Aging Impact on Thoracic Aorta 3D Morphometry in Intermediate-Risk Subjects: Looking Beyond Coronary Arteries with Non-Contrast Cardiac CT

Craiem, Damián; Chironi, Gilles; Redheuil, Alban; Casciaro, Mariano E.; Mousseaux, Élie; Simon, Alain; Armentano, Ricardo L.

doi:10.1007/s10439-011-0487-y

Cited by 52 publications

(62 citation statements)

References 33 publications

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“…Automated 3D centreline extraction methods would streamline PWV analysis, and possibly reduce the inter- and intra-observer variability. Automated aortic centreline tracking has been evaluated both on CT angiography [25–28] and CMR [29–31]. Often an initial lumen segmentation is obtained first, from which the centreline is extracted [26, 30, 31].…”

Section: Introductionmentioning

confidence: 99%

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction

Engelen

Vieira

Rafiq

et al. 2016

Journal of Cardiovascular Magnetic Resonance

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BackgroundPulse wave velocity (PWV) is a biomarker for the intrinsic stiffness of the aortic wall, and has been shown to be predictive for cardiovascular events. It can be assessed using cardiovascular magnetic resonance (CMR) from the delay between phase-contrast flow waveforms at two or more locations in the aorta, and the distance on CMR images between those locations. This study aimed to investigate the impact of different distance measurement methods on PWV. We present and evaluate an algorithm for automated centreline tracking in 3D images, and compare PWV calculations using distances derived from 3D images to those obtained from a conventional 2D oblique-sagittal image of the aorta.MethodsWe included 35 patients from a twin cohort, and 20 post-coarctation repair patients. Phase-contrast flow was acquired in the ascending, descending and diaphragmatic aorta. A 3D centreline tracking algorithm is presented and evaluated on a subset of 30 subjects, on three CMR sequences: balanced steady-state free precession (SSFP), black-blood double inversion recovery turbo spin echo, and contrast-enhanced CMR angiography. Aortic lengths are subsequently compared between measurements from a 2D oblique-sagittal plane, and a 3D geometry.ResultsThe error in length of automated 3D centreline tracking compared with manual annotations ranged from 2.4 [1.8-4.3] mm (mean [IQR], black-blood) to 6.4 [4.7-8.9] mm (SSFP). The impact on PWV was below 0.5m/s (<5%). Differences between 2D and 3D centreline length were significant for the majority of our experiments (p < 0.05). Individual differences in PWV were larger than 0.5m/s in 15% of all cases (thoracic aorta) and 37% when studying the aortic arch only. Finally, the difference between end-diastolic and end-systolic 2D centreline lengths was statistically significant (p < 0.01), but resulted in small differences in PWV (0.08 [0.04 - 0.10]m/s).ConclusionsAutomatic aortic centreline tracking in three commonly used CMR sequences is possible with good accuracy. The 3D length obtained from such sequences can differ considerably from lengths obtained from a 2D oblique-sagittal plane, depending on aortic curvature, adequate planning of the oblique-sagittal plane, and patient motion between acquisitions. For accurate PWV measurements we recommend using 3D centrelines.

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Section: Introductionmentioning

confidence: 99%

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction

Engelen

Vieira

Rafiq

et al. 2016

Journal of Cardiovascular Magnetic Resonance

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“…Although most of the patients had calcifications in the arch and descending aorta, this distribution did not differ between men and women ( Table 2). In recent works, we showed that the thoracic aorta suffers a significant enlargement with age, whereas its curvilinear arch widens in a denominated "unfolding process" [10]. Hypertension was reported to accelerate this deformation [11].…”

Section: Resultsmentioning

confidence: 98%

“…1(a), assuming the aorta as a variable radius cylinder deformed in space along a curve corresponding to its central skeleton. A correction post-processing is performed to ensure oblique planes remain orthogonal to the centerline curve [10]. The result of this algorithm is a list of centerline points and the corresponding diameters that approximate the cross section of the aorta in that position.…”

Section: Semiautomatic Segmentationmentioning

confidence: 99%

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Automated Assessment of Thoracic Aorta Morphology and Calcium Distribution

et al. 2015

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Abstract-Calcifications are heterogeneously distributed within different vascular beds. The presence and extent of calcium can be measured from non-contrast CT images and has been associated with higher cardiovascular risks. Using heart scans, thoracic aorta calcium (TAC) can be simultaneously assessed, although the aortic arch is systematically excluded. In this work we developed an automated technique that estimated the thoracic aorta (TA) morphology in 3D and the associated calcifications. One hundred non-diabetic patients (male gender 50%, aging 55-to-60 y.o.) at intermediate risk were randomly selected. Extended non-contrast CT scans, that included the aortic arch, were conducted. A custom software segmented the thoracic aorta using an adaptive circle fitting method that estimated the aortic centerline and diameter in 140 points per patient. Traditional risk factors were similar between men and women (p=NS). As expected, the Framingham risk score was higher in men (p<0.001). All TA size measurement were larger in men, including mean diameter, length and volume (p<0.001). In shape variables, aortic arch width was wider in men (p<0.001), although the arch height and tortuosity were similar with respect to women (p=NS). We did not find differences in TAC distribution for the ascending, arch and descending segments. Calcifications were mostly concentrated in the aortic arch and the proximal descending portions. We conclude that, in spite of having larger and wider TAs, men and women had similar calcification distribution. Calcium appeared along the TA curvilinear portion that remains invisible in traditional coronary calcium examinations. Further analyses are required to evaluate if this extended TAC inspection could be used to revise its prognostic value in prospective studies.

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“…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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Aging Impact on Thoracic Aorta 3D Morphometry in Intermediate-Risk Subjects: Looking Beyond Coronary Arteries with Non-Contrast Cardiac CT

Cited by 52 publications

References 33 publications

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction

Automated Assessment of Thoracic Aorta Morphology and Calcium Distribution

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

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