Background: Type 2 diabetes mellitus (T2DM) increases the risks of heart failure and mortality in patients with hypertension, however the underlying mechanism is unclear. This study aims to investigate the impact of coexisting T2DM on left ventricular (LV) deformation and myocardial perfusion in hypertensive individuals. Materials and methods: Seventy hypertensive patients without T2DM [HTN(T2DM−)], forty patients with T2DM [HTN(T2DM+)] and 37 age- and sex-matched controls underwent cardiac magnetic resonance examination. Left ventricular (LV) myocardial strains, including global radial (GRPS), circumferential (GCPS) and longitudinal peak strain (GLPS), and resting myocardial perfusion indices, including upslope, time to maximum signal intensity (TTM), and max signal intensity (MaxSI), were measured and compared among groups by analysis of covariance after adjusting for age, sex, body mass index (BMI) and heart rate followed by Bonferroni's post hoc test. Backwards stepwise multivariable linear regression analyses were performed to determine the effects of T2DM on LV strains and myocardial perfusion indices in patients with hypertension. Results: Both GRPS and GLPS deteriorated significantly from controls, through HTN(T2DM−), to HTN(T2DM+) group; GCPS in HTN(T2DM+) group was lower than those in both HTN(T2DM−) and control groups. Compared with controls, HTN(T2DM−) group showed higher myocardial perfusion, and HTN(T2DM+) group exhibited lower perfusion than HTN(T2DM−) group and controls. Multiple regression analyses considering covariates of systolic blood pressure, age, sex, BMI, heart rate, smoking, indexed LV mass and eGFR demonstrated that T2DM was independently associated with LV strains (GRPS: p = 0.002, model R2= 0.383; GCPS: p < 0.001, model R2= 0.472; and GLPS: p = 0.002, model R2= 0.424, respectively) and perfusion indices (upslope: p < 0.001, model R2= 0.293; TTM: p < 0.001, model R2= 0.299; and MaxSI: p < 0.001, model R2= 0.268, respectively) in hypertension. When both T2DM and perfusion indices were included in the regression analyses, both T2DM and TTM were independently associated with GRPS (p = 0.044 and 0.017, model R2= 0.390) and GCPS (p = 0.002 and 0.001, model R2= 0.424), and T2DM but not perfusion indices was independently associated with GLPS (p = 0.002, model R2= 0.424). Conclusion: In patients with hypertension, T2DM had an additive deleterious effect on subclinical LV systolic dysfunction and myocardial perfusion, and impaired myocardial perfusion by coexisting T2DM was associated with deteriorated LV systolic dysfunction.
Keywords: Hypertension; Type 2 diabetes mellitus; Left ventricular strains; Perfusion; Magnetic resonance imaging
Xue-Ming Li and Li Jiang contributed equally to this work and should be considered as the equal first authors
Given their common risk factors, essential hypertension and type 2 diabetes mellitus (T2DM) frequently coexist. Approximately 70% of patients with T2DM have hypertension, and the development of T2DM is almost 2.5 times more likely in patients with precedent hypertension [[
Cardiac magnetic resonance (CMR) has less shortcomings of echocardiography, such as acoustic window limitations, low spatial resolution and high operator dependency, and can evaluate cardiac anatomy and function as well as myocardial perfusion in a single examination [[
Although limited echocardiographic studies have observed more severe subclinical systolic dysfunction in patients with coexisting hypertension and T2DM than in those with T2DM alone [[
From January 2016 to January 2020, 179 Adult Chinese Han race essential hypertensive patients with or without T2DM [HTN(T2DM+) and HTN(T2DM−), respectively] who underwent CMR at our institution were consecutively included. Hypertension was defined as a clinical systolic blood pressure (SBP) ≥ 140 mmHg and/or a diastolic blood pressure (DBP) ≥ 90 mmHg or a history of antihypertensive medications. The diagnosis of T2DM was based on the current American Diabetes Association guideline recommendations [[
Graph: Fig. 1 Flow diagram of the study patients. CMR, cardiac magnetic resonance; HTN, hypertension; T2DM, type 2 diabetes mellitus; HCM, hypertrophic cardiomyopathy; DCM, dilated cardiomyopathy; CAD, coronary artery disease; MI, myocardial infarction; HF, heart failure; LVEF, left ventricular ejection fraction; eGFR, estimated glomerular filtration rate
This study was approved by the Biomedical Research Ethics Committee of our hospital and conducted in accordance with the Declaration of Helsinki (2013 EDITION).
All the CMR examinations were performed using a 3.0 T whole-body scanner (Trio Tim; Siemens Medical Solutions, Erlangen, Germany) in the supine position. Data acquisition was performed with a standard ECG-triggering device that monitored each subject's dynamic ECG changes during the end-inspiratory breath hold period. A balanced steady-state free precession (bSSFP) sequence (repetition time [TR]: 39.34 ms, echo time [TE]: 1.22 ms, flip angle: 40°, slice thickness: 8 mm, field of view [FOV]: 250 × 300 mm, and matrix size: 208 × 139) was used to acquire 8 - 12 continuous cine images from the base to the apex in the short-axis view, as well as vertical LV two- and four-chamber cine images in the long-axis view. For perfusion imaging, a dose of 0.2 mL/kg gadobenate dimeglumine (MultiHance 0.5 mmol/mL; Bracco, Milan, Italy) was injected into the right antecubital vein with a power injector (Stellant, MEDRAD, Indianola, PA, USA) at a flow rate of 2.5–3.0 mL/s, followed by 20 mL of saline. Rest first-pass perfusion images were acquired in three standard short-axis slices (basal, middle, and apical) and in one four-chamber view slice by inversion recovery prepared echo-planar imaging sequence (TR/TE: 163.0/1.12 ms, flip angle: 10°, slice thickness: 8 mm, FOV: 360 mm × 270 mm, and matrix size: 256 × 192). To exclude myocardial infarction, late gadolinium enhancement (LGE) images were acquired by segmented-turbo-FLASH–phase-sensitive inversion recovery (PSIR) sequences (TR/TE: 750 ms/1.18 ms; flip angle: 40°, slice thickness: 8 mm, FOV: 400 × 270 mm, and matrix size: 256 × 148) 10–15 min after contrast administration.
CMR images were evaluated using offline commercially available software (cvi42, v. 5.10.2; Circle Cardiovascular Imaging, Calgary, Canada) by two radiologists with more than 3 years of CMR experience, who were blinded to the clinical data.
The endocardial and epicardial contours of the LV myocardium on the short-axis cine images were manually traced at the end-diastolic and end-systolic phases in the cvi42 short-3D module. Then, LV mass at end-diastole, LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LVEF, stroke volume and cardiac index were computed automatically. The trabeculae and papillary muscles were excluded from the LV mass and included in the LV cavity. LV mass, LVEDV and LVESV indexed for body surface area (BSA) (LVMI, LVEDVI and LVESVI, respectively) were calculated using the Mosteller formula [[
The LV global radial (GRPS), circumferential (GCPS) and longitudinal peak strain (GLPS) were obtained by manually delineating the endocardium and epicardium of the cine images at the end-diastole from the short-axis and long-axis two- and four-chamber slice views in the tissue tracking module. Strain was depicted as relative lengthening, shortening and thickening of the myocardium from end diastole (reference phase).
For the evaluation of first-pass myocardial perfusion (Fig. 2), the endocardium and epicardium and a region of interest drawn in the LV chamber were manually determined in the first-pass perfusion images (basal, middle and apical). Then, signal intensity-time curves were generated for the blood pool and each myocardial segment based on the 16-segment heart model. Consequently, semiquantitative segmental perfusion indices including the upslope, time to maximum signal intensity (TTM), and max signal intensity (MaxSI) were acquired automatically, and the global first-pass myocardial perfusion indices for each subject were calculated by averaging the regional values of the 16 myocardial segments. In addition, the presence of LGE was visually evaluated by the two radiologists with consensus.
Graph: Fig. 2 Representative first-pass myocardial perfusion MR images and signal intensity-time curves obtained from left mid-ventricular slice in normal controls (A, B), patients with HTN (T2DM−) (C, D) and HTN (T2DM+) (E, F). The orange curve (a) represents blood-pooled time-signal intensity curve and other colour curves represent time-signal intensity curves in each myocardial segment. The x-axis represents time and y-axis represents signal intensity
Intra- and inter-observer variabilities for the LV global myocardial strain and perfusion indices were analyzed in 30 random cases including 20 HTN patients and 10 controls. To determine the intra-observer variability, one observer (XM. L) evaluated the same subjects on two separate measurements 1 month apart. For the inter-observer variability evaluation, a second investigator (L. J) who was blinded to the first observer's results and clinical data reanalyzed the measurements.
Categorical variables are presented as frequencies (percentages) and were compared using Chi square tests. Continuous variables were evaluated for normality distribution by the Shapiro–Wilk test and are expressed as the mean ± standard deviation (SD). One-way analysis of variance (one-way ANOVA) was used to compare the baseline characteristics among the normal and HTN groups. Comparisons of the CMR-derived parameters between different groups were evaluated by analysis of covariance (ANCOVA) after adjusting for age, sex, body mass index (BMI) and heart rate followed by Bonferroni's post hoc test. Pearson's correlation coefficient was used to determine the correlation between LV myocardial strain and first-pass myocardial perfusion indices in HTN. Backwards stepwise multivariable linear regression analyses were performed to determine the predictors for LV strains and myocardial perfusion indices in the whole population and patients with HTN. Inter- and intra-observer agreements were determined by the evaluation of intraclass correlation coefficients (ICCs). All analyses were performed in SPSS version 21 (IBM, Armonk, New York, USA), and a two-tailed p < 0.05 was considered significant.
The main clinical characteristics of the study participants are summarized in Table 1. Age, BSA, heart rate, plasma triglycerides, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and eGFR were not significantly different between the observed groups (all p > 0.05), except for a higher BMI in both the HTN (T2DM−) and HTN (T2DM+) groups than in the control group (all p < 0.01). As expected, fasting blood glucose was significantly higher in the HTN (T2DM+) group than in the HTN (T2DM−) group and control group (all p < 0.001). In addition, both SBP and DBP were significantly higher in the hypertensive groups than in the control group (all p < 0.001).
Baseline characteristics of the study cohort
Controls HTN (T2DM−) HTN (T2DM+) n = 37 n = 70 n = 40 Demographics Age (years) 54.2 ± 10.5 55.0 ± 14.1 55.7 ± 9.8 Male; n (%) 19 (51.4) 35 (50.0) 20 (50.0) BMI (kg/m2) 23.00 ± 2.74 24.76 ± 3.01* 25.04 ± 2.20* BSA (kg/m2) 1.70 ± 0.18 1.71 ± 0.18 1.74 ± 0.16 Smoking, n (%) 0 27 (38.6) 12 (30.0) Laboratory data Fasting blood glucose (mmol/L) 5.61 ± 1.67 5.30 ± 1.01 7.98 ± 2.67§ Plasma triglycerides (mmol/L) 1.34 ± 0.53 1.76 ± 1.28 1.92 ± 1.64 Total cholesterol (mmol/L) 4.71 ± 1.04 4.39 ± 1.04 4.22 ± 0.80 HDL (mmol/L) 1.44 ± 0.40 1.40 ± 1.12 1.21 ± 0.28 LDL (mmol/L) 2.82 ± 0.97 2.52 ± 0.81 2.38 ± 0.67 eGFR (mL/min/1.73 m2) 98.4 ± 14.5 93.6 ± 18.8 90.2 ± 18.8 Hemodynamic variables Heart rate (beats/min) 70.1 ± 9.9 72.9 ± 16.7 71.5 ± 10.1 SBP (mmHg) 114.2 ± 13.2 141.1 ± 19.5* 138.7 ± 14.5* DBP (mmHg) 71.6 ± 8.5 87.7 ± 16.5* 84.6 ± 9.6* HTN treatment ACEI/ARB, n (%) 0 28 (40.0) 14 (35.0) Beta-blocker, n (%) 0 27 (38.6) 16 (40.0) Calcium channel blocker, n (%) 0 39 (55.7) 19 (47.5) Diuretics, n (%) 0 10 (14.3) 6 (15.0) Diabetes treatment Oral, n (%) 0 0 33 (82.5) Insulin, n (%) 0 0 7 (17.5)
The values are the mean ± SD, Numbers in the brackets are percentages HTN, hypertension; T2DM, type 2 diabetes mellitus; BMI, body mass index; BSA, body surface area; HDL, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; eGFR, estimated glomerular filtration rate; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker * p < 0.005 versus controls
The CMR findings for the observed groups are shown in Table 2. The LVMI (p < 0.001 and = 0.005, respectively) and LV remodeling index (p < 0.001 and = 0.040, respectively) in both the HTN (T2DM−) and HTN (T2DM+) groups were significantly higher than those in the control group, whereas the LVEDVI, LVESVI, LVEF, stroke volume and cardiac index were not significantly different among the groups (all p > 0.05).
Comparisons of CMR findings between controls, HTN (T2DM−) group and HTN (T2DM+) group after adjustment for age, sex, BMI and heart rate
Controls HTN (T2DM−) HTN (T2DM+) n = 37 n = 70 n = 40 LV geometry and function LVMI (g/m2) 44.55 ± 8.06 58.07 ± 16.02* 55.22 ± 13.22* < 0.001 LVEDVI (mL/m2) 75.92 ± 12.42 78.26 ± 17.00 76.95 ± 13.51 0.223 LVESVI (mL/m2) 28.51 ± 7.62 28.65 ± 10.71 29.39 ± 9.02 0.437 LVEF (%) 62.85 ± 6.20 63.84 ± 7.04 63.00 ± 7.66 0.408 Stroke volume (mL) 78.09 ± 12.04 83.99 ± 21.10 80.18 ± 14.66 0.082 Cardiac index (L/min/m2) 3.27 ± 0.60 3.70 ± 0.86 3.37 ± 0.72 0.068 LV remodeling index (g/mL) 0.60 ± 0.12 0.75 ± 0.17* 0.73 ± 0.18* 0.001 Myocardial strain GRPS (%) 38.98 ± 8.14 36.57 ± 10.81* 31.77 ± 10.91*§ < 0.001 GCPS (%) − 21.44 ± 2.74 − 21.41 ± 3.10 − 19.88 ± 3.59*§ 0.004 GLPS (%) − 14.94 ± 2.42 − 13.14 ± 2.66* − 11.75 ± 3.69*§ < 0.001 Myocardial perfusion Upslope 2.73 ± 1.17 3.30 ± 1.29* 1.83 ± 0.74*§ < 0.001 TTM (s) 26.90 ± 10.15 23.30 ± 8.78 31.65 ± 12.57*§ 0.002 MaxSI 23.03 ± 8.03 27.10 ± 9.64* 18.05 ± 6.78§ < 0.001
HTN, hypertension; T2DM, type 2 diabetes mellitus;LV, left ventricular; M, mass; EDV, end diastolic volume; ESV, end systolic volume; I, indexed to BSA; EF, ejection fraction; GRPS, global radial peak strain; GCPS, global circumferential peak strain; GLPS, global longitudinal peak strain; TTM, time to maximum signal intensity; MaxSI, max signal intensity * p < 0.05 versus controls
The LV GRPS and GLPS (all p < 0.05 and 0.027, respectively) declined significantly from controls, through HTN (T2DM−) group, to HTN(T2DM+) group. Compared with the control group, the LV GCPS was decreased in the HTN(T2DM+) group (p = 0.005) but preserved in the HTN (T2DM−) group.
Compared with the control group, higher myocardial perfusion was observed in the HTN (T2DM−) group as supported by increased upslope (p = 0.023) and MaxSI (p = 0.005), and lower myocardial perfusion was demonstrated in the HTN (T2DM+) group as supported by decreased upslope (p = 0.036) and increased TTM (p = 0.038). In addition, the HTN (T2DM+) group exhibited worse myocardial perfusion than the HTN (T2DM−) group, which was supported by a reduced upslope and MaxSI (all p < 0.001) and increased TTM (all p = 0.001) values.
Multivariable linear regression analyses demonstrated that considering the covariates of SBP, age, sex, BMI, BSA, heart rate, SV and LVM, both hypertension and T2DM were independently associated with LV GLPS (β = 1.469 and 1.569, p = 0.006 and 0.003, model R
LV GRPS, GCPS and GLPS were significantly associated with upslope and TTM, whereas they were not associated with MaxSI (Table 3).
Correlation of LV myocardial strain with first-pass perfusion indices in all patients with hypertension
Upslope TTM (s) Max SI GRPS (%) 0.292 0.003 − 0.355 <0.001 0.092 0.362 GCPS (%) − 0.226 0.024 0.390 <0.001 − 0.067 0.508 GLPS (%) − 0.299 0.002 0.279 0.005 − 0.144 0.152
Multivariable linear regression analyses (Table 4) revealed that considering the covariates of SBP, age, sex, BMI, heart rate, smoking, LVMI and eGFR, T2DM was independently associated with LV strains (GRPS: β = − 6.178, p = 0.002, model R
Multivariable association of diabetes with first-pass myocardial perfusion indices or LV strains in all patients with hypertension adjusted for SBP, age, sex, BMI, heart rate, smoking, LVMI and eGFR
Model 1 TTM Upslope MaxSI Coefficient (95% CI) Coefficient (95% CI) Coefficient (95% CI) Diabetes 8.188 (4.063 to 12.312) * 0.299 − 1.448 (− 1.952 to − 0.944) * 0.293 − 9.325 (− 13.117 to − 5.533) * 0.268
Multivariable association of diabetes with first-pass myocardial perfusion indices or LV strains in all patients with hypertension adjusted for SBP, age, sex, BMI, heart rate, smoking, LVMI and eGFR
GRPS GCPS GLPS Coefficient (95% CI) Coefficient (95% CI) Coefficient (95% CI) Model 2 Diabetes − 6.178 (− 10.059 to − 2.297)* 0.383 2.314 (1.231 to 3.398)* 0.472 1.685 (0.621 to 2.750)* 0.424 Model 3 Diabetes − 4.233 (− 8.343 to − 0.123)* 0.390 1.868 (0.718 to 3.018)* 0.495 1.685 (0.621 to 2.750* 0.424 TTM − 0.221 (− 0.401 to − 0.041)* 0.054 (0.001 to 0.107)* – Upslope – – – MaxSI – – –
Abbreviation of SBP, BMI and eGFR are shown in Table 1; and LVMI, LVEDVI, GRPS, GCPS, GLPS, TTM and MaxSI in Table 2 Model 1: Association between diabetes and perfusion indices Model 2: Association between diabetes and LV strains Model 3: Association of LV strains with diabetes and perfusion indices * p < 0.05; values are unstandardized estimate coefficients (B) and 95% confident interval (CI)
As demonstrated in Table 5, there were excellent intra- and inter-observer agreements in the measurement of LV global myocardial peak strain (ICC = 0.934–0.972 and 0.938–0.957, respectively) and first-pass myocardial perfusion (ICC = 0.912–0.931 and 0.891–0.956, respectively).
Intra-and inter-observer variability of LV strains and perfusion indices
Intra-observer Inter-observer ICC 95% CI ICC 95% CI GRPS 0.934 0.891–0.954 0.945 0.857–0.989 GCPS 0.972 0.915–0.991 0.957 0.945–0.994 GLPS 0.938 0.878–0.988 0.938 0.852–0.978 Upslope 0.931 0.920–0.986 0.915 0.895–0.983 TTM (s) 0.912 0.905–0.975 0.891 0.840–0.932 MaxSI 0.920 0.869–0.945 0.956 0.869–0.978
Abbreviation of GRPS, GCPS, GLPS, TTM and MaxSI are shown in Table 2 ICC, intraclass correlation coefficient; CI, confidence interval
The main findings of this study are as follows: (
Similar to most progressive myocardial diseases, subendocardial fibers are more vulnerable to being affected; thus, longitudinal contractile function representing as GLPS may be impaired earlier and more severely [[
In both hypertension and T2DM, there are structural and functional abnormalities in coronary microvasculature, including hypertrophic remodeling of small arteries and arterioles, microvascular rarefaction, and functional increases in vasoconstriction due to endothelial dysfunction [[
To our knowledge, reports about the combined effect of hypertension and T2DM on myocardial microcirculation are still missing. We found that patients with HTN (T2DM+) showed worsened myocardial perfusion than those with HTN (T2DM−) and control group. A possible explanation for this may be that although hypertension and T2DM increase resting myocardial perfusion to meet increased oxygen consumption, their coexistence may amplify the abovementioned abnormalities of microvasculature that have reduced myocardial perfusion at rest.
In our study, there was a significant correlation between subclinical LV systolic dysfunction and impaired myocardial perfusion, and impaired myocardial perfusion by T2DM was associated with the deterioration of subclinical LV systolic dysfunction in patients with hypertension. Our results were consistent with the study by Jiang et al. [[
Several limitations in this study merit comment. First, this was a cross-sectional single-center study with a relatively small sample size, and further multicenter studies with a larger population should be performed to validate our findings. Second, The PROCEED study revealed that duration of T2DM and systolic blood pressure are determinants of severity of coronary stenosis in asymptomatic diabetes [[
In patients with hypertension, T2DM had an additive deleterious effect on subclinical LV systolic dysfunction and myocardial perfusion. In addition, impaired myocardial perfusion by coexisting T2DM was associated with deteriorated LV systolic dysfunction, which may contribute to increased adverse outcomes.
This work was supported by a grant from the National Natural Science Foundation of China (81771887 and 81471722) and 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYGD18013).
Not applicable.
XML and LJ designed the study. XML analyzed the data and wrote the manuscript. GYK participated in the study design, data analyze, editing and review of the manuscript. YZG supervised the overall study and contributed to study design, editing and review of the manuscript. RY, PLH researched data and review the manuscript. RY, PLH, LQP, RS and WFY were responsible for collecting, sorting and statistical data. ZGY is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
This study was approved by the Biomedical Research Ethics Committee of our Hospital, Sichuan University (Chengdu, Sichuan, China) with a waiver of informed consent due to the retrospective nature of this investigation.
Not applicable.
The authors declare that there are no conflicts of interest.
• HTN
- Hypertension
• T2DM
- Type 2 diabetes mellitus
• LV
- Left ventricular
• CMR
- Cardiac magnetic resonance
• EDV
- End-diastolic volume
• ESV
- End-systolic volume
• LVEF
- Left ventricular ejection fraction
• LVMI
- LV mass index
• GRPS
- Global radial peak strain
• GCPS
- Global circumferential peak strain
• GLPS
- Global longitudinal peak strain
• TTM
- Time to maximum signal intensity
• MaxSI
- Max signal intensity
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By Xue-Ming Li; Li Jiang; Ying-Kun Guo; Yan Ren; Pei-Lun Han; Li-Qing Peng; Rui Shi; Wei-Feng Yan and Zhi-Gang Yang
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