Benedetta Leonardi

A Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot

Cardiac remodelling plays a crucial role in heart diseases. Analyzing how the heart grows and remodels over time can provide precious insights into pathological mechanisms, eventually resulting in quantitative metrics for disease evaluation and therapy planning. This study aims to quantify the regional impacts of valve regurgitation and heart growth upon the end-diastolic right ventricle (RV) in patients with tetralogy of Fallot, a severe congenital heart defect. The ultimate goal is to determine, among clinical variables, predictors for the RV shape from which a statistical model that predicts RV remodelling is built. Our approach relies on a forward model based on currents and a diffeomorphic surface registration algorithm to estimate an unbiased template. Local effects of RV regurgitation upon the RV shape were assessed with Principal Component Analysis (PCA) and cross-sectional multivariate design. A generative 3-D model of RV growth was then estimated using partial least squares (PLS) and canonical correlation analysis (CCA). Applied on a retrospective population of 49 patients, cross-effects between growth and pathology could be identified. Qualitatively, the statistical findings were found realistic by cardiologists. 10-fold cross-validation demonstrated a promising generalization and stability of the growth model. Compared to PCA regression, PLS was more compact, more precise and provided better predictions.

Imaging modalities in children with vascular ring and pulmonary artery sling

Our aim is to compare new non‐invasive imaging modalities in the evaluation of vascular ring (VR) and pulmonary artery sling (PAS) and to understand the role of bronchoscopy in comparison with them in assessing tracheobronchial tree.

Computational modelling of the right ventricle in repaired tetralogy of Fallot: Can it provide insight into patient treatment?

AIMS Pulmonary regurgitation (PR) causes progressive right ventricle (RV) dilatation and dysfunction in repaired tetralogy of Fallot (rToF). Declining RV function is often insidious and the timing of pulmonary valve replacement remains under debate. Quantifying the pathophysiology of adverse RV remodelling due to worsening PR may help in defining the best timing for pulmonary valve replacement. Our aim was to identify whether complex three-dimensional (3D) deformations of RV shape, as assessed with computer modelling, could constitute an anatomical biomarker that correlated with clinical parameters in rToF patients. METHODS AND RESULTS We selected 38 rToF patients (aged 10-30 years) who had complete data sets and had not undergone PVR from a population of 314 consecutive patients recruited in a collaborative study of four hospitals. All patients underwent cardiovascular magnetic resonance (CMR) imaging: PR and RV end-diastolic volumes were measured. An unbiased shape analysis framework was used with principal component analysis and linear regression to correlate shape with indexed PR volume. Regurgitation severity was significantly associated with RV dilatation (P = 0.01) and associated with bulging of the outflow tract (P = 0.07) and a dilatation of the apex (P = 0.08). CONCLUSION In this study, we related RV shape at end-diastole to clinical metrics of PR in rToF patients. By considering the entire 3D shape, we identified a link between PR and RV dilatation, outflow tract bulging, and apical dilatation. Our study constitutes a first attempt to correlate 3D RV shape with clinical metrics in rToF, opening new ways to better quantify 3D RV change in rToF.

Comparison of contrast and noncontrast magnetic resonance angiography for quantitative analysis of thoracic arteries in young patients with congenital heart defects

Background: Contrast MRA (C-MRA) is the standard for quantitative analysis of thoracic vessels. We evaluated a noncontrast MRA (NC-MRA) sequence (3-D EKG and navigator-gated SSFP) for quantitative evaluation of the thoracic aorta and branch pulmonary arteries in young patients with congenital heart disease. Objective: To compare contrast and noncontrast magnetic resonance angiography for quantitative analysis of thoracic arteries in young patients with congenital heart defects. Methods: Measurements of thoracic aorta and branch pulmonary arteries were obtained from C-MRA and NC-MRA images in 51 patients, ages 2–35 years. Vessel diameters were compared using correlation and Bland-Altman analysis. Interobserver variability was assessed using percent variation. Results: C-MRA and NC-MRA measurements were highly correlated (r = 0.91-0.98) except for the right pulmonary artery (r = 0.74, 0.78). Agreement of measurements was excellent (mean difference –0.07 to –0.53 mm; mean % difference –1.8 to –4.9%) except for the right pulmonary artery which was less good (mean difference 0.73, –1.38 mm; –3, –10%). Interobserver variability ranged from 5% to 8% for aortic and from 10% to 16% for pulmonary artery measures. The worse agreement and greater variability of the pulmonary artery measures appears due to difficulty standardizing the measurements in patients with abnormal and irregular vessels. Conclusion: These data indicate that C-MRA and NC-MRA measures are comparable and could be used interchangeably, avoiding administration of contrast in selected patients.

Ventricular mechanics in patients with aortic valve disease: longitudinal, radial, and circumferential components.

BACKGROUND Reduced long-axis shortening despite enhanced global function has been reported in aortic stenosis. We sought to improve the understanding of this phenomenon using multi-dimensional strain analysis in conjunction with the evaluation of left ventricular rotation and twist - ventricular torsion - using tissue Doppler techniques. METHODS A total of 57 patients with variable severity of aortic stenosis, aortic regurgitation, or mixed aortic valve disease, subdivided into six groups, were studied. Ventricular morphology was assessed using long-axis/short-axis and mass/volume ratios, afterload using end-systolic meridional wall stress, and global performance using ejection fraction. The circumferential and longitudinal strain was measured from two-dimensional images, and left ventricular rotation and twist were estimated as the difference in rotation between the base and apex of the ventricle. RESULTS Aortic stenosis was associated with higher mass/volume, ejection fraction, circumferential strain and left ventricular rotation and twist, significantly lower end-systolic wall stress, and a trend towards lower longitudinal strain compared with normal. Myocardial mechanics in aortic regurgitation were normal despite ventricular dilation. Mixed aortic valve disease showed findings similar to aortic stenosis. Left ventricular rotation and twist correlated with midwall circumferential strain (r = 0.62 and p < 0.0001), endocardial circumferential strain (r = 0.61 and p < 0.0001), and end-systolic wall stress (r = 0.48 and p < 0.0001), but not with longitudinal strain (r = 0.18 and p > 0.05). CONCLUSIONS Myocardial mechanics are normal in patients with aortic regurgitation, independent of abnormalities in cardiac geometry. Conversely, in aortic stenosis and mixed aortic valve disease, significant alterations in the patterns of fibre shortening are found. The effects of stenosis on cardiac function seem to dominate the effect of ventricular remodelling.

Multicenter review: role of cardiovascular magnetic resonance in diagnostic evaluation, pre-procedural planning and follow-up for patients with congenital heart disease

The number of patients with congenital heart disease (CHD) is rapidly increasing in the adult population, mainly due to the improved long-term survival. Serial follow-up with cardiac magnetic resonance imaging (CMR) is very appealing due to its non-invasive nature. CMR exam is able to provide specific information about cardiac function, hemodynamics, anatomy and tissue characterization unlikely achievable by other diagnostic techniques. CMR in CHD plays a role both in early diagnosis and in post-operative follow-up. Black Blood T1 weighted sequences are used to acquire morphological information. Cine Steady State Free Precession sequences are mainly used to provide data about cardiac function and kinesis. Hemodynamic assessment is routinely performed using phase contrast sequences, which provide reliable information concerning vessel flow pattern, cardiac output and intracardiac shunts. Magnetic Resonance Angiography (MRA) and 3D coronary MRA of the whole thorax can provide detailed morphological information regarding great vessels and proximal coronary arteries. Presence of late gadolinium enhancement suggesting myocardial macroscopic fibrosis seems to play a prognostic and diagnostic role even in this field.

Coronary artery ectasia in Noonan syndrome: Report of an individual with SOS1 mutation and literature review.

Noonan syndrome (NS) is the second most frequent hereditary syndrome with cardiac involvement. Pulmonary valve stenosis and hypertrophic cardiomyopathy are the most prevalent cardiovascular abnormalities. We report on a 14‐year‐old girl with NS due to SOS1 mutation with pulmonary stenosis and idiopathic coronary ectasia. To the best of our knowledge, this is the first report describing coronary ectasia in a patient with NS secondary to a SOS1 mutation. We include a literature review of this rare association.

Noninvasive hemodynamic assessment, treatment outcome prediction and follow-up of aortic coarctation from MR imaging

PURPOSE Coarctation of the aorta (CoA) is a congenital heart disease characterized by an abnormal narrowing of the proximal descending aorta. Severity of this pathology is quantified by the blood pressure drop (△P) across the stenotic coarctation lesion. In order to evaluate the physiological significance of the preoperative coarctation and to assess the postoperative results, the hemodynamic analysis is routinely performed by measuring the △P across the coarctation site via invasive cardiac catheterization. The focus of this work is to present an alternative, noninvasive measurement of blood pressure drop △P through the introduction of a fast, image-based workflow for personalized computational modeling of the CoA hemodynamics. METHODS The authors propose an end-to-end system comprised of shape and computational models, their personalization setup using MR imaging, and a fast, noninvasive method based on computational fluid dynamics (CFD) to estimate the pre- and postoperative hemodynamics for coarctation patients. A virtual treatment method is investigated to assess the predictive power of our approach. RESULTS Automatic thoracic aorta segmentation was applied on a population of 212 3D MR volumes, with mean symmetric point-to-mesh error of 3.00 ± 1.58 mm and average computation time of 8 s. Through quantitative evaluation of 6 CoA patients, good agreement between computed blood pressure drop and catheter measurements is shown: average differences are 2.38 ± 0.82 mm Hg (pre-), 1.10 ± 0.63 mm Hg (postoperative), and 4.99 ± 3.00 mm Hg (virtual stenting), respectively. CONCLUSIONS The complete workflow is realized in a fast, mostly-automated system that is integrable in the clinical setting. To the best of our knowledge, this is the first time that three different settings (preoperative--severity assessment, poststenting--follow-up, and virtual stenting--treatment outcome prediction) of CoA are investigated on multiple subjects. We believe that in future-given wider clinical validation-our noninvasive in-silico method could replace invasive pressure catheterization for CoA.

Role of right ventricular three-dimensional electroanatomic voltage mapping for arrhythmic risk stratification of patients with corrected tetralogy of Fallot or other congenital heart disease involving the right ventricular outflow tract.

BACKGROUND The post-surgical history of repaired congenital heart disease (rCHD), in particular tetralogy of Fallot (TOF), is often complicated by sudden death. Electrical myocardial abnormalities could be a substrate for malignant ventricular arrhythmias. METHODS AND RESULTS 146 patients with TOF or other rCHD involving a subpulmonary right ventricle, considered to be at high arrhythmic risk, underwent right ventricular (RV) electroanatomic voltage mapping (EVM). Maps showed endocardial scars (<0.5mV) in all cases, mainly involving the RV outflow tract (n=141, 96.6%). In 28 cases (19.2%), other areas were involved. Total scar extension, expressed as % of total endocardial area, was significantly higher in patients with QRS ≥180ms [4.5% (±2.5) vs 2.8% (±2.4), p=0.014], left and right ventricular systolic dysfunction [4.5% (±3.2) vs 2.8% (±2.3), p=0.016 and 3.5% (±3.0) vs 2.6% (±1.9), p=0.03, respectively], premature ventricular contractions (PVCs) [3.2% (±2.6) vs 2.2% (±1.8), p<0.05], exercise-induced PVCs [3.8% (±2.4) vs 2.6% (±2.2), p=0.01], previous shunt [4.0% (±2.7) vs 2.6% (±2.2), p=0.01] and reintervention [4.2% (±3.2) vs 2.6% (±2.0), p=0.008]. Scar size also showed a positive correlation with duration of post-surgical follow-up (ρ=0.01), age at correction (ρ=0.01) and absolute QRS duration (ρ=0.05). CONCLUSIONS Patients with rCHD involving the right ventricle show electrical scars with variable distribution, not necessarily matching with sites of surgical lesions. Scar extension correlates with some of the risk factors for life-threatening arrhythmias in CHD, such as prolonged QRS. Thus EVM could be considered an additional tool in the assessment of risk stratification in this particular population.

Fully-automatic, patient-specific 3D aortic arch modeling for patient treatment with aortic arch anomalies

Summary Timing and type of aortic wall abnormalities (AWC) repair are still being debated. Automatically patient-specific 3D aortic arch geometrical model estimation from MRI images can provide a better knowledge of the geometry of the aortic arch anomaly and can be useful to evaluate preoperatively the best treatment. Therefore, we have developed a software to automatically compute a patient-specific 3D aortic arch geometrical model from CMR data and we have validated it. Background Timing and type of surgical or transcatheter repair of aortic wall abnormalities (AWC) in patients with aortic coarctation (COA) and/or bicuspid aortic valve (BAV) are presently being debated, as associated morbidity and mortality can still occur. We have developed a system to automatically compute a patient-specific 3D aortic arch geometrical model from CMR data, which provides crucial information to understand the geometry of the pathophysiological abnormalities of the aortic arch and to evaluate preoperatively the best treatment. Aim To validate the accuracy of the computed 3D geometrical model of the aortic arch by comparing manual measurements extracted directly from CMR images with the one automatically derived from the geometrical model. Methods The system performance was evaluated on 32 patients with aortic arch anomalies (age: 5-36 years), 17 with COA and 15 with BAV and ascending aorta dilation. For reference, the aortic arch min and max diameters were measured manually from unenhanced, free breathing, T2-prepared, segmented 3D SSFP sequence at aortic sinus (AS), sino-tubular junction (STJ), ascending aorta (AAO), transverse arch (TA), and descending aorta (DA). A computer-based, hierarchical model, which includes the aortic root, the ascending/descending aorta and the aortic arch, was estimated automatically from the CMR data using a novel machine learning algorithm (Figure 1). Diameter measurements at corresponding positions were then automatically derived from the computer-based model and compared with manual ones. Results Statistical results significantly correlated (p < 0.001, r = 0.94) between min and max manual and automatic aortic measurements: AS (min p < 0.001 r = 0.85; max p < 0.001 r = 0.94), STJ (min p < 0.001 r = 0.88; max p < 0.001 r = 0.90), AAO (min p < 0.001 r = 0.94; max p < 0.001 r = 0.94), TA (min p < 0.001 r = 0.89; max p < 0.001 r = 0.93), DA (min p < 0.001 r = 0.90; max p < 0.001 r = 0.92). Mean measurement error of 1.59±0.6 mm was achieved for the min diameter and 1.44±0.9 mm for the max diameter. The maximal error occurred at the minimum diameter of each segment with the STJ the greatest (min 2.07±2.53) and the DA the least (min 0.8±0.83). Mean processing time for fully automatic aortic model estimation and measurement extraction was 1.5 s.