Accuracy of vascular tortuosity measures using computational modelling

Kashyap, Vishesh; Gharleghi, Ramtin; Li, Darson Dezheng; McGrath-Cadell, Lucy; Graham, Robert M.; Ellis, Chris; Webster, Mark; Beier, Susann

doi:10.1038/s41598-022-04796-w

Cited by 23 publications

(8 citation statements)

References 49 publications

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“…Taking into account the significance of the vessel's physical properties for the reconstruction of clinical conditions [36,37], our study is consistent with the observations made by Pahlevan et al [37], who identified changes in the aortic pressure wave associated with varying aortic stiffness, and Li et al [38], who documented the age-related stiffening of the ascending aorta. Kashyap et al [39] analyzed the accuracy of the tortuosity index in the left main coronary artery using computational modeling, contrasting with our results, which indicated a good agreement between the experimental and clinical data. Additionally, our study differs from the findings of Malve et al and Pinho et al [40,41], who noted higher averages and wider spreads of the WSS values.…”

Section: Discussioncontrasting

confidence: 95%

Reconstruction of the Physiological Behavior of Real and Synthetic Vessels in Controlled Conditions

Polanczyk,

Piechota-Polanczyk,

Piastowska-Ciesielska

et al. 2024

Applied Sciences

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The objective of this study is to assess the ability of an Artificial Circulatory Phantom (ACP) to verify its accuracy in simulating the movement of artificial vessels vs. real vessels under changing cardiovascular parameters such as heartbeat, ejection fraction, and total peripheral resistance. The experiments were conducted with blood-like fluid that flows through two types of vessels: iliac arteries and different types of ePTFE vascular prostheses. Parameters such as diameter and tortuosity were measured and analyzed. The flow characteristics included a pulsating pattern with a frequency of 60–120 min−1 and ejection volumes ranging from 70 to 115 mL. The results showed a predominantly positive correlation between wall displacement (Wd) and tortuosity index (Ti) for the iliac artery (R2 = 0.981), as well as between Wd and mean tortuosity index (MTi) (R2 = 0.994). Similarly, positive correlations between Wd and Ti (R2 = 0.942) and Wd and MTi (R2 = 0.922) were computed for the ePTFE vascular prosthesis. The ACP introduced in this study is a valuable tool for evaluating various vessel types and the spatial configurations of vascular prostheses under diverse hemodynamic conditions. These findings are promising for the advancement of novel approaches to the testing and design of vascular grafts, ultimately enhancing their patency rates in future applications.

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Section: Discussioncontrasting

confidence: 95%

Reconstruction of the Physiological Behavior of Real and Synthetic Vessels in Controlled Conditions

Polanczyk,

Piechota-Polanczyk,

Piastowska-Ciesielska

et al. 2024

Applied Sciences

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“…DDS Cursor velocities were oriented toward the target (within the angle formed by the pair of lines tangent to the two sides of the target) more often than other decoders ( Fig.2E ) and DDS had substantially more trajectories that moved toward the target throughout the entire trial (sharp increase at the 100% bin). We evaluated cursor path simplicity using a tortuosity measure that integrates the instantaneous curvature derivative 27 , such that simple constant curvature shapes (an arc of a circle or straight-line segment) have zero tortuosity. We found that ≈11% of all DDS trajectories were completely straight ( Fig.2F , bottom points).…”

Section: Resultsmentioning

confidence: 99%

Less is more: selection from a small set of options improves BCI velocity control

Alcolea,

Ma,

Bodkin

et al. 2024

Preprint

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We designed the discrete direction selection (DDS) decoder for intracortical brain computer interface (iBCI) cursor control and showed that it outperformed currently used decoders in a human-operated real-time iBCI simulator and in monkey iBCI use. Unlike virtually all existing decoders that map between neural activity and continuous velocity commands, DDS uses neural activity to select among a small menu of preset cursor velocities. We compared closed-loop cursor control across four visits by each of 48 naïve, able-bodied human subjects using either DDS or one of three common continuous velocity decoders: direct regression with assist (an affine map from neural activity to cursor velocity), ReFIT, and the velocity Kalman Filter. DDS outperformed all three by a substantial margin. Subsequently, a monkey using an iBCI also had substantially better performance with DDS than with the Wiener filter decoder (direct regression decoder that includes time history). Discretizing the decoded velocity with DDS effectively traded high resolution velocity commands for less tortuous and lower noise trajectories, highlighting the potential benefits of simplifying online iBCI control.

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“…The study recently published demonstrates that curvature-based methods exhibit greater consistency and intuitiveness compared to the tortuosity index. Additionally, it highlights an inherent limitation in metrics like the tortuosity index, which fail to account for the entirety of the geometry 30 .…”

Section: Methodsmentioning

confidence: 99%

Automated diagnosis of plus disease in retinopathy of prematurity using quantification of vessels characteristics

Sharafi,

Ebrahimiadib,

Roohipourmoallai

et al. 2024

Sci Rep

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The condition known as Plus disease is distinguished by atypical alterations in the retinal vasculature of neonates born prematurely. It has been demonstrated that the diagnosis of Plus disease is subjective and qualitative in nature. The utilization of quantitative methods and computer-based image analysis to enhance the objectivity of Plus disease diagnosis has been extensively established in the literature. This study presents the development of a computer-based image analysis method aimed at automatically distinguishing Plus images from non-Plus images. The proposed methodology conducts a quantitative analysis of the vascular characteristics linked to Plus disease, thereby aiding physicians in making informed judgments. A collection of 76 posterior retinal images from a diverse group of infants who underwent screening for Retinopathy of Prematurity (ROP) was obtained. A reference standard diagnosis was established as the majority of the labeling performed by three experts in ROP during two separate sessions. The process of segmenting retinal vessels was carried out using a semi-automatic methodology. Computer algorithms were developed to compute the tortuosity, dilation, and density of vessels in various retinal regions as potential discriminative characteristics. A classifier was provided with a set of selected features in order to distinguish between Plus images and non-Plus images. This study included 76 infants (49 [64.5%] boys) with mean birth weight of 1305 ± 427 g and mean gestational age of 29.3 ± 3 weeks. The average level of agreement among experts for the diagnosis of plus disease was found to be 79% with a standard deviation of 5.3%. In terms of intra-expert agreement, the average was 85% with a standard deviation of 3%. Furthermore, the average tortuosity of the five most tortuous vessels was significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The curvature values based on points were found to be significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The maximum diameter of vessels within a region extending 5-disc diameters away from the border of the optic disc (referred to as 5DD) exhibited a statistically significant increase in Plus images compared to non-Plus images (p ≤ 0.0001). The density of vessels in Plus images was found to be significantly higher compared to non-Plus images (p ≤ 0.0001). The classifier's accuracy in distinguishing between Plus and non-Plus images, as determined through tenfold cross-validation, was found to be 0.86 ± 0.01. This accuracy was observed to be higher than the diagnostic accuracy of one out of three experts when compared to the reference standard. The implemented algorithm in the current study demonstrated a commendable level of accuracy in detecting Plus disease in cases of retinopathy of prematurity, exhibiting comparable performance to that of expert diagnoses. By engaging in an objective analysis of the characteristics of vessels, there exists the possibility of conducting a quantitative assessment of the disease progression's features. The utilization of this automated system has the potential to enhance physicians' ability to diagnose Plus disease, thereby offering valuable contributions to the management of ROP through the integration of traditional ophthalmoscopy and image-based telemedicine methodologies.

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Accuracy of vascular tortuosity measures using computational modelling

Cited by 23 publications

References 49 publications

Reconstruction of the Physiological Behavior of Real and Synthetic Vessels in Controlled Conditions

Reconstruction of the Physiological Behavior of Real and Synthetic Vessels in Controlled Conditions

Less is more: selection from a small set of options improves BCI velocity control

Automated diagnosis of plus disease in retinopathy of prematurity using quantification of vessels characteristics

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