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Christoph Strecker

Publications and source records attributed to Christoph Strecker.

4 recordsLinked to original sources

Comparative Evaluation of Carotid Artery Hemodynamics: Patient-Specific CFD Simulations vs. 4D flow MRI

Wall shear stress (WSS) is implicated in carotid atherosclerosis, and 4D flow MRI offers a non-invasive route to its estimation, but the agreement of MRI-derived plaque-surface WSS with computational fluid dynamics (CFD) has not been quantified in a large cohort. We compared peak-systolic velocity and WSS from 4D flow MRI and patient-specific CFD in 240 carotid arteries of 120 patients, with CFD geometries and boundary conditions derived from MRI. Velocity and circumferential WSS were compared at three standardized cross-sections, and plaque-surface WSS in 63 of 149 stenosed arteries with a reliably segmented plaque. Agreement was assessed with Bland-Altman analysis, Spearman correlation with stenosis degree, and exploratory multivariable regression of the plaque-surface discrepancy on hemodynamic and geometric variables. MRI reproduced the broad flow features but underestimated peak velocity, increasingly toward the distal internal carotid artery. WSS disagreement was location dependent: mean circumferential WSS showed little average bias in the common carotid artery, whereas MRI missed the high WSS at the bifurcation apex and underestimated plaque-surface mean and maximum WSS by $40.9 \pm 28.8\%$ and $44.5 \pm 26.8\%$; the difference in Pa increased with stenosis degree ($ρ= 0.47$ and $0.50$). In exploratory regression, the CFD-derived pressure drop across the plaque was the only significant correlate of the mean WSS discrepancy, whereas stenosis degree and geometric variables were associated with the maximum WSS discrepancy. Under the present protocol, MRI-derived plaque-surface WSS showed magnitude- and location-dependent disagreement with CFD, greater in more severely stenosed arteries and, in exploratory analyses, associated with factors beyond stenosis degree.

physics.flu-dyn↗

CaroTo: A Tool for Fast Comprehensive Analysis of Carotid Artery Stenosis in 4D PC- and 3D BB-MRI Data

Atherosclerosis of the carotid artery increases stroke risk. Atherosclerosis assessment with MRI requires multimodal and multidimensional segmentation of the carotid artery, reproducible extraction of biomarkers, and the visualization of segmentations and biomarkers. We developed CaroTo, a tool that allows for standardized carotid atherosclerosis assessment. It combines the capabilities of MEVISFlow with specialized tools for carotid geometry and vessel wall assessment. It supports manual and automatic segmentation for 2D, 2D+time, and 3D images, facilitating precise and consistent evaluations of carotid artery stenosis.

eess.IV↗

Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations

We propose a novel approach that uses sparse annotations from clinical studies to train a 3D segmentation of the carotid artery wall. We use a centerline annotation to sample perpendicular cross-sections of the carotid artery and use an adversarial 2D network to segment them. These annotations are then transformed into 3D pseudo-labels for training of a 3D convolutional neural network, circumventing the creation of manual 3D masks. For pseudo-label creation in the bifurcation area we propose the use of cross-sections perpendicular to the bifurcation axis and show that this enhances segmentation performance. Different sampling distances had a lesser impact. The proposed method allows for efficient training of 3D segmentation, offering potential improvements in the assessment of carotid artery stenosis and allowing the extraction of 3D biomarkers such as plaque volume.

cs.CV↗

Carotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations

Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters have potential applications in stroke risk analysis, evaluation of therapy effectiveness, and plaque progression prediction. Methods: We propose a novel method for extracting a plaque mesh from 3D vessel wall segmentation using distance encoding on the inner and outer wall mesh for precise plaque structure analysis. A case-specific threshold, derived from the normal vessel wall thickness, was applied to extract plaques from a dataset of 202 T1-weighted black-blood MRI scans of subjects with up to 50% stenosis. Applied to baseline and one-year follow-up data, the method supports detailed plaque morphology analysis over time, including plaque volume quantification, aided by improved visualization via mesh unfolding. Results: We successfully extracted plaque meshes from 341 carotid arteries, capturing a wide range of plaque shapes with volumes ranging from 2.69μl to 847.7μl. The use of a case-specific threshold effectively eliminated false positives in young, healthy subjects. Conclusion: The proposed method enables precise extraction of plaque meshes from 3D vessel wall segmentation masks enabling a correspondence between baseline and one-year follow-up examinations. Unfolding the plaque meshes enhances visualization, while the mesh-based analysis allows quantification of plaque parameters independent of voxel resolution.

cs.CV↗