A total of 197 consecutive clinical patients from July 2020 to October 2020 were selected. Forty-seven were excluded for the following reasons: 3 of 17 consecutive myocardial segments were unclear (n = 20); difficulty with holding one’s breath (n = 7); and generation of an incorrect left ventricular mold by automatic quantification software that could not be manually edited and corrected (n = 20). A total of 150 patients were finally enrolled in this study and divided into the following four groups. Group A was the control group (n = 42, 18 males, 24 females), with an average age of 39 ± 12 years and an average body surface area (BSA) of 1.68 ± 0.13 m². Patients were included after ruling out organic heart diseases by evaluating the patient’s medical history and family history and obtaining an electrocardiogram or conventional echocardiogram. Group B was the dilated cardiomyopathy (DCM) group (n = 35, 21 males and 14 females), with an average age of 53 ± 15 years and an average BSA of 1.69 ± 0.16 m²; 4 patients also had atrial fibrillation, and 15 had an implanted pacemaker. Patients were those without significant epicardial coronary artery obstructions but with an enlarged left ventricle and diminished left ventricular wall motion on ultrasound. Group C consisted of patients with ventricular remodeling after acute myocardial infarction (AMI) (n = 41, 28 males and 13 females), with an average age of 63 ± 11 years and an average BSA of 1.67 ± 0.12 m²; 11 patients had a ventricular aneurysm, 9 had atrial fibrillation, 11 were implanted with a pacemaker, and 4 had a history of mitral valve replacement. All patients had a history of AMI and coronary angiography and ultrasound confirmed segmental or diffuse wall motion abnormalities. Group D was the HCM group (n = 32 cases, 22 males and 10 females), with an average age of 55 ± 14 years and an average BSA of 1.73 ± 0.17 m². Five patients had atrial fibrillation. The diagnostic standard for HCM, thickness of at least one myocardial segment ≥ 15 mm that cannot be explained by load alone, was in accordance with the adult standard in the 2014 European Cardiology Association HCM Diagnosis and Treatment Guidelines. The study was approved by the ethics committee of Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, with a wavier for individual consent by the committee owing to the retrospective study design.

All patients underwent 2D and 3D transthoracic echocardiographic examination using a Philips EPIQ 7C echocardiography diagnosis instrument with an X5-1 probe (1-5 MHz). The instrument was equipped with the HeartModel (HM) 3D image acquisition mode and the QLab10.5 software package, including a 3D quantification (3DQ) Advance plug-in image analyzer. A senior doctor with more than 10 years of experience in echocardiography was responsible for the image collection; another 2 sonographers who had been engaged in echocardiography for more than 5 years were responsible for processing the data.

After placing the subject in the left lateral position, the electrocardiogram leads were connected, and the instrument parameters were adjusted to obtain the best imaging. M-mode echocardiography was used to measure the left ventricular end-diastolic and end-systolic diameters, and the machine calculated the left ventricular volumes and LVEF automatically by the Teichholzholz method. Images from at least 4 cardiac cycles in dynamic apical two-chamber, three-chamber, and four-chamber views were obtained. Using the biplane Simpson method in the instrument, the endocardium was automatically tracked and then manually adjusted if necessary. The measurement results were recorded as the average of the 3 cardiac cycles with the best image quality (IQ).

After the above steps, the xPlane mode was started, the angle and instrument settings were adjusted, and the frame rate was kept > 18 frames/s. The patient was instructed to maintain a breathhold, at the end of expiration, after which the “HM ACQ” button was clicked to collect 6 consecutive cardiac cycles. Clicking the “HM” button, the system automatically calculated the LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LVEF and left atrial end-systolic volume (LAESV). Using the boundary setting HM80-40, the average of the 3 cardiac cycles with the best IQ was obtained to record the HM data without endocardial boundary editing (HM-NE). Then, the endocardial boundary was manually fine-tuned as needed, and the average of the 3 best-quality cardiac cycles was again obtained to record the HM data with endocardial boundary editing (HM-RE). One week later, the same observer analyzed all the images again, while a second observer analyzed them for the first time (Figure 1).

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Figure 1 HeartModel algorithm. The HeartModel algorithm automatically detects three-dimensional end-diastolic and end-systolic endocardial contours of the left ventricle and the left atrium with possibility of further manual adjustments if needed. Right chamber contours are also delineated; however, numerical results are not provided in the current version of the software.

3DQ method: Offline analysis of the 3D images collected in full volume mode was performed using QLab 10.5 software and the 3DQ Advance plug-in to analyze the images acquired in the apical four-chamber and two-chamber views and the left ventricular short axis view, and the plane on the 2D images was manually corrected. The average of the 3 best-quality cardiac cycles was taken as the measurement result, while in the software, the IQ index was calculated; a value above 50% was defined as good IQ, while that below 40% was defined as poor IQ.

Advanced cardiac 3DQ (3DQA) method: The QLab 10.5 software 3DQ plug-in was used to analyze the 3D images collected in full volume mode using the images obtained in three cross-sectional views used for the 3DQA method. After determining the end-diastolic frame, the region of interest was drawn on the four-chamber and two-chamber views of the apical long axis to obtain the left ventricular area model; the steps were repeated for the end-systolic frame. The above steps were repeated, and the average of the 3 best-quality cardiac cycles was taken as the measurement result.

SPSS 23.0 software and GraphPad Prism 8 software were used to analyze the data. The mean ± SD is used to represent the measurement data, and depending on the distribution of the data, parameter comparisons between the groups were performed using one-way ANOVA or the matched samples rank-sum test. The correlation and agreement between two sets of measurements were tested by Spearman’s correlation coefficient. Bland-Altman analysis was performed by calculating the bias and the limits of agreement; if more than 90% of the points fell within the 95% confidence interval, the consistency was considered high. Statistical significance was defined as P < 0.05. The intragroup and intergroup repeatability of the different quantitative methods are expressed by the coefficient of variation.

Among all volumetric data collected, 93 patients required manual editing, including 20 patients in group A (47%), 15 in group B (42%), 26 in group C (63%), and 32 patients in group D (100%). Of the cases with a Q-Index > 50%, 45% of the images still needed to be edited again.

The differences in the LVEDV, LVESV, LVEF and LAESV values measured by the different methods in the four groups were statistically significant (P < 0.05 for all), as shown in Table 1. Among them, the LVEDV and LVESV of group B were higher than those of the other groups (P < 0.05 for all), the LVEF of group B was lower than that of the other groups (P < 0.05 for all), and the LVEF of group D was higher than that of the other groups (P < 0.05 for all). In all groups, the measured values of LVEDV, LVESV, LVEF and LAESV obtained by HM-NE and HM-RE were greater than those of the 3DQA and Simpson methods (P < 0.05 for all).

Compared with HM-NE, manual adjustment yielded reduced LVEDV, LVESV, and LAESV values in group A, LVEDV, LVEF, and LAESV values in group C, and LVEDV and LVESV values in group D, but the LVEF value of group D was increased. The remaining parameters were not significantly different before and after manual adjustment (P > 0.05) (Table 2). When contour adjustment was performed, group D showed a wide bias, while the bias in group A was the smallest among the four groups. Compared with the measured value of LV volume, the deviation bias of the measured LAESV value of the four groups was smaller (Figure 2).

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Figure 2 Bland-Altman analysis for left heart volumes and ejection fraction between HeartModel with and without contour edit. A: Left ventricular end-diastolic volume; B: Left ventricular end-systolic volume; C: Left ventricular ejection fraction; D: Left atrial end-systolic volume. HM-NE: HeartModel without contour edit; HM-RE: HeartModel with contour edit; LVEDV: Left ventricular end-diastolic volume; LVESV: Left ventricular end-systolic volume; LVEF: Left ventricular ejection fraction; LAESV: Left atrial end-systolic volume.

Compared with those measured by 3DQA, the volume values measured by HM-NE and HM-RE in each group were higher. Among all the methods, the 3DQ measurements had the highest correlation with 3DQA (r_s= 0.96-0.98, P < 0.01 for all), and the consistency was good (LVEDV bias = 2.4 mL, LVESV bias = 1.3 mL, LVEF bias = 0.1%). The correlation between the LVEDV, LVESV, LVEF values measured by HM-NE and 3DQA (r_s= 0.85-0.90, P < 0.01 for all) was similar to that of the Teichholz method, but the deviation bias (LVEDV, 33.4 mL, LVESV, 15.7 mL, LVEF, 0.2%) was smaller than that of the Teichholz method. After fine-tuning, the correlation (r_s= 0.91-0.95, P < 0.01 for all) and consistency (bias: LVEDV, 28.1 mL; LVESV, 14.9 mL; LVEF, 0.0%; LAESV, 8.1 mL) were all increased; the Teichholz method had the lowest correlation with 3DQA (r_s= 0.82-0.89, P < 0.01 for all) (Table 3, Figures 2 and 3).

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Figure 3 Correlation and Bland-Altman analysis for left heart volumes and ejection fraction between HeartModel without contour edit and advanced cardiac three-dimensional quantification. A and B: Left ventricular end-diastolic volume; C and D: Left ventricular end-systolic volume; E and F: Left ventricular ejection fraction; G and H: Left atrial end-systolic volume. HM-NE: HeartModel without contour edit; 3DQA: Advanced cardiac three-dimensional quantification; LVEDV: Left ventricular end-diastolic volume; LVESV: Left ventricular end-systolic volume; LVEF: Left ventricular ejection fraction; LAESV: Left atrial end-systolic volume.

The correlation of left ventricular volume and LVEF between 3DQA and HM-NE in group A (r_s= 0.73-0.81, P < 0.01 for all) was slightly lower than that between the Simpson method (r_s= 0.83-0.85, P < 0.01 for all), which was manually fine-tuned, and HM-NE. The correlations of these values between the traditional methods and HM-RE were relatively increased (r_s= 0.82-0.96, P < 0.01 for all). In group B, the LVEF value of HM-NE had a low correlation with that of 3DQA (r_s= 0.46, P < 0.01). After manual fine-tuning, the correlation for LVEDV and LVESV increased slightly, and the correlation for LVEF increased significantly (r_s= 0.71, P < 0.01). In group C, the correlation for left ventricular volume and LVEF between HM-NE and 3DQA was higher than that between HM-NE and both the Teichholz method and Simpson method. After manual fine-tuning, the correlation was further improved (r_s= 0.80-0.90, P < 0.01 for all). The values measured with HM-NE in group D had a low correlation with those measured with 3DQA (LVESV r_s= 0.35, LVEDV r_s= 0.46, LVEF r_s= 0.63, P < 0.01 for all). After manual fine-tuning, the correlation was slightly improved, but the correlation for LVESV was still low (r_s= 0.48, P < 0.01 for all). The measured LAESV values of the two HM methods were highly correlated with those of the 3DQA method (r_s= 0.93-0.95, P < 0.01 for all). In group D, the LAESV measured by HM-RE had the highest correlation with the 3DQA LAESV (r_s= 0.98, P < 0.01), which was slightly higher than that of group A (r_s= 0.97, P < 0.01).

The deviation bias of each HM-NE measurement in groups A and D was the largest among all methods and was significantly reduced after fine-tuning. The LVEF measurement bias of HM-NE in group B had the largest deviation and was reduced after fine-tuning, but the deviation bias of LVEDV, LVESV and LAESV was not significantly reduced after fine-tuning. In group C, the deviation bias of LVEDV and LVESV was the largest with the Teichholz method, and the deviation bias of LVEF and LAESV was the largest with HM-NE. After manual fine-tuning, the deviation bias of the two methods was significantly reduced, with the reduction in the bias of LVEF being the most significant (Table 4, Figure 4).

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Figure 4 Correlation and Bland-Altman analysis for left heart volumes and ejection fraction between HeartModel with contour edit and advanced cardiac three-dimensional quantification. A and B: Left ventricular end-diastolic volume; C and D: Left ventricular end-systolic volume; E and F: Left ventricular ejection fraction; G and H: Left atrial end-systolic volume. HM-RE: HeartModel with contour edit; 3DQA: Advanced cardiac three-dimensional quantification; LVEDV: Left ventricular end-diastolic volume; LVESV: Left ventricular end-systolic volume; LVEF: Left ventricular ejection fraction; LAESV: Left atrial end-systolic volume.

Because HM-NE is a fully automatic method, the intraobserver and interobserver coefficients of variation were both zero. Among the other methods, except for the repeatability between the observers for group D, the intraobserver and interobserver repeatability of the HM-RE measurements in the other groups was better than those of the other methods. The intra- and interobserver repeatability of the measured values for the different methods in group D was lower than those of the other groups. The intraobserver repeatability of the HM-RE method was slightly higher than the interobserver repeatability, but the difference was small, and its interobserver repeatability was slightly higher than that of the other methods (Table 5).

First, the study excluded patients with a poor acoustic window who were unable to perform a breathhold; therefore, the feasibility and accuracy of the study results cannot be extended to all patients. Second, only the traditional 3DQA measurement was used as the standard, and MRI measurements were not used; however, previous studies confirmed that the two measurement methods demonstrate a good correlation. Third, previous studies[22] showed that when the default HM value was 80-40, the intraobserver and interobserver coefficients of variation were low (3%-9%), and the correlation with MRI was above 0.91. However, in patients with severe ventricular dilatation and an LVEF ≤ 50%, the consistency with MRI was higher when the boundary was set to HM90-50, but in this study, we used a preset value of HM80-40 and did not make any comparisons with HM90-50. Further study is required to determine the effect of the two preset values. Finally, the sample size of this study was small and should be further increased in the future to evaluate the application value of HM in all patients with common clinical cardiovascular diseases.

This study used HeartModel (HM), a new software to quickly quantify the left heart volume and left ventricular function in patients with common heart diseases to determine whether there are differences in the feasibility, accuracy, and repeatability of measuring the left ventricular end-diastolic (LVEDV), LV ejection fraction (LVEF) and left atrial end-systolic volume (LAESV) and to compare these measurements with those obtained with traditional methods.

Compared with traditional three-dimensional echocardiography (3DE), HM is easier to operate and boasts better measurement accuracy and repeatability. At present, the application value of HM in quantifying left heart volume and left ventricular function in patients with common heart diseases remains unclear.

The study aimed to assess the value of HM in quantifying the left heart volume and left ventricular function of patients with common heart diseases.

This study retrospectively assessed patients with common heart diseases who were divided into 4 groups: (1) Patients with normal heart shape and function (control group, Group A); (2) patients with dilated cardiomyopathy (DCM) (Group B); (3) patients with LV remodeling after acute myocardial infarction (Group C); and (4) patients with hypertrophic cardiomyopathy (HCM) (Group D). The measurements obtained were assessed.

HM without regional endocardial border editing (HM-NE) quantified left ventricular volume parameters, obtaining values that were highly correlated and larger than those obtained with advanced cardiac 3D quantification (3DQA) (bias: LVEDV, 28.17 mL; LVESV, 14.92 mL; LAESV, 8.18 mL; LVEF, -0.04%). The correlations between HM without regional endocardial border editing (HM-RE) and 3DQA (r_s= 0.91-0.95, P < 0.05 for all) were higher than those between HM-NE (r_s= 0.85-0.93, P < 0.05 for all). The correlations of LVEDV and LVESV between HM-RE and 3DQA were good for the control group, dilated cardiomyopathy group and segmental wall motion abnormality group, but remained weak for the HCM group (r_s= 0.48-0.54, P < 0.05 for all). The intraobserver and interobserver variability for the HM-RE measurements were low.

HM can accurately assess the left atrial volume of common clinical heart disease and fibrillation patients with a high correlation.

Future studies should increase the sample size and are confirm that these findings can be extended to more patients.