Reproducibility of a novel echocardiographic 3D automated software for the assessment of mitral valve anatomy

Mitral Annulus Geometry and Dynamic Motion Changes in Patients With Aortic Regurgitation: A Three-Dimensional Transesophageal Echocardiographic Study

OBJECTIVE

The aim of the present study was to investigate the mitral annulus (MA) geometry and dynamic motion changes in patients with aortic regurgitation (AR) before and after aortic valve replacement (AVR). Moreover, the difference in the effect of the type of prosthetic aortic valve on MA was compared.

DESIGN

Prospective observational study.

SETTING

Cardiac operating room at a single hospital.

PARTICIPANTS

Eighty-two patients with isolated moderate-to-severe AR who underwent AVR. Forty patients with normal valves were enrolled as controls.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The MA geometry and dynamic motion throughout the cardiac cycle were evaluated semiautomatically by three-dimensional transesophageal echocardiography. The severity of functional mitral regurgitation was intraoperatively evaluated. All patients were divided into 2 groups depending on the type of prosthetic valve (mechanical valve and bioprosthetic valve groups). Before AVR, compared with the control group without AR, the AR group demonstrated larger MA dimensions and the MA geometry was flatter. The contraction fraction of the MA area, perimeter, and height during the whole cardiac cycle were larger in the AR group (p < 0.05 for all). After AVR, most MA geometric and dynamic parameters decreased and functional mitral regurgitation also improved. In the postoperative subset analyses, the mechanical valve group showed a larger contraction fraction of the MA area and perimeter than the bioprosthetic valve group (p < 0.05 for both).

CONCLUSIONS

The MA geometry and dynamic motion changed markedly in patients with AR. These spatial and dynamic changes were restored to a certain extent after surgical correction of the aortic valve. However, the effects produced by mechanical and bioprosthetic valves on MA were different.

Mitral valve prolapse in patients with atrial septal defect: A quantitative three-dimensional echocardiographic analysis

INTRODUCTION AND OBJECTIVES

Mitral valve (MV) prolapse is highly prevalent in patients with atrial septal defect (ASD). Abnormal left ventricular geometry has been proposed as the main mechanism of MV prolapse in ASD, however, the changes in the morphology of the MV apparatus remain to be clarified. Our aim was to assess the MV geometry in patients with ASD and MV prolapse.

METHODS

We evaluated 99 patients (73% female, median age 40 years) with ASD who underwent a three-dimensional transesophageal echocardiogram. Three-dimensional analysis of the MV was done using dedicated automated software. Transthoracic echocardiographic parameters were assessed post ASD closure in 28 patients.

RESULTS

MV prolapse was found in 39% of patients. Although smaller left ventricular dimensions and greater interatrial shunt were found in patients with MV prolapse compared with those without prolapse, there was no difference in the subvalvular parameters. MV prolapse was associated with larger mitral anterior-posterior diameter, anterolateral-posteromedial diameter, anterior perimeter, posterior perimeter, total perimeter, and anterior leaflet area (all p < 0.05). Mitral regurgitation was more frequent in patients with MV prolapse (80 vs. 48%, p = 0.002).

CONCLUSIONS

In patients with ASD, the main mechanism of MV prolapse is the presence of an organic primary process of the MV apparatus (excessive anterior mitral leaflet tissue and mitral annular enlargement).

ACR Appropriateness Criteria® Dyspnea-Suspected Cardiac Origin (Ischemia Already Excluded): 2021 Update

Dyspnea is the symptom of perceived breathing discomfort and is commonly encountered in a variety of clinical settings. Cardiac etiologies of dyspnea are an important consideration; among these, valvular heart disease (Variant 1), arrhythmia (Variant 2), and pericardial disease (Variant 3) are reviewed in this document. Imaging plays an important role in the clinical assessment of these suspected abnormalities, with usually appropriate procedures including resting transthoracic echocardiography in all three variants, radiography for Variants 1 and 3, MRI heart function and morphology in Variants 2 and 3, and CT heart function and morphology with intravenous contrast for Variant 3. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

The role of artificial intelligence in paediatric cardiovascular magnetic resonance imaging

Artificial intelligence (AI) offers the potential to change many aspects of paediatric cardiac imaging. At present, there are only a few clinically validated examples of AI applications in this field. This review focuses on the use of AI in paediatric cardiovascular MRI, using examples from paediatric cardiovascular MRI, adult cardiovascular MRI and other radiologic experience.

Atrial myxomas arise from multipotent cardiac stem cells

Aims

Cardiac myxomas usually develop in the atria and consist of an acid-mucopolysaccharide-rich myxoid matrix with polygonal stromal cells scattered throughout. These human benign tumours are a valuable research model because of the rarity of cardiac tumours, their clinical presentation and uncertain origin. Here, we assessed whether multipotent cardiac stem/progenitor cells (CSCs) give rise to atrial myxoma tissue.

Methods and results

Twenty-three myxomas were collected and analysed for the presence of multipotent CSCs. We detected myxoma cells positive for c-kit (c-kit^pos) but very rare Isl-1 positive cells. Most of the c-kit^pos cells were blood lineage-committed CD45^pos/CD31^pos cells. However, c-kit^pos/CD45^neg/CD31^neg cardiac myxoma cells expressed stemness and cardiac progenitor cell transcription factors. Approximately ≤10% of the c-kit^pos/CD45^neg/CD31^neg myxoma cells also expressed calretinin, a characteristic of myxoma stromal cells. In vitro, the c-kit^pos/CD45^neg/CD31^neg myxoma cells secrete chondroitin-6-sulfate and hyaluronic acid, which are the main components of gelatinous myxoma matrix in vivo. In vitro, c-kit^pos/CD45^neg/CD31^neg myxoma cells have stem cell properties being clonogenic, self-renewing, and sphere forming while exhibiting an abortive cardiac differentiation potential. Myxoma-derived CSCs possess a mRNA and microRNA transcriptome overall similar to normal myocardium-derived c-kit^pos/CD45^neg/CD31^negCSCs , yet showing a relatively small and relevant fraction of dysregulated mRNA/miRNAs (miR-126-3p and miR-335-5p, in particular). Importantly, myxoma-derived CSCs but not normal myocardium-derived CSCs, seed human myxoma tumours in xenograft’s in immunodeficient NOD/SCID mice.

Conclusion

Myxoma-derived c-kit^pos/CD45^neg/CD31^neg CSCs fulfill the criteria expected of atrial myxoma-initiating stem cells. The transcriptome of these cells indicates that they belong to or are derived from the same lineage as the atrial multipotent c-kit^pos/CD45^neg/CD31^neg CSCs. Taken together the data presented here suggest that human myxomas could be the first-described CSC-related human heart disease.

Integration of artificial intelligence into clinical patient management: focus on cardiac imaging

Cardiac imaging is a crucial component in the management of patients with heart disease, and as such it influences multiple, inter-related parts of the clinical workflow: physician-patient contact, image acquisition, image pre- and postprocessing, study reporting, diagnostics and outcome predictions, medical interventions, and, finally, knowledge-building through clinical research. With the gradual and ubiquitous infiltration of artificial intelligence into cardiology, it has become clear that, when used appropriately, it will influence and potentially improve-through automation, standardization and data integration-all components of the clinical workflow. This review aims to present a comprehensive view of full integration of artificial intelligence into the standard clinical patient management-with a focus on cardiac imaging, but applicable to all information handling-and to discuss current barriers that remain to be overcome before its widespread implementation and integration.

Abnormal Papillary Muscle Signal on Cine MRI As a Typical Feature of Mitral Valve Prolapse

BACKGROUND

Mitral valve prolapse (MVP) is characterized by an abnormal movement of the valvular apparatus which may affect the papillary muscles (PMs) function and structure. Aim of the study was to investigate abnormal PM signal in MVP by using cardiac magnetic resonance imaging (MRI).

METHODS AND RESULTS

We enrolled 47 consecutive patients with MVP evaluated by cardiac MRI. Additional groups included healthy volunteers, patients with moderate-to-severe mitral regurgitation (not caused by MVP) and patients with hypertrophic cardiomyopathy. Visual assessment of the PM signals was carried out and the signal intensity (SI) of both the antero-lateral and postero-medial PMs was normalized by that of the left ventricular (LV) parietal myocardium. Our results show that in the MVP group only, the PM signal intensity was significantly lower compared to the one of the LV parietal myocardium. This sign did not correlate with either LV late gadolinium enhancement or positive anamnesis for significant arrhythmias.

CONCLUSIONS

In MVP patients only, PM signal is significantly reduced compared to LV parietal myocardium ("darker appearance"). The described findings are not clearly related to evidence of myocardial fibrosis, as assessed by MRI, and to previous occurrence of complex ventricular arrhythmias.

Topical rifampicin for prevention of deep sternal wound infections in patients undergoing coronary artery bypass grafting

Deep sternal wound infections (DSWI), although an infrequent complication, significantly impair postoperative outcomes after coronary artery bypass grafting (CABG) surgery. Among several preventive strategies, topical antibiotic therapy immediately before sternal closure has been strongly advocated. In this retrospective analysis, the incidence of DSWI in 517 patients undergoing isolated CABG and receiving rifampicin irrigation of mediastinum, sternum and suprasternal tissues was compared to an historical consecutive cohort of 448 patients. To account for the inherent selection bias, a 1:1 propensity matched analysis was performed. Patients receiving topical rifampicin experienced significantly less occurrence of postoperative DSWI (0.2% vs 2.5%, p = 0.0016 in the unmatched analysis; 0.3% vs 2.1%, p = 0.0391 in the matched analysis). Intensive care unit stay, hospital stay, and operative mortality were similar between groups. This study shows that topical rifampicin in combination with commonly prescribed preventative strategies significantly reduces the incidence of DSWI to less than 0.3% in unselected patients undergoing a full median sternotomy for CABG. Further studies, including a larger number of patients and with a randomization design, would establish the potential preventative role of topical rifampicin in reducing the occurrence of DSWI.

Mitral Annulus Segmentation Using Deep Learning in 3-D Transesophageal Echocardiography

3D Transesophageal Echocardiography is an excellent tool for evaluating the mitral valve and is also well suited for guiding cardiac interventions. We introduce a fully automatic method for mitral annulus segmentation in 3D Transesophageal Echocardiography, which requires no manual input. One hundred eleven multi-frame 3D transesophageal echocardiography recordings were split into training, validation, and test sets. Each 3D recording was decomposed into a set of 2D planes, exploiting the symmetry around the centerline of the left ventricle. A deep 2D convolutional neural network was trained to predict the mitral annulus coordinates, and the predictions from neighboring planes were regularized by enforcing continuity around the annulus. Applying the final model and post-processing to the test set data gave a mean error of 2.0 mm - with a standard deviation of 1.9 mm. Fully automatic segmentation of the mitral annulus can alleviate the need for manual interaction in the quantification of an array of mitral annular parameters and has the potential to eliminate inter-observer variability.

Automated Spectral Doppler Profile Tracing

OBJECTIVE

The authors hypothesized that automated tracings of both pulsed wave (PW) and continuous wave (CW) Doppler correlate well with manual measurements performed by an experienced echocardiographer.

DESIGN

The authors performed a retrospective analysis of spectral Doppler profile measurements performed by automated software and an echocardiographer.

SETTING

University hospital, single institution.

PARTICIPANTS

The authors reviewed transesophageal echocardiographic examinations from patients undergoing transcatheter aortic valve (AV) replacement procedures at their institution.

INTERVENTIONS

No interventions were performed solely for research purposes.

MEASUREMENTS AND MAIN RESULTS

PW and CW spectral envelopes at the left ventricular outflow tract (LVOT) and AV were analyzed. Blinded, a board-certified echocardiographer performed manual measurements of the identical spectral envelopes. Peak velocities, mean gradients, and velocity time integrals (VTI) were collected. A total of 33 PW as well as 33 CW Doppler spectral envelopes were evaluated. There was no significant difference between the measurements provided by the automated software and manual tracings. LVOT PW VTI automated versus manual: 18.2 cm versus 15.9 cm, p = 0.11. AV CW VTI automated versus manual: 65.8 cm versus 64.8 cm, p = 0.90. AV CW mean gradient automated versus manual: 24.3 mmHg versus 23.4 mmHg, p = 0.84. AV CW peak velocity automated versus manual: 3.00 m/s versus 2.98 m/s, p = 0.93. Correlation coefficients were all above 0.9.

CONCLUSIONS

Automated measurements of peak velocities, mean gradients, and VTI of spectral Doppler correlate closely with manual measurements performed by an experienced echocardiographer.

Differences in Two- and Three-Dimensional Assessment of the Mitral Valve by Novices and Experts, Illustrated Using Anterior Mitral Valve Leaflet Length

OBJECTIVES

In this measurement validation study, the authors evaluated agreement between 2-dimensional (2D) and three-dimensional (3D) transesophageal echocardiography (TEE), measuring anterior mitral valve leaflet length by both novice and experienced echocardiographers.

DESIGN

This was a retrospective, observational study.

SETTING

Single university hospital.

PARTICIPANTS

Analyses on datasets from 44 patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Fifty datasets from 44 patients with mitral regurgitation were analyzed by 4 observers (2 novices, 2 experts). All observers measured the anterior mitral valve leaflet length from end-systolic 2D TEE images from the midesophageal longitudinal axis view and 3D software-augmented TEE images. The overall mean anterior mitral valve leaflet length was significantly shorter with 3D versus 2D TEE measurements (24.6 ± 4.5 mm v 26.2 ± 5.3 mm; p < 0.001), with novices measuring shorter leaflets than experts for both techniques (p < 0.001 and p = 0.005, respectively). Bland-Altman plots of 3D and 2D TEE measurements showed mean biases (95% limits of agreement) of -1.6 mm (-9.0 to 5.9 mm), -1.8 mm (-9.6 to 6.0 mm), and -1.3 mm (-8.4 to 5.7 mm) for all observers, novices, and experts, respectively. For 2D measurements, interobserver reliability was very strong among experts and strong among novices (Pearson's r = 0.83 v 0.66; p = 0.055). For 3D measurements, interobserver reliability was strong in experts and moderate in novices (Pearson's r = 0.69 v 0.51; p = 0.168).

CONCLUSION

For both novices and experts, 3D TEE measurements of the anterior mitral valve leaflet were significantly shorter than 2D measurements. Interobserver reliability was lowest for novices making 3D TEE measurements, indicating that reliable, quantitative evaluation of 3D TEE may require a greater amount of practice.

Advanced Imaging Techniques for Mitral Regurgitation

Mitral regurgitation (MR) is one of the most commonly encountered valvular lesions in clinical practice. MR can be either primary (degenerative) or secondary (functional) depending on the etiology of MR and the pathology of the mitral valve (MV). Echocardiography is the primary diagnostic tool for MR and is key in determining this etiology as well as MR severity. While clinicians usually turn to 2 Dimensional echocardiography as first-line imaging, 3 Dimensional echocardiography (3DE) has continually shown to be superior in terms of describing MV anatomy and pathology. This review article elaborates on 3DE techniques, modalities, and advances in software. Furthermore, the article demonstrates how 3DE has reformed MR evaluation and has played a vital role in determining patient management.

Automation, machine learning, and artificial intelligence in echocardiography: A brave new world

Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to improve accuracy and efficiency of manual tracings. Automation with longitudinal strain and 3D echocardiography has shown great accuracy and reproducibility allowing the incorporation of these techniques into daily workflow. This will give further experience to nonexpert readers and allow the integration of these essential tools into more echocardiography laboratories. The potential for machine learning in cardiovascular imaging is still being discovered as algorithms are being created, with training on large data sets beyond what traditional statistical reasoning can handle. Deep learning when applied to large image repositories will recognize complex relationships and patterns integrating all properties of the image, which will unlock further connections about the natural history and prognosis of cardiac disease states. The purpose of this review article was to describe the role and current use of automation, machine learning, and AI in echocardiography and discuss potential limitations and challenges of in the future.

Superiority of novel automated assessment of aortic annulus by intraoperative three-dimensional transesophageal echocardiography in patients with severe aortic stenosis: Comparison with conventional cross-sectional assessment

BACKGROUND

Previous studies have demonstrated that three-dimensional (3D) transesophageal echocardiography (TEE) is an alternative to multi-detector computed tomography (MDCT) for aortic valve sizing in transcatheter aortic valve replacement (TAVR). However, conventional cross-sectional analysis of aortic annulus by 3D TEE has some limitations such as lengthy analytical time. A novel software for automated valve measurement has been developed for 3D TEE. We evaluated the accuracy and analytical time of aortic annular measurements using this novel automated software in the clinical setting.

METHODS

We retrospectively studied 43 patients with symptomatic severe aortic stenosis (AS) who underwent TAVR. All patients underwent intraoperative TEE and MDCT. We measured aortic annular area by automated, semi-automated, and cross-sectional methods using 3D TEE datasets. These measurements were compared to the corresponding MDCT reference values. We also compared the analytical time of the three methods.

RESULTS

Automated and semi-automated analyses required significantly shorter analytical time compared to cross-sectional analysis (automated: 30.1±5.79s, semi-automated: 74.1±15.0s, manual: 81.8±18.5s, p<0.05). Compared to MDCT measurement (393.7±81.0mm²), annular areas measured by automated and cross-sectional methods were significantly smaller (automated: 380.6±77.1mm², cross-sectional: 374.7±76.8mm², p<0.05), while that obtained by semi-automated method was not significantly different (387.7±75.8mm²). Annular areas determined by semi-automated and cross-sectional analyses had narrower limits of agreement (LOA) with MDCT measurements, compared to automated analysis (automated: -68.6 to 94.7mm², semi-automated: -48.3 to 60.2mm², cross-sectional: -40.0 to 77.9mm²). Measurements by all three methods using 3D TEE showed high correlation with MDCT measurement (automated: r=0.86, semi-automated: r=0.94, cross-sectional: r=0.93).

CONCLUSIONS

For aortic annular measurements using 3D TEE in AS patients, semi-automated analysis using the novel automated software reduced analytical time while maintaining similar accuracy compared to the conventional cross-sectional analysis. This automated software may have acceptable feasibility in the clinical setting.

Fully automated software for mitral annulus evaluation in chronic mitral regurgitation by 3-dimensional transesophageal echocardiography

Three-dimensional (3D) transesophageal echocardiography (TEE) is the gold standard for mitral valve (MV) anatomic and functional evaluation. Currently, dedicated MV analysis software has limitations for its use in clinical practice. Thus, we tested here a complete and reproducible evaluation of a new fully automatic software to characterize MV anatomy in different forms of mitral regurgitation (MR) by 3D TEE.Sixty patients were included: 45 with more than moderate MR (28 organic MR [OMR] and 17 functional MR [FMR]) and 15 controls. All patients underwent TEE. 3D MV images obtained using 3D zoom were imported into the new software for automatic analysis. Different MV parameters were obtained and compared. Anatomic and dynamic differences between FMR and OMR were detected. A significant increase in systolic (859.75 vs 801.83 vs 607.78 mm; P = 0.002) and diastolic (1040.60 vs. 1217.83 and 859.74 mm; P < 0.001) annular sizes was observed in both OMR and FMR compared to that in controls. FMR had a reduced mitral annular contraction compared to degenerative cases of OMR and to controls (17.14% vs 32.78% and 29.89%; P = 0.007). Good reproducibility was demonstrated along with a short analysis time (mean 4.30 minutes).Annular characteristics and dynamics are abnormal in both FMR and OMR. Full 3D software analysis automatically calculates several significant parameters that provide a correct and complete assessment of anatomy and dynamic mitral annulus geometry and displacement in the 3D space. This analysis allows a better characterization of MR pathophysiology and could be useful in designing new devices for MR repair or replacement.