Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this study was to develop a fully automatic system to detect TAC and to evaluate its performance for classifying the patients into four TAC risk categories. The method started by segmenting the thoracic aorta, combining three UNets trained with axial, sagittal and coronal CT images. Afterwards, the surrounding lesion candidates were classified using three combined convolutional neural networks (CNNs) trained with orthogonal patches. Image datasets included 1190 non-enhanced ECG-gated cardiac CT studies from a cohort of cardiovascular patients (age 57 ± 9 years, 80% men, 65% TAC > 0). In the test set (N = 119), the combination of UNets was able to successfully segment the thoracic aorta with a mean volume difference of 0.3 ± 11.7 ml (<6%) and a median Dice coefficient of 0.947. The combined CNNs accurately classified the lesion candidates and 87% of the patients (N = 104) were accurately placed in their corresponding risk categories (Kappa = 0.826, ICC = 0.9915). TAC measurement can be estimated automatically from cardiac CT images using UNets to isolate the thoracic aorta and CNNs to classify calcified lesions.

Abdominal aortic calcium and geometry in patients with essential hypertension.

PURPOSE: Abdominal aorta calcium (AAC) burden and dilatation are associated with an increased risk of mortality. The purpose of this study was to investigate determinants of AAC and abdominal aorta size in patients with essential hypertension. MATERIALS AND METHODS: Patients with uncomplicated essential hypertension who had undergone non-enhanced abdominal CT to rule out secondary hypertension in addition to biological test were recruited between 2010 and 2018. A semi-automatic system was designed to estimate the aortic size (diameter, length, volume) and quantify the AAC from mesenteric artery to bifurcation using the Agatston score. Determinants of aortic size and those related to AAC were searched for using uni- and multivariables analyses. RESULTS: Among 293 randomly selected patients with hypertension (age 52 ± 11 [SD] years) included, 23% had resistant hypertension. Mean abdominal aorta diameter was 20.1 ± 2.1 (SD) mm. Eight (3%) patients had abdominal aorta aneurysm ≥ 30 mm and 58 (20%) had dilated abdominal aorta ≥ 27 mm. Median AAC score was 38 and calcifications were detected in the infra- and supra-renal abdominal aortic portions in 59% and 26% of the patients, respectively. After adjustment for age, male sex and body surface area, abdominal aorta diameter was positively associated with diastolic blood pressure (P = 0.0019). Smoking was the single variable associated with calcified abdominal aorta (P < 0.001) after adjustment for cofactors. In patients with calcifications of abdominal aorta, the score increased with smoking history (P < 0.001), statins treatment (P < 0.01), greater number of anti-hypertensive drugs (P < 0.01), larger abdominal aorta (P < 0.05) and greater systolic blood pressure (P < 0.05). Patients with resistant hypertension had more AAC in the supra-renal abdominal aorta portion than those without resistant hypertension (P < 0.01). CONCLUSION: In patients with essential hypertension, abdominal aorta dilation is related with diastolic blood pressure while AAC is associated with smoking history and resistant hypertension when located to the supra-renal abdominal aorta portion.

Echocardiographic Measurements of Left Heart Chamber Size in a Large Cohort of Subjects: Comparison of Body Surface Area and Height Indexing to Account for Effects of Obesity.

BACKGROUND: The assessment of cardiac chamber size in the obese population is a challenging subject. Values usually indexed to body surface area (BSA) are smaller in obese subjects and prone to overcorrection. The aims of this study were to find reference thresholds to account for the effects of obesity among a large cohort of patients and to evaluate indexing to height as an alternative to BSA. METHODS: The past 10 years of records from a single echocardiography unit were retrospectively analyzed, and 14,007 subjects without known cardiac disease were included (mean age, 45 ± 15 years; 54% women; 20% obese). Measurements included left atrial diameter, area, and volume, left ventricular (LV) end-diastolic and end-systolic diameters, aortic root diameter, and LV mass. Absolute, BSA-indexed, and height-indexed maximum thresholds (mean + 1.96 SDs) were calculated. Allometric indexing of the form variable/heightß was tested. Correlation coefficients between indexed and absolute values were calculated to evaluate their proportional association (ideally r = 1). Correlations between indexed values and body size represented residual associations to be minimized (ideally r = 0). RESULTS: The strongest association of echocardiographic measurements with body size was observed for BSA (r = 0.36-0.63), whereas the isometric and allometric height models showed lower comparable values (r = 0.28-0.48). Positive correlations with body mass index were mostly observed for left atrial size (r ≈ 0.36) and LV mass (r ≈ 0.36) measurements. Values of the scaling exponent ß for allometric height indexing were 1.72 for left atrial volume and 2.33 for LV mass. Correlations between indexed and absolute values were higher for height than BSA (0.80-0.98 vs 0.44-0.92). Correlations between indexed values and height were closer to 0 than for BSA, particularly using the allometric model. The overcorrection observed with increasing obesity class after BSA indexing was avoided after height indexing. CONCLUSIONS: Unlike BSA, height indexing provided adequate body size scaling of left heart chamber size, avoiding overcorrection using allometric models in particular.

Thoracic Aorta Calcium Detection and Quantification Using Convolutional Neural Networks in a Large Cohort of Intermediate-Risk Patients.

Arterial calcification is an independent predictor of cardiovascular disease (CVD) events whereas thoracic aorta calcium (TAC) detection might anticipate extracoronary outcomes. In this work, we trained six convolutional neural networks (CNNs) to detect aortic calcifications and to automate the TAC score assessment in intermediate CVD risk patients. Cardiac computed tomography images from 1415 patients were analyzed together with their aortic geometry previously assessed. Orthogonal patches centered in each aortic candidate lesion were reconstructed and a dataset with 19,790 images (61% positives) was built. Three single-input 2D CNNs were trained using axial, coronal and sagittal patches together with two multi-input 2.5D CNNs combining the orthogonal patches and identifying their best regional combination (BRC) in terms of lesion location. Aortic calcifications were concentrated in the descending (66%) and aortic arch (26%) portions. The BRC of axial patches to detect ascending or aortic arch lesions and sagittal images for the descending portion had the best performance: 0.954 F1-Score, 98.4% sensitivity, 87% of the subjects correctly classified in their TAC category and an average false positive TAC score per patient of 30. A CNN that combined axial and sagittal patches depending on the candidate aortic location ensured an accurate TAC score prediction.

Comprehensive assessment of local and regional aortic stiffness in patients with tricuspid or bicuspid aortic valve aortopathy using magnetic resonance imaging.

BACKGROUND: We aimed to provide a comprehensive aortic stiffness description using magnetic resonance imaging (MRI) in patients with ascending thoracic aorta aneurysm and tricuspid (TAV-ATAA) or bicuspid (BAV) aortic valve. METHODS: This case-control study included 18 TAV-ATAA and 19 BAV patients, with no aortic valve stenosis/severe regurgitation, who were 1:1 age-, gender- and central blood pressures (BP)-matched to healthy volunteers. Each underwent simultaneous aortic MRI and BP measurements. 3D anatomical MRI provided aortic diameters. Stiffness indices included: regional ascending (AA) and descending (DA) aorta pulse wave velocity (PWV) from 4D flow MRI; local AA and DA strain, distensibility and theoretical Bramwell-Hill (BH) model-based PWV, as well as regional arch PWV from 2D flow MRI. RESULTS: Patient groups had significantly higher maximal AA diameter (median[interquartile range], TAV-ATAA: 47.5[42.0-51.3]mm, BAV: 45.0[41.0-47.0]mm) than their respective controls (29.1[26.8-31.8] and 28.1[26.0-32.0]mm, p < 0.0001), while BP were similar (p ≥ 0.25). Stiffness indices were significantly associated with age (ρ ≥ 0.33), mean BP (arch PWV: ρ = 0.25, p = 0.05; DA distensibility: ρ = -0.30, p = 0.02) or AA diameter (arch PWV: ρ = 0.28, p = 0.03; DA PWV: ρ = 0.32, p = 0.009). None of them, however, was significantly different between TAV-ATAA or BAV patients and their matched controls. Finally, while direct PWV measures were significantly correlated to BH-PWV estimates in controls (ρ ≥ 0.40), associations were non-significant in TAV-ATAA and BAV groups (p ≥ 0.18). CONCLUSIONS: The overlap of MRI-derived aortic stiffness indices between patients with TAV or BAV aortopathy and matched controls highlights another heterogeneous feature of aortopathy, and suggests the urgent need for more sensitive indices which might help better discriminate such diseases.

Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model.

OBJECTIVE: To evaluate an automatic correction method for velocity offset errors in cardiac 4D-flow acquisitions. MATERIALS AND METHODS: Velocity offset correction was done in a plane-by-plane scheme and compared to a volumetric approach. Stationary regions were automatically detected. In vitro experiments were conducted in a phantom using two orientations and two encoding velocities (Venc). First- to third-order models were fit to the time-averaged images of the three velocity components. In vivo experiments included realistic ROIs in a volunteer superimposed to a phantom. In 15 volunteers, blood flow volume of the proximal and distal descending aorta, of the pulmonary artery (Qp) and the ascending aorta (Qs) was compared. RESULTS: Offset errors were reduced after correction with a third-order model, yielding residual phantom velocities below 0.6 cm/s and 0.4% of Venc. The plane-by-plane correction method was more effective than the volumetric approach. Mean velocities through superimposed ROIs of a volunteer vs phantom were highly correlated (r2 = 0.96). The significant difference between proximal and distal descending aortic flows was decreased after correction from 8.1 to - 1.4 ml (p < 0.001) and Qp/Qs reduced from 1.08 ± 0.09 to 1.01 ± 0.05. DISCUSSION: An automatic third-order model corrected velocity offset errors in 4D-flow acquisitions, achieving acceptable levels for clinical applications.

Abdominal Aortic Aneurysm Volumetric Evaluation During Mid-term Follow-Up After Endovascular Sealing Using the Nellix™ Device.

OBJECTIVES: To analyze the volumetric evolution of abdominal aortic aneurysms after endovascular sealing (EVAS) with the Nellix™ device during follow-up. METHODS: Patients who underwent elective EVAS in our institution in 2014 and 2015 were retrospectively reviewed. Preoperative, postoperative and 1-year scans were processed. A custom software was conceived to assess semi-automated measurements of the aneurysm sac and the endograft sizes including volume, maximum diameter, sectional area and perimeter. Thrombus volume, aneurysm length, mean distance between the stents inside the polymer-filled sacs and endograft migration were also estimated. Manual maximum diameters were measured for comparison. Inter and intra-observer variability of the proposed semi-automated method was evaluated. RESULTS: Pre-EVAS, post-EVAS and last follow-up scans of 12 patients were finally analyzed during a mean follow-up of 17 ± 5 months. No endograft migration or endoleak were detected. During follow-up, aneurysm volume and perimeter slightly increased compared to post-EVAS scans (+ 1 and + 5%, respectively, p < 0.05). A systematic 6% enlargement of the endobag volume was also observed (range 1-15 mL, p < 0.001). Endobag maximum diameter, area and perimeter increased 4, 8, and 8%, respectively (all p < 0.01). Mean plane-by-plane distance between stents increased 4% (p < 0.05). Mean thrombus volume did not change during follow-up, although a high variability was observed. Aneurysm and thrombus volume changes were highly correlated (r = 0.93, p < 0.001). No associations were observed between aneurysm and endobag volume changes. Intra- and inter-observer variability was below 1.7 and 2.4% for diameter and volume measurements, respectively. The automated measurements of post-EVAS aneurysm diameter and volume were higher than preoperative (p < 0.05). Maximum diameters measured manually did not differ between scans. CONCLUSION: Small aneurysm volume enlargement detected during a mid-term follow-up was associated with thrombus size change, whereas systematic endograft expansion resulted independent from the aortic growth. Volumetric measurements using a semi-automated method could quantify small changes in aneurysm, endograft and thrombus sizes not detected by manually defined maximal diameters.

Effects on Aortoiliac Fluid Dynamics After Endovascular Sealing of Abdominal Aneurysms.

OBJECTIVES:: To evaluate the effects on aortoiliac fluid dynamics after the implantation of an endograft based on endovascular aneurysm sealing (EVAS) versus endovascular aneurysm repair (EVAR) strategy. METHODS:: An adaptive geometrical deformable model was used for aortic lumen segmentation in 8 patients before and after the surgery. Abdominal aneurysms were treated with an endograft based on the EVAS system (Nellix, n = 4) and with a device based on an anatomical fixation technology (n = 4). Pressure, blood velocity, and wall shear stress (WSS) were estimated at different aortic regions using computational fluid dynamics methods. Physiologic inlet/outlet flow values at the abdominal aorta, the celiac trunk, and the mesenteric and the renal arteries were set. Pressure references were set at iliac arteries outlet. RESULTS:: Maximum aneurysm sizes were similar for both groups in the preoperative scans. The lumen area was lower after EVAR ( P < .05) and EVAS ( P < .01) compared to preoperative aortic lumen sizes. Pressure increase was higher in the proximal abdominal aorta after EVAS compared to EVAR (2.3 ± 0.3 mm Hg vs 0.9 ± 0.3 mm Hg, P < .001). Peak blood velocities inside the endografts were 3-fold higher for EVAS compared to EVAR (54 ± 5 cm/s vs 17 ± 4 cm/s, P < .01). Velocities at the iliac arteries also remained higher for EVAS (38 ± 4 cm/s vs 24 ± 4 cm/s, P < .05). Peak WSS at the iliac arteries remained higher for EVAS compared to EVAR group ( P < .05). CONCLUSION:: The significant modification of the aortic bifurcation anatomy after EVAS alters aortoiliac fluid dynamics, showing a pressure impact at the renal arteries level and an acceleration of the blood velocity at the iliac region with a concomitant increase in peak WSS.

Age-related changes of thoracic aorta geometry used to predict the risk for acute type B dissection.

AIMS: Risk models that use a single aortic diameter threshold have failed to successfully predict acute type B aortic dissection (TBAD). We sought to identify meaningful age-indexed anatomical variables to predict TBAD risk. METHODS AND RESULTS: A geometric deformable model, consisting of virtual elastic balloons that inflate inside a vessel lumen, was developed to quantify thoracic aorta geometry. In the presence of TBAD, true and total artery lumen morphology were assessed. A stepwise logistic model was built to predict TBAD risk. Initial covariates included age, gender, body mass index and all anatomic variables not directly related to the dissected segment. Patients with acute TBAD (n=34, 62±12years old, 57% male gender) were compared with subjects with symptoms of dissection, but with a subsequent negative diagnosis (n=51, 62±12years old, 76% male gender). Patient risk factors did not differ between groups. Most aortic anatomical variables were age-dependent. Aortic size was larger in every segment of the dissected with respect to non-dissected aortas (p<0.001). Variables entering the TBAD risk prediction model were aortic arch diameter, thoracic aorta length and age (predictability=0.9764, r=0.85), confirmed by a bootstrap internal validation. In dissected aortas, the true lumen volume was correlated to age (r=0.72). CONCLUSIONS: TBAD probability increases with a larger aortic arch diameter and a longer thoracic aorta, whereas threshold values increase with age. The aortic morphology was age-dependent. After dissection, true lumen volume correlated to age. The use of threshold values indexed to age should be encouraged to better prevent and eventually treat TBAD.

Asociación entre el calcio de la aorta torácica y la geometría de esta en una cohorte de sujetos asintomáticos con riesgo cardiovascular aumentado / Association between thoracic aorta calcium and thoracic aorta geometry in a cohort of asymptomatic participants at increased cardiovascular risk

Introducción y objetivos: La detección del calcio de la aorta torácica mejora la predicción del riesgo cardiovascular, en cuanto a los eventos cardiacos y no cardiacos, respecto a la obtenida solo con los factores de riesgo tradicionales. En este trabajo se ha investigado la influencia de la morfometría de la aorta torácica en la presencia y la magnitud de las calcificaciones aórticas. Métodos: Se realizaron exploraciones por tomografía computarizada cardiaca sin contraste en 970 participantes asintomáticos con riesgo cardiovascular aumentado. Se utilizó un algoritmo automático para estimar la geometría de toda la aorta torácica y se cuantificó la puntuación de Agatston del calcio aórtico. Se utilizó un modelo no paramétrico para analizar los percentiles de la puntuación de calcio según la edad. Se calcularon modelos de regresión logística para identificar asociaciones anatómicas con las concentraciones de calcio. Resultados: Las calcificaciones se concentraron en el cayado aórtico y la aorta descendente. Las mayores cantidades de calcio se asociaron con una aorta agrandada, desplegada, con menor estrechamiento y más tortuosa. El tamaño de la aorta ascendente no mostró correlación con la puntuación de calcio de la aorta, mientras que el tamaño de la aorta descendente es el parámetro que mostró mayor asociación: el riesgo de tener una puntuación de calcio global superior al percentil 90 fue 3,62 veces (intervalo de confianza, 2,30-5,91; p < 0,001) mayor por cada 2,5 mm de aumento del diámetro de la aorta descendente. La reducción gradual del diámetro, la tortuosidad, el despliegue y los volúmenes del cayado aórtico y la aorta descendente estaban correlacionados con mayor cantidad de calcio. Conclusiones: Las calcificaciones se hallaron predominantemente en el cayado aórtico y la aorta descendente y mostraron asociación positiva con el tamaño de la aorta descendente y el cayado aórtico, pero no con el tamaño de la aorta ascendente. Estas observaciones indican que la dilatación aórtica puede tener mecanismos diferentes y, por consiguiente, requiere estrategias preventivas distintas según el segmento considerado (AU)

Introduction and objectives: Thoracic aorta calcium detection is known to improve cardiovascular risk prediction for cardiac and noncardiac events beyond traditional risk factors. We investigated the influence of thoracic aorta morphometry on the presence and extent of aortic calcifications. Methods: Nonenhanced computed tomography heart scans were performed in 970 asymptomatic participants at increased cardiovascular risk. An automated algorithm estimated the geometry of the entire thoracic aorta and quantified the aortic calcium Agatston score. A nonparametric model was used to analyze the percentiles of calcium score by age. Logistic regression models were calculated to identify anatomical associations with calcium levels. Results: Calcifications were concentrated in the aortic arch and descending portions. Higher amounts of calcium were associated with an enlarged, unfolded, less tapered and more tortuous aorta. The size of the ascending aorta was not correlated with aortic calcium score, whereas enlargement of the descending aorta had the strongest association: the risk of having a global calcium score > 90th percentile was 3.62 times higher (confidence interval, 2.30-5.91; P < .001) for each 2.5-mm increase in descending aorta diameter. Vessel taper, tortuosity, unfolding and aortic arch and descending volumes were also correlated with higher amounts of calcium. Conclusions: Thoracic aorta calcium was predominantly found at the arch and descending aorta and was positively associated with the size of the descending aorta and the aortic arch, but not with the size of the ascending aorta. These findings suggest that aortic dilatation may have different mechanisms and may consequently require different preventive strategies according to the considered segments (AU)

Association Between Thoracic Aorta Calcium and Thoracic Aorta Geometry in a Cohort of Asymptomatic Participants at Increased Cardiovascular Risk.

INTRODUCTION AND OBJECTIVES: Thoracic aorta calcium detection is known to improve cardiovascular risk prediction for cardiac and noncardiac events beyond traditional risk factors. We investigated the influence of thoracic aorta morphometry on the presence and extent of aortic calcifications. METHODS: Nonenhanced computed tomography heart scans were performed in 970 asymptomatic participants at increased cardiovascular risk. An automated algorithm estimated the geometry of the entire thoracic aorta and quantified the aortic calcium Agatston score. A nonparametric model was used to analyze the percentiles of calcium score by age. Logistic regression models were calculated to identify anatomical associations with calcium levels. RESULTS: Calcifications were concentrated in the aortic arch and descending portions. Higher amounts of calcium were associated with an enlarged, unfolded, less tapered and more tortuous aorta. The size of the ascending aorta was not correlated with aortic calcium score, whereas enlargement of the descending aorta had the strongest association: the risk of having a global calcium score > 90th percentile was 3.62 times higher (confidence interval, 2.30-5.91; P < .001) for each 2.5-mm increase in descending aorta diameter. Vessel taper, tortuosity, unfolding and aortic arch and descending volumes were also correlated with higher amounts of calcium. CONCLUSIONS: Thoracic aorta calcium was predominantly found at the arch and descending aorta and was positively associated with the size of the descending aorta and the aortic arch, but not with the size of the ascending aorta. These findings suggest that aortic dilatation may have different mechanisms and may consequently require different preventive strategies according to the considered segments.

Association of thoracic aorta calcium and non cardiac vascular events in cardiac disease-free individuals.

OBJECTIVE: Thoracic aorta calcium (TAC) is measurable on the same computed tomography (CT) scan as coronary artery calcium (CAC) but has still unclear clinical value. We assessed TAC and CAC relations with non-cardiac vascular events history in a cohort of subjects at risk for cardiovascular disease. METHODS: We analyzed retrospectively 1000 consecutive subjects having undergone CAC detection by non-contrast multi-slice CT with measurement field longer than usual in order to measure total TAC including aortic arch calcium. We also determined partial TAC restricted to ascending and descending thoracic aorta sites by removing arch calcium from total TAC. Calcium deposits were measured with a custom made software using Agatston score. RESULTS: Compared with the rest of the cohort, the 30 subjects with non-cardiac vascular event history had higher median values [95% CI] of total TAC (282 [28-1809] vs 39 [0-333], p < 0.01) and partial TAC (4 [0-284] vs 0 [0-5], p < 0.01) but no different value of CAC (73 [0-284] vs 16 [0-148]). Odds ratio [95% CI] of having non-cardiac vascular event per 1-SD increase in log-transformed calcium value was significant for total TAC but not for CAC, if total TAC and CAC were entered separately (1.56 [1.12-2.24], p < 0.01 and 1.13 [0.86-1.50], respectively) or together (1.57 [1.10-2.32], p < 0.01 and 0.98 [0.73-1.32], respectively) in the logistic adjusted model. CONCLUSION: TAC assessment simultaneous with CAC detection provides complementary information on the extra coronary component of cardiovascular risk beyond CAC's coronary risk prediction. Further studies are required to prospectively confirm this result.

Deformable Surface Model for the Evaluation of Abdominal Aortic Aneurysms Treated with an Endovascular Sealing System.

Rupture of abdominal aortic aneurysms (AAA) is responsible for 1-3% of all deaths among the elderly population in developed countries. A novel endograft proposes an endovascular aneurysm sealing (EVAS) system that isolates the aneurysm wall from blood flow using a polymer-filled endobag that surrounds two balloon-expandable stents. The volume of injected polymer is determined by monitoring the endobag pressure but the final AAA expansion remains unknown. We conceived and developed a fully deformable surface model for the comparison of pre-operative sac lumen size and final endobag size (measured using a follow-up scan) with the volume of injected polymer. Computed tomography images were acquired for eight patients. Aneurysms were manually and automatically segmented twice by the same observer. The injected polymer volume resulted 9% higher than the aneurysm pre-operative lumen size (p < 0.05), and 11% lower than the final follow-up endobag volume (p < 0.01). The automated method required minimal user interaction; it was fast and used a single set of parameters for all subjects. Intra-observer and manual vs. automated variability of measured volumes were 0.35 ± 2.11 and 0.07 ± 3.04 mL, respectively. Deformable surface models were used to quantify AAA size and showed that EVAS system devices tended to expand the sac lumen size.

Calcifications of the thoracic aorta on extended non-contrast-enhanced cardiac CT.

BACKGROUND: The presence of calcified atherosclerosis in different vascular beds has been associated with a higher risk of mortality. Thoracic aorta calcium (TAC) can be assessed from computed tomography (CT) scans, originally aimed at coronary artery calcium (CAC) assessment. CAC screening improves cardiovascular risk prediction, beyond standard risk assessment, whereas TAC performance remains controversial. However, the curvilinear portion of the thoracic aorta (TA), that includes the aortic arch, is systematically excluded from TAC analysis. We investigated the prevalence and spatial distribution of TAC all along the TA, to see how those segments that remain invisible in standard TA evaluation were affected. METHODS AND RESULTS: A total of 970 patients (77% men) underwent extended non-contrast cardiac CT scans including the aortic arch. An automated algorithm was designed to extract the vessel centerline and to estimate the vessel diameter in perpendicular planes. Then, calcifications were quantified using the Agatston score and associated with the corresponding thoracic aorta segment. The aortic arch and the proximal descending aorta, "invisible" in routine CAC screening, appeared as two vulnerable sites concentrating 60% of almost 11000 calcifications. The aortic arch was the most affected segment per cm length. Using the extended measurement method, TAC prevalence doubled from 31% to 64%, meaning that 52% of patients would escape detection with a standard scan. In a stratified analysis for CAC and/or TAC assessment, 111 subjects (46% women) were exclusively identified with the enlarged scan. CONCLUSIONS: Calcium screening in the TA revealed that the aortic arch and the proximal descending aorta, hidden in standard TA evaluations, concentrated most of the calcifications. Middle-aged women were more prone to have calcifications in those hidden portions and became candidates for reclassification.

Identifying the principal modes of variation in human thoracic aorta morphology.

PURPOSE: Diagnosis and management of thoracic aorta (TA) disease demand the assessment of accurate quantitative information of the aortic anatomy. We investigated the principal modes of variation in aortic 3-dimensional geometry paying particular attention to the curvilinear portion. MATERIALS AND METHODS: Images were obtained from extended noncontrast multislice computed tomography scans, originally intended for coronary calcium assessment. The ascending, arch, and descending aortas of 500 asymptomatic patients (57 ± 9 y, 81% male) were segmented using a semiautomated algorithm that sequentially inscribed circles inside the vessel cross-section. Axial planes were used for the descending aorta, whereas oblique reconstructions through a toroid path were required for the arch. Vessel centerline coordinates and the corresponding diameter values were obtained. Twelve size and shape geometric parameters were calculated to perform a principal component analysis. RESULTS: Statistics revealed that the geometric variability of the TA was successfully explained using 3 factors that account for ∼80% of total variability. Averaged aortas were reconstructed varying each factor in 5 intervals. Analyzing the parameter loadings for each principal component, the dominant contributors were interpreted as vessel size (46%), arch unfolding (22%), and arch symmetry (12%). Variables such as age, body size, and risk factors did not substantially modify the correlation coefficients, although some particular differences were observed with sex. CONCLUSIONS: We conclude that vessel size, arch unfolding, and symmetry form the basis for characterizing the variability of TA morphology. The numerical data provided in this study as supplementary material can be exploited to accurately reconstruct the curvilinear shape of normal TAs.

Towards automatic measurement of anteversion and neck-shaft angles in human femurs using CT images.

Automatic assessment of human femur morphology may provide useful clinical information with regard to hip and knee surgery, prosthesis design and management of hip instability. To this end, neck-shaft and anteversion angles are usually used. We propose a full automatic method to estimate these angles in human femurs. Multislice CT images from 18 dried bones were analysed. The algorithm fits 3D cylinders to different regions of the bone to estimate the angles. A manual segmentation and a conventional angle assessment were used for validation. We found anteversion angle as 20 ± 7° and neck-shaft angle as 130 ± 9°. Mean distances from femur surface to cylinders were 5.5 ± 0.6, 3.5 ± 0.6 and 2.4 ± 0.4 mm for condyles, diaphysis and neck regions, respectively. Automatic and conventional angles were positively correlated (r(2)>0.85). Manual and automatic segmentations did not differ. The method was fast and 100% reproducible. A robust in vivo segmentation algorithm should be integrated to advance towards a clinically compliant methodology.

Effects of aging on thoracic aorta size and shape: a non-contrast CT study.

Measures of atherosclerosis burden like coronary artery calcification are performed using non-contrast heart CT. However, additional information can be derived from these studies, looking beyond the coronary arteries without exposing the patients to further radiation. We present a semi-automated method to assess ascending, arch and descending aorta geometry from non-contrast CT datasets in 250 normotensive patients. We investigated the effect of aging on thoracic aorta morphometry. The algorithm identifies the aortic centerline coordinates following a toroidal path for the curvilinear portion and axial planes for descending aorta. Then it reconstructs oblique planes orthogonal to the centerline direction and a circle fitting process estimates the vessel cross-section. Finally, global thoracic aorta dimensions (diameter, volume and length) and shape (vessel curvature and tortuosity, aortic arch width and height) are calculated. From a multivariate analysis, adjusted for gender and body-size area, aortic volume and arch width were the descriptors that better represented the aortic size and shape alterations with aging. The thoracic aorta suffers an expanding and unfolding process with aging that deserves further attention to prevent aortic aneurisms.

Angle estimation of human femora in a three-dimensional virtual environment.

The estimation of human femur morphology and angulation provide useful information for assisted surgery, follow-up evaluation and prosthesis design, cerebral palsy management, congenital dislocation of the hip and fractures of the femur. Conventional methods that estimate femoral neck anteversion employ planar projections because accurate 3D estimations require complex reconstruction routines. In a recent work, we proposed a cylinder fitting method to estimate bifurcation angles in coronary arteries and we thought to test it in the estimation of femoral neck anteversion, valgus and shaft-neck angles. Femora from 10 patients were scanned using multisliced computed tomography. Virtual cylinders were fitted to 3 regions of the bone painted by the user to automatically estimate the femoral angles. Comparisons were made with a conventional manual method. Inter- and intra-reading measurements were evaluated for each method. We found femoral angles from both methods strongly correlated. Average anteversion, neck-shaft and valgus angles were 17.5°, 139.5°, 99.1°, respectively. The repeatability and reproducibility of the automated method showed a 5-fold reduction in inter- and intra-reading variability. Accordingly, the coefficients of variation for the manual method were below 25% whereas for the automated method were below 6%. The valgus angle assessment was globally the most accurate with differences below 1°. Maximum distances from true surface bone points and fitting cylinders attained 6 mm. The employment of virtual cylinders fitted to different regions of human femora consistently helped to assess true 3D angulations.

Estimation of coronary length-volume allometric relations of human arteries in vivo using CT.

Assessing the individual geometry of the coronary arteries in a patient can help to explain diffuse artery disease. Some allometric functions, relating arterial length and volume, were verified in porcine arteries and human autopsies but not in vivo. In this work we use skeletonization methods on MSCT images to render the whole coronary tree in healthy and cardiovascular patients. Twenty patients with and without coronary artery disease were recruited. The coronary was segmented with minimum user intervention. Vessels were separated and measured. A 3D coronary map was individually calculated. The allometric length-volume function L=k(v)V(ß) was evaluated in each patient and plotted in a Log-Log scale. The coefficient k(v) ranged 1.00 ± 0.35. Slopes ranged ß = 0.69-0.88 and seemed to overlap in the scatter Log plot. The analysis of covariance verified this perception and concluded that lines were parallel. In other words, the allometric function stood for all patients. Values were not different from other studies in humans and pigs. The combination of multislice CT with morphological extraction algorithms was effective to extract allometric functions from coronary arteries in patients and can be easily applied in the clinic.