Clinical utility of the four-dimensional automatic left atrial quantification technique in evaluating left atrial volume and function in patients with heart failure with preserved ejection fraction

Introduction

As has been well documented, heart failure with preserved ejection fraction (HFpEF) accounts for 70% of heart failure cases in older adult patients, and its prevalence and morbidity are rapidly rising (1). HFpEF is a clinical syndrome primarily characterized by impaired left ventricular (LV) diastolic function, with preserved or mildly reduced systolic function [LV ejection fraction (LVEF) ≥50%]. Persistent elevation of LV filling pressures promotes increased left atrial (LA) pressure, leading to LA enlargement, hypertrophy, and fibrosis. Meanwhile, atrial cardiomyopathy specifically refers to the presence of abnormalities in the atrial structure, function, or electrophysiology, often independent of ventricular function. The diagnostic and clinical overlap between atrial cardiomyopathy and HFpEF is substantial, and atrial cardiomyopathy is a common comorbidity and consequence of the elevated LA pressure in HFpEF. Conversely, atrial dysfunction can exacerbate diastolic dysfunction and contribute to the symptoms of HFpEF. This synergy creates a diagnostic challenge, as manifestations such as exercise intolerance, pulmonary congestion, and atrial fibrillation are common to both conditions, blurring the lines between them.

Earlier studies have established the pivotal role of structural and functional abnormalities of the LA in the progression of HFpEF (2). Dysfunctional LA function in these patients contributes to pulmonary vascular remodeling, right ventricular dysfunction, and an increased risk of atrial fibrillation, all of which result in diminished exercise capacity and adverse outcomes. In addition, studies have found that patients with HFpEF and substantial LA dysfunction frequently experience a significantly worse prognosis (3), highlighting the urgent need to clarify the role of the LA in HFpEF.

Although two-dimensional speckle-tracking echocardiography (2D-STE) has been extensively employed in the assessment of LA function in patients with HFpEF, the accuracy of the results is compromised by the irregular shape or the thin myocardium of the left chamber (4). We thus conducted a study using LA quantification (LAQ) technology, specifically with four-dimensional (4D) software especially designed for atrial assessment, to evaluate the LA of patients with HFpEF (5). It should be noted that 4D LAQ technology overcomes several limitations associated with conventional techniques, such as the dependence of the ratio of peak early diastolic velocities and early diastolic mitral annular velocity (E/e') ratio on ultrasound angle and the labor-intensive and time-consuming process of the 2D LA maximum volume index (LAVImax) measurement. In addition, 4D LAQ allows for a comprehensive evaluation of LA function in 4D, providing detailed insights into the longitudinal and circumferential myocardial strain of the left atrium. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1046/rc).

Methods

Study population

This study enrolled 211 consecutive patients with signs or symptoms of HF and LVEF ≥50% attending The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing, China, between January 2024 and February 2025. These patients were further classified into two subgroups based on their Heavy, Hypertensive, Atrial Fibrillation, Pulmonary Hypertension, Elder, and Filling Pressure (H₂FPEF) score (6). In the H₂FPEF scheme, obesity [body mass index (BMI) >30 kg/m²] =2 points, hypertension (HTN) (use of ≥2 medications for HTN) =1 point, atrial fibrillation (paroxysmal or persistent) =3 points, pulmonary HTN (echocardiographic pulmonary artery systolic pressure >35 mmHg) =1 point, elder status (age >60 years) =1 point, and elevated filling pressure (echocardiographic E/e' ratio >9) =1 point. Specifically, patients with a score of 6–9 points were assigned to the HFpEF group, whereas those with a score of 2–5 points were assigned to the non-HFpEF group. Sixty-eight age- and sex-matched volunteers served as the control group.

The exclusion criteria were as follows: the presence of congenital heart disease (pre- or postsurgery), history of post-valve replacement or severe valvular disease, chronic obstructive pulmonary disease (COPD), prior cardiac interventions, systemic diseases affecting the heart (e.g., hyperthyroidism, renal failure, or connective tissue diseases), pericardial disease, persistent atrial fibrillation, and poor imaging quality.

As illustrated in Figure 1, 27 patients were excluded based due to the presence of congenital heart disease (n=1), severe COPD (n=5), severe valvular disease (n=8), prosthetic heart valve or prosthetic ring (n=4), persistent atrial fibrillation (n=4), or poor imaging (n=5).

Figure 1 Study protocol. 2D, two-dimensional; 4D LAQ, four-dimensional automatic left atrial quantification; BNP, B-type natriuretic peptide; HFpEF, heart failure with preserved ejection fraction.

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Institutional Ethics Committee of The Fourth Affiliated Hospital of Nanjing Medical University (approval No. 20240320-K032). The requirement for informed consent was waived due to the retrospective nature of the analysis.

Clinical and laboratory data

The clinical data of patients were collected within 24 hours of transthoracic echocardiography (TTE) and included age, sex, systolic and diastolic blood pressure (DBP), height, and weight, from which BMI and body surface area (BSA) were then calculated. Concurrently, medical histories of diabetes, HTN, coronary heart disease (CHD), and hyperlipidemia were retrieved from electronic medical records. Plasma B-type natriuretic peptide (BNP) and serum creatinine (Cr) levels were measured within 5 days of TTE.

Echocardiographic analysis

All participants underwent resting transthoracic echocardiographic examinations performed by an experienced cardiac sonographer using a commercially available ultrasound system (Vivid E95 version 203, GE HealthCare, Chicago, IL, USA) equipped with an M5S 3.5-MHz transducer. Parameters were acquired in accordance with the most recent guidelines of the American Society of Echocardiography (7). The LA diameter (LAD) and LV end-diastolic diameter (LVEDd) were examined from the parasternal long-axis view. LVEF was calculated via the modified Simpson method. The LV mass index (LVMI) was derived by tracing the long axis and the short axis of the LV. Tricuspid regurgitation (TR) peak velocity, mitral inflow peak (E), peak (A), and issue early diastolic annular velocity (e') were measured via Doppler imaging, after which the E/e' ratio was calculated.

4D-LAQ image acquisition and analysis

A Vivid E95 device, equipped with a 4-V transducer (1.4–5.2 MHz) and the EchoPAC 204 workstation (GE HealthCare) were used for 4D LA imaging. After the 4D-LAQ analysis software was opened, the sampling fan angle and depth were adjusted, after which the target point was set at the intersection of the mitral valve center and the LA. Dynamic images were continuously collected for at least three consecutive cardiac cycles in the apical four-chamber (A4C) view. As displayed in Figure 2, the software automatically identified and delineated the endocardial border of the LA to obtain 4D LA parameters [LA minimum volume (LAVmin), LA maximum volume (LAVmax), LA presystolic volume (LAVpreA), LAVImax, LA emptying volume (LAEV), LA ejection fraction (EF)], LA reservoir longitudinal strain (LASr), LA conduit longitudinal strain (LAScd), LA contractile longitudinal strain (LASct), LA reservoir circumferential strain (LASr_c), LA conduit circumferential strain (LAScd_c), and LA contractile circumferential strain (LASct_c). Subsequently, the LA distension index (LAEI), LA passive ejection fraction (LApEF), and LA active ejection fraction (LAaEF) were respectively calculated as follows: LAEI = (LAVmax − LAVmin)/LAVmin, LApEF = (LAVmax − LApreA)/LAVmax, and LAaEF = (LApreA − LAVmin)/LApreA. The A4C, apical two-chamber (A2C), and apical three-chamber (A3C) views were collected with a 4-V probe. At least three consecutive cardiac cycles of standard echocardiographic views were recorded. All segments of the LV wall were required to be completely displayed at an image frame rate exceeding 40 frames/s. Global longitudinal myocardial strain [left ventricular global longitudinal strain (LVGLS)] was assessed with Automated Function Imaging software (GE HealthCare).

Figure 2 Quantitative 4D LAQ volume-strain results of representative patients across the three groups: (A) HFpEF patient; (B) non-HFpEF patient; (C) healthy control. 2D, two-dimensional; 4D LAQ, four-dimensional automatic left atrial quantification; ED, end-diastole; ES, end-systole; HFpEF, heart failure with preserved ejection fraction; LAEF, left atrial emptying fraction; LAEV, left atrial emptying volume; LAScd, left atrial conduit longitudinal strain; LAScd_c, left atrial conduit circumferential strain; LASct, left atrial contraction longitudinal strain; LASct_c, left atrial contraction circumferential strain; LASr, left atrial reservoir longitudinal strain; LASr_c, left atrial reservoir circumferential strain; LAVImax, left atrial maximum volume index; LAVmax, left atrial maximum volume; LAVmin, left atrial minimum volume; LAVpreA, left atrial presystolic volume.

Statistical analysis

Statistical analyses were performed with SPSS 25.0 (IBM Corp., Armonk, NY, USA) and MedCalc 22.0.18 (MedCalc Software, Ostend, Belgium). GLS and LA strain values are expressed as positive numbers for ease of analysis and interpretation. The normality of data distribution was assessed with the Kolmogorov-Smirnov test. Normally distributed continuous variables are reported as the mean ± standard deviation, nonnormality distributed variables are reported as the median and interquartile range, and categorical variables are expressed as frequencies (percentage). Between-group differences in categorical variables were assessed with the Chi-squared test or the Fisher exact test. Multigroup comparisons of continuous variables were performed via one-way analysis of variance or nonparametric tests. Pairwise comparisons were made conducted via least significant difference and Student-Newman-Keuls methods. In our multicollinearity detection, if the variance inflation factor (VIF) of a variable exceeds 5, multicollinearity is considered to be present, and the stepwise regression method is then applied to address this issue. Univariate and multivariate binary logistic regression analyses were used to identify independent predictors of 4D LAQ parameters for distinguishing HFpEF from non-HFpEF. Receiver operating characteristic (ROC) curves were plotted to assess diagnostic performance. Meanwhile, calibration curves and decision curve analysis were applied to assess diagnostic performance, calibration, and the predictors’ net clinical benefits. Intraclass correlation coefficients (ICCs) were calculated to evaluate intra- and interobserver reliability. A P value <0.05 was considered statistically significant.

Results

Patient characteristics

A total of 300 patients were initially recruited. After the application of exclusion criteria, 95 patients with HFpEF, 89 non-HFpEF patients, and 68 healthy volunteers were included. The clinical and echocardiographic characteristics of patients are summarized in Tables 1,2.

Compared with the healthy group, the HFpEF group had a significantly higher BMI, BSA, DBP, HTN, prevalence of diabetes mellitus (DM) and CHD, BNP, Cr, triglycerides (TGs), TR velocity, E/e', and relative wall thickness (RWT), LVMI, LAVmin, LAVmax, LAVpreA, and LAVImax; meanwhile, they exhibited significantly impaired LVGLS, LASr, LASct, LASr_c, and LASct_c, along with a lower LAEF, LAEI, and LApEF (P<0.05). In contrast, no significant between-group differences were observed in LAEV, LAaEF, LAScd, or LAScd_c (Tables 1,2).

Compared with the non-HFpEF group, the HFpEF group had a significantly higher DBP, BNP, LAVmin, LAVmax, LAVpreA, and LAVImax but a significantly lower LASr and LASr_c, along with absolute values of LVGLS, LASct, and LASct_c. Meanwhile, the BMI, BSA, TR velocity, LAEV, LAaEF, LAScd, and LAScd_c were comparable (P>0.05) (Tables 1,2).

Compared with the healthy control group, the non-HFpEF group had significantly higher BMI, BSA, DM, BNP, Cr, TG, TR velocity, E/e', RWT, LVMI, and LAVmin; on the other hand, the absolute values of LVGLS and LASct_c were significantly lower.

Meanwhile, LAVImax, LAEF, LASr, and LASr_c, along with the absolute value of LASct, LAScd, and LAScd_c were comparable (P>0.05) (Table 2).

Univariate and multivariate logistic regression analysis

Univariate analyses was carried out to identify potential factors associated with HFpEF. However, multicollinearity was considered to be present, particularly with indicators such as LASct_c (VIF =5.5), LASr_c (VIF =6.5), LApEF (VIF =8.9), LAEF (VIF =5.8), LAEI (VIF =12.7), LAVmin (VIF =46.8), LAVmax (VIF =26.8), and LAVpreA (VIF =38.7). Multivariate logistic regression analysis with the stepwise method was adopted. As detailed in Table 3, the results revealed that LAVImax [odds ratio (OR) =1.169; 95% confidence interval (CI): 1.001–1.353; P=0.046], LASr (OR =0.852; 95% CI: 0.732–0.990; P=0.037), LASr_c (OR =0.846; 95% CI: 0.723–0.991; P=0.039), LASct_c (OR =0.608; 95% CI: 0.463–0.822; P=0.001), base-ten logarithmic transformation of B-type natriuretic peptide (BNPlog) (OR =0.122; 95% CI: 0.021–0.842; P=0.033), and LVGLS (OR =0.643; 95% CI: 0.473–0.872; P=0.005) were independently associated with HFpEF.

Assessment of relevant 4D-LAQ parameters

LASct_c, LASr, and LASr_c showed the highest area under the curve (AUC) among all the parameters (AUC 0.918, 0.773, and 0.787, respectively). LAVImax, BNP, and LVGLS showed satisfactory discriminatory capacity, with AUCs of 0.685, 0.734, and 0.754, respectively (Table 4). Importantly, LASct_c outperformed the other parameters in terms of diagnostic accuracy (P<0.001) (Table 5). LASr_c demonstrated a significant difference in diagnostic performance compared to LAVImax (P=0.0328). As presented in Table 3 and Figure 3, the sensitivity and specificity of LASct_c, LASr_c, and LASr were 85.26% and 91.01%, 67.37% and 79.78%, and 54.74% and 85.39%, respectively. Furthermore, LASct_c demonstrated the best agreement between predicted and observed probabilities (Figure 3B) among all the predictors (Figure 3C-3G). Decision curves indicated that patient threshold probabilities in the range of approximately 0.1–1.0 add more net benefit to using LASct_c and BNP than do other parameters when compared to strategies that treat all patients or no patients in the HFpEF group (Figure 3H). However, it was found that LASct_c would yield the highest net clinical benefit in predicting significant HFpEF (Figure 3H).

Figure 3 The value of relevant 4D-LAQ parameters. (A) ROC curves of different logistic regression models examining the association between relevant 4D-LAQ parameters and HFpEF. (B-G) Calibration curve for predicting HFpEF with LASct_c, LASr_c, LASr, LVGLS, BNPlog, and LAVImax. (H) Decision curves of LASct_c, LASr_c, LASr, LVGLS, BNPlog, and LAVImax for predicting significant HFpEF. 4D LAQ, four-dimensional automatic left atrial quantification; BNPlog, base-ten logarithmic transformation of B-type natriuretic peptide; HFpEF, heart failure with preserved ejection fraction; LASct_c, left atrial contraction circumferential strain; LASr, left atrial reservoir longitudinal strain; LASr_c, left atrial reservoir circumferential strain; LAVImax, left atrial maximum volume index; LVGLS, left ventricular global longitudinal strain; ROC, receiver operating characteristic.

Repeatability test

A total of 15 patients from the control, HFpEF, and non-HFpEF groups were randomly selected for the intra- and interobserver repeatability tests. Intraobserver variability was assessed by comparing the results of a repeated analysis of identical images by a single observer after a 2-week interval. Interobserver variability was evaluated by comparing measurements obtained by two observers with similar experience levels. As anticipated, the LA parameters examined via 4D-LAQ had outstanding repeatability (ICC >0.75) (Table 6).

Discussion

HFpEF is a widely prevalent subtype of heart failure characterized by LV diastolic dysfunction, accompanied by normal or marginally impaired LVEF (8). In recent years, this condition garnered widespread attention due to the elevated rates of hospitalization and mortality (9). Numerous studies have examined changes in LV structure and function in patients with HFpEF (10,11). Interestingly, an earlier study reported that the left atrium is closely related to LV function and regulates LV filling pressure through storage, conduit, and pumping contractile function, which plays a key role in overall cardiac function (12). According to the relevant research, LA strain is significantly impaired in patients with HFpEF, which has been linked to a poorer prognosis (13,14). In addition, conventional ultrasound parameters offer limited sensitivity in evaluating the structure and function of the left atrium in patients with HFpEF (15). Therefore, in this study, 4D LAQ was used to evaluate changes in LA volume and function in patients with HFpEF. 4D LAQ is a technique designed specifically for the study of the left atrium, and its strain parameters not only allow for the quantification of the longitudinal strain of the LA myocardium but also for the evaluation of circumferential strain, which is consistent with the anatomical characteristics of the LA myocardium. Additionally, it facilitates the three-dimensional assessment of the LA volume throughout the cardiac cycle, thereby enhancing convenience and accuracy LA function assessment (16).

As mentioned above, HFpEF is a complex cardiovascular disease. Haass et al. demonstrated that the incidence of obesity is relatively high among patients with HFpEF, and there is a U-shaped relationship between BMI and the risk of cardiovascular events, and thus both excessively low and high BMI are associated with a poor prognosis (17). Additionally, Rao et al. found that obesity is also linked to changes in cardiac structure and function, such as ventricular hypertrophy and diastolic dysfunction (18). In another study, Elkholey et al. observed that obese patients showed a better response to spironolactone, suggesting that obesity may influence the efficacy of pharmacotherapy (19). Furthermore, research has revealed that low DBP is associated with adverse prognosis in patients with HFpEF and may increase the risk of readmission due to heart failure (20,21). TG levels are also regarded as an important metabolic indicator in patients with HFpEF. Studies have shown that treatment with sacubitril/valsartan can significantly reduce TG levels, particularly in patients with high baseline TG levels. This effect may be related to its impact on natriuretic peptide activity (22). As a marker of renal function, serum Cr levels are closely associated with the prognosis of individuals with HFpEF. Kanjanahattakij et al. found a negative correlation between right ventricular stroke work index (RVSWI) and glomerular filtration rate (GFR), indicating that increased right ventricular load may lead to the deterioration of renal function (23). BNP levels are commonly used for the diagnosis and prognostic evaluation of heart failure, they may be relatively low in patients with HFpEF—especially in obese patients—which could affect its accuracy as a prognostic marker (24,25). The findings of our study are consistent with those described above.

Several previous studies (26,27) have demonstrated that HFpEF patients with reduced LVGLS and increased E/e' have impaired LVEF function, which is in line with our results. Although GLS is a useful index for the assessment of LV myocardial function, GLS can decrease when the load pressure increases. In a study by Ng et al. (28), RWT and LVMI were significantly increased in patients with HFpEF; in Lin et al.’s study (26), LVMI was not found to have a significant ability to asses ventricular function in this population. Our findings are consistent with the latter study. Taken together, these observations suggest that myocardial damage in patients with HFpEF precedes changes in chamber morphology. Within the context, of chronic elevation in LV filling pressure, the left atrium is intolerant to pressure and volume overload due to its anatomic features (thin walls and short myocardial fibers) (27), resulting in altered E/e', which generally occurs prior to the onset of LV dysfunction.

Our findings differed from those of Lin et al. (29), who reported that the LA reservoir phase, conduit phase, and contractile phase were all impaired as indicated by 2D STE; additionally, they found that LASr (AUC 0.82) had good diagnostic performance in evaluating LA function impairment. In our study, we found that the LA longitudinal and circumferential reservoir phases, as well as the contractile phase, were impaired, with the that of the circumferential contractile phase being more prominent. The LASt_c (AUC 0.918), LASr_c (AUC 0.787), and LASr (AUC 0.773) all performed well in evaluating LA function impairment, with circumferential strain rate showing superior evaluation performance, but the longitudinal and circumferential impairment during the conduit phase was not significant. We speculated that LA conduit phase function is closely related to ventricular diastole, while reservoir function and contractile function largely reflect atrial compliance and contractility. In patients with HFpEF, LV filling pressure is elevated. The left atrium compensates for this increased LV filling pressure while maintaining adequate cardiac output. Moreover, the arrangement of myocardial fibers in the left atrium differs from that in the left ventricle: it mainly consists of subepicardial and subendocardial myocardial fibers, where the subendocardial myocardium is primarily composed of longitudinal fibers, and the subepicardial layer is composed of circumferential fibers (30). In addition, 2D STE was originally designed for examining the LV myocardium. However, the LA myocardium is much thinner compared to the LV myocardium, and the presence of the LA appendage and pulmonary veins makes it difficult to reliably track and accurately perform layered analysis.

We further found that compared with the control and non-HFpEF groups, the HFpEF group had significantly higher LAVmin, LAVmax, LAVImax, and LAVpreA but significantly lower LAEF, LAEI, and LApEF, along with absolute values of LASr, LASr_c, LASct, and LASct_c (all P values <0.05). Collectively, this suggests the presence of increased LA volume and reduced function in patients with HFpEF. Earlier studies established that persistent LA diastolic dysfunction and elevated filling pressures increase LA load, thereby promoting LA myocardial fibrosis and decreasing LA compliance and deformability (31). In conjunction with hemodynamic alterations and decreased peak oxygen consumption (32), this manifests as decreased LA reserve and systolic LA function, which enhances the compensatory capacity of myocardial contraction (33). Notably, no significant differences in LAScd and LAScd_c were noted between the three groups in our study, suggesting that the LA conduit may be preserved until the later stages and may be followed by the deterioration of reserve and systolic function.

HFpEF is characterized by its complexity and variability (34). For high-risk patients, various triggers can promote disease progression (35), highlighting the need for early monitoring and intervention. The prognosis of patients with HFpEF presenting with LA remodeling is poorer, and thus close monitoring is necessary (36). Furthermore, timely interventions are crucial for preventing adverse cardiovascular events. The univariate and multivariate logistic regression analyses in our study indicated that LAVImax, LASr, LASr_c, LASct_c, BNP, and LVGLS were independently correlated with HFpEF. Meanwhile, according to ROC curve, calibration curves, and decision curve analysis, among these indicators, LASct_c had the highest diagnostic performance and outperformed the other five indicators. In addition, LASr_c outperformed LAVImax in terms of diagnostic performance and comparable to LASct_c. However, no significant differences were observed between LAVImax, LASr, BNP, and LVGLS. These findings are consistent with anatomical evidence suggesting that the left atrium is primarily composed of circumferential muscle fibers (37), which may be more sensitive to LV filling pressures than longitudinal muscles during the progression of HFpEF (38).

Furthermore, it is important to acknowledge that the HFpEF population enrolled in this study represents a broad disease spectrum with significant heterogeneity in etiology, comorbidity burden, and hemodynamic profiles. However, the LA strain parameters (e.g., LASct_c) demonstrated a relatively high value in assessing LA damage in patients with HFpEF. Future research aimed at more refined phenotyping of HFpEF will help further clarify the role of these parameters within certain subgroups. Overall, this study provides a reference for clinical decision-making and prognostic stratification in patients with HFpEF.

Study limitations

Certain limitations to this study should be addressed. To begin, we employed a single-center design with a relatively small sample composed entirely of Chinese individuals; moreover, our results were not validated in an external dataset. Therefore, the generalizability of the results may be limited. Second, the invasive tests are the gold standard for diagnosing HFpEF. Previous studies have shown that the H₂FPEF scores have limitations when applied in an Asian setting due to the lower prevalence of obesity and smaller heart sizes in Asian populations (39). However, most patients can be diagnosed through noninvasive tests such as examination of clinical symptoms, measurement of natriuretic peptide levels, and echocardiography. Invasive tests are only considered when resting echocardiography results are inconclusive or when HFpEF is highly suspected but cannot be confirmed by routine tests. Furthermore, most of the patients with inconclusive or highly suspected HFpEF decline invasive tests due to being asymptomatic or for reasons of safety. Patients with an H₂FPEF score of 6 or less did not undergo cardiac catheterization or stress echocardiography for further assessment of LV filling pressure. Third, the potential for reversal of LV volume and function following treatment was not investigated. Finally, the influence of confounders (e.g., blood pressure, glucose, and blood lipids) were not analyzed due to the small sample size.

Conclusions

Patients with HFpEF exhibited early alterations in LA volume and function, particularly impaired circumferential strain, prior to the onset of detectable chamber enlargement. 4D LAQ technology provides a clinically valuable, noninvasive method for the comprehensive assessment of LA dynamics, offering both diagnostic and prognostic stratification capabilities for guiding therapeutic decision-making.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1046/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1046/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1046/coif). The authors have no conflicts of interest to declare.

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 The Fourth Affiliated Hospital of Nanjing Medical University (approval No. 20240320-K032) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Gray)