- Academic Editor
†These authors contributed equally.
Background: Inflammation is essential in cardiorenal syndrome, however
there is still a lack of evidence proving the interaction between cardiac injury,
renal dysfunction and the inflammatory response. This study aimed to illustrate
the association between renal dysfunction and cardiac injury with a specific
focus on the role of inflammation. Methods: A single-center,
retrospective study included patients with heart failure admitted to the
cardiovascular department from September 2019 to April 2022. Patients received
cardiovascular magnetic resonance (CMR) imaging (T1 mapping and late gadolinium
enhancement (LGE)). Demographic, creatinine and native T1 were analyzed using
pearson correlation, linear regression and adjusted for confounders. Interaction
and subgroup analysis were performed. Results: Finally, 50 validated
heart failure (HF) patients (age 58.5
Heart failure often coexists with several comorbidities of which chronic kidney
disease (CKD) is a strong predictor of poor outcomes [1, 2, 3]. The interaction
between heart and kidney dysfunction is both complex and bi-directional, and has
been referred to as cardiorenal syndrome. Three mechanisms have been proposed to
contribute to the development of cardiorenal syndrome, including hemodynamic,
hormonal, and cardiovascular disease-related factors [4, 5]. Systemic and chronic
low-grade inflammation increased expression of interleukin (IL)-1
However, detecting subtle pathological changes during the progress of cardiorenal syndrome can be challenging due to the limited accuracy and specificity of current biomarkers [1, 8, 9]. Cardiovascular imaging may provide valuable insights into organ damage and inflammation in this context. T1 mapping, assessed by cardiovascular magnetic resonance (CMR) imaging, is a surrogate biomarker of myocardial fibrosis burden. Previous studies have demonstrated the association between T1 mapping and worsening kidney function, suggesting that it might be a practical tool in assessing the presence and progression of cardiorenal syndrome [10, 11, 12, 13, 14]. As indicators of renal dysfunction, creatinine and eGFR were frequently used.
This study aimed to illustrate the association between renal dysfunction and cardiac injury with a specific focus on the role of inflammation, as represented by C-reactive protein (CRP). By comprehensively examining the association between cardiac injury and renal function in heart failure patients, we hope to gain a better understanding of inflammatory damage in the cardiorenal syndrome.
It was a retrospective, single-center study approved by the institutional review board. Informed consent was obtained from patients for this study (Num-2020-1052). Participants received CMR at our institution between September 2019 to April 2022. The inclusion criteria were as follows: heart failure with symptomatic clinical syndrome with or without elevated N-terminal pro-B type natriuretic peptide (NT-proBNP); received cardiovascular magnetic resonance imaging (T1 mapping and LGE (late gadolinium enhancement)). Exclusion criteria for this study were defined as follows: individuals with implanted pacemakers or defibrillators, hypertrophic cardiomyopathy, infiltrated cardiomyopathy, valvular heart disease, congenital cardiac disease, or pericardial disease. Details were summarized in Fig. 1. This study complied with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Flow chart of patients selection. CMR, magnetic resonance image; LGE, late gadolinium enhancement.
Demographics and laboratory data were recorded from the electronic medical
system. Laboratory items were listed below: CRP, Hematocrit (HCT),
glycated hemoglobin (HbA1c), low-density lipoprotein (LDL), D-dimer, NT-proBNP,
white blood cell count (WBC), alanine aminotransferase (ALT), cardiac troponin I
(cTnI), serum creatinine (Cr), lymphocyte count and
ratio, neutrophil count and ratio. The patients were divided according to eGFR
All magnetic resonance imaging (MRI) data were
acquired on a 1.5 T MRI system (Aera, Siemens Healthineers). Cine images with
retrospective electrocardiogram (ECG) gating during a breath-hold were adopted
from a balanced steady-state free precession sequence. The imaging parameters
were as follows: the average temporal resolution 45.6 ms. 9–12 slices of
short-axis views (8 mm thickness) and three long-axis views were obtained using
the following sequence parameters: flip angle 35°, echo time (TE) 1.12
ms, repetition time (TR) 2.60 ms, and average in-plane resolution 2.10
LGE images were acquired 10 minutes after administration of gadolinium agent
using a gradient-spoiled, turbo-fast, low-angle shot sequence with a
phase-sensitive inversion recovery sequence. The images were obtained in the
long-axis views (2-chamber and 4-chamber), as well as a series of contiguous 6-mm
LV (left ventricle) short-axis slices that covered the entire LV. The imaging
parameters were as follows: TR/TE, 700 ms/1.28 ms; time of inversion (TI) 350 ms;
flip angle 40°, spatial resolution 1.8
The pre-contrast modified look-locker inversion recovery (MOLLI) images followed
the 5(3)3 protocol during a breath-hold. Post-contrast MOLLI images followed the
4(1)3(1)2 protocol during a breath-hold 10 min after contrast administration. T1
images were acquired from 3 short-axis slices (basal, mid, and apical). The
apical slice was chosen as the most proximal slice of the apical segment to avoid
partial volume averaging. Imaging parameters were: TR = 2.60 ms, TE = 1.12 ms, flip angle (FA)
= 35°, in-plane resolution = 2.10
An experienced physician used CVI42 version 5.13.4 (Circle Cardiovascular Imaging Inc., Calgary, Canada) to analyze MRI images. The measures included LV end-diastolic volume, LV end-systolic volume, stroke volume, LV mass, and LV ejection fraction (EF), right ventricle (RV) EF, left atrium volume. Global longitudinal strain (GLS, %), global radial strain (GRS, %), and global circumferential strain (GCS, %) were also calculated through CVI42.
T1 relaxation times were measured using regions of interest drawn in the short-axis views. Regions of interest avoided the papillary muscles and border of blood partial volume effect. Averaged T1 values of the short-axis slices were calculated, and global T1 values were defined as the mean value.
An extracellular volume (ECV) map was generated from a native T1 map and a post-contrast T1 map through CVI42. It was calculated using the mean segmental pixel value from the MOLLI ECV maps and using the formula below:
Intra-observer variabilities for T1 values of the LV segments were assessed in a randomly selected 10 subjects.
Categorical and consecutive data were presented as number (%), mean
Baseline demographics of all heart failure patients are summarized in Table 1.
Non-significant differences were observed between the two groups regarding age,
sex, blood pressure, and heart rate except for body mass index (BMI). Compared to
patients with eGFR
High eGFR group | Low eGFR group | p | ||
(N = 29) | (N = 21) | |||
Demographics | ||||
Sex (male) | 20 (69.0%) | 19 (90.5%) | 0.092 | |
Age | 58.7 (14.8) | 58.2 (15.2) | 0.901 | |
Weight (kg) | 59.2 (8.3) | 83.6 (10.9) | ||
Height (cm) | 163.4 (7.7) | 168.4 (7.2) | 0.023 | |
Body mass index (kg/m |
22.2 (2.6) | 29.1 (3.1) | ||
Systolic BP (mmHg) | 113.7 (17.8) | 110.3 (11.5) | 0.417 | |
Diastolic BP (mmHg) | 67.8 (12.4) | 67.7 (16.4) | 0.985 | |
Heart rate | 77.0 [62.0; 85.0] | 77.0 [73.0; 102.0] | 0.226 | |
Smoke | 3 (10.3%) | 7 (33.3%) | 0.073 | |
Alcohol | 4 (13.8%) | 5 (23.8%) | 0.464 | |
Hypertension | 13 (44.8%) | 12 (57.1%) | 0.567 | |
Diabetes | 7 (24.1%) | 3 (14.3%) | 0.488 | |
Coronary artery disease | 11 (37.9%) | 11 (52.4%) | 0.467 | |
Atrial fibrillation | 4 (13.8%) | 5 (23.8%) | 0.464 | |
Thyroid disease | 1 (3.4%) | 0 (0.0%) | 0.999 | |
Stroke | 2 (6.9%) | 1 (4.8%) | 0.999 | |
NYHA |
7 (24.1%) | 4 (19.0%) | 0.836 | |
ARNi | 20 (69.0%) | 19 (90.5%) | 0.092 | |
Beta blocker | 22 (75.9%) | 19 (90.5%) | 0.271 | |
MRA | 23 (79.3%) | 17 (81.0%) | 0.999 | |
Diuretics | 20 (69.0%) | 17 (81.0%) | 0.531 | |
Digoxin | 2 (6.9%) | 0 (0.0%) | 0.503 | |
Amiodarone | 2 (6.9%) | 3 (14.3%) | 0.638 | |
CCB | 0 (0.0%) | 1 (4.8%) | 0.420 | |
Anti platelet | 15 (51.7%) | 10 (47.6%) | 0.999 | |
Anti coagulation | 7 (24.1%) | 4 (19.0%) | 0.741 | |
Statin | 19 (65.5%) | 12 (57.1%) | 0.759 | |
Laboratory tests | ||||
Hct (L/L) | 41.6 (5.7) | 42.8 (5.1) | 0.413 | |
HbA1c (%) | 5.9 [5.5; 6.4] | 6.0 [5.5; 6.7] | 0.595 | |
D-dimer (ug/L) | 330.0 [220.0; 1020.0] | 400.0 [230.0; 590.0] | 0.774 | |
Alanine aminotransferase (mmol/L) | 29.0 [26.0; 36.0] | 31.0 [27.0; 36.0] | 0.984 | |
NT-proBNP (pg/mL) | 1184.0 [216.0; 2685.0] | 1020.0 [402.0; 1856.0] | 0.992 | |
cTnI (ng/mL) | 0.738 | |||
Creatinine (umol/L) | 81.0 [63.0; 97.0] | 81.0 [75.0; 90.0] | 0.776 | |
eGFR (mL/min/1.73 m |
80.8 (8.3) | 56.4 (10.9) | ||
CRP (mg/L) | 5.0 [3.4; 21.7] | 5.0 [3.4; 9.3] | 0.633 | |
WBC (10 |
6.2 (1.8) | 6.6 (2.0) | 0.455 | |
Lymphocyte count (10 |
1.3 [1.0; 1.7] | 1.5 [1.4; 2.3] | 0.014 | |
Lymphocyte ratio (%) | 25.2 (8.7) | 27.2 (10.8) | 0.475 | |
Neutrophil count (10 |
3.8 [2.8; 4.9] | 4.5 [3.7; 5.3] | 0.194 | |
Neutrophil ratio (%) | 64.8 [59.2; 69.4] | 68.7 [56.2; 72.8] | 0.768 | |
CMR parameters | ||||
LV end-diastolic volume (mL) | 242.1 (83.2) | 274.6 (73.6) | 0.152 | |
LV end-systolic volume (mL) | 178.8 (82.2) | 215.0 (78.7) | 0.123 | |
LV EF (%) | 27.1 [17.4; 36.8] | 22.4 [13.1; 33.7] | 0.382 | |
Stroke volume (mL) | 58.1 [41.2; 74.8] | 59.0 [42.4; 79.2] | 0.875 | |
Cardiac mass (g) | 118.9 [92.8; 145.8] | 144.4 [124.5; 166.2] | 0.006 | |
RV EF (%) | 35.5 (15.6) | 28.5 (14.8) | 0.112 | |
LA volume (mL) | 82.7 [74.8; 98.1] | 121.2 [83.7; 152.4] | 0.006 | |
LV GCS (%) | –8.4 [–10.2; –6.5] | –5.8 [–9.5; –4.5] | 0.135 | |
LV GRS (%) | 10.7 [8.2; 14.2] | 8.1 [5.3; 14.3] | 0.205 | |
LV GLS (%) | –8.1 [–10.6; –6.2] | –6.7 [–10.3; –5.4] | 0.326 | |
LGE (positive) | 22 (75.9%) | 14 (66.7%) | 0.692 | |
Native T1 (ms) | 1117.0 (56.6) | 1096.5 (61.8) | 0.236 | |
Post T1 (ms) | 274.6 (71.2) | 310.6 (49.8) | 0.041 | |
Extracellular volume (%) | 39.1 (9.5) | 35.4 (10.2) | 0.203 |
All values are presented as the means (SD) or n (%) or as the median [interquartile range]. N, number of individuals; CRP, c-reactive protein; HbA1c, glycated hemoglobin; eGFR, estimated glomeruar filtration rate; BP, blood pressure; NT-proBNP, N-terminal pro-B type natriuretic peptide; WBC, white blood cell count; NYHA, New York Heart Association; ARNi, angiotensin receptor neprilysin inhibitor; cTnI, cardiac troponin I; MRA, mineralcorticoid recept antagonist; CCB, calcium channel blocker; Hct, hematocrit value; CMR, magnetic resonance image; LV, left ventricle; EF, ejection fraction; RV, right ventricle; LA, left atrium; LGE, late gadolinium enhancement; GLS, global longitudinal strain; GRS, global radial strain; GCS, global circumferential strain.
There was no significant difference in LV end-diastolic volume, LV EF, RV EF,
and myocardial strain (Table 1). Over 60% of all patients had myocardial scar
with no overall difference between the two groups for the LGE existence
(p = 0.692). Significant differences were observed between the two
groups, and both the high eGFR group (eGFR
Asymptomatic heart failure patients with elevated creatinine level and CRP level
received cardiovascular magnetic resonance imaging and the results demonstrated a
lesion in the cardiac (late gadolinium enhancement in the middle segment of
inter-ventricular septum in short-axis view) (Fig. 2). The correlation between
creatinine and the cardiac global native T1 was shown in Fig. 3. Serum creatinine
level was significantly correlated with cardiac T1 (R = 0.34, p
Typical cardiovascular magnetic resonance images from a 58-year-old male patient with chronic kidney disease. PSIR, LGE images (A–C), native T1 (D–F) and post T1 images (G–I) were displayed separately in different columns. Segments from basal to apical were displayed in rows. Color bars were added separately for images from (D–F) and (G–I). PSIR, phase-sensitive inversion recovery; LGE, late gadolinium enhancement.
Scatterplots (A to I) comparing serum creatinine and cardiac T1 (A,B,C,D), CRP, lymphocyte ratio, neutrophil ratio, NT-proBNP and LVEF. Pearson correlation was adopted. CRP, c-reactive protein; NT-proBNP, N-terminal pro-B type natriuretic peptide; LVEF, left ventricle ejection fraction; Cr, serum creatinine.
Table 2 summarizes the results of linear regression analysis for determinants of
creatinine in all HF patients. Univariate analysis identified global native T1
(
Univariate | Multivariable | |||||
95% CI | p | 95% CI | p | |||
Age | 0.57 | 0.07~1.07 | 0.029 | 0.38 | –0.07~0.83 | 0.100 |
Sex | –6.52 | –25.02~11.98 | 0.493 | |||
Diabetes | 21.4 | 3.12~39.67 | 0.026 | 8.05 | –9.27~25.37 | 0.354 |
Coronary artery disease | 14.1 | –0.89~29.10 | 0.071 | |||
Atrial fibrillation | –12.27 | –32.01~7.47 | 0.229 | |||
Stroke | 18.85 | –13.14~50.83 | 0.254 | |||
Body mass index | –0.82 | –2.56~0.91 | 0.358 | |||
CRP | 0.3 | 0.15~0.45 | 0.24 | 0.09~0.40 | 0.003 | |
Global native T1 | 0.16 | 0.04~0.28 | 0.014 | 0.12 | 0.01~0.23 | 0.040 |
Extracellular volume | 0.41 | –0.37~1.19 | 0.306 | |||
LV EF | –0.06 | –0.62~0.49 | 0.82 | |||
RV EF | 0.36 | –0.13~0.85 | 0.154 | |||
LA volume (mL) | –0.05 | –0.16~0.06 | 0.356 | |||
LV GCS | 1.22 | –0.50~2.94 | 0.171 | |||
LV GRS | –0.45 | –1.38~0.49 | 0.355 | |||
LV GLS | 1.46 | –0.45~3.37 | 0.140 | |||
LGE | 10.2 | –6.71~27.10 | 0.243 |
CRP, C-reactive protein; LV, left ventricle; EF, ejection fraction; RV, right ventricle; LA, left atrium; LGE, late gadolinium enhancement; GCS, global circumferential strain; GRS, global radial strain; GLS, global longitudinal strain.
In order to analyze the association between CRP and native T1, an interaction
analysis was performed (Fig. 4). We grouped the strata factors, which were
classified into two categories (according to the mean of CRP): low (CRP
Predicted probabilities of serum creatinine based on the interaction between CRP and cardiac native T1. CRP was classified into two categories according to the mean value of CRP. CRP, C-reactive protein.
T1 mapping showed excellent intra-observer agreement: native T1: ICC = 0.998, 95% CI: 0.998–0.998; ECV: ICC = 0.992, 95% CI: 0.733–0.980.
In this retrospective study, we demonstrate associations between creatinine levels and cardiac native T1. Native T1 was significantly associated with worsening kidney function. A serological marker of creatinine was associated with native T1 and CRP respectively. A significant interaction between CRP and native T1 was observed in different creatinine levels. According to these results, the interaction between myocardial injury and kidney dysfunction is contingent on the severity of the inflammatory response.
Our research provided clinical evidence that heart failure is associated with
worsening kidney dysfunction. Native T1 was sensitive to myocardial fibrosis,
edema, and iron overload. A previous cardiovascular magnetic resonance imaging
study reported that native T1 (
This research extended the current understanding of cardiorenal syndrome. We provided evidence that myocardial damage (native T1 elevation) interacted with inflammation response in relation to kidney dysfunction. The association between myocardial damage and kidney dysfunction was less significant among individuals with low CRP levels compared to those with high levels. This phenomenon could be explained by cardiorenal syndrome, a bi-directional connection. A previous study demonstrated that inflammation contributed to the pathogenesis of cardiorenal syndrome [18]. Inflammatory biomarkers of CRP are known to predict worseoutcomes in cardiovascular and chronic diseases [19, 20, 21]. Various factors such as fluid retention, oxidative stress, obesity, smoking, and genetic factors contribute to this inflammation [4, 5]. Biomarkers of inflammation such as CRP pentraxin-3, IL-10, and IL-6 are associated with adeclining renal function [7, 22]. Besides, the inflammatory response plays a crucial role in vasculopathy and tissue remodeling in heart and kidney dysfunction [4, 23, 24]. Several potential biomarkers have been identified as practical tools for the assessment of cardiorenal syndrome, including native T1, a surrogate cardiac image biomarker. Native T1 is one of the parameters provided by cardiovascular T1 mapping. Besides, previous studies have shown that extracellular volume, another parameter of T1 mapping, is associated with a worse prognosis in heart failure patients [25, 26].
Although T1 mapping has been extensively studied, we discovered the usefulness
of elevated native T1 as a biomarker for cardio-renal syndrome instead of ECV. A
similar result was reported by a meta-analysis which showed that in the diagnosis
of myocarditis, the area under curve (AUC) for T1 mapping was 0.95 (95% CI: 0.93
to 0.97), for ECV 0.81 (95% CI: 0.78 to 0.85), for LGE 0.87 (95% CI: 0.84 to
0.90) [27]. Accordingly, in diffuse amyloidosis cardiac damage, native T1
demonstrated a similar diagnostic value [28]. A possible explanation is that LGE
is a quantifiable parameter that cannot reflect diffuse fibrosis, while ECV
carries multiple measurement errors. Besides, a previous study found an
independent association between native T2 and hs-cTnT in patients with severe CKD
(eGFR
First, this study was a small sample, retrospective study. A further prospective, large cohort study would prove the diagnostic and prognostic value of inflammation in the cardiorenal syndrome. Second, it would be desirable to include measurements such as T2 mapping, and T2* mapping and proteinuria at the original design to fully characterize tissue of cardiac and kidney, and help understand the connection of cardiorenal syndrome; however, due to the retrospective design, there is limited data when parameter mapping was not commonly adopted in the clinical practice. Thirdly, tissue biopsy would serve as the gold standard for myocardial and renal pathological changes, and provide solid evidence for the theory of inflammation-driven cardiorenal syndrome. We aim to discuss this issue in future studies.
This study demonstrates myocardial inflammation and fibrosis assessed by CMR correlate with renal dysfunction in heart failure patients. T1 mapping identifies myocardial injury associated with elevated inflammatory markers and renal impairment. Cardiac inflammation likely mediates the link between cardiomyopathy and kidney disease.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
XHX, JHC, LY, JZS, CCZ, QQD contributed in the data processing and the manuscript writing. Cardiovascular magnetic resonance imaging and analyzing—CCZ, JZS and LY. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
The Second Affiliated Hospital of Zhejiang University, Institutional Review Board approved this study. Informed consent was obtained from patients for this study (Num-2020-1052).
Not applicable.
This research received no external funding.
The authors declare no conflict of interest.
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