Anatomical Regurgitant Orifice Detection and Quantification from 3-D Echocardiographic Images

The vena contracta and effective regurgitant orifice area (EROA) are currently used for the clinical assessment of mitral regurgitation (MR) from 2-D color Doppler imaging. In addition to being highly user dependent and having low repeatability, these methods do not represent accurately the anatomic regurgitant orifice (ARO), which affects the adequate assessment of MR patients. We propose a novel method for semi-automatic detection and quantitative assessment of the 3-D ARO shape from 3-D transesophageal echocardiographic images. The algorithm was tested on a set of 25 patients with MR, and compared with EROA for validation. Results indicate the robustness of the proposed approach, with low variability in relation to different settings of user-defined segmentation parameters. Although EROA and ARO exhibited a good correlation (r = 0.8), relatively large biases were measured, indicating that EROA probably underestimates the real shape and size of the regurgitant orifice. Along with the higher reproducibility of the proposed approach, this highlights the limitations of current clinical approaches and underlines the importance of accurate assessment of the ARO shape for diagnosis and treatment in MR patients

Comparison of image processing techniques for nonviable tissue quantification in late gadolinium enhancement cardiac magnetic resonance images

Purpose: The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue analysis from cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) images. Materials and Methods: The investigated segmentation techniques were: (i) n-standard deviations thresholding; (ii) full width at half maximum thresholding; (iii) Gaussian mixture model classification; and (iv) fuzzy c-means clustering. These algorithms were applied either in each short axis slice (single-slice approach) or globally considering the entire short-axis stack covering the LV (global approach). CMR-LGE images from 20 patients with ischemic cardiomyopathy were retrospectively selected, and results from each technique were assessed against manual tracing. Results: All methods provided comparable performance in terms of accuracy in scar detection, computation of local transmurality, and high correlation in scar mass compared with the manual technique. In general, no significant difference between single-slice and global approach was noted. The reproducibility of manual and investigated techniques was confirmed in all cases with slightly lower results for the nSD approach. Conclusions: Automated techniques resulted in accurate and reproducible evaluation of LV scars from CMR-LGE in ischemic patients with performance similar to the manual technique. Their application could minimize user interaction and computational time, even when compared with semiautomated approaches

Comparison of the diagnostic performance of 64-slice computed tomography coronary angiography in diabetic and non-diabetic patients with suspected coronary artery disease

<p>Abstract</p> <p>Background</p> <p>Diabetics have high prevalence of subclinical coronary artery disease (CAD) with typical characteristics (diffuse disease, large calcifications). Although 64-slice multidetector computed tomography (MDCT) coronary angiography has high diagnostic accuracy to detect CAD, its diagnostic performance in diabetics with suspected CAD is unknown. To compare the diagnostic performance of 64-slice MDCT between diabetics and non-diabetics with suspected CAD scheduled for invasive coronary angiography (ICA).</p> <p>Methods</p> <p>We enrolled one hundred and five diabetic patients (92 men, age 65 +/- 9 years, Group 1) and 105 non-diabetic patients (63 men, age 63+/-5 years, Group 2) with indication to ICA for suspected CAD undergoing coronary 64-slice MDCT before ICA.</p> <p>Results</p> <p>In Group 1, the overall feasibility of coronary artery visualization was 93.8%. The most frequent artifact was blooming due to large coronary calcifications (54 artifacts, 67%). In Group 2, the overall feasibility was significantly higher vs. Group 1 (97%, p < 0.0001). In Group 1, the segment-based analysis showed a MDCT sensibility, specificity, positive predictive value, negative predictive value and accuracy for the detection of ≥50% luminal narrowing of 77%, 90%, 70%, 93% and 87%, respectively. In Group 2, all these parameters were significantly higher vs. Group 1. In the patient-based analysis, specificity, negative predictive value and accuracy were significantly lower in Group 1 vs. Group 2.</p> <p>Conclusions</p> <p>Although MDCT has high sensitivity for early identification of significant CAD in diabetics, its diagnostic performance is significantly reduced in these patients as compared to non-diabetics with similar clinical characteristics.</p

Right ventricular endocardial segmentation in CMR images using a novel inter-modality statistical shape modelling approach

Statistical shape modelling (SSM) approaches have been proposed as a powerful tool to segment the left ventricle in cardiac magnetic resonance (CMR) images. Our aim was to extend this method to segment the RV cavity in CMR images and validate it compared to the conventional gold-standard (GS) manual tracing. A SSM of the RV was built using a database of 4347 intrinsically 3D surfaces, extracted from transthoracic 3D echo cardiographic (3DE) images of 219 retrospective patients. The SSM was then scaled and deformed on the base of some features extracted, with different strategies, from each short-axis plane until a stable condition was reached. The proposed approach, tested on 14 patients, resulted in a high correlation (r2=0.97) and narrow limits of agreement (± 17% error) when comparing the semiautomatic volumes to the GS, confirming the accuracy of this approach in segmenting the RV endocardium

Evaluation of different statistical shape models for segmentation of the left ventricular endocardium from magnetic resonance images

International audienceStatistical shape models (SSMs) represent a powerful tool used in patient-specific modeling to segment medical images because they incorporate a-priori knowledge that guide the model during deformation. Our aim was to evaluate segmentation accuracy in terms of left ventricular (LV) volumes obtained using four different SSMs versus manual gold standard tracing on cardiac magnetic resonance (CMR) images. A database of 3D echocardiographic (3DE) LV surfaces obtained in 435 patients was used to generate four different SSMs, based on cardiac phase selection. Each model was scaled and deformed to detect LV endocardial contours in the enddiastolic (ED) and end-systolic (ES) frames of a CMR short-axis (SAX) stack for 15 patients with normal LV function. Linear correlation and Bland–Altman analyses versus gold-standard showed in all cases high correlation (r²>0.95), non-significant biases and narrow limits of agreement

Predicting Long-Term Mortality in TAVI Patients Using Machine Learning Techniques

Background: Whereas transcatheter aortic valve implantation (TAVI) has become the gold standard for aortic valve stenosis treatment in high-risk patients, it has recently been extended to include intermediate risk patients. However, the mortality rate at 5 years is still elevated. The aim of the present study was to develop a novel machine learning (ML) approach able to identify the best predictors of 5-year mortality after TAVI among several clinical and echocardiographic variables, which may improve the long-term prognosis. Methods: We retrospectively enrolled 471 patients undergoing TAVI. More than 80 pre-TAVI variables were collected and analyzed through different feature selection processes, which allowed for the identification of several variables with the highest predictive value of mortality. Different ML models were compared. Results: Multilayer perceptron resulted in the best performance in predicting mortality at 5 years after TAVI, with an area under the curve, positive predictive value, and sensitivity of 0.79, 0.73, and 0.71, respectively. Conclusions: We presented an ML approach for the assessment of risk factors for long-term mortality after TAVI to improve clinical prognosis. Fourteen potential predictors were identified with the organic mitral regurgitation (myxomatous or calcific degeneration of the leaflets and/or annulus) which showed the highest impact on 5 years mortality

Arrhythmic Mitral Valve Prolapse: Introducing an Era of Multimodality Imaging-Based Diagnosis and Risk Stratification.

Mitral valve prolapse is a common cardiac condition, with an estimated prevalence between 1% and 3%. Most patients have a benign course, but ever since its initial description mitral valve prolapse has been associated to sudden cardiac death. Although the causal relationship between mitral valve prolapse and sudden cardiac death has never been clearly demonstrated, different factors have been implicated in arrhythmogenesis in patients with mitral valve prolapse. In this work, we offer a comprehensive overview of the etiology and the genetic background, epidemiology, pathophysiology, and we focus on the state-of-the-art imaging-based diagnosis of mitral valve prolapse. Going beyond the classical, well-described clinical factors, such as young age, female gender and auscultatory findings, we investigate multimodality imaging features, such as alterations of anatomy and function of the mitral valve and its leaflets, the structural and contractile anomalies of the myocardium, all of which have been associated to sudden cardiac death.This research received no external fundingS

Predictive Value of Pre-Operative 2D and 3D Transthoracic Echocardiography in Patients Undergoing Mitral Valve Repair: Long Term Follow Up of Mitral Valve Regurgitation Recurrence and Heart Chamber Remodeling

: The "ideal" management of asymptomatic severe mitral regurgitation (MR) in valve prolapse (MVP) is still debated. The aims of this study were to identify pre-operatory parameters predictive of residual MR and of early and long-term favorable remodeling after MVP repair. We included 295 patients who underwent MV repair for MVP with pre-operatory two- and three-dimensional transthoracic echocardiography (2DTTE and 3DTTE) and 6-months (6M) and 3-years (3Y) follow-up 2DTTE. MVP was classified by 3DTTE as simple or complex and surgical procedures as simple or complex. Pre-operative echo parameters were compared to post-operative values at 6M and 3Y. Patients were divided into Group 1 (6M-MR &lt; 2) and Group 2 (6M-MR ≥ 2), and predictors of MR 2 were investigated. MVP was simple in 178/295 pts, and 94% underwent simple procedures, while in only 42/117 (36%) of complex MVP a simple procedure was performed. A significant relation among prolapse anatomy, surgical procedures and residual MR was found. Post-operative MR ≥ 2 was present in 9.8%: complex MVP undergoing complex procedures had twice the percentage of MR ≥ 2 vs. simple MVP and simple procedures. MVP complexity resulted independent predictor of 6M-MR ≥ 2. Favorable cardiac remodeling, initially found in all cases, was maintained only in MR &lt; 2 at 3Y. Pre-operative 3DTTE MVP morphology identifies pts undergoing simple or complex procedures predicting MR recurrence and favorable cardiac remodeling

Composition of the Essential Oil of Coristospermum cuneifolium and Antimicrobial Activity Evaluation

AbstractFor the first time, the chemical composition and antimicrobial evaluation of Coristospermum cuneifolium (previously named Ligusticum lucidum subsp. cuneifolium) essential oil obtained from the aerial parts are reported in this work. Approximately 85% of the total constituents were identified by GC-MS analysis, evidencing the presence of 12 chemical components which belong to several classes of natural compounds. Most of them are reported for the first time in the Ligusticum genus (s.l.) and in the Apiaceae family. Their presence was able to provide a rationale for essential oil use in the field similar to those obtained from other species of the Ligusticum genus (s.l.). Moreover, the huge presence of aromatizing and flavoring components, accounting for 44.4% of the essential oil composition, might make C. cuneifolium a useful natural source of aromatic components for the food and cosmetic fields. In addition to this, a deep comparison of the essential oil of this species with that of other entities within the Ligusticum genus (s.l.) was performed and discussed on a chemotaxonomic basis.The essential oil was tested for its antimicrobial activity at both high and low inoculum (~5×105 and ~ 5×103 cfu/mL, respectively) against several bacterial and fungal strains, including methicillin-susceptible Staphylococcus aureus (ATCC 29213), Escherichia coli (ATCC 25922), Candida albicans (ATCC 14053), methicillin-resistant S. aureus (clinical strain), carbapenem-susceptible Klebsiella pneumoniae (clinical strain), carbapenem-resistant K. pneumoniae (clinical strain), and carbapenem-resistant Acinetobacter baumannii (clinical strain).A high potency against C. albicans was shown, with an absence of growth at the concentration of 3.01 mg/mL; similarly, for methicillin-susceptible S. aureus and methicillin-resistant S. aureus, a reduction of 1.73 and 2 log10 cfu/mL at the concentration of 3.01 mg/mL was observed. With regard to gram-negative microorganisms, only slight potency against A. baumannii was shown, whereas no activity was found against E. coli and K. pneumoniae