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Echocardiographic analysis of cardiac chamber volumes throughout the heart cycle is important to assess left- and right-heart function. We have developed and validated a method to simultaneously segment all four heart chambers in 3D echocardiography cine loops. We described the heart using several Doo Sabin models, one for each chamber and one for the pericardium. The model was fitted to 3D echo images using edge detection and a Kalman filter. The average signed error in estimating volume across all chambers was −1.0 ±± 12.3 ml. These results show that the model slightly underestimates the volumes. Average signed error for the ejection fraction was −3.2 ± 7.4 pts, with the highest error being the right atrium. This all-chamber automatic segmentation method provides high accuracy and may have utility in understanding chamber interactions.

My work focused on the fabrication of superhydrophobic surfaces (SHSs) by deposition of Al2O3 nanoparticles (NPs) and chemical modification with fluoroalkylsilanes (FAS). I synthesized Al2O3 NPs via sol-gel method in water or isopropyl alcohol, assessing the differences between the suspensions in physicochemical properties and coating effectiveness on different materials. In some cases, the dispersant played a role in the homogeneity and performance of the coating. I explored two deposition techniques, with dip coating proving more effective than spray coating. After NPs deposition, few thermal treatments were required. I assessed the influence of treatment temperature (T) on the coating, especially for a sensitive material like copper. The crucial step of the process was the immersion in boiling water to form a flower-like boehmite nanostructure. After grafting FAS chains, the surface became superhydrophobic. I characterized the coating in terms of wetting properties (static contact angle CA and contact angle hysteresis CAH) with water and other liquids and it proved superhydrophobic and highly oleophobic. I also assessed coating durability by performing ageing tests in chemically and mechanically aggressive conditions. The coating displayed remarkable resistance, still delivering excellent liquid repellence after the tests. Furthermore, I determined surface morphology with FESEM observations throughout the process, while colleagues at Università La Sapienza investigated the surface chemical composition with XPS analysis and DFT calculations. FAS molecules formed an ordered and stable monolayer on the boehmite coating. Further characterizations concerned coating adhesion to different substrates and roughness. As SHSs have a wide range of potential applications, it is useful to assess their behavior in “dynamic” conditions. For example, the study of single drop impacts is crucial in applications like sprays or ink-jet printers. Thus, I observed the impact of water and hexadecane drops on SHSs with different morphology and chemical composition. Surprisingly, it was not possible to easily correlate wetting properties and drop impact outcome, as surfaces with the same CAs provided different drop impact results. Parameters related to the liquid (velocity, surface tension, viscosity) and to the surface (morphology, roughness and, unexpectedly, chemical composition) played relevant roles in determining impact outcomes. I also studied the drop shedding behavior on the SHSs at different T and relative humidity (RH) conditions. At room T and low RH, a sessile drop could be easily shed by a low-speed airflow. On the other hand, high RH and T < 0°C strongly hindered shedding, thus requiring much higher airflow speed U to occur. Furthermore, surface roughness proved influent in determining critical U. I also tried to quantify the delay in drop freezing provided by the superhydrophobic coating, but instrumental issues made it difficult to obtain reliable data. Moreover, I measured the evolution of CAH when the surface was kept in high RH environment. An interesting drop in CAH after long condensation times was observed, but further investigations are needed. Finally, I evaluated the anti-friction properties of the coating deposited on pump components. The coating provided a remarkable and long-lasting friction reduction, with positive effects on pump efficiency. In summary, the hybrid, nanostructured coating owned remarkable liquid-repellent properties, due to the combination of flower-like morphology and grafted FAS molecules. The coating displayed excellent durability in a wide spectrum of aggressive environments and proved efficient even in dynamic conditions (e.g. drop impact, drop shedding with airflow). However, limitations appeared in severe conditions like high pH, high RH and freezing T. Future work must be devoted to the optimization of the coating to widen its range of potential applications.

Pulmonary arterial hypertension (PAH) is a common cause of tricuspid valve (TV) dilatation. Because of the impact of PAH on the right ventricle (RV), in-depth understanding of TV morphology and function is important. Methods: Novel custom software was used to trace and measure TV annulus (TVA) in 10 patients with PH and 10 control subjects (CTRL). To trace the TVA, points were selected in rotated planes and then interpolated. TVA was automatically tracked throughout cardiac cycle. Commissures were identified and used to divide the TVA into three segments. After initialization of the coaptation the TV leaflets were identified. The following parameters were automatically computed in 3D throughout the cardiac cycle: annular area, height, eccentricity and displacement, as well as intercommissural segment lengths. Results: Compared to CTRL, in patients with PAH, TVA was larger. The TA was also more circular and with less longitudinal displacement. Changes in annular remodeling were not uniform. The anterior and posterior segments were enlarged, while the septal remained unchanged, probably because the septal leaflet is fixed between the fibrous trigones. Conclusions: This novel software revealed that PAH affects size, shape and function of the TVA, suggesting that 3D analysis may be useful for evaluation of different RV disease states.

We present an automated technique using noise-based level-set methods and non-rigid registration for myocardial detection as a basis for perfusion quantification from cardiac magnetic resonance (CMR) images. We studied 27 patients undergoing contrast-enhanced CMR imaging (1.5T) at rest and during adenosine stress, and validated our technique against conventional manual analysis both directly and using quantitative coronary angiography (QCA) as reference. Contrast enhancement time-curves were constructed and used to calculate a number of perfusion indices. Measured segmental pixel intensities in each frame correlated highly with manual analysis (r=0.95). Bland-Altman analysis showed small biases (1.3 at rest; 0.0 at stress) and narrow limits of agreement (±13 at rest; ±14 at stress). The derived perfusion indices showed the same diagnostic accuracy as manual analysis (AUC up to 0.71 vs. 0.70). These results indicate that our automated technique allows fast detection of myocardial ROIs and quantification of perfusion abnormalities as accurately as manual analysis.

We developed a method for automated quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images. Our approach uses region-based and edge-based level set techniques for endocardial and epicardial border detection combined with non-rigid registration achieved by a 2D multi-scale cross-correlation and contour adaptation. This method was tested on 66 short-axis image sequences (Philips 1.5T) obtained in 11 patients at rest and during vasodilator stress at 3 levels of the left ventricle during first pass of a Gadolinium-DTPA bolus. Myocardial ROIs were automatically defined and contrast enhancement curves were constructed throughout the image sequence. Analysis of one sequence required

INTRODUCTION Myocardial perfusion assessment from cardiac magnetic resonance (CMR) images has proven to be feasible and useful. Extraction of quantitative perfusion information relies on the definition of myocardial regions of interest (ROI). This is usually achieved by manually drawing ROIs in one frame and then adjusting their position on subsequent frames. Unfortunately this tecnique requires a large amount of time and is potentially inaccurate. We recently developed a method based on image segmentation and registration for automated dynamic endocardial and epicardial borders detection for quantification of left ventricular perfusion. METHODS Data Acquisition: LV short-axis images (Philips 1.5T) were obtained at three levels of the left ventricle during first pass of a Gadolinium-DTPA bolus (0.10mmol/kg @5ml/ sec). Images were acquired using a hybrid gradient echo/echo planar imaging sequence (3 slices, thickness 10mm, pixel size 2.5x2.5mm, nonselective 90° saturation pulse followed by 80 ms delay, flip angle 20°, TR=5.9 ms, TE=2.7 ms, EPI factor 5, SENSE factor 2). Image segmentation: For each slice, the only manual action required was to place a seed point inside the LV cavity on a single frame. Starting from that point, an automated algorithm was developed to detect the two best frames for endocardial and epicardial boundaries segmentation, respectively. These frames were compulsory chosen among the first part of the image sequence, in which no myocardium movement took place. Hence the endocardial boundary was automatically computed using a modified region-based model based on the noise probability distribution of gray levels in MRI. Then epicardial boundary was detected using a classical edge based level-set model with curvature, advection and expansion driving terms. Both of the boundaries underwent a slight regularization motion in order to get a more physiological shape. Image registration: this step was necessary to compensate for respiratory motion and consisted in the rigid movement of the boundaries computed during the segmentation step. The goal was achieved by the implementation of two-dimensional cross-correlation. This algorithm was modified in order to look for correlation between the gradient of the images, in order to seek shape rather than intensity correspondence. Contrast enhancement curves extraction: Six standard myocardial ROIs were automatically defined and contrast enhancement curves were constructed throughout the image sequence. This approach was tested on 24 slices during first pass perfusion by: (1) visually judging frame-byframe the accuracy of endo- and epicardial boundary positions, and (2) calculating the ratio between the amplitude of the contrast enhancement curve and the SD of the plateau phase (SNR), which should be a good performance indicator of the algorithm as a whole. All the code was written in MATLAB® (The MathWorks, Natick, MA, USA). RESULTS Time needed to complete the automated analysis of one perfusion slice was less than 1 minute on a personal computer. The outcome of endo- and epicardial boundaries segmentation and registration was judged accurate in all image sequences. The computed contrast enhancement curves clearly showed the typical pattern of first-pass perfusion, with its wash-in slope and subsequent plateau phases. SNR averaged over 24 image sequences was 32±10. CONCLUSION Detection of myocardial boundaries and quantification of intra-myocardial contrast can be done in a fast, automated and dynamic fashion. The final outcome consists in regional contrast enhancement curves with excellent noise levels, which can be used to extract parameters of clinical value. The described approach provides a user-friendly and potentially more accurate technique, which may fulfill the strong need for clinical quantitative evaluation of myocardial perfusion from contrastenhanced CMR images.

International audience; Mitral valve (MV) physiopathological function and the effects of surgical repair can be studied through finite element models (FEMs). However, this approach assumes idealized morphology and boundary conditions limiting the analysis to paradigmatic scenarios and precluding patient-specific surgical planning. To overcome this limitation, we integrated into a MV FEM the patient-specific information about leaflets, annulus and papillary muscles geometry and dynamics, obtained from real-time 3D echocardiography. An ad-hoc web platform was created to facilitate FEM development from remote users, and grant access to parallel computing facilities. This approach was tested simulating MV closure in three normal subjects. Modelled valvular dynamics and quantitative results were consistent with experimental findings from literature. FEMs implementation required about 6 min, while simulations required about 7.5 hours on 32 parallel CPUs. Our approach appears reliable, reproducible and reasonably fast and may constitute the basis for the development of patient-specific tools for MV surgery. Introduction