床分析开辟了道路。

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