Abstract
Background
There is a paucity of information concerning automatic mitral valve apparatus (MVA) analysis of patients with mitral valve prolapse (MVP). We aimed to study with an automatic three-dimensional (3D) transesophageal echocardiography (TEE)-dedicated software, patients with moderate and severe mitral regurgitation when compared to patients with no structural cardiac chamber alterations [patients with patent foramen ovale (PFO) who underwent TEE].
Methods
We employed TEE software dedicated to automatic analysis of 34 parameters of the MVA, comparing MVP patients with moderate and severe mitral regurgitation and patients with PFO without cardiac chamber structural alterations. Mitral valve effective regurgitant orifice (ERO) and regurgitant volume were correlated to automatic MVP parameters.
Results
Fifty-nine MVP patients and 43 PFO patients were analyzed. All MVP patients presented P2 MVP, 15 (25.4%) with both posterior and anterior prolapse. Twenty-seven automatic parameters (79%) were different concerning MVP and PFO patients (P<0.05): diameters, area, perimeter, height, angle, coaptation width, length, closure line length, and annulus. ERO was 0.43±0.11 cm2, and regurgitant volume was 62.9±14.9 mL/beat. Automatic analysis correlated to 75th percentile ERO MVP patients (ERO >0.48 cm2): posterior leaflet area (r=0.74, P=0.03); posterior leaflet length (r=0.73, P=0.03); tenting area (r=0.41, P=0.048).
Conclusions
Automatic mitral valve parameters differed significantly between patients with MVP and those without structural cardiac chamber remodeling. In exploratory analysis, patients in the upper range of ERO values (≥75th percentile) showed patterns involving posterior leaflet geometry that were consistent with the associations observed in continuous-variable analysis. These findings support the potential role of automated 3D assessment in the anatomical characterization of MVP.
Keywords: Mitral insufficiency, valvular heart disease, three-dimensional echocardiography (3D echocardiography), artificial intelligence
Highlight box.
Key findings
• Automatic mitral valve parameters differed significantly between patients with mitral valve prolapse (MVP) and those without structural cardiac chamber remodeling.
What is known and what is new?
• Artificial intelligence algorithms may be employed for mitral valve analysis. There is a paucity of information concerning automatic mitral valve apparatus analysis of patients with MVP.
• In exploratory analysis, patients in the upper range of ERO values (≥75th percentile) showed patterns involving posterior leaflet geometry that were consistent with the associations observed in continuous-variable analysis.
What is the implication, and what should change now?
• These findings support the potential role of automated three-dimensional assessment in the anatomical characterization of MVP.
Introduction
Mitral valve regurgitation caused by mitral valve prolapse (MVP) presents clinical relevance due to its high prevalence in clinical practice (1-13). Mitral valve apparatus (MVA) consists of a complex group of structures (1-13). Each of mitral valve anatomic elements has its own characteristics and particular aspects which make the MVA very unique.
A better understanding of the structures that make up the mitral valve allows us to determine the best time for surgical or percutaneous intervention (1-13). Imaging methods for the geometric and functional analysis of heart disease have evolved rapidly with the development of computing, nanotechnology, and artificial intelligence. For the analysis of valvular heart disease, echocardiography occupies a prominent position due to its ability to demonstrate cardiac anatomy with great accuracy and proximity to anatomical reality (1-13). In the 21st century, we have the opportunity to rapidly demonstrate cardiac structures using transesophageal echocardiography (TEE) and artificial intelligence from multiple spatial planes, taking into account multiplanar three-dimensional (3D) analysis, in real time, with the aid of algorithms specifically designed for demonstrating the MVA.
Thus, we planned a study to determine the different elements that make up the MVA, the morphofunctional analysis of the structures related to the valve apparatus (left atrium, left ventricle), using a 3D TEE automatic algorithm dedicated to the analysis of the MVA (Figures 1,2), when compared to patients without structural cardiac chamber changes. The software employed in the current study allows the automatic study of a higher number of mitral valve parameters when compared to previous investigations (6,11). This morphofunctional analysis of the MVA may even be more important in patients at the upper range of regurgitation severity. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1300/rc).
Figure 1.
Imaging with transthoracic (superior left image) and transesophageal tridimensional echocardiography and with the automatic dedicated software. Superior left image: demonstration of the posterior cusp prolapse. Central superior image: Barlow’s disease mitral valve (view from left atrium). Superior right image: demonstration of color flow Doppler severe mitral valve regurgitation. Inferior left image: different planes for apparatus reconstruction. Central inferior image: mitral valve reconstruction in green (PFO patient). Inferior right image: mitral valve reconstruction (MVP patient). In red MVP, view from the left atrium and lateral view. MVP, mitral valve prolapse; PFO, patent foramen ovale.
Figure 2.
MVP patient. Demonstration of different MVA variables measured with the automatic software. Mitral valve in green (atrial view). MVA, mitral valve apparatus; MVP, mitral valve prolapse.
Methods
Patients
Study design
A single-center prospective study from a Brazilian tertiary hospital center between August 2024 and September 2025 evaluating transesophageal 3D echocardiographic variables with a mitral valve automatic analysis algorithm was performed in 59 consecutive patients with mitral valve regurgitation (grade 2 and 3) due to MVP and 43 patients without structural cardiac chamber alterations who went to echocardiographic examination due to patent foramen ovale (PFO). Patients from both groups were matched by body surface.
The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of Hospital Israelita Albert Einstein, São Paulo, Brazil (under the number CAAE: 65875322.4.0000.0071 in 02/08/2024). Informed consent was obtained from all individual participants.
Inclusion criteria
Consecutive patients with moderate to severe mitral valve regurgitation resulting from valve prolapse in analysis for structural treatment;
Mitral valve regurgitation was graded after echocardiographic analysis: effective regurgitant orifice (ERO), regurgitant volume, vena contracta, color flow Doppler 3D [3D vena contracta area (VCA)];
Consecutive patients with clinical suspicion of PFO;
Patients over 18 years of age;
Signed informed consent form to participate in the study.
Exclusion criteria
Atrial fibrillation or tachyarrhythmia with hemodynamic instability;
Presence of significant aortic insufficiency, significant aortic stenosis, or significant mitral stenosis.
Echocardiography
Image acquisition
The images were acquired using a Philips Healthcare Epiq CVx echocardiography device by different investigators of the study. Images were acquired during a conventional transesophageal echocardiographic examination using conventional two-dimensional (2D) projections, with analysis of the complex MVA, including detailed analysis of all its components: annulus, cusps, commissures, chordae, papillary muscles, and left ventricle. All patients performed a transthoracic echocardiographic examination pre transesophageal investigation. The projections used for image transesophageal acquisition were: midesophageal commissural, long-axis, two-chamber, and four-chamber views with and without anteroflexion of the probe; and transgastric short-axis and long-axis views. After the 2D evaluation, 3D acquisitions were obtained in 3D zoom and full-volume formats (3D zoom images). Repeated 3D zoom images of the mitral valve complex were taken from the atrial aspect corresponding to the surgical view. Such acquisitions consist of obtaining subvolumes with angle and temporal resolution greater than the 3D zoom format with a higher volume rate, higher than 25 Hz, coupled to the electrocardiogram in consecutive cardiac cycles, and digitally stored for later analysis of the processed images.
Conventional 2D echocardiographic and Doppler parameters were measured, following previously published international recommendations (14).
Imaging analysis
The images extracted from the 3D transesophageal study were evaluated using Philips Health Care’s automatic software dedicated to the analysis of the MVA, which is part of Philips Health Care’s QLAB software, version 15.0.0. The analysis was performed offline on a workstation by two researchers involved in the investigation.
Echocardiographic variables to be analyzed with automatic software dedicated to the analysis with 3D TEE of the elements of the MVA in patients with mitral regurgitation and in patients with PFO: mitral annulus anteroposterior (AP) diameter, mitral annulus anterolateral-posteromedial (AL-PM) diameter, sphericity index (AP/AL-PM), intertrigonal distance, commissural diameter, saddle shaped annulus area (3D), saddle shaped annulus perimeter (3D), D-shaped annulus area (2D), D-shaped annulus perimeter, annulus height, non-planar angle, tenting volume, coaptation depth, tenting area, angle aortic [ascending aorta (AAo)-AP], maximum prolapse height, maximal open coaptation gap, maximal open coaptation width, total open coaptation area (3D), anterior leaflet area, posterior leaflet area, distal anterior leaflet angle, posterior leaflet angle, anterior leaflet length, posterior leaflet length, annulus area (2D), anterior closure line length (2D), anterior closure line length (3D), posterior closure line length (2D), posterior closure line length (3D), C-shaped annulus, annular displacement (max), annular displacement velocity (max), tenting volume fraction, annulus area fraction (2D) (Figures 1,2).
Statistical analysis
Normally distributed quantitative variables were expressed as mean ± standard deviation (SD) or as median and interquartile range (IQR) when not normally distributed; qualitative variables were summarized as number and percentage. The comparison between etiologies (MVP and PFO) was performed using Student's t-test for quantitative variables that were normally distributed. For those that were not normally distributed, the Mann-Whitney test was used. For data from participants with MI, Pearson correlation coefficient (r) and its 95% confidence interval (CI) were calculated between the variables ERO and regurgitant volume. The Pearson correlation coefficient and its 95% CI were also calculated between each of the variables in the new software and ERO and Regurgitant Volume. When correlation values were P<0.20, simple linear regression models were adjusted, thus obtaining the coefficient of explanation (R2) for each of the adjusted models. To adjust a multiple linear regression model, we first assessed the presence of multicollinearity among the variables obtained via the new software, and then selected which variables would be introduced into the multiple linear regression model.
The ERO and regurgitant volume variables were categorized based on the 75th percentile of each distribution. Each of the variables obtained via the new software was compared according to the ERO and regurgitant volume variable groups. The Student’s t-test was applied, and the effect size was calculated using Cohen’s test when the variables were normally distributed; otherwise, the Mann-Whitney test was applied, and the effect size was calculated using Cliff’s δ. All analyses were performed in StataNow/MP 19.5 (StataCorp, College Station, TX, USA), results with P values less than 0.05 were considered significant. Intra- and inter-observer variability [intraclass correlation coefficient (ICC)] were tested in 15 patients from MVP and PFO groups by the same operator and by a second operator 10 months after the first acquisition.
Results
The distribution of demographic data according to etiology, echocardiogram measurements according to etiology, comparison of new automatic software measures between etiologies, descriptive measures of ERO and regurgitant volume among patients with MVP, new automatic software measures according to 75th percentile of ERO, new automatic software measures according to 75th percentile of regurgitant volume are depicted in Tables 1-5. Vena contracta and color flow Doppler 3D (3D VCA) in patients with mitral valve regurgitation were as follows: 5–10 (7.3±3) mm; 0.30–0.60 (0.43±0.15) cm2.
Table 1. Distribution of demographic data according to etiology.
| Variables | Total (n=102) | Etiology | P value | |
|---|---|---|---|---|
| MVP (n=59) | PFO (n=43) | |||
| Sex | 0.001* | |||
| Female | 43 (42.2) | 17 (28.8) | 26 (60.5) | |
| Male | 59 (57.8) | 42 (71.2) | 17 (39.5) | |
| Age (years) | 57.2±18.1 | 61.4±17.2 | 51.5±18 | 0.006* |
| Weight (kg) | 74.4±15.1 | 76.4±16.1 | 71.7±13.4 | 0.12 |
| BMI (kg/m2) | 25.4±3.8 | 25.8±4.2 | 24.9±3.2 | 0.23 |
| Body surface (m2) | 1.86±0.23 | 1.89±0.25 | 1.82±0.20 | 0.13 |
Data are presented as n (%) or mean ± SD. *, P<0.05. BMI, body mass index; MVP, mitral valve prolapse; PFO, patent foramen ovale; SD, standard deviation.
Table 2. Echocardiographic measurements according to etiology.
| Variables | Total (n=102) | Etiology | P value | |
|---|---|---|---|---|
| MVP (n=59) | PFO (n=43) | |||
| LV diastolic diameter (mm) | 50.4±7.4 | 53.8±7.1 | 45.6±4.7 | <0.001* |
| Septum diastolic diameter (mm) | 9.6±1.7 | 10.2±1.6 | 8.8±1.7 | <0.001* |
| Posterior wall diastolic diameter (mm) | 9.3±1.5 | 9.8±1.3 | 8.6±1.4 | <0.001* |
| RV diastolic diameter (mm) | 25.2±3.4 | 25.5±3.4 | 25.1±3.3 | 0.81 |
| LVEF (%) | 61.8±8 | 60.4±9.9 | 63.6±3.8 | 0.03* |
| LA AP diameter (mm) | 40.7±8.3 | 45.4±7.2 | 34.3±4.8 | <0.001* |
| LA volume (mL) | 42.9±16.8 | 51.5±16,8 | 31±6 | <0.001* |
| PSAP (mmHg) | 31.9±12.9 | 34.9±13.8 | 24.1±4.7 | <0.001* |
Data are presented as mean ± SD. *, P<0.05. AP, anteroposterior; MVP, mitral valve prolapse; LA, left atrium; LV, left ventricle; LVEF, left ventricular ejection fraction (Teicholz method); PSAP, pulmonary artery systolic pressure; PFO, patent foramen ovale; RV, right ventricle; SD, standard deviation.
Table 3. Comparison of new automatic software measures between etiologies.
| Variables | Etiology | Difference (95% CI) | Hedges’ g (95% CI) | P value | |
|---|---|---|---|---|---|
| MVP (n=59) | PFO (n=43) | ||||
| AP diameter | 4.15±0.47 | 3.48±0.31 | 0.67 (0.52 to 0.83) | 1.62 (1.17 to 2.08) | <0.001* |
| AL-PM diameter | 4.43±0.61 | 3.57±0.29 | 0.86 (0.68 to 1.04) | 1.72 (1.26 to 2.17) | <0.001* |
| Sphericity index (AP/AL-PM) | 0.94±0.06 | 0.98±0.06 | −0.04 (−0.07 to −0.02) | −0.69 (−1.08 to −0.31) | <0.001* |
| Commissural diameter | 4.33±0.58 | 3.36±0.28 | 0.97 (0.80 to 1.14) | 2.01 (1.53 to 2.50) | <0.001* |
| Saddle shaped annulus area (3D) | 15.0±3.5 (n=56) | 10.4±1.6 (n=42) | 4.6 (3.5 to 5.6) | 1.56 (1.10 to 2.02) | <0.001* |
| Saddle shaped annulus perimeter (3D) | 14.2±1.7 (n=55) | 11.9±0.9 (n=42) | 2.3 (1.8 to 2.9) | 1.68 (1.21 to 2.15) | <0.001* |
| D-shaped annulus area (2D) | 13.3±3.3 (n=54) | 8.8±1.5 (n=42) | 4.5 (3.5 to 5.5) | 1.70 (1.23 to 2.17) | <0.001* |
| D-shaped annulus perimeter | 13.2±2.1 (n=54) | 11.0±0.9 (n=42) | 2.2 (1.6 to 2.9) | 1.34 (0.89 to 1.78) | <0.001* |
| Annulus height | 1.00±0.25 | 0.91±0.20 | 0.09 (0.01 to 0.18) | 0.41 (0.01 to 0.80) | 0.044* |
| Non-planar angle | 143.9±11.5 | 135.7±9.7 | 8.2 (4.0 to 12.3) | 0.75 (0.34 to 1.16) | <0.001* |
| Tenting volume | 2.45 (1.59–3.83) (n=36) | 3.37 (2.85–3.37) (n=42) | −0.85 (−1.59 to −0.11) | −0.76 (−1.41 to 0.05) | 0.04* |
| Coaptation depth | 9.3±5.2 (n=56) | 11.1±2.4 (n=42) | −1.8 (−3.4 to −0.3) | −0.44 (−0.83 to −0.04) | 0.02* |
| Tenting area | 1.66±0.94 (n=51) | 1.99±0.62 (n=43) | −0.33 (−0.66 to 0.00) | −0.40 (−0.81 to 0.00) | 0.052 |
| Angle AAo-AP | 112.5±10.2 | 115.6±8.4 | −3.1 (−6.8 to 0.5) | −0.33 (−0.72 to 0.06) | 0.10 |
| Maximum prolapse height | 7.19 (3.61–8.86) (n=54) | 1.04 (1.04–2.26) (n=41) | 5.91 (4.29 to 7.53) | 4.22 (2.69 to 6.40) | <0.001* |
| Maximal open coaptation gap | 2.11 (0–3.91) (n=17) | 0.00 (0–1.88) (n=10) | 2.11 (−0.54 to 4.76) | 0.53 (0.00 to 2.62) | 0.18 |
| Maximal open coaptation width | 42.4±7.8 (n=54) | 32.1±2.9 (n=40) | 10.3 (8.0 to 12.6) | 1.63 (1.16 to 2.11) | <0.001* |
| Total open coaptation area (3D) | 0.19 (0–0.54) (n=17) | 0.00 (0–0.24) (n=10) | 0.19 (−0.25 to 0.63) | 0.08 (0.00 to 0.45) | 0.23 |
| Anterior leaflet area | 8.92±2.32 (n=59) | 6.10±1.90 (n=42) | 2.82 (1.99 to 3.66) | 1.30 (0.86 to 1.73) | <0.001* |
| Posterior leaflet area | 10.64±3.26 (n=59) | 7.38±4.20 (n=42) | 3.26 (1.71 to 4.80) | 0.88 (0.46 to 1.29) | <0.001* |
| Distal anterior leaflet angle | 19.8±10.8 (n=59) | 28.1±6.4 (n=41) | −8.3 (−11.7 to −4.8) | −0.89 (−1.26 to −0.51) | <0.001* |
| Posterior leaflet angle | 29.0±18.4 (n=59) | 38.4±11.9 (n=41) | −9.4 (−15.4 to −3.4) | −0.58 (−0.97 to −0.19) | 0.005* |
| Anterior leaflet length | 2.93±0.48 (n=58) | 2.54±0.56 (n=42) | 0.39 (0.17 to 0.60) | 0.74 (0.33 to 1.15) | <0.001* |
| Posterior leaflet length | 2.52±0.55 (n=59) | 1.96±0.45 (n=42) | 0.56 (0.37 to 0.76) | 1.09 (0.67 to 1.52) | <0.001* |
| Annulus area (2D) | 14.5±3.6 (n=58) | 9.9±1.6 (n=42) | 4.6 (3.5 to 5.6) | 1.54 (1.09 to 1.99) | <0.001* |
| Anterior closure line length (2D) | 4.08±0.70 (n=57) | 3.08±0.26 (n=41) | 1.00 (0.80 to 1.21) | 1.77 (1.29 to 2.24) | <0.001* |
| Anterior closure line length (3D) | 4.26±0.75 (n=57) | 3.17±0.29 (n=41) | 1.09 (0.86 to 1.30) | 1.77 (1.30 to 2.25) | <0.001* |
| Posterior closure line length (2D) | 4.08±0.70 (n=57) | 3.08±0.26 (n=41) | 1.00 (0.80 to 1.20) | 1.78 (1.30 to 2.25) | <0.001* |
| Posterior closure line length (3D) | 4.25±0.74 (n=57) | 3.30±0.84 (n=41) | 0.95 (0.62 to 1.27) | 1.21 (0.77 to 1.64) | <0.001* |
| C-shaped annulus | 10.37±1.34 (n=57) | 8.34±0.89 (n=42) | 2.03 (1.58 to 2.47) | 1.72 (1.25 to 2.18) | <0.001* |
| Annular displacement (max) | 9.8±2.6 (n=57) | 10.2±1.8 (n=41) | −0.4 (−1.3 to 0.5) | −0.18 (−0.58 to 0.22) | 0.38 |
| Annular displacement velocity (max) | 35.3±9.0 (n=9) | 57.0±20.9 (n=6) | −21.7 (−43.7 to 0.3) | −1.38 (−2.27 to −0.50) | 0.052 |
| Tenting volume fraction | 55.6±24.2 (n=24) | 65.3±23.7 (n=40) | −9.7 (−22.2 to 2.8) | −0.40 (−0.90 to 0.10) | 0.12 |
| Annulus area fraction (2D) | 7.7 (4.0–17.2) (n=53) | 14.3 (9.1–7.7) (n=42) | −6.9 (−14.1 to 0.25) | −7.10 (−10.80 to −1.50) | 0.006* |
Data are presented as mean ± SD or median (IQR), unless otherwise specified. *, P<0.05. 2D, two-dimensional; 3D, three-dimensional; AAo, ascending aorta; AL-PM, anterolateral-posteromedial; AP, anteroposterior; CI, confidence interval; IQR, interquartile range; MVP, mitral valve prolapse; PFO, patent foramen ovale; SD, standard deviation.
Table 4. Descriptive measures of ERO and regurgitant volume among patients with MVP.
| Measure | ERO (cm2) | Regurgitant volume (mL/beat) |
|---|---|---|
| Mean | 0.43 | 62.9 |
| SD | 0.11 | 14.2 |
| Median | 0.42 | 64 |
| IQR | 0.35–0.48 | 54–70 |
| Minimum | 0.20 | 30 |
| Maximum | 0.77 | 115 |
ERO, effective regurgitant orifice; IQR, interquartile range; MVP, mitral valve prolapse; SD, standard deviation.
Table 5. New automatic software measures according to 75th percentile of ERO.
| Variables | Total (n=51) | ERO | P value | Effect size† | |
|---|---|---|---|---|---|
| ≥0.48 cm2 (n=12) | <0.48 cm2 (n=39) | ||||
| AP diameter | 4.21±0.46 | 4.35±0.46 | 4.17±0.46 | 0.22 | 0.41 |
| AL-PM diameter | 4.49±0.58 | 4.70±0.64 | 4.42±0.56 | 0.15 | 0.49 |
| Sphericity index (AP/AL-PM) | 0.94±0.06 | 0.93±0.06 | 0.95±0.07 | 0.46 | 0.47 |
| Commissural diameter | 4.37±0.60 | 4.58±0.68 | 4.30±0.56 | 0.16 | 0.47 |
| Saddle shaped annulus area (3D) | 15.3±3.6 (n=48) | 15.9±4.0 (n=10) | 15.1±3.5 (n=38) | 0.53 | 0.22 |
| Saddle shaped annulus perimeter (3D) | 14.3±1.7 (n=48) | 14.6±1.9 (n=10) | 14.2±1.7 (n=38) | 0.55 | 0.22 |
| D-shaped annulus area (2D) | 13.5±3.3 (n=47) | 14.1±3.8 (n=10) | 13.4±3.3 (n=37) | 0.58 | 0.20 |
| D-shaped annulus perimeter | 13.3±2.2 (n=47) | 13.7±1.8 (n=10) | 13.1±2.3 (n=37) | 0.49 | 0.25 |
| Annulus height | 1.00±0.25 | 0.97±0.24 | 1.01±0.25 | 0.59 | −0.18 |
| Non-planar angle | 144.0±11.5 | 145.3±10.6 | 143.6±11.9 | 0.65 | 0.15 |
| Tenting volume | n=31 | n=5 | n=26 | 0.81 | −0.08 |
| Median (IQR) | 2.10 (1.58–3.60) | 1.86 (1.14–3.42) | 2.18 (1.59–3.60) | ||
| Minimum–maximum | 0.17–8.53 | 1.04–8.53 | 0.17–7.34 | ||
| Coaptation depth | n=48 | n=10 | n=38 | 0.68 | −0.09 |
| Median (IQR) | 9.2 (4.7–12.8) | 7.1 (4.7–14.6) | 10.6 (4.7–12.5) | ||
| Minimum–maximum | 0.5–19.5 | 1.7–19.5 | 0.5–16.3 | ||
| Tenting area | n=44 | n=10 | n=34 | 0.048* | −0.41 |
| Median (IQR) | 1.37 (1.02–1.98) | 1.02 (0.67–1.31) | 1.53 (1.17–2.13) | ||
| Minimum–maximum | 0.20–4.53 | 0.38–4.53 | 0.20–3.50 | ||
| Angle AAo-AP | 112.7±10.9 | 112.5±9.7 | 112.8±11.3 | 0.93 | −0.03 |
| Maximum prolapse height | n=46 | n=10 | n=36 | 0.23 | 0.39 |
| Median (IQR) | 7.20 (3.68–8.86) | 7.87 (6.95–8.86) | 6.65 (3.65–8.82) | ||
| Minimum–maximum | 0.39–14.63 | 1.57–11.64 | 0.88–14.63 | ||
| Maximal open coaptation gap | n=16 | n=3 | n=13 | 0.72 | 0.18 |
| Median (IQR) | 1.76 (0–3.58) | 0 (0–11.74) | 2.11 (0.3–3.24) | ||
| Minimum–maximum | 0–11.74 | 0–11.74 | 0–5.63 | ||
| Maximal open coaptation width | 42.4±7.9 (n=46) | 42.8±7.9 (n=10) | 42.3±8.3 (n=36) | 0.84 | 0.07 |
| Total open coaptation area (3D) | n=16 | n=3 | n=13 | 0.72 | 0.18 |
| Median (IQR) | 0.17 (0–0.53) | 0 (0–2.79) | 0.19 (0.02–0.52) | ||
| Minimum–maximum | 0–2.79 | 0–2.79 | 0–0.97 | ||
| Anterior leaflet area | 8.9±2.4 | 9.5±2.5 | 8.8±2.3 | 0.35 | 0.31 |
| Posterior leaflet area | 10.9±3.4 | 12.7±4.3 | 10.4±2.9 | 0.03* | 0.74 |
| Distal anterior leaflet angle | 19.7±10.9 | 17.7±11.1 | 20.3±10.9 | 0.47 | −0.24 |
| Posterior leaflet angle | 27.0±15.4 | 23.7±17.1 | 28.0±14.9 | 0.40 | 0.28 |
| Anterior leaflet length | 2.89±0.45 (n=50) | 2.91±0.55 (n=12) | 2.89±0.42 (n=38) | 0.90 | 0.04 |
| Posterior leaflet length | 2.58±0.56 | 2.88±0.67 | 2.48±0.50 | 0.03* | 0.73 |
| Annulus area (2D) | 14.8±3.7 (n=50) | 16.2±4.2 (n=12) | 14.3±3.5 (n=38) | 0.12 | 0.53 |
| Anterior closure line length (2D) | 4.10±0.71 (n=49) | 4.21±0.72 (n=12) | 4.07±0.71 (n=37) | 0.55 | 0.20 |
| Anterior closure line length (3D) | 4.26±0.76 (n=49) | 4.39±0.77 (n=12) | 4.22±0.76 (n=37) | 0.53 | 0.21 |
| Posterior closure line length (2D) | 4.10±0.70 (n=49) | 4.21±0.72 (n=12) | 4.06±0.71 (n=37) | 0.52 | 0.21 |
| Posterior closure line length (3D) | 4.26±0.74 (n=49) | 4.36±0.72 (n=12) | 4.22±0.75 (n=37) | 0.58 | 0.19 |
| C-shaped annulus | 10.48±1.37 (n=49) | 10.90±1.55 (n=12) | 10.35±1.30 (n=37) | 0.23 | 0.41 |
| Annular displacement (max) | 9.96±2.62 (n=49) | 10.46±2.81 (n=12) | 9.80±2.57 (n=37) | 0.45 | 0.25 |
| Annular displacement velocity (max) | 35.3±9.0 (n=9) | 51.3 (n=1) | 33.3±7.2 (n=8) | – | – |
| Tenting volume fraction | 56.7±24.2 (n=19) | 50.4±29.0 (n=5) | 58.9±23.0 (n=14) | 0.52 | 0.35 |
| Annulus area fraction (2D) | n=45 | n=11 | n=34 | 0.70 | 0.08 |
| Median (IQR) | 7.6 (3.7–17.2) | 6.7 (2.1–17.2) | 7.6 (4.0–14.1) | ||
| Minimum–maximum | 0.7–31.8 | 1.0–31.8 | 0.7–31.8 | ||
Data are presented as mean ± SD or mean, unless otherwise specified. *, P<0.05. †, d-Cohen for Student t-test or Cliff for Mann-Whitney test. 2D, two-dimensional; 3D, three-dimensional; AAo, ascending aorta; AL-PM, anterolateral-posteromedial; AP, anteroposterior; ERO, effective regurgitant orifice; IQR, interquartile range; SD, standard deviation.
No statistically significant differences were observed in automated mitral valve parameters when patients were categorized by the 75th percentile of regurgitant volume.
ICC for intra-observer variability was >0.96 for all variables for MVP and PFO patients with coefficient of variation <2.2%. For inter-observer variability, ICC was >0.95, with coefficient of variation <2.7%. for all variables for MVP and PFO patients. These findings indicate high measurement consistency for the automated analysis workflow.
Discussion
The main finding of this manuscript is that twenty-seven automatic parameters (79%) were different concerning MVP and patients without structural cardiac chamber remodeling (PFO patients) (P<0.05): AP annular diameter, AL-PM diameter, commissural diameter, saddle shaped annulus area (3D), saddle shaped annulus perimeter (3D), D-shaped annulus area (2D), D-shaped annulus perimeter, annulus height, non-planar angle, maximal open coaptation width, anterior leaflet area, posterior leaflet area, anterior leaflet length, posterior leaflet length, annulus area (2D), anterior closure line length (2D), anterior closure line length (3D), posterior closure line length (2D), posterior closure line length (3D), C-shaped annulus (P<0.05). Other two parameters (5%), tenting area and annular displacement velocity max, were marginally different concerning groups (both P=0.052), The effect sizes (Hedges’ g between 1.0 and 2.0) indicate very large differences. with 95% CIs far from zero, reflecting annular remodeling and global enlargement of the valve apparatus in cases of MI. These differences suggest significant dilatation of the annulus and valve leaflets, consistent with the pathophysiology of degenerative mitral regurgitation.
The variable maximum prolapse height was not normally distributed, but through the Mann-Whitney test it was possible to verify that patients with MVP had a statistically higher median maximum prolapse height than that presented by patients with PFO (P<0.001), with a very large effect size (g=4.22; 95% CI: 2.69–6.40), corroborating the greater degree of leaflet prolapse.
The combination of clinically relevant absolute differences (0.6–1.0 cm in principal diameters) and very large effect sizes (Hedges’ g>1.5) supports the clinical relevance of the anatomical discrepancies identified by the automatic software, regardless of the absence of prior sample size calculation.
The mean ERO (0.43 cm2) and regurgitant volume (62.9 mL/beat) observed in this cohort were close to thresholds commonly associated with clinically relevant mitral regurgitation. For this reason, an exploratory categorization based on the 75th percentile of ERO was applied to descriptively examine patients with more advanced anatomical involvement. However, the subgroup defined by ERO ≥0.48 cm2 included a limited number of patients, which constrains statistical power and precludes definitive inference from categorical comparisons alone. Accordingly, these subgroup findings should be interpreted as hypothesis-generating and primarily intended to complement the continuous-variable analyses, which represent the main inferential framework of the study.
In exploratory subgroup analyses, patients were categorized according to the 75th percentile of ERO (≥0.48 cm2) to descriptively characterize those at the upper range of regurgitation severity. As shown in Table 5, patients with ERO ≥0.48 cm² exhibited higher values of posterior leaflet area and posterior leaflet length compared with those below this threshold. Posterior leaflet area was descriptively higher in the ERO ≥0.48 cm2 group (mean difference =2.39±1.07; 95% CI: 0.23 to 4.54; P=0.03), with a moderate effect size (Cohen’s d=0.74). Similarly, posterior leaflet length showed higher mean values in the upper ERO subgroup (mean difference =0.40±0.18; 95% CI: 0.04 to 0.75; P=0.03; Cohen’s d=0.73). Tenting area presented an asymmetric distribution and was descriptively smaller among patients with ERO ≥0.48 cm2 compared with those below this threshold [median (IQR), 1.02 (0.67–1.31) vs. 1.53 (1.17–2.13); P=0.048; Cliff’s δ=0.41]. These findings should be interpreted cautiously given the limited number of patients in this subgroup and are presented as exploratory, complementing the continuous-variable analyses.
Previous studies have addressed tridimensional echocardiography software dedicated to MVA analysis (6,8,15-19). They brought important information concerning mitral annulus (8), distance from posteromedial papillary muscles to mitral valve edge what can bring implications to good results for surgical repair (11). Also, information from a semi-automatic MVA study demonstrated that P2 leaflet length ≥20 mm and area ≥3.4 cm2 presented relevance to the performance of the cusp resection (6).
Importantly, the automated workflow demonstrated excellent intra- and inter-observer reproducibility. ICCs were greater than 0.96 for intra-observer variability and greater than 0.95 for inter-observer variability, with low coefficients of variation. These findings indicate high measurement consistency when the same 3D datasets are analyzed using the software. However, reproducibility should not be interpreted as evidence of measurement accuracy. A method may produce highly consistent values while still differing from a true anatomical reference. Therefore, the present study supports the reliability of the automated analysis workflow, but it does not establish the absolute validity of the measurements. This distinction is particularly relevant because the present investigation did not include an independent reference standard. Automated measurements were not compared with expert manual measurements, blinded independent echocardiographic readers, surgical findings, cardiac computed tomography, cardiac magnetic resonance imaging, or another validated anatomical reference. Accordingly, our results should be interpreted as evidence of standardized anatomical characterization and measurement reproducibility, rather than as definitive validation of the software’s accuracy. Future prospective studies comparing automated measurements with expert-derived and surgical reference standards are necessary to determine the absolute accuracy and clinical decision-making value of this approach.
Mitral valve repair, first described by Carpentier 56 years ago (20), remains the gold standard for treating degenerative mitral regurgitation. Recent advances in minimally invasive and robotic cardiac surgery aim to enhance the safety and efficacy of mitral valve repair (13). In this setting, the development of automated echocardiographic software tools may further improve reproducibility and standardization of the procedure, supporting its wider adoption in clinical practice. We believe that our investigation could bring and add new information concerning automatic mitral valve analysis and eventual useful information for surgical treatment. The efficiency, accuracy and potential use of the coming MVA analysis software are to be validated in future investigations (15-20).
This investigation concerns a small sample single center MVP patients with moderate and severe mitral regurgitation from a tertiary Brazilian hospital. Our results have to be validated in a higher population sample involving multiple centers in different countries. In addition, subgroup analyses based on the 75th percentile of ERO and regurgitant volume included a small number of patients, limiting statistical power and the robustness of categorical comparisons. Also, we did not consider age and sex for matching groups, just body surface. Although this strategy reduced differences in cardiac size, residual confounding from demographic characteristics cannot be excluded. Therefore, findings derived from these subgroup analyses should be considered exploratory and interpreted in conjunction with the continuous-variable analyses.
Although the automated measurements demonstrated excellent intra- and inter-observer reproducibility, the present study did not evaluate their absolute accuracy against an independent reference standard. Automated measurements were not compared with expert manual measurements, independent blinded echocardiographic readers, surgical findings, cardiac computed tomography, cardiac magnetic resonance imaging, or other validated imaging techniques. Consequently, our findings support the reproducibility and clinical applicability of the automated workflow but should not be interpreted as definitive validation of measurement accuracy. Finally, all automated analyses were performed using a single commercially available software platform (Philips Healthcare QLAB version 15.0.0). Therefore, the present findings may not be directly applicable to automated mitral valve analysis software developed by other manufacturers.
Conclusions
Automatic mitral valve parameters differed significantly between patients with MVP and those without structural cardiac chamber remodeling. Exploratory analyses of patients in the upper range of ERO values suggested descriptive associations involving posterior leaflet geometry, consistent with findings from continuous-variable analyses. These results highlight the potential clinical value of automated 3D mitral valve assessment in the anatomical characterization and procedural planning of MVP, while underscoring the need for validation in larger, multicenter cohorts.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of Hospital Israelita Albert Einstein, São Paulo, Brazil (under the number CAAE: 65875322.4.0000.0071 in 02/08/2024). Informed consent was obtained from all individual participants.
Footnotes
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1300/rc
Funding: None.
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1300/coif). The authors have no conflicts of interest to declare.
Data Sharing Statement
Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1300/dss
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