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.

Fig. 1.

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 $\ge$75 mL/min/1.73 m${}^2$.

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 $\times$ 1.40 mm${}^2$.

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 $\times$ 1.8 $\times$ 8 mm${}^3$.

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 $\times$ 1.41 mm${}^2$, slice thickness = 8 mm.

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:

$$\begin{array}{c}\hfill \mathrm{ECV}=\left(\mathrm{\Delta }{\mathrm{R1}}_{\text{myocardium}}/\mathrm{\Delta }{\mathrm{R1}}_{\text{blood}}\right)*(1-\text{hematocrit})\hfill \\ \hfill \mathrm{R1}=1/\mathrm{T1}\text{time}\hfill \end{array}$$

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 $\pm$ standard deviation (data fitted normal distribution), or media, quartile (data did not fit normal distribution). An unpaired t-test or Kruskal-Wallis test was adopted to evaluate differences between means as appropriate. Pearson correlation was adopted for correlation analysis between variables. Univariate and Multivariable linear regression was carried out to investigate the association of creatinine with native T1 and CRP. Interaction analysis was conducted. Intra-observer repeatability was assessed for T1 mapping using the intraclass correlation coefficient. Statistical significance was defined as p 0.05. Statistical analysis was performed using the R package (version 4.11, R foundation for statistical computing, Vienna, Austria).

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 $\ge$75 mL/min/1.73 m${}^2$ (high eGFR group), patients with eGFR 75 mL/min/1.73 m${}^2$ (low eGFR group) had higher lymph count, LA volume, LV mass, and body mass index (p 0.05). The two groups were similar in New York Heart Association class, heart failure biomarker, and medication history. A significant difference in comorbidity including coronary artery disease, atrial fibrillation, and hypertension was not identified between the two groups (Table 1).

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 $\ge$75 mL/min/1.73 m${}^2$) and the low eGFR group (eGFR 75 mL/min/1.73 m${}^2$) patients’ groups regarding myocardial post T1 which were higher in the high eGFR group (high eGFR: 274.6 $\pm$ 71.2 ms vs low eGFR: 310.6 $\pm$ 49.8 ms, p = 0.041). Non-significant differences of native T1 (high eGFR: 1117.0 $\pm$ 56.6 ms vs low eGFR: 1096.5 $\pm$ 61.8 ms, p = 0.236) and ECV (high eGFR: 39.1 $\pm$ 9.5 ms vs low eGFR: 35.4 $\pm$ 10.2 ms, p = 0.203) were observed between the two groups.

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 0.014), both in global and segmented analysis. A moderate correlation was observed in myocardial global T1 (R = 0.34, p = 0.014). Besides, there was a mild correlation between creatinine and inflammation marker (CRP R = 0.49, p 0.001; lymphocyte R = –0.29, p 0.044; Neutrophil R = 0.42, p = 0.003). Both LVEF and NT-proBNP were not significantly correlated with creatinine.

Fig. 2.

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.

Fig. 3.

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 ($\beta$ = 0.16, 95% confidence interval (CI): 0.04–0.28, p = 0.014) and CRP ($\beta$ = 0.30, 95% CI: 0.15–0.45, p 0.001) as determinants of creatinine when age and diabetes were also screened. Multivariable linear regression analysis identified global native T1 ($\beta$ = 0.12, 95% CI: 0.01–0.123, p 0.040) as the determinant of creatinine while age and diabetes were adjusted.

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 19.41 mg/L), and high levels (CRP $\ge$19.41 mg/L). Significant interactions between CRP and global native T1 in relation to creatinine levels (p for interaction = 0.005) were identified. The interaction tests for age and diabetes were not significant (p for interaction 0.352, 0.969 respectively).

Fig. 4.

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.

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.