Geometry of the Carotid Bifurcation Predicts Its Exposure to Disturbed Flow

Lee, Sangwook; Antiga, Luca; Spence, J. David; Steinman, David A.

doi:10.1161/strokeaha.107.510644

Cited by 318 publications

(314 citation statements)

References 42 publications

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“…Multiple applications of CFD for the evaluation of human flow characteristics have been reported in the past years including, for example, the simulation of time-resolved 3D flow patterns in the left ventricle, in geometrically complex aneurysms, or the carotid artery bifurcation (41)(42)(43)(44)(45). Such numerical simulations permit the detailed analysis of local flow patterns and calculation of additional relevant parameters such as pressure differences or wall shear rates.…”

Section: Discussionmentioning

confidence: 99%

Three‐dimensional analysis of segmental wall shear stress in the aorta by flow‐sensitive four‐dimensional‐MRI

Frydrychowicz

Stalder

Russe

et al. 2009

Magnetic Resonance Imaging

165

138

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Purpose:To assess the distribution and regional differences of flow and vessel wall parameters such as wall shear stress (WSS) and oscillatory shear index (OSI) in the entire thoracic aorta. Materials and Methods:Thirty-one healthy volunteers (mean age ϭ 23.7 Ϯ 3.3 years) were examined by flow-sensitive four-dimensional (4D)-MRI at 3T. For eight retrospectively positioned 2D analysis planes distributed along the thoracic aorta, flow parameters and vectorial WSS and OSI were assessed in 12 segments along the vascular circumference. Conclusion:The normal distribution of vectorial WSS and OSI in the entire thoracic aorta derived from flow-sensitive 4D-MRI data provides a reference constituting an important perquisite for the examination of patients with aortic disease. Marked regional differences in absolute WSS and OSI may help explaining why atherosclerotic lesions predominantly develop and progress at specific locations in the aorta. COMPLEX VASCULAR GEOMETRY AND PULSATILE FLOW in the human arterial system lead to regionally different flow characteristics and thus spatial and temporal changes in shear forces acting on the vessel wall. These forces can be characterized by wall shear stress (WSS) or oscillatory shear index (OSI) that play an important role in flow-mediated atherogenesis and arterial remodeling (1-3). While WSS values reported in the literature typically reflect the time-averaged shear forces acting on the vessel wall, OSI describes the existence and magnitude of WSS changes over the cardiac cycle. Recent reports stressed the importance of WSS and OSI with respect to the formation and stability of atherosclerotic plaques (4). A number of studies have shown that low WSS and high OSI represent sensitive markers for formation of plaques in the aorta, carotid, or coronary arteries (5,6). Particularly, the assessment of both WSS and OSI can help to determine the complexity of the lesions. A recent study with animal models and deliberately altered flow characteristics in the carotid arteries demonstrated the close correlation of low WSS with the development of vulnerable high-risk plaques whereas high OSI induce stable lesions (4). In addition, the effects of selected pathologies on regionally-varying WSS and OSI values have been reported (7,8).Among other methods, MRI is a feasible and extensively validated technique to derive quantitative flow information from arterial vessels (9 -12). Due to its intrinsic sensitivity to flow and the possibility to acquire true time-resolved three-dimensional (3D) data, in vivo analyses of blood-flow and derived vessel wall parameters are promising. However, earlier reports on MRbased analysis of aortic hemodynamics were either based on incomplete vascular coverage and separately acquired 2D slices (13-17), a combination of MR mea-

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Section: Discussionmentioning

confidence: 99%

Three‐dimensional analysis of segmental wall shear stress in the aorta by flow‐sensitive four‐dimensional‐MRI

Frydrychowicz

Stalder

Russe

et al. 2009

Magnetic Resonance Imaging

165

138

View full text Add to dashboard Cite

show abstract

“…The observed morphometric differences imply differences in hemodynamics, by virtue of the influence of geometry on blood flow patterns [5][6][7]40] . In particular, the tilt and twist angles quantify the "distortion" of the aorta, which is expected to impart an abrupt change in the direction of blood flow.…”

Section: Discussionmentioning

confidence: 99%

“…Examples include the detection of anatomical abnormalities [1] , preoperative planning and follow-up of patients with cardiovascular diseases [2][3][4] , risk prediction associated with atherosclerosis development [5][6][7][8] , and cardiovascular devices design support [9] . In particular, morphometry-based analysis finds massive adoption for current research of mapping the effects of natural aging on the structural and functional properties of the aorta [10][11][12][13][14][15][16][17] .…”

Section: Introductionmentioning

confidence: 99%

Cardiovascular morphometry with high-resolution 3D magnetic resonance: First application to left ventricle diastolic dysfunction

Gallo

Vardoulis

Monney

et al. 2017

Medical Engineering & Physics

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a b s t r a c tIn this study, an image-based morphometry toolset quantifying geometric descriptors of the left ventricle, aorta and their coupling is applied to investigate whether morphological information can differentiate between subjects affected by diastolic dysfunction (patient group) and their age-matched controls (control group). The ventriculo-aortic region of 20 total participants (10 per group) were segmented from highresolution 3D magnetic resonance images, from the left ventricle to the descending aorta. Each geometry was divided into segments in correspondence of anatomical landmarks. The orientation of each segment was estimated by least-squares fitting of the respective centerline segment to a plane. Curvature and torsion of vessels' centerlines were automatically extracted, and aortic arch was characterized in terms of height and width.Tilt angle between subsequent best-fit planes in the left ventricle and ascending aorta regions, curvature and cross-sectional area in the descending aorta resulted significantly different between patient and control groups ( P -values < 0.05). Aortic volume ( P = 0.04) and aortic arch width ( P = 0.03) resulted significantly different between the two groups. The observed morphometric differences underlie differences in hemodynamics, by virtue of the influence of geometry on blood flow patterns.The present exploratory analysis does not determine if aortic geometric changes precede diastolic dysfunction, or vice versa. However, this study (1) underlines differences between healthy and diastolic dysfunction subjects, and (2) provides geometric parameters that might help to determine early aortic geometric alterations and potentially prevent evolution toward advanced diastolic dysfunction.

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“…According to [20], it is possible to characterize the curvature, torsion, and tortuosity by applying classical differential geometry of curves on the line segments that compose the centerline. Lee et al [21] investigated the carotid geometry and its impact in the blood flow. The exposure to the so-called "disturbed" flow may be a risk factor for atherosclerosis.…”

Section: Future Work and Discussionmentioning

confidence: 99%

Estimating 3D lumen centerlines of carotid arteries in free-hand acquisition ultrasound

et al. 2011

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Purpose The purpose of this paper is to present a methodology to estimate the carotid artery lumen centerlines in ultrasound (US) images obtained in a free-hand examination. Challenging aspects here are speckle noise in US images, artifacts, and the lack of contrast in the direction orthogonal to the US beam direction. Method An algorithm based on a rough lumen segmentation obtained by robust ellipse fitting was developed to deal with these conditions and estimate the lumen center in 2D B-mode scans. In a free-hand sweep examination, continuous image acquisitions are performed through time when the radiologist moves the probe on the patient's neck. The result is a series of images that show 2D cross-sections of the carotid's morphology. A tracking sensor (Flock of Birds) was attached to the probe and both were connected to a PC executing the Stradwin software, which relates spatial information to the acquisition data of the US probe. The spatial information was combined with the 2D lumen center estimates to provide a centerline in 3D. For validation, 19 carotid scans from 15 different patients were scanned, their centerlines calculated by the algorithm and compared with results acquired by manual annotations. Results The average Euclidean distance between both among all the examinations was 0.82 mm. For each examination, the percentage of these Euclidean distances below 2 mm was calculated; the average over all examinations was 92%. Conclusion Automated 3D estimation of carotid artery lumen centerlines in free-hand real-time ultrasound is feasible and can be performed with high accuracy. The algorithm is robust enough to keep the centerlines inside the vessel, even in the absence of contrast in parts of the vessel wall.

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Geometry of the Carotid Bifurcation Predicts Its Exposure to Disturbed Flow

Cited by 318 publications

References 42 publications

Three‐dimensional analysis of segmental wall shear stress in the aorta by flow‐sensitive four‐dimensional‐MRI

Three‐dimensional analysis of segmental wall shear stress in the aorta by flow‐sensitive four‐dimensional‐MRI

Cardiovascular morphometry with high-resolution 3D magnetic resonance: First application to left ventricle diastolic dysfunction

Estimating 3D lumen centerlines of carotid arteries in free-hand acquisition ultrasound

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