Position-based dynamics simulator of vessel deformations for path planning in robotic endovascular catheterization

A major challenge during autonomous navigation in endovascular interventions is the complexity of operating in a deformable but constrained workspace with an instrument. Simulation of deformations for it can provide a cost-effective training platform for path planning. Aim of this study is to develop a realistic, auto-adaptive, and visually plausible simulator to predict vessels’ global deformation induced by the robotic catheter’s contact and cyclic heartbeat motion. Based on a Position-based Dynamics (PBD) approach for vessel modeling, Particle Swarm Optimization (PSO) algorithm is employed for an auto-adaptive calibration of PBD deformation parameters and of the vessels movement due to a heartbeat. In-vitro experiments were conducted and compared with in-silico results. The end-user evaluation results were reported through quantitative performance metrics and a 5-Point Likert Scale questionnaire. Compared with literature, this simulator has an error of 0.23±0.13% for deformation and 0.30±0.85mm for the aortic root displacement. In-vitro experiments show an error of 1.35±1.38mm for deformation prediction. The end-user evaluation results show that novices are more accustomed to using joystick controllers, and cardiologists are more satisfied with the visual authenticity. The real-time and accurate performance of the simulator make this framework suitable for creating a dynamic environment for autonomous navigation of robotic catheters

Prevalence of Coronary Microvascular Disease and Coronary Vasospasm in Patients With Nonobstructive Coronary Artery Disease: Systematic Review and Meta-Analysis

Background A relevant proportion of patients with suspected coronary artery disease undergo invasive coronary angiography showing normal or nonobstructive coronary arteries. However, the prevalence of coronary microvascular disease (CMD) and coronary spasm in patients with nonobstructive coronary artery disease remains to be determined. The objective of this study was to determine the prevalence of coronary CMD and coronary vasospastic angina in patients with no obstructive coronary artery disease. Methods and Results A systematic review and meta-analysis of studies assessing the prevalence of CMD and vasospastic angina in patients with no obstructive coronary artery disease was performed. Random-effects models were used to determine the prevalence of these 2 disease entities. Fifty-six studies comprising 14 427 patients were included. The pooled prevalence of CMD was 0.41 (95% CI, 0.36-0.47), epicardial vasospasm 0.40 (95% CI, 0.34-0.46) and microvascular spasm 24% (95% CI, 0.21-0.28). The prevalence of combined CMD and vasospastic angina was 0.23 (95% CI, 0.17-0.31). Female patients had a higher risk of presenting with CMD compared with male patients (risk ratio, 1.45 [95% CI, 1.11-1.90]). CMD prevalence was similar when assessed using noninvasive or invasive diagnostic methods. Conclusions In patients with no obstructive coronary artery disease, approximately half of the cases were reported to have CMD and/or coronary spasm. CMD was more prevalent among female patients. Greater awareness among physicians of ischemia with no obstructive coronary arteries is urgently needed for accurate diagnosis and patient-tailored management. Keywords: angina with nonobstructive coronary artery disease; ischemia with no obstructive coronary artery disease; vasospastic angina

Position-based dynamics simulator of vessel deformations for path planning in robotic endovascular catheterization

A major challenge during autonomous navigation in endovascular interventions is the complexity of operating in a deformable but constrained workspace with an instrument. Simulation of deformations for it can provide a cost-effective training platform for path planning. Aim of this study is to develop a realistic, auto-adaptive, and visually plausible simulator to predict vessels’ global deformation induced by the robotic catheter's contact and cyclic heartbeat motion. Based on a Position-based Dynamics (PBD) approach for vessel modeling, Particle Swarm Optimization (PSO) algorithm is employed for an auto-adaptive calibration of PBD deformation parameters and of the vessels movement due to a heartbeat. In-vitro experiments were conducted and compared with in-silico results. The end-user evaluation results were reported through quantitative performance metrics and a 5-Point Likert Scale questionnaire. Compared with literature, this simulator has an error of 0.23±0.13% for deformation and 0.30±0.85mm for the aortic root displacement. In-vitro experiments show an error of 1.35±1.38mm for deformation prediction. The end-user evaluation results show that novices are more accustomed to using joystick controllers, and cardiologists are more satisfied with the visual authenticity. The real-time and accurate performance of the simulator make this framework suitable for creating a dynamic environment for autonomous navigation of robotic catheters

Model-to-Image Registration via Deep Learning towards Image-Guided Endovascular Interventions

Cardiologists highlight the need for an intra-operative 3D visualization to assist interventions. The intra-operative 2D X-ray/Digital Subtraction Angiography (DSA) images in the standard clinical workflow limit cardiologists’ views significantly. Compared with image-to-image registration, model-to-image registration is an essential approach taking advantage of the reuse of pre-operative 3D models reconstructed from Computed Tomography Angiography (CTA) images. Traditional optimized-based registration methods suffer severely from high computational complexity. Moreover, the consequence of lacking ground truth for learning-based registration approaches should not be neglected. To overcome these challenges, we introduce a model-to-image registration framework via deep learning for image-guided endovascular catheterization. This work performs autonomous vessel segmentation from intra-operative fluoroscopy images via a deep residual U-net and a model-to-image matching via a convolutional neural network. For this study, image data were collected from 10 patients who performed Transcatheter Aortic Valve Implantation (TAVI) procedures. It was found that vessel segmentation of test data results in median values of Dice Similarity Coefficient, Precision, and Recall of (0.75, 0.58, 0.67) for femoral artery, and (0.71, 0.56, 0.74) for aortic root. The segmentation network behaves better than manual annotation, and it recognizes part of vessels that were not labeled manually. Image matching between the transformed moving image and the fixed image results in a median value of Recall of 0.90. The proposed approach achieves a good accuracy of vessel segmentation and a good recall value of model-to-image matching.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Medical Instruments & Bio-Inspired Technolog

#FullPhysiology: a systematic step-by-step guide to implement intracoronary physiology in daily practice

: #FullPhysiology is a comprehensive and systematic approach to evaluate patients with suspected coronary disease using PressureWire technology (Abbott Vascular, Santa Clara, CA, USA). This advancement in technology enables the investigation of each component of the coronary circulation, including epicardial, microvascular, and vasomotor function, without significantly increasing procedural time or technical complexity. By identifying the predominant physiopathology responsible for myocardial ischemia, #FullPhysiology enhances precision medicine by providing accurate diagnosis and facilitating tailored interventional or medical treatments. This overview aims to provide insights into modern coronary physiology and describe a systematic approach to assess epicardial flow-limiting disease, longitudinal physiological vessel analysis, microvascular and vasomotor dysfunction, as well as post- percutaneous coronary intervention (PCI) physiological results

Prevalence of coronary microvascular disease and coronary vasospasm in patients with nonobstructive coronary artery disease: systematic review and meta‐analysis

Background: A relevant proportion of patients with suspected coronary artery disease undergo invasive coronary angiography showing normal or nonobstructive coronary arteries. However, the prevalence of coronary microvascular disease (CMD) and coronary spasm in patients with nonobstructive coronary artery disease remains to be determined. The objective of this study was to determine the prevalence of coronary CMD and coronary vasospastic angina in patients with no obstructive coronary artery disease. Methods and Results: A systematic review and meta‐analysis of studies assessing the prevalence of CMD and vasospastic angina in patients with no obstructive coronary artery disease was performed. Random‐effects models were used to determine the prevalence of these 2 disease entities. Fifty‐six studies comprising 14 427 patients were included. The pooled prevalence of CMD was 0.41 (95% CI, 0.36–0.47), epicardial vasospasm 0.40 (95% CI, 0.34–0.46) and microvascular spasm 24% (95% CI, 0.21–0.28). The prevalence of combined CMD and vasospastic angina was 0.23 (95% CI, 0.17–0.31). Female patients had a higher risk of presenting with CMD compared with male patients (risk ratio, 1.45 [95% CI, 1.11–1.90]). CMD prevalence was similar when assessed using noninvasive or invasive diagnostic methods. Conclusions: In patients with no obstructive coronary artery disease, approximately half of the cases were reported to have CMD and/or coronary spasm. CMD was more prevalent among female patients. Greater awareness among physicians of ischemia with no obstructive coronary arteries is urgently needed for accurate diagnosis and patient‐tailored management

Vessel Fractional Flow Reserve and Graft Vasculopathy in Heart Transplant Recipients

Background. Cardiac allograft vasculopathy (CAV) remains the Achilles’ heel of long-term survival after heart transplantation (HTx). The severity and extent of CAV is graded with conventional coronary angiography (COR) which has several limitations. Recently, vessel fractional flow reserve (vFFR) derived from COR has emerged as a diagnostic computational tool to quantify the functional severity of coronary artery disease. Purpose. The present study assessed the usefulness of vFFR to detect CAV in HTx recipients. Methods. In HTx patients referred for annual check-up, undergoing surveillance COR, the extent of CAV was graded according to the criteria proposed by the international society of heart and lung transplantation (ISHLT). In addition, three-dimensional coronary geometries were constructed from COR to calculate pressure losses using vFFR. Results. In 65 HTx patients with a mean age of 53.7 ± 10.1 years, 8.5 years (IQR 1.90, 15.2) years after HTx, a total number of 173 vessels (59 LAD, 61 LCX, and 53 RCA) were analyzed. The mean vFFR was 0.84 ± 0.15 and median was 0.88 (IQR 0.79, 0.94). A vFFR ≤ 0.80 was present in 24 patients (48 vessels). HTx patients with a history of ischemic cardiomyopathy (ICMP) had numerically lower vFFR as compared to those with non-ICMP (0.70 ± 0.22 vs. 0.79 ± 0.13, p=0.06). The use of vFFR reclassified 31.9% of patients compared to the anatomical ISHLT criteria. Despite a CAV score of 0, a pathological vFFR ≤ 0.80 was detected in 8 patients (34.8%). Conclusion. The impairment in epicardial conductance assessed by vFFR in a subgroup of patients without CAV according to standard ISHLT criteria suggests the presence of a diffuse vasculopathy undetectable by conventional angiography. Therefore, we speculate that vFFR may be useful in risk stratification after HTx