Determining blood flow direction from short neurovascular surgical microscope videos. Issue 6 (26th November 2019)

• Record Type: Journal Article
• Authors: Vassallo, Reid; Rankin, Adam; Lownie, Stephen P.; Fukuda, Hitoshi; Kasuya, Hidetoshi; Lo, Benjamin W.Y.; Peters, Terry; Xiao, Yiming
• Is Part Of: Healthcare technology letters. Volume 6:Issue 6(2019)
• Page Start: 191
• Page End: 196
• Publication Date: 2019-11-26
• Subjects: biomechanics -- blood vessels -- image segmentation -- brain -- bone -- blood -- augmented reality -- biomedical optical imaging -- biomedical ultrasonics -- surgery -- diseases -- medical image processing -- haemodynamics -- neurophysiology -- phantoms; blood flow direction -- short neurovascular surgical microscope videos -- neurovascular surgery -- damaged blood vessels -- static pre‐operative images -- routinely used surgical microscopes -- blood pulsation -- surgical videos -- video segments -- subtle colour fluctuations -- Fourier space -- physical phantom; Biomedical engineering -- Periodicals; Medical technology -- Periodicals; 610.28
• DOI: 10.1049/htl.2019.0080
• Languages: English
• ISSNs: 2053-3713

Abstract

Abstract : Neurovascular surgery aims to repair diseased or damaged blood vessels in the brain or spine. There are numerous procedures that fall under this category, and in all of them, the direction of blood flow through these vessels is crucial information. Current methods to determine this information intraoperatively include static pre‐operative images combined with augmented reality, Doppler ultrasound, and injectable fluorescent dyes. Each of these systems has inherent limitations. This study includes the proposal and preliminary validation of a technique to identify the direction of blood flow through vessels using only video segments of a few seconds acquired from routinely used surgical microscopes. The video is enhanced to reveal subtle colour fluctuations related to blood pulsation, and these rhythmic signals are further analysed in Fourier space to reveal the direction of blood flow. The proposed method was validated using a novel physical phantom and retrospective analysis of surgical videos and demonstrated high accuracy in identifying the direction of blood flow.