Quantitative analysis of digital subtraction angiography using optical flow method on occlusive cerebrovascular disease

Wu, Tsu‐Juey; Cc, Lin; Lin, Yang-Hsien; Guo, Wan‐Yuo; Huang, Tzung-Chi

doi:10.1016/j.cmpb.2013.06.012

Cited by 11 publications

(5 citation statements)

References 15 publications

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“…The measurement of access flow involves a complex interplay of multiple factors that includes optimizing the parameters of injection and imaging duration and managing the radiation dose in a manner that maximizes the diagnostic value with minimum risk for radiation-induced injury [43,54,60,61]. Since the determination of blood flow is entirely dependent on the analysis of radiological exams, it is necessary to have good quality images with adequate temporal information to enable accurate quantification [62,63].…”

Section: Discussionmentioning

confidence: 99%

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Koirala

McLennan

2021

Diagnostics

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Blood flow rate in dialysis (vascular) access is the key parameter to examine patency and to evaluate the outcomes of various endovascular interve7ntions. While angiography is extensively used for dialysis access–salvage procedures, to date, there is no image-based blood flow measurement application commercially available in the angiography suite. We aim to calculate the blood flow rate in the dialysis access based on cine-angiographic and fluoroscopic image sequences. In this study, we discuss image-based methods to quantify access blood flow in a flow phantom model. Digital subtraction angiography (DSA) and fluoroscopy were used to acquire images at various sampling rates (DSA—3 and 6 frames/s, fluoroscopy—4 and 10 pulses/s). Flow rates were computed based on two bolus tracking algorithms, peak-to-peak and cross-correlation, and modeled with three curve-fitting functions, gamma variate, lagged normal, and polynomial, to correct errors with transit time measurement. Dye propagation distance and the cross-sectional area were calculated by analyzing the contrast enhancement in the vessel. The calculated flow rates were correlated versus an in-line flow sensor measurement. The cross-correlation algorithm with gamma-variate curve fitting had the best accuracy and least variability in both imaging modes. The absolute percent error (mean ± SEM) of flow quantification in the DSA mode at 6 frames/s was 21.4 ± 1.9%, and in the fluoroscopic mode at 10 pulses/s was 37.4 ± 3.6%. The radiation dose varied linearly with the sampling rate in both imaging modes and was substantially low to invoke any tissue reactions or stochastic effects. The cross-correlation algorithm and gamma-variate curve fitting for DSA acquisition at 6 frames/s had the best correlation with the flow sensor measurements. These findings will be helpful to develop a software-based vascular access flow measurement tool for the angiography suite and to optimize the imaging protocol amenable for computational flow applications.

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Section: Discussionmentioning

confidence: 99%

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Koirala

McLennan

2021

Diagnostics

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“…The velocity of moving blood cells can also be measured by estimating the slope of the spacetime diagram of the light intensity changes in a line selected along a blood vessel [32]; however, this also results in the sacrifice of spatial resolution. To improve the spatial resolution of PIV, optical flow analysis is introduced, to trace the blood-flow velocity [33][34][35][36][37][38]. Given the assumption of constancy and similarity in the local brightness patterns in classic optical flow theory, the variation in the pixel brightness between consecutive frames is used to calculate the direction and speed of the moving blood cells.…”

Section: Introductionmentioning

confidence: 99%

Optical Flow-Based Full-Field Quantitative Blood-Flow Velocimetry Using Temporal Direction Filtering and Peak Interpolation

Meng

Huang

Feng

et al. 2023

IJMS

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The quantitative measurement of the microvascular blood-flow velocity is critical to the early diagnosis of microvascular dysfunction, yet there are several challenges with the current quantitative flow velocity imaging techniques for the microvasculature. Optical flow analysis allows for the quantitative imaging of the blood-flow velocity with a high spatial resolution, using the variation in pixel brightness between consecutive frames to trace the motion of red blood cells. However, the traditional optical flow algorithm usually suffers from strong noise from the background tissue, and a significant underestimation of the blood-flow speed in blood vessels, due to the errors in detecting the feature points in optical images. Here, we propose a temporal direction filtering and peak interpolation optical flow method (TPIOF) to suppress the background noise, and improve the accuracy of the blood-flow velocity estimation. In vitro phantom experiments and in vivo animal experiments were performed to validate the improvements in our new method.

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“…To detect its change, blood flow has been measured before and after CAS using magnetic resonance (MR) perfusion [ 5 – 8 ], MR phase-contrast imaging [ 9 , 10 ], MR imaging with arterial spin labeling [ 11 – 13 ], X-ray computed tomography perfusion [ 14 – 23 ], nuclear studies [ 24 – 29 ], ultrasound [ 28 , 30 – 33 ], digital subtraction angiography [ 34 ], and near-infrared spectroscopy [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Multiple blood flow measurements before and after carotid artery stenting via phase-contrast magnetic resonance imaging: An observational study

et al. 2018

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After carotid artery stenting, the procurement of information about blood flow redistribution among brain-feeding arteries and its time trend is essential to understanding a patient’s physiological background and to determine their care regimen. Cerebral blood flow has been measured twice following carotid artery stenting in few previous studies, with some discrepancies in the results. The purpose of this study was to measure cerebral blood flow at multiple time points after carotid artery stenting, and to elucidate the time trend of cerebral blood flow and redistribution among arteries. Blood flow rates in 11 subjects were measured preoperatively, at one day, one week, and about three months, respectively after carotid artery stenting by using phase-contrast magnetic resonance imaging. The target vessels were the bilateral internal carotid arteries, the basilar artery, and the bilateral middle cerebral arteries. Lumen was semi-automatically defined using an algorithm utilizing pulsatility. The results showed that blood flow rates in the stented internal carotid artery and the ipsilateral middle cerebral artery increased following carotid artery stenting. Blood flow rates in the contralateral internal carotid artery and the basilar artery gradually declined, and they were lower than the preoperative values at three months after stenting. The sum of blood flow rates of the bilateral internal carotid arteries and the basilar artery increased after carotid artery stenting, and then decreased over the next three months. There was no significant change in the blood flow rate in the contralateral middle cerebral artery. From these results, it was concluded that redistribution among the bilateral internal carotid arteries and the basilar artery occurs after carotid artery stenting, and that it takes months thereafter to reach another equilibrium.

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Quantitative analysis of digital subtraction angiography using optical flow method on occlusive cerebrovascular disease

Cited by 11 publications

References 15 publications

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Optical Flow-Based Full-Field Quantitative Blood-Flow Velocimetry Using Temporal Direction Filtering and Peak Interpolation

Multiple blood flow measurements before and after carotid artery stenting via phase-contrast magnetic resonance imaging: An observational study

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