The impact of body mass index and epicardial adipose tissue on left atrial function in hypertensive patients: a cardiac magnetic resonance feature tracking study

Introduction

Hypertension (HTN) is a major risk factor for the development and progression of cardiovascular disease, with the heart and vasculature serving as primary target organs of injury (1,2). Cardiovascular remodeling in HTN encompasses structural and functional alterations. These represent interacting adaptive changes in response to elevated blood pressure, manifesting in diverse remodeling patterns. Left atrial (LA) remodeling reflects such adaptive change, driven by sustained high blood pressure (HBP) or HBP superimposed on age-related LA alterations (3,4). LA enlargement is an early manifestation of cardiac remodeling in HTN, potentially occurring independently of left ventricular (LV) changes and often being the sole echocardiographic sign of early cardiac remodeling in hypertensive patients (5). A study indicated that LA enlargement is more prevalent than LV enlargement (57.2% vs. 17.9%), and occurs more frequently in patients with heart failure with preserved ejection fraction (EF) compared to those with reduced EF (82.9% vs. 49.0%) (6). LA enlargement results from LV diastolic dysfunction: elevated LV filling pressure due to diastolic dysfunction is transmitted retrogradely to the LA, leading to LA enlargement and dysfunction (7,8). The LA regulates LV filling through three phases: (I) reservoir function (collecting pulmonary venous flow during LV systole); (II) conduit function (acting as a passive conduit for pulmonary venous flow to enter the LV during early diastole); and (III) pump function (actively contracting to augment LV filling during late diastole). Recently, LA strain has emerged as a promising non-invasive marker of cardiac function. LA strain abnormalities often precede LA enlargement and offer greater sensitivity than traditional volumetric assessment in detecting atrial mechanical changes (9,10), while also providing prognostic value for adverse cardiovascular outcomes (11,12).

Obesity is a significant risk factor for HTN, demonstrating a strong association with its prevalence (13,14). Research shows that for every 5 kg/m² increase in body mass index (BMI), the risk of developing HTN increases by 49% (15). Cardiac magnetic resonance (CMR) can detect subclinical myocardial alterations in overweight to obese individuals without established cardiovascular disease. Dietary-induced weight loss has been shown to improve LV strain parameters and LA size (16). Compared to controls with similar BMI, patients with type 2 diabetes mellitus exhibit significantly reduced reservoir and conduit function, with BMI independently correlating with LA total strain (ε_s) and passive strain (ε_e) (17). Furthermore, studies incorporating epicardial adipose tissue (EAT) have revealed unique correlations between LA functional indices (18,19). However, research specifically elucidating how obesity indices mechanistically influence LA function in hypertensive patients remains scarce. Understanding the impact of obesity metrics on myocardial dysfunction in HTN could clarify underlying mechanisms and guide early intervention strategies.

Therefore, this study utilized CMR feature-tracking (CMR-FT)—an imaging technique offering non-invasiveness, a large field of view (FOV), and high soft-tissue resolution—to analyze LA functional parameters including strain and strain rate. We aimed to characterize LA strain features in patients with HTN and further determine the influence of BMI and EAT on its LA function. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2461/rc).

Methods

Study population

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethical Committee of Beijing Friendship Hospital (No. 2022-P2-173). Informed consent was provided by all the patients. In this cross-sectional study, we identified patients with essential hypertension (EH) who underwent CMR examination at our medical center between February 2019 and July 2024. EH was defined as systolic blood pressure (SBP) ≥140 mmHg, diastolic blood pressure (DBP) ≥90 mmHg, a confirmed diagnosis of HTN, or current antihypertensive treatment. Complete BMI data and CMR examination were required. The exclusion criteria included coronary artery disease, valvular heart disease, cardiomyopathy, stroke, severe arrhythmias, symptomatic heart failure, LVEF <50%, congenital heart disease, and severe hepatic or renal insufficiency (glomerular filtration rate <30 mL/min). A total of 129 patients were enrolled. Based on their BMI values and according to World Health Organization (WHO) obesity classifications, they were categorized into three groups: normal weight (BMI: 18.5–24.9 kg/m²), overweight (BMI: 25.0–29.9 kg/m²), and obese (BMI: ≥30 kg/m²).

CMR imaging

Patients fasted from food and water for 8–12 hours before CMR examination, and refrained from beta-blocker (BB), nitroglycerin, and theophylline for 24 hours prior, as well as caffeine for 1 week before the examination. All patients had a heart rate (HR) <70 beats per minute during CMR examination. For cardiac function and myocardial strain analysis, cine sequences were selected from patients acquired using three different 3.0 T magnetic resonance imaging (MRI) scanners: Prisma (Siemens, Erlangen, Germany), SIGNA Pioneer (GE Medical Systems, Chicago, IL, USA), and UIHMR870 [United Imaging Healthcare (UIH), Shanghai, China]. Scanning positions included two-chamber (2Ch) view, four-chamber (4Ch) view, three-chamber (3Ch) view, and 8–12 short-axis slices covering from the base to apex of the heart. All cine sequences employed the steady-state free precession (SSFP) technique with the following standard scanning parameters: (I) Siemens—repetition time (TR): 3.3 ms; echo time (TE): 1.43 ms; flip angle (FA): 80°; slice thickness: 8 mm; voxel size: 1.6 mm × 1.6 mm × 8.00 mm; FOV: 340 mm × 265 mm. (II) GE Medical Systems—TR: 2.9 ms; TE: minimum; FA: 45°; slice thickness: 8 mm; voxel size: 2.2 × 1.6 × 8.00 mm; FOV: 350 mm × 350 mm. (III) UIH—TR: 3.32 ms; TE: 1.57 ms; FA: 55°; slice thickness: 8 mm; voxel size: 1.61 mm × 1.61 mm × 8.00 mm; FOV: 360 mm × 320 mm.

CMR analysis

LV structure and function: LV end-diastolic diameter was measured on short-axis cine images at the papillary muscle level. End-systolic and end-diastolic LV contours were automatically traced using the CVI42 software’s (Circle Cardiovascular Imaging Inc., Calgary, Canada) function sax module and manually adjusted if necessary. The software automatically calculated LVEF, LV cardiac output (CO), LV cardiac index (CI), and LV mass (LVM).

LA structure and function

LA anteroposterior diameter (LA Antpost) and LA lateral diameter (LA Lat) were measured on LV end-diastolic 4Ch view images. LA strain analysis was performed using the strain module. On 2Ch and 4Ch cine images, the LA endocardial and epicardial borders (excluding pulmonary veins and the LA appendage) were manually traced at the time points of maximum LA volume (typically LV end-systole) and minimum LA volume (typically LV end-diastole). The software propagated the contours across all frames of the cardiac cycle (25 frames per cycle). The quality of myocardial tracking was visually inspected for all frames; inaccurate contours were manually adjusted, and the propagation algorithm was rerun. Global longitudinal LA strain and strain rate values were averaged from the 2Ch and 4Ch views. The software reported the following LA strain parameters: ε_s (reservoir function), ε_a (pump function), ε_e (conduit function, calculated as ε_s – ε_a), peak positive strain rate (SRs, reservoir function), peak early negative strain rate (SRe, conduit function), and peak late negative strain rate (SRa, pump function). The software automatically derived the LA volume curve and the following volumetric parameters from the LA endocardial contours: maximal LA volume (LAV_max) at LV end-systole, LA volume pre-atrail contraction (LAV_pre-a) at LV end-diastole, and minimal LA volume (LAV_min) at late LV diastole. LA emptying fraction (LAEF) was calculated as follows: (I) LA total emptying fraction (LAEF_total) = [(LAV_max – LAV_min)/LAV_max] × 100%; (II) LA passive emptying fraction (LAEF_passive) = [(LAV_max – LAV_pre-a)/LAV_max] × 100%; (III) LA active emptying fraction (LAEF_active) = [(LAV_pre-a – LAV_min)/LAV_pre-a] × 100%.

EAT

EAT quantification was performed by loading the short-axis cine stack into the CVI42 Tissue Signal Intensity module. EAT was defined as adipose tissue located between the myocardium and the visceral pericardium. Contours were drawn on the LV end-diastolic frames. To maintain a standardized approach, EAT was quantified on short-axis slices of cine that contained at least 180 degrees of myocardial coverage. Figures 1,2 show examples of LA strain analysis and EAT segmentation.

Figure 1 LA strain analysis: representative 4Ch (B-D) and 2Ch (E-G) cine images at LV end-systole from a hypertensive patient, LAV_max (B,E), LAV_pre-a (C,F), LAV_min (D,G). Schematic representations of LA strain (A) and strain rate (H) curves. 2Ch, two-chamber; 4Ch, four-chamber; AIL, anterior-inferior-lateral; ALS, anterolateral segment; IL, inferior-lateral; LA, left atrial; LAV_max, maximal LA volume; LAV_min, minimal LA volume; LAV_pre-a, LA volume pre-atrial contraction; LPI, lateral-posterior-inferior; LV, left ventricular; PRI, posterior-right-inferior; PSR, posterior-septal-right; RAS, right-anterior-septal; SR, superior region; SRa, peak late negative strain rate; SRe, peak early negative strain rate; SRs, peak positive strain rate; ε_a, active strain; ε_e, passive strain; ε_s, total strain.

Figure 2 EAT delineation. (A-H) Representative short-axis images from a hypertensive patient demonstrating EAT contour using the CVI42 Tissue Signal Intensity module. The software automatically calculated the corresponding EAT volume. Red line: endocardial contour. Green line: epicardial contour. EAT, epicardial adipose tissue; IRA, inferior right atrial; LPI, lateral posterior inferior; RAS, right anterior septal; SLP, septal, lateral, posterior.

Reproducibility

A total of 30 patients were randomly selected and divided into three groups of 10 patients. Observer 1 (with 2 years of cardiovascular imaging experience) and Observer 2 (with 5 years of cardiovascular imaging experience) independently measured LA strain and strain rate parameters to assess inter-observer agreement. Observer 1 repeated the measurements on the same 30 patients after a one-month interval to assess intra-observer agreement.

Statistical analysis

Data analysis was performed using R4.4.3 (R Foundation for Statistical Computing, Vienna, Austria) and the SPSSAU project [2025]. SPSSAU (Version 25.0) [online application software], retrieved from https://www.spssau.com. Categorical data were presented as numbers (percentages) and compared using the Chi-squared or Fisher’s exact test. Normally distributed continuous variables were expressed as mean ± standard deviation and compared using one-way analysis of variance (ANOVA). When ANOVA results were significant, Tukey’s honestly significant difference (HSD) post-hoc test was used for pairwise comparisons, correcting for multiple testing. Non-normally distributed variables were expressed as median [interquartile range (IQR)] and compared using the Kruskal-Wallis H test. When significant, Dunn’s test with Bonferroni correction was used for pairwise comparisons. Spearman’s rank correlation coefficient (ρ) was used to analyze correlations between variables within the total cohort and within each BMI group. Multiple linear regression models were constructed to identify independent determinants of LA strain and strain rate parameters, with standardized regression coefficients (β) reported to indicate the strength and direction of independent associations. Intra-class correlation coefficients were used to assess intra- and inter-observer variability for strain and strain rate parameters. Statistical significance was defined as a two-tailed P value <0.05.

Results

Baseline characteristics

According to the inclusion and exclusion criteria, 129 patients with EH were enrolled (97 males, 32 females). Based on WHO obesity criteria, patients were categorized into normal weight (n=36), overweight (n=50), and obese (n=43) groups. There were no significant differences between the groups regarding gender distribution, height, SBP, or DBP (all P>0.05). The median age of all enrolled patients was 41.0 years. Patients in the obesity group had a significantly lower median age of 38.0 years compared to the normal weight group (P=0.003) and the overweight group (P=0.021). Compared to the normal weight group, the obesity group demonstrated a significantly increased EAT volume (93.6±29.3 vs. 83.1±27.5 mL, P<0.001). EAT volume exhibited a progressive increase from normal weight to overweight to obesity. Baseline characteristics are detailed in Table 1.

LV structure and function

There were no significant differences between the three groups in LV end-diastolic short-axis diameter (LV ShortDiam), LVEF, or HR. LV ShortDiam and LVEF were within normal ranges (LVEF >50%) for all patients. From the normal weight to the overweight to the obesity group, a gradual increasing trend was observed in LV end-diastolic volume (EDV), LV end-systolic volume (ESV), stroke volume (SV), CO, and LVM. Conventional LV morphological and functional parameters are detailed in Table 2.

LA structure and function

Among the three patient groups, parameters of LA AntPost, LAV_max, LAV_pre-a, and LAV_min all demonstrated a progressively increasing trend. However, no significant differences were observed among the groups after these volume indices were normalized to body surface area (LAVI_max, LAVI_pre-a, LAVI_min). No significant intergroup differences were found in the global LAEF or strain parameters. In contrast, a significant decline was noted in LA strain rates; compared to the normal weight group, the obesity group had significantly impaired SRs (P<0.001), SRe (P=0.029), and SRa (P=0.029). Furthermore, SRs was significantly lower in the obesity group than it was in the overweight group (P<0.01).

Conventional LA morphological and functional parameters are detailed in Table 3.

Correlation between LA strain parameters and other variables

Correlation analysis for all patients and BMI subgroups

Univariate correlation analysis (assessing age, obesity indices, LA and LV morphology and function) in the total cohort of hypertensive patients revealed the following significant associations: BMI and LAEF correlated significantly with ε_s, with the strongest correlation observed for LAEF_total (ρ=0.742, P<0.001). EAT and LAEF correlated significantly with ε_e, with the strongest correlation for LAEF_passive (ρ=0.743, P<0.001). Age, BMI, LVEF, LAEF_total, and LAEF_active correlated significantly with ε_a, with the strongest correlation for LAEF_active (ρ=0.641, P<0.001). BMI, EAT, LVEF, ESV, and LAEF correlated significantly with SRs, with the strongest correlation for LAEF_total (ρ=0.673, P<0.001). Age, BMI, EAT, LA AntPost, and LAEF correlated significantly with SRe, with the strongest correlation for LAEF_passive (ρ=−0.709, P<0.001). Age, BMI, and LAEF correlated significantly with SRa, with the strongest correlation for LAEF_active (ρ=−0.72, P<0.001). Figure 3 displays a correlation heatmap of all parameters for the total patient cohort.

Figure 3 Correlation heatmap: Spearman correlation coefficients (ρ) between all analyzed parameters in the total patient cohort. Color depth and circle size represent the magnitude of the correlation coefficient. BMI, body mass index; EAT, epicardial adipose tissue; EDV, end-diastolic volume; ESV, end-systolic volume; LA, left atrial; LA AntPost, left atrial anteroposterior diameter; LAEF_active, LA active emptying fraction; LAEF_passive, LA passive emptying fraction; LAEF_total, left atrial total emptying fraction; LVEF, left ventricular ejection fraction; SRa, peak late negative strain rate; SRe, peak early negative strain rate; SRs, peak positive strain rate; SV, stroke volume; ε_a, active strain; ε_e, passive strain; ε_s, total strain.

Regression analysis for all patients and BMI subgroups

To investigate the factors influencing LA longitudinal strain and strain rate, based on the previous analysis results while considering multicollinearity, predictors exhibiting a variance inflation factor (VIF) >10 were removed. A multivariable regression model was initially constructed with age, BMI, LAEF_passive, and LAEF_active as independent variables. The results are presented in the Tables S1-S4. After adjusting for the effects of age and LAEF_passive and LAEF_active, a higher BMI remained an independent correlate of both SRs (β=−0.194, P<0.05) and SRe (β=−0.213, P<0.01). Concurrently, LAEF_passive and LAEF_active were themselves significant independent predictors of both SRe and SRa (all P<0.01). However, these correlations were no longer significant when analyzed within individual subgroups.

Subsequently, EAT volume was incorporated into the regression model, with the results shown in Tables 4,5. After including EAT, BMI no longer demonstrated an independent correlation with LA strain or strain rates in the overall cohort or in any subgroup. For the overall cohort, EAT volume emerged as an independent predictor of SRs (β=−0.189, P<0.05) and SRe (β=0.204, P<0.01). Subgroup analyses revealed that the significant associations of EAT with SRs (β=−0.317, P<0.05) and SRe (β=0.317, P<0.01) were concentrated in the overweight population, with no such associations observed in the normal weight or obese EH patients. Across all models, LAEF_passive and LAEF_active consistently constituted the most robust predictors of the LA functional parameters.

Reproducibility

Intra- and inter-observer reproducibility for LA strain and strain-rate measurements were excellent, with all intra-class correlation coefficients exceeding 0.80 and 0.85, respectively. The corresponding intra- and inter-observer correlation coefficients are presented in Table 6.

Discussion

This study employed CMR-FT to investigate LA functional alterations across BMI categories in hypertensive patients, revealing specific associations between obesity severity and LA strain parameters. The principal findings were as follows: (I) the obese group (BMI ≥30 kg/m²) exhibited significant LV volumetric enlargement (increased EDV, ESV, SV, CO) and LA structural remodeling (enlarged LA Antpost, elevated LAV_max, LAV_pre-a, and LAV_min); (II) despite no significant reduction in LVEF in all groups, strain rates can serve as a sensitive indicator for the early detection of subtle LA dysfunction in patients with HTN and obesity; (III) LAEF_passive and LAEF_active were the principal determinants of LA deformation. EAT may provide incremental explanatory value beyond BMI for obesity-related LA dysfunction in hypertensive patients, particularly in the overweight subgroup.

Obesity promotes LA structural remodeling

The elevation of LA volumetric parameters (LAV_max, LAV_pre-a, LAV_min) in the obese group occurred concomitantly with LV volumetric enlargement (increased EDV, ESV). A plausible explanation is that obesity increases blood volume, directly augmenting cardiac preload and leading to LV EDV expansion. Chronic LV volume overload further elevates LV filling pressure, which is transmitted retrogradely via ventricular-atrial coupling to the LA, resulting in passive LA dilatation (20). This aligns with findings by Cameli et al. (21) that LA enlargement in HTN with obesity represents a combined outcome of adaptive remodeling and pathological injury. Notably, the absence of significant differences in LA volume indices between groups suggests that the absolute volume increase may be counterbalanced by body surface area.

Sensitivity of strain parameters for early dysfunction

Our study found that although LVEF was within normal limits and LAEF showed no significant differences between groups in this hypertensive cohort, strain rates (SRs, SRe, SRa) were significantly reduced in the obese group. This highlights the sensitivity of LA strain in detecting more subtle impairments in function among hypertensive patients. Strain parameters, by quantifying the rate of myocardial deformation, reflect myocardial mechanical abnormalities earlier than volumetric indices (22). Our conclusions are consistent with Wu et al. (23), demonstrating that myocardial reservoir and conduit function decline prior to LA enlargement, allowing strain parameters to detect LA dysfunction early. Obesity and HTN likely synergistically promote myocardial collagen deposition, increasing myocardial stiffness. Reduced LV early diastolic compliance diminishes the LA-LV pressure gradient, impairing the LA’s rapid emptying capacity, thereby reducing SRe. Myocardial fibrosis also decreases LA myocardial compliance, affecting its passive distensibility as a “conduit” (24). Our study found that from the normal weight group to the overweight group, the parameters reflecting LA pump function (ε_a, SRa) either increased or at least did not decrease. This may be attributed to a compensatory state of the left atrium under the combined effects of HTN and obesity at this stage. However, in the obese group, these LA pump function indicators decreased, particularly SRa, compared to the normal weight group. This suggests that the LA pump function has decompensated and can no longer maintain normal function through active contraction.

Additional role of EAT

Our results demonstrated strong correlations between LAEF_total, LAEF_passive, LAEF_active, and ε_s, ε_e, ε_a, consistent with prior studies (23,25) and the anatomical-functional relationship of the LA. EAT volume increased progressively from normal weight to overweight to obesity and was independently associated with ε_e, SRe, and SRs in the total EH cohort. Subgroup analysis revealed independent associations specifically between EAT and SRe/SRs in the overweight group, but not in the normal weight or obese groups. EAT may influence LA function via dual pathways: (I) mechanical compression—pericardial fat encasing the heart may reduce myocardial compliance and restrict contractile function. In obese patients, increased abdominal and thoracic adipose tissue can also exert external physical compression, thereby impairing myocardial strain (26); (II) metabolic interference—as a metabolically active fat depot, EAT secretes pro-inflammatory cytokines and vasoactive substances [e.g., interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)] (27). These cytokines can directly damage cardiomyocytes, reducing compliance and contractile function. One speculative hypothesis to explain the observed independent association of EAT specifically in the overweight subgroup on SRe and SRs is that this may represent a critical transitional stage where EAT accumulation reaches a potential ‘threshold’ for exerting a detectable mechanical effect. Conversely, we hypothesize that in the obese group, a potential ‘ceiling effect’ might occur, where the substantial EAT burden reaches a point beyond which additional volume has diminishing marginal effects on the measured parameters (28,29). However, this is only our hypothesis; further evidence is needed to confirm this.

The effect of BMI

Following the inclusion of EAT in the multivariable linear regression analysis, the independent correlation between BMI and both SRs and SRe was abolished. This finding does not imply that BMI is unimportant. Rather, it may be explained by the fact that BMI is a crude macroscopic measure, whereas LA strain is a precise microscopic mechanical parameter. The negative impact of BMI on LA function is likely not direct but mediated through a cascade of intermediate factors, most notably EAT. Once EAT is entered into the model, the independent contribution of BMI is no longer statistically significant (30). These findings indicate that EAT may provide incremental value over BMI in predicting more subtle cardiac dysfunction in hypertensive patients.

Limitations

Our study has several limitations that should be acknowledged. First, this was a cross-sectional, single-center study with a limited sample size. Consequently, the ability to draw causal inferences regarding the impact of BMI and EAT on LA strain is constrained. Our conclusions require validation through future prospective, multicenter studies with larger cohorts. Second, the absence of a healthy control group limits the comparison for establishing normative strain values. The inclusion of healthy participants in future research would provide a valuable reference context. Third, the relatively thin LA wall necessitates manual tracing by experienced observers, which may introduce inter-observer variability. Future studies should employ standardized analysis protocols and software with dedicated LA strain modules to mitigate this potential source of error. Fourth, the use of MRI scanners from three distinct manufacturers represents a potential methodological limitation. Although consistent SSFP sequences were applied, inter-manufacturer differences in specific parameters and inherent technical variations could introduce systematic bias into the measurement of LA strain. Scanner type was not adjusted for as a covariate in our statistical models, which may limit the precision of our strain comparisons. Fifth, the cross-sectional design precludes the assessment of the prognostic value of LA strain parameters. Longitudinal follow-up studies are necessary to determine their predictive potential for adverse outcomes in hypertensive patients with obesity. Finally, incorporating additional obesity metrics like visceral fat area or subcutaneous fat thickness could provide a more comprehensive exploration of obesity’s impact on LA function.

Conclusions

In patients with HTN and obesity, CMR-FT strain parameters serve as early indicators of LA dysfunction that are detectable prior to overt LA volumetric changes. Although LAEF_passive and LAEF_active were the principal determinants of LA deformation, EAT volume may provide incremental explanatory value beyond BMI for obesity-related LA dysfunction. Therefore, reducing EAT burden may represent a potential therapeutic target for improving LA function in obese patients with HTN.

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-aw-2461/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2461/dss

Funding: This study was supported by the grants from the National Natural Science Foundation of China (No. 82272068) and the Beijing Municipal Natural Science Foundation (No. L256013).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2461/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 Ethical Committee of Beijing Friendship Hospital (No. 2022-P2-173). Informed consent was taken from all the patients.

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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