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

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 in vivo 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.

Automated summary

Quantification of vascularization volume provides valuable information for vascular pathologies. An adaptive clutter filtering and noise equalization method called MANIOQ is proposed to analyze the microvascularization in gliomas intra-operatively.