CMR-LGE imaging features of dilated cardiomyopathy and relationship with left ventricular function

Baixiang Zhang; Zhongxiao Liu; Sidra Farooq; Mingchang Du; Peng Lu; Yu Yang; Wensu Chen

doi:10.1038/s41598-025-27411-0

. 2025 Dec 12;15:43696. doi: 10.1038/s41598-025-27411-0

CMR-LGE imaging features of dilated cardiomyopathy and relationship with left ventricular function

Baixiang Zhang ^1,^#, Zhongxiao Liu ^2,^#, Sidra Farooq ^1,^#, Mingchang Du ¹, Peng Lu ¹, Yu Yang ^1,^✉, Wensu Chen ^1,^3,^✉

PMCID: PMC12701005 PMID: 41387979

Abstract

Previous studies have reported positive late gadolinium enhancement (LGE) rates ranging from 30% to 72% in dilated cardiomyopathy (DCM). There is no unified consensus on the relationship between different LGE features and left ventricular (LV) function. This study aimed to demonstrate the LGE characteristics in patients with DCM and to further investigate the relationship between LGE distribution, location and load and LV function. A total of 193 patients diagnosed with DCM were enrolled from February 2018 to May 2020 in the First Affiliated Hospital of Nanjing Medical University. All patients underwent cardiac magnetic resonance (CMR). The parameters of LV function, volume, and global LGE burden were obtained. According to the myocardial level of LGE distribution, stage of LGE distribution, and LGE load, the grouping included 3 types. A total of 127 patients (80.9%) were enrolled with LGE positive. The median LV LGE load was 15.5%. The proportion of midmyocardial and subepicardial myocardial involvement was significantly higher than that of subendocardial myocardial involvement (60.6%, 50.4% vs. 10.2%, P < 0.001). LGE distributed more often in the ventricular septum, which was significantly higher than in the free-wall segments. Left ventricular ejection fraction and global radial strain in the midmyocardial LGE group and the multilayer LGE group were lower than in the LGE(-) group (p < 0.005). Kaplan-Meier survival analysis revealed that compared to the LGE-negative group, both the midmyocardial LGE group and the multilayer LGE group exhibited significantly elevated risks of long-term MACE (Log-rank p < 0.05). Dilated cardiomyopathy LGE most commonly involves the septal myocardium of the basal and intermediate segments of the left ventricle, and predominantly involves the middle layer and subepicardium. LGE involvement of the LV midmyocardium is associated with poorer LV function and higher risks of long-term MACE.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-27411-0.

Keywords: Dilated cardiomyopathy, Cardiac magnetic resonance, Strain, Ring-like late gadolinium enhancement, Left ventricular function

Subject terms: Cardiology, Risk factors

Introduction

Dilated cardiomyopathy (DCM) is a common end-stage cardiac manifestation of which the etiology is not yet fully understood¹. The poor prognosis of DCM due to the impaired left ventricular function imposes a heavy burden on society². It is particularly necessary and urgent to improve the prognosis of patients with dilated cardiomyopathy as well as the quality of their survival. Myocardial fibrosis, as a consequence of myocellular damage, can lead to cardiac dysfunction or ventricular remodeling and dilatation due to impaired contractile function of cardiomyocytes³.

Cardiac magnetic resonance (CMR) can noninvasively and reliably identify myocardial fibrosis, and it has been widely used in both research and clinical work to improve the diagnosis and management of the disease^4,5. CMR is based on two main imaging techniques to reflect myocardial fibrosis: Late gadolinium enhancement (LGE) technique and T1 mapping (including extracellular volume) technique^6,7. LGE imaging can well identify focal dense scar tissue⁸ and T1 mapping (including extracellular volume) technique is mainly used to identify diffuse interstitial fibrosis⁹. A number of studies have demonstrated that the presence of CMR-LGE is significantly associated with a wide range of poor prognoses in patients with DCM, including all-cause mortality, rehospitalization rates, and various malignant ventricular arrhythmias^10–12. Our previous study showed that the ring-like pattern of LGE is independently associated with an increased risk of ventricular tachyarrhythmias in patients with non ischaemic DCM¹³. However, as a disease with unknown etiology and high heterogeneity, the diagnosis and treatment of DCM may be affected by factors such as different regions, different races, and different levels of medical technology, and different studies have found that LGE exists in 30%-72% of patients with dilated cardiomyopathy¹⁴. Besides, so far, the relationship between specific LGE features, such as the extent, location and the ring-like pattern, and ventricular function in DCM remains unclear^{10–12,15–17}. The aims of this study include the following: First, to summarize the imaging features of CMR-LGE in DCM patients in our center; Second, to analyze the relationship between the specific LGE features and LV systolic function, structure, and myocardial strain.

Materials and methods

Study population

This is a retrospective observational study and a substudy of a previous article¹³. A total of 193 consecutive patients with non-ischemic dilated cardiomyopathy admitted to the First Affiliated Hospital of Nanjing Medical University from February 2018 to May 2020 were included in this study, all of whom underwent CMR scanning and completed delayed-enhancement sequence scanning. All patients were admitted for the planned implantation of implantable cardioverter-defibrillator (ICD). All studies were conducted before ICD implantation. Due to the limitations of CMR, patients with a history of pacemaker (PM) or cardiac resynchronization therapy (CRT) implantation were excluded from this study. The clinical diagnosis of DCM was defined as the presence of a dilated left ventricle after exclusion of other confounding etiologies, including ischemic cardiomyopathy, hypertension, cardiac valvular disease, infiltrative heart disease, and congenital heart disease, etc., presenting with left ventricular or biventricular dilatation and cardiac systolic dysfunction¹⁸. Ventricular systolic dysfunction is assessed on the basis of reduced left ventricular ejection fraction (LVEF) according to published gender-specific reference values and elevated left ventricular end diastolic volume index (LVEDVI)¹⁹. Specifically, an LVEDVI of ≥ 75 mL/m² in males and ≥ 62 mL/m² in females. Left ventricular global systolic dysfunction is defined by LVEF < 50%. Exclusion criteria were patients with missing follow-up data or poor CMR imaging quality, ischemic cardiomyopathy, history of myocarditis or hypertrophic cardiomyopathy, noncompaction of the ventricular myocardium, severe cardiac valvular disease, alcoholic cardiomyopathy, and dilated cardiomyopathy associated with metabolic diseases. All ischemic cardiomyopathies were excluded using coronary angiography or CT coronary angiography. In CMR images, all those with infarct patterns of LGE were also excluded¹. The diagnosis of myocarditis was excluded based on clinical diagnostic criteria as well as CMR diagnostic criteria, and no patient underwent endomyocardial biopsy. All methods were performed in accordance with the relevant guidelines and regulations. All experimental protocols were approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University. The informed consent was obtained from all subjects and/or their legal guardian(s).

CMR image acquisition and analysis

CMR scans were all performed on a 3.0T Siemens scanner (Skyra, Siemens Healthcare, Erlangen, Germany). Movie images were obtained using a balanced steady-state free precession (b-SSFP) sequence. Detailed parameters were as follows: field of view (FOV), 340–380 mm; repetition time (TR)/echo time (TE), 44.8/1.4 ms; matrix size, 208 × 188 mm; voxel size, 1.6 × 1.6 × 8.0 mm; bandwidth, 962 Hz/Px; flip angle (FA), 47°; slice thickness, 8 mm; inter-slice gap, 2 mm. LGE imaging was performed using a phase-sensitive inversion-recovery gradient-echo sequence 10–15 min after intravenous gadolinium-DTPA (0.2 mmol/kg, Magnevist, Bayer, Berlin, Germany). The inversion time was optimized to nullify the signal from normal myocardium. All CMR images were analyzed using dedicated commercial software (CVI42, version 5.13.1, Calgary, Canada). The software depicts endocardial and epicardial contours at end-diastole and end-systole, respectively, in short-axis views of the LV, which are then manually corrected by an experienced imaging physician and are used to obtain the LVEF, end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), cardiac output (CO), and left ventricular mass (LVM), all corrected using body surface area (BSA). Based on the previous reference²⁰, CMR feature tracking was applied to measure the overall myocardial strain values, including the global radial strain (GRS), global circumferential strain (GCS), and global longitudinal strain (GLS). GCS and GRS were calculated in the short axis of the heart, and the short axis were used for full coverage. GLS was performed in the vertical and horizontal long-axis.

Positive LGE was defined as LGE seen in the long-axis and short-axis planes in both phase-encoding directions. Patients were defined as LGE(+) or LGE(-) group according to this criterion. The mean signal intensity and standard deviation (SD) of the myocardium in the region of interest were measured, and regions of myocardium with delayed enhancement were defined as those in which the signal intensity was 5 SD above the distal normal myocardial signal. The overall LGE load was calculated as the sum of the LGE areas within each layer of the short-axis image multiplied by the thickness of the slice covering the entire left ventricle and expressed as a percentage of the left ventricular mass (Fig. S1). Compared with the previous article¹³, we have additionally included punctate LGE in the right ventricular insertion site as LGE-positive. The grouping of the LGE distribution patterns was determined individually by two independent radiologists, with a third experienced radiology director providing the determination when the results were in dispute. According to the LGE distribution characteristics, the grouping included 3 types. First, according to the myocardial level of LGE distribution, it was divided into: subepicardial LGE group, midmyocardial LGE group, and multilayer LGE group. The subepicardial LGE and midmyocardial LGE groups were defined as only subepicardial myocardium or only midmyocardium involvement, and the multilayer LGE group was defined as at least 2 or more layers of myocardial involvement. Second, according to the stage of LGE distribution, it was divided into: septal LGE group, free wall LGE group, and diffuse LGE group; septal LGE group was defined as only septal involvement or right ventricular insertion involvement, and the free wall LGE group was defined as myocardial involvement at all non-septal sites. Third, it was divided into 3 groups based on overall LGE load < 10%, 10–20%, and > 20%. The LGE(-) group was used as a control for all the above groups. The definition of subendocardial involvement was consistent with that of involvement in other regions, both referring to involvement limited to the respective part (subendocardium). The distribution of LGE and the corresponding images are shown in Fig. S2. The inter-observer and intra-observer agreement for LGE assessment are shown in Table S1.

Clinical data collection

The medical records of all patients were reviewed and relevant clinical information and drug use were extracted, including gender, age, BSA, left bundle branch block (LBBB), the New York Heart Association (NYHA) functional classification, history of smoking, hypertension, diabetes mellitus, and atrial fibrillation. The drugs used were also recorded, including beta-blockers, aldosterone receptor antagonists, angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blocker (ARB), and other drugs. The level of N-terminal pro-brain natriuretic peptide (NT-proBNP) in the blood was recorded.

Clinical outcomes and follow-up

Routine clinical follow-ups were scheduled at 1, 3, and 6 months after the CMR examination. Thereafter, patients were advised to return for evaluation every 6 to 12 months. During the follow-up period, blinded assessment and data extraction were performed for 24-hour Holter recordings, device interrogation reports of implanted cardiac electronic devices—including ICD or CRT—as well as outpatient, emergency, and rehospitalization records. All cardiac devices were implanted after completion of the CMR scan. The primary endpoint of follow-up was the occurrence of major adverse cardiovascular events (MACE), defined as all-cause mortality, ventricular tachyarrhythmias (including sustained ventricular tachycardia or ventricular fibrillation), and hospitalization for heart failure. Sustained ventricular tachycardia was characterized by a heart rate ≥ 100 beats per minute lasting ≥ 30 s or requiring therapeutic intervention for termination¹³. Heart failure was diagnosed according to the current European Society of Cardiology guidelines²¹.

Statistical analyses

Data were processed using SPSS (version 24.0, IBM Corporation, Chicago, IL, USA) and GraphPad Prism software (version 9.0.0, GraphPad Software, La Jolla, CA, USA). Continuous variables were tested for normality using the Kolmogorov-Smirnov test. Continuous variables that met the normal distribution were expressed as mean ± standard deviation, and comparisons between groups were made using the independent samples t-test. Continuous variables that did not conform to normal distribution was expressed as median (Q25, Q75), and comparisons between groups were made using the Mann-Whitney U test. Categorical variables were expressed as frequencies (percentages), and comparisons between groups were made using the χ2 test. A multivariable liner regression analysis adjusting for age, hypertension, and diabetes was performed to confirm that LGE associations with LV function are independent of these confounders. Kaplan-Meier survival analysis was employed to investigate the impact of different LGE distribution patterns on the long-term risk of MACE. A two-sided P value of < 0.05 was considered statistically significant.

Results

Patients characteristics

Of the 193 patients with DCM initially enrolled, a total of 15 patients with a history of ischemic heart disease (n = 6), viral myocarditis (n = 3), hypertrophic cardiomyopathy (n = 3), severe valvular disease (n = 2), or alcoholic cardiomyopathy (n = 1) were excluded, and 21 patients with incomplete follow-up data (n = 6) and poor-quality images (n = 15) were excluded (Fig. 1). Finally, 157 patients were included, with a mean age of 52.3 ± 16 years and 111 patients (70.7%) were male. A total of 127 patients (80.9%) had LGE, and the median LV LGE load was 15.5% (8.4%, 28.2%). The level of NT-proBNP and the proportion of hypertension were significantly higher in the LGE(+) group than in the LGE(-) group (p < 0.05). The patients in the LGE(+) group had a significantly worse LVEF, LV-EDVI, LV-ESVI, and LVMI than the patients in the LGE(-) group (p < 0.05) (Tables 1 and 2).

Fig. 1 — Flow chart. MACE, major adverse cardiovascular events.

Table 1.

Baseline characteristics of patients with DCM.

	Overall (n = 157)	LGE(-) (n = 30)	LGE(+) (n = 127)	P
Age, years	52.3 ± 16.1	47.2 ± 18.3	52.9 ± 16.0	0.116
Male, n (%)	111 (70.7)	19 (63.3)	92 (72.4)	0.374
BSA, (m²)	1.78 ± 0.21	1.81 ± 0.25	1.76 ± 0.26	0.676
Diabetes, n (%)	14 (8.9)	1 (3.3)	13 (10.2)	0.309
Hypertension, n (%)	51 (32.5)	7 (23.3)	44 (34.6)	0.003
Smoking, n (%)	48 (30.6)	6 (20.0)	42 (33.1)	0.191
Atrial fibrillation, n (%)	20 (12.7)	2 (6.7)	18 (14.2)	0.369
LBBB, n (%)	36 (22.9)	8 (26.7)	28 (22.0)	0.631
NYHA, n (%)
II	47 (29.9)	9 (30.0)	38 (29.9)	0.279
III	92 (58.6)	20 (66.7)	72 (56.7)	0.202
IV	18 (11.5)	1 (3.3)	17 (13.4)	0.420
Heart rate, bpm	70.2 ± 14.1	69.2 ± 14.6	71.1 ± 15.7	0.675
LGE load (%)	11.5 (4.4, 23.0)	0	15.5 (8.4, 28.2)
ARA, n (%)	126 (80.3)	22 (73.3)	104 (81.9)	0.312
ACEI/ARB, n (%)	104 (66.2)	22 (73.3)	82 (64.6)	0.399
beta-blockers, n (%)	140 (89.2)	27 (90.0)	113 (89.0)	1.000
NT-proBNP, ng/L	1548 (462, 3981)	1046 (147, 2802)	1686 (611, 4723)	0.048

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DCM, dilated cardiomyopathy; BSA, body surface area; LBBB, left bundle branch block; NYHA, New York Heart Association; LGE, late gadolinium enhancement; ARA, aldosterone receptor antagonists; ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; BNP, brain natriuretic peptide.

Table 2.

LGE and cardiac function and myocardial strain.

	Overall (n = 157)	LGE(-) (n = 30)	LGE(+) (n = 127)	P
LGE load, %	11.5 (4.4, 23.0)	-	15.5 (8.4, 28.2)	-
LVEF, %	27.0 ± 10.7	31.6 ± 13.0	25.9 ± 9.9	0.047
LV-EDV index, ml/m²	160 ± 62.4	132 ± 43.7	167.8 ± 69.6	0.004
LV-ESV index, ml/m²	121 ± 60.2	95 ± 47.9	128.5 ± 66.3	0.005
LVM, g	186 ± 50.5	171 ± 48.0	189.4 ± 51.1	0.054
LVM index, g/m²	106 ± 27.7	94.0 ± 29.6	109.6 ± 29.3	0.003
Left ventricular global strain
GRS, %	9.7 ± 5.2	12.8 ± 7.3	8.9 ± 4.3	0.009
GCS, %	-7.4 ± 3.3	-9.2 ± 4.4	-6.9 ± 2.9	0.011
GLS, %	-8.0 ± 3.8	-9.6 ± 4.8	-7.6 ± 3.4	0.043
LA-EDV index, ml/m²	31.90 ± 8.53	31.36 ± 7.62	34.20 ± 11.49	0.101
LA-ESV index, ml/m²	48.92 ± 11.07	48.09 ± 10.15	52.47 ± 13.98	0.051
RV-EDV index, ml/m²	110.2 ± 17.1	108.2 ± 19.8	110.7 ± 16.4	0.467
RV-ESV index, ml/m²	67.8 ± 12.9	64.7 ± 15.6	68.5 ± 12.1	0.146
RVEF, %	33.4 ± 9.7	35.7 ± 7.2	32.8 ± 10.1	0.150

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LGE, late gadolinium enhancement; LA, left atrium; LVEF, left ventricular ejection fraction; RVEF, right ventricular ejection fraction; EDV, end-diastolic volume; ESV, end-systolic volume; LVM, left ventricular mass; GRS, global radial strain; GCS, global circumferential strain; GLS, global longitudinal strain.

The association between LGE and LV function

Considering the potential selection bias between LGE-positive and LGE-negative groups, and in line with previous literature reports, a multivariable regression analysis adjusting for age, hypertension, and diabetes was performed to confirm that LGE associations with LV function are independent of these confounders. The results demonstrated that the presence of LGE remained an independent correlate of LV function (Table 3).

Table 3.

Multivariable linear regression analysis.

Variables	LVEF		GLS		GCS		GRS
Variables	β (95%CI)	P	β (95%CI)	P	β (95%CI)	P	β (95%CI)	P
Age	0.06 (-0.05 ~ 0.17)	0.264	0.01 (-0.03 ~ 0.05)	0.662	0.03 (0.01 ~ 0.06)	0.046	-0.04 (-0.09 ~ 0.01)	0.101
Diabetes	0.22 (-5.80 ~ 6.24)	0.943	0.85 (-1.26 ~ 2.97)	0.430	0.81 (-1.01 ~ 2.63)	0.386	-0.10 (-3.01 ~ 2.81)	0.945
Hypertension	-0.44 (-4.11 ~ 3.22)	0.813	-0.19 (-1.48 ~ 1.09)	0.768	0.41 (-0.70 ~ 1.52)	0.471	-0.42 (-2.19 ~ 1.35)	0.643
LGE (+)	-6.22 (-10.47 ~ -1.97)	0.005	2.25 (0.76 ~ 3.75)	0.004	2.31 (1.03 ~ 3.58)	< 0.001	-4.10 (-6.10 ~ -2.09)	< 0.001

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LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; GRS, global radial strain; GCS, global circumferential strain; GLS, global longitudinal strain.

LGE distributions in patients with DCM

In a cohort of 127 (80.9%) DCM patients with LGE(+), LGE occurred mostly in the basal and intermediate segments of the ventricles, with a lower percentage of apical segments involved (96.9%, 90.6%, 36.2%, P < 0.001). 103 patients (81.1%) had concomitant LGE involvement in septal segments, which was significantly higher than that in non-septal segments (81.1% vs. 41.8%, with P = 0.005). Grouped according to the distribution of subepicardial, midlayer, and subendocardial myocardium, the proportion of midlayer and subepicardial myocardium with LGE involvement was significantly higher than that of subendocardial myocardium in this cohort (60.6%, 50.4% vs. 10.2%, P < 0.001). According to the AHA 17-segment model, the basal and intermediate segments had the most severe septal involvement, with 78 patients (61.4%) with positive LGE in the anterior septum, 82 patients (64.6%) with positive LGE in the posterior septum, 65 patients (51.2%) with positive LGE in the anterior septum, and 71 (55.9%) with positive LGE in the posterior septum in the intermediate segments. The inferior wall, lateral wall and anterior wall were involved to a lesser extent than the septal myocardium (Table S2, Fig. 2).

Fig. 2 — Distribution characteristics of LGE in DCM. (A) Division of myocardium according to the AHA 17-segment model, LGE in DCM patients mostly occurred in the basal and mid segments, with a lower proportion in the apical segment. Within the same level, LGE occurred more often in the septal segment. (B) Division of myocardium according to subepicardial, midlayer, and subendocardial, the proportion of midlayer and subepicardial myocardium involvement was significantly higher than the proportion of subendocardial myocardium involvement.

Different LGE distributions and left ventricular function

LVEF, GRS, GCS and GLS were lower in the midmyocardial LGE group and multilayer LGE group than in the LGE(-) group (p < 0.05), and there was no significant difference in the subepicardial LGE group. LVEDVI was higher in the midmyocardial LGE group and multilayer LGE group than in the LGE(-) group (p < 0.05), and there was no statistically significant difference in the subepicardial LGE. Besides, compared with the subepicardial LGE group, the midmyocardial LGE group and multilayer LGE group had a poorer left ventricular function (Table S3, Figs. 3 and 4).

Fig. 3 — The myocardial level of LGE distribution and left ventricular function. (A) the myocardial level of LGE distribution and LVEF. (B) the myocardial level of LGE distribution and LVEDVI. LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; LVEDVI, left ventricular end-diastolic volume index. * p < 0.05, ** p < 0.001, *** p < 0.0001, ns p > 0.05.

Fig. 4 — The myocardial level of LGE distribution and global strain. (A) the myocardial level of LGE distribution and GRS. (B) the myocardial level of LGE distribution and GCS. (C) the myocardial level of LGE distribution and GLS. LGE, late gadolinium enhancement; GRS, global radial strain; GCS, global circumferential strain; GLS, global longitudinal strain. * p < 0.05, ** p < 0.001, *** p < 0.0001, ns p > 0.05.

Compared with the LGE(-) group, there was no statistically significant difference in the LVEF in the septal LGE group, free wall LGE group and diffuse LGE group. LVEDVI was higher in the septal LGE group than in the LGE(-) group (p < 0.05), whereas there was no statistical difference in the free wall LGE group and diffuse LGE group. Compared with the LGE(-) group, GRS and GCS were significantly lower in the septal LGE group, free wall LGE group and diffuse LGE group (p < 0.05). Regarding GLS, only the septal LGE group was significantly different from the LGE(-) group (p < 0.05) (Table S4, Figs. 5 and 6).

Fig. 5 — The stage of LGE distribution and left ventricular function. (A) the stage of LGE distribution and LVEF. (B) the stage of LGE distribution and LVEDVI. LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; LVEDVI, left ventricular end-diastolic volume index. ** p < 0.001, ns p > 0.05.

Fig. 6 — The stage of LGE distribution and global strain. (A) the stage of LGE distribution and GRS. (B) the stage of LGE distribution and GCS. (C) the stage of LGE distribution and GLS. LGE, late gadolinium enhancement; GRS, global radial strain; GCS, global circumferential strain; GLS, global longitudinal strain. * p < 0.05, ** p < 0.001, ns p > 0.05.

Compared with the LGE(-) group, there was no statistically significant difference in the LVEF in the different LGE load groups. LVEDVI was higher in the LGE load < 10% group than in the LGE(-) group (p < 0.05), whereas there was no statistical difference in the LGE load 10–20% group and LGE load > 20% group. There was a tendency for the global strain to be reduced in the groups with different degrees of LGE load compared with the LGE(-) group, but the difference was not statistically significant (Table S5, Figs. 7 and 8).

Fig. 7 — LGE load and left ventricular function. (A) LGE load and LVEF. (B) LGE load and LVEDVI. LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; LVEDVI, left ventricular end-diastolic volume index. * p < 0.05, ns p > 0.05.

Fig. 8 — LGE load and global strain. (A) LGE load and GRS. (B) LGE load and GCS. (C) LGE load and GLS. LGE, late gadolinium enhancement; GRS, global radial strain; GCS, global circumferential strain; GLS, global longitudinal strain. ns p > 0.05.

The impact of different LGE distribution patterns on the risk of MACE

Based on the distribution pattern of LGE, patients were categorized into three groups: subepicardial LGE group, midmyocardial LGE group, and multilayer LGE group. A total of 10 patients were lost to follow-up. During a median follow-up period of 73 (68, 78) months, a total of 103 patients (70.0%) experienced MACE. These events included 43 cases of all-cause mortality (29.3%), 28 cases of ventricular arrhythmias (19.0%), and 32 cases of heart failure rehospitalization (21.8%). Kaplan-Meier survival analysis revealed that compared to the LGE-negative group, patients with subepicardial LGE did not demonstrate a statistically significant difference in long-term risk of MACE (Log-rank p = 0.082) (Fig. 9A). In contrast, both the midmyocardial LGE group and the multilayer LGE group exhibited significantly elevated risks of long-term MACE (Log-rank p < 0.05) (Fig. 9B,C).

Fig. 9 — Kaplan-Meier survival analysis. (A) Kaplan-Meier survival analysis between LGE (-) and subepicardial LGE. (B) Kaplan-Meier survival analysis between LGE (-) and midmyocardial LGE. (C) Kaplan-Meier survival analysis between LGE (-) and multilayer LGE. LGE, late gadolinium enhancement.

Discussion

The aim of our study was to observe the characteristics of LGE distribution and its relationship with LV function in patients with DCM. The main findings were as follows: First, in patients with DCM, LGE mainly involved the septal myocardium in basal and intermediate segments, and the midmyocardium and subepicardial myocardium were predominantly involved, while the apical and subendocardial myocardium were less frequently involved. Second, LGE was associated with worse LV systolic function and global strain. Third, further analysis of subgroups based on the distribution characteristics of LGE showed that the patients with LGE involvement in the midmyocardium generally had worse LVEF, LVEDVI, and global strain. Forth, there was no significant association between the LGE load and LVEF, LVEDVI, and global strain. Fifth, both the midmyocardial LGE group and the multilayer LGE group exhibited significantly elevated risks of long-term MACE.

The characteristics of LGE distribution

In a previous prospective study, 116 (63%) patients had LGE²². The higher incidence of LGE in our study may be attributed to the fact that all these patients were DCM patients with ICD indications, and thus had more severe conditions. Previous studies have shown that septal myocardial midmyocardial fibrosis can be one of the imaging features of CMR to differentiate DCM from ischemic heart disease and other types of cardiomyopathy^23,24. In an analysis of 874 patients with nonischemic dilated cardiomyopathy, Brian P. Halliday et al.¹² found that of the 300 LGE-positive cases, 258 (86%) involved the septum, and 253 (84.3%) involved the midmyocardium. Similar to these findings, our study found that LGE in patients with DCM mostly involves the septum and midmyocardium. There is significant heterogeneity in the diagnosis and treatment of DCM¹⁴, and our study may provide some insights into the CMR-LGE characteristics of DCM from different populations.

Different LGE distributions and left ventricular function

The presence of myocardial fibrosis is significantly associated with a worse prognosis. Similarly, in our study patients in the LGE(+) group had worse left ventricular function compared to patients in the LGE(-) group. Theoretically, the higher the degree of myocardial fibrosis, the more pronounced the impaired myocardial function may be. However, our study found that the degree of myocardial fibrosis and the degree of deterioration of LV function were not proportional. By comparing the LV function of patients with different degrees of LGE load, we found that LVEF, LVEDVI, and global strain did not change significantly with increasing LGE load, suggesting that the main factor affecting LV function may not be the degree of myocardial fibrosis. Of note, in our study, patients with midmyocardial involvement (both the midmyocardial LGE group and the multilayer LGE group) had worse LVEF and LVEDVI not only compared with the LGE(-) group but also compared with patients in the subepicardial LGE group. These results suggest that the midlayer myocardium may contribute more to LV function compared with the subepicardial myocardium. In addition, subgroup analysis based on LGE-involved segments showed that LVEDVI was higher in septal involvement than in the LGE (-) group, whereas it was not statistically different in the other two groups. This result suggests that the presence of septal myocardial scarring may be associated with more severe myocardial damage. Similarly, Ansari et al.²⁵ found that among patients receiving cardiac contractility modulation (CCM) therapy, a significant improvement in LVEF was observed when the leads were placed in septal myocardial segments with a CMR-LGE burden of less than 25%. In a previous study, we also found that the pattern of LGE is important, and the ring-like LGE was an independent marker of elevated clinical ventricular tachyarrhythmia risk¹³. Previous studies have found that LV global strain are more sensitive than LVEF to the contractility of myocardial fibers to the heart and the degree of myocardial deformation^26,27. Both necrosis and atrophy are modes of cellular injury. Cellular injury occurs in various tissues and organs of the body and it is a physiologic or pathologic process that is important for maintaining cellular morphology and function²⁸. Cardiomyocytes are terminally differentiated cells with very limited regenerative capacity. Various injuries can lead to irreversible damage to cardiomyocytes, resulting in worsening cardiac dysfunction²⁹. Importantly, these regulated forms of cell death are a major feature of the pathogenesis of dilated cardiomyopathy³⁰. Previous studies have shown that cellular injury is strongly associated with cardiac dysfunction and that LGE is an important indicator of myocardial necrosis^7,31. Ito H et al.³² found that global strain was significantly lower in patients with heart failure with preserved ejection fraction compared with healthy controls. Zerhouni et al.³³ suggested the application of CMR myocardial strain techniques to compensate for the lack of information on ejection fraction. In the subgroup analysis with LGE involvement in different segments, LVEF and LVEDVI did not reflect the differences between the septal LGE group, the free wall LGE group, and the LGE-negative group well, whereas GRS and GCS reflected well the differences between the different LGE subgroups and the LGE(-) group. Global strain as a more sensitive marker may partially explain the findings of our study. In addition, patients with LGE had a higher prevalence of hypertension, diabetes, and a tendency to be older, which may also partially explain the differences in LV systolic function. However, after adjusting for these variables, LGE remained independently associated with LV function, suggesting that LGE assessment provides incremental value beyond conventional parameters. DCM is a progressive disease, and in early stages, patients may be accompanied by only impaired diastolic function of the left heart without a severe systolic function decline^34–38, and given the high sensitivity and reliability of CMR, it may assist in the early diagnosis and clinical management of patients with DCM. The characteristics of LGE may indicate lower absolute values of strain and a risk of worse prognosis. As demonstrated in our results section, both midmyocardial LGE patterns and multilayer LGE distributions exhibited more significant impacts on long-term patient outcomes compared to subepicardial LGE. However, we must acknowledge the limitation of our sample size. More robust evidence would require future large-scale studies to further validate these findings. In conclusion, our study suggests that the location of LGE distribution may be a more important influence on LV function in patients with DCM. Additional attention to the location of LGE distribution may be needed in clinical practice.

However, there are some limitations of this study that need to be elaborated. First, this study was a single-center retrospective study with a relatively small sample size, and only the LGE(-) group was used as a control, a healthy population was not established for comparison. Therefore, there may be limitations such as insufficient sample representativeness, limited external validity of research results, and risks to data quality and bias. A prospective and more optimized study design is still anticipated. Second, all patients were admitted for the planned implantation of ICD. This is a very important bias that would limit external applicability. Third, further subgroup analysis of patients with only anterior, inferior, or lateral wall involvement was not possible due to sample size issues. Forth, diffuse interstitial fibrosis in non-LGE regions was not assessed in this study, and the effects of myocardial dense fibrosis and diffuse interstitial fibrosis on cardiac function and myocardial strain should be considered in future studies by combining LGE and T1 mapping (including extracellular volume) techniques. Fifth, genetic factors may play an important role in DCM, however, our study lacked genetic studies. In particular, the relationship between genetic information and LGE in DCM may be a very interesting topic. Sixth, the unavailability of appropriate long-axis views for some patients makes segmentation in LAX potentially inaccurate. Finally, ultrastructural abnormalities in necrotic and/or atrophic cardiomyocytes are an important pathophysiologic mechanism of LV dysfunction. Unfortunately no image technique can give information about. Therefore, the specific mechanism of action may require more studies to elucidate.

Conclusions

Dilated cardiomyopathy LGE most commonly involves the septal myocardium of the basal and intermediate segments of the left ventricle, and predominantly involves the middle layer and subepicardium. LGE involvement of the LV midmyocardium is associated with poorer LV function and higher risks of long-term MACE.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1^{(2.2MB, docx)}

Author contributions

BZ, SF, ZL, MD, PL, and WC drafted the manuscript, collected the data and analysed the data. WC and ZL analyzed the magnetic resonance images. WC, and YY designed the study. BZ, YY, and WC revised the manuscript. All authors read and approved the final manuscript.

Funding

This work was partly supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (Grant No.2024ZD0524000), and Jiangsu Association for Science & Technology Youth Science & Technology Talents Lifting Project (JSTJ-2023-XH011).

Data availability

The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

All methods were performed in accordance with the relevant guidelines and regulations. All experimental protocols were approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University. The informed consent was obtained from all subjects and/or their legal guardian(s).

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Baixiang Zhang, Zhongxiao Liu and Sidra Farooq contributed equally to this work.

Contributor Information

Yu Yang, Email: xzyangyu@163.com.

Wensu Chen, Email: chen.wensu@163.com.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1^{(2.2MB, docx)}

Data Availability Statement

The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

[CR1] 1.Arbelo, E. et al. 2023 ESC guidelines for the management of cardiomyopathies. Eur. Heart J.44 (37), 3503–3626. 10.1093/eurheartj/ehad194 (2023). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Li, J. et al. Predictive value for mortality of left ventricular wall thickness in dilated cardiomyopathy. ESC Heart Fail.10 (6), 3538–3545. 10.1002/ehf2.14534 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR3] 3.Li, L., Zhao, Q. & Kong, W. Extracellular matrix remodeling and cardiac fibrosis. Matrix Biol.68–69, 490–506. 10.1016/j.matbio.2018.01.013 (2018). [DOI] [PubMed] [Google Scholar]

[CR4] 4.Mayala, H. A., Bakari, K. H. & Zhaohui, W. The role of cardiac magnetic resonance (CMR) in the diagnosis of cardiomyopathy: A systematic review. Malawi Med. J.31 (3), 241–245. 10.4314/mmj.v31i3.14 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Chen, L. et al. Prognostic value of strain by tissue tracking cardiac magnetic resonance in myocardial infarction with nonobstructive coronary arteries. J. Am. Heart Assoc.14 (8), e039395. 10.1161/JAHA.124.039395 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Chen, L. et al. Establishment of a synthetic ECV model and its prognostic value in diabetes patients with acute myocardial infarction. Front. Endocrinol. (Lausanne). 16, 1534236. 10.3389/fendo.2025.1534236 (2025). Published 2025 Jun 25. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Bakhshi, H. et al. Association between proteomic biomarkers and myocardial fibrosis measured by MRI: the multi-ethnic study of atherosclerosis. EBioMedicine90, 104490. 10.1016/j.ebiom.2023.104490 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Scholtz, L., Sarkin, A. & Lockhat, Z. Current clinical applications of cardiovascular magnetic resonance imaging. Cardiovasc. J. Afr.25 (4), 185–190. 10.5830/CVJA-2014-021 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Reiter, C., Puseljic, M., Fuchsjäger, M. & Schmid, J. Estimating synthetic hematocrit and extracellular volume from native blood pool T1 times at 3 Tesla CMR: derivation of a conversion equation, accuracy and comparison with published formulas. Eur. J. Radiol.178, 111659. 10.1016/j.ejrad.2024.111659 (2024). [DOI] [PubMed] [Google Scholar]

[CR10] 10.Castrichini, M. et al. Magnetic resonance imaging characterization and clinical outcomes of dilated and arrhythmogenic left ventricular cardiomyopathies. J. Am. Coll. Cardiol.83 (19), 1841–1851. 10.1016/j.jacc.2024.02.041 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Zhou, D. et al. A novel cardiac magnetic resonance-based personalized risk stratification model in dilated cardiomyopathy: a prospective study. Eur. Radiol.34 (6), 4053–4064. 10.1007/s00330-023-10415-7 (2024). [DOI] [PubMed] [Google Scholar]

[CR12] 12.Halliday, B. P. et al. Outcome in dilated cardiomyopathy related to the Extent, Location, and pattern of late gadolinium enhancement. JACC Cardiovasc. Imaging. 12 (8 Pt 2), 1645–1655. 10.1016/j.jcmg.2018.07.015 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Chen, W. et al. Ring-like late gadolinium enhancement for predicting ventricular tachyarrhythmias in non-ischaemic dilated cardiomyopathy. Eur. Heart J. Cardiovasc. Imaging. 22 (10), 1130–1138. 10.1093/ehjci/jeab117 (2021). [DOI] [PubMed] [Google Scholar]

[CR14] 14.Becker, M. A. J. et al. The prognostic value of late Gadolinium-Enhanced cardiac magnetic resonance imaging in nonischemic dilated cardiomyopathy: A review and Meta-Analysis. JACC Cardiovasc. Imaging. 11 (9), 1274–1284. 10.1016/j.jcmg.2018.03.006 (2018). [DOI] [PubMed] [Google Scholar]

[CR15] 15.Li, X. et al. A novel risk stratification score for sudden cardiac death prediction in Middle-Aged, nonischemic dilated cardiomyopathy patients: the ESTIMATED score. Can. J. Cardiol.36 (7), 1121–1129. 10.1016/j.cjca.2019.11.009 (2020). [DOI] [PubMed] [Google Scholar]

[CR16] 16.Shin, D. G. et al. Pattern of late gadolinium enhancement predicts arrhythmic events in patients with non-ischemic cardiomyopathy. Int. J. Cardiol.222, 9–15. 10.1016/j.ijcard.2016.07.122 (2016). [DOI] [PubMed] [Google Scholar]

[CR17] 17.Mikami, Y. et al. Objective criteria for septal fibrosis in non-ischemic dilated cardiomyopathy: validation for the prediction of future cardiovascular events. J. Cardiovasc. Magn. Reson.18 (1), 82. 10.1186/s12968-016-0300-z (2016). Published 2016 Nov 14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Weintraub, R. G., Semsarian, C. & Macdonald, P. Dilated cardiomyopathy. Lancet390 (10092), 400–414. 10.1016/S0140-6736(16)31713-5 (2017). [DOI] [PubMed] [Google Scholar]

[CR19] 19.Vera, A. et al. Electrocardiogram and CMR to differentiate tachycardia-induced cardiomyopathy from dilated cardiomyopathy in patients admitted for heart failure. Heart Vessels. 37 (11), 1850–1858. 10.1007/s00380-022-02102-2 (2022). [DOI] [PubMed] [Google Scholar]

[CR20] 20.Korosoglou, G. et al. Strain-encoded magnetic resonance: a method for the assessment of myocardial deformation. ESC Heart Fail.6 (4), 584–602. 10.1002/ehf2.12442 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.McDonagh, T. A. et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur. Heart J.42 (48), 4901. 10.1093/eurheartj/ehab670.] (2021). [DOI] [PubMed]

[CR22] 22.Barison, A. et al. The extent and location of late gadolinium enhancement predict defibrillator shock and cardiac mortality in patients with non-ischaemic dilated cardiomyopathy. Int. J. Cardiol.307, 180–186. 10.1016/j.ijcard.2020.02.028 (2020). [DOI] [PubMed] [Google Scholar]

[CR23] 23.Patel, A. R. & Kramer, C. M. Role of cardiac magnetic resonance in the diagnosis and prognosis of nonischemic cardiomyopathy. JACC Cardiovasc. Imaging10 (10 Pt A), 1180–1193. 10.1016/j.jcmg.2017.08.005 (2017). [DOI] [PMC free article] [PubMed]

[CR24] 24.Mitropoulou, P. et al. Multi-Modality imaging in dilated cardiomyopathy: with a focus on the role of cardiac magnetic resonance. Front. Cardiovasc. Med.7, 97. 10.3389/fcvm.2020.00097 (2020). Published 2020 Jul 2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Ansari, U. et al. Septal myocardial Scar burden predicts the response to cardiac contractility modulation in patients with heart failure. Sci. Rep.12 (1), 20504. 10.1038/s41598-022-24461-6 (2022). Published 2022 Nov 28. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR26] 26.Barison, A. et al. Cardiovascular magnetic resonance for the diagnosis and management of heart failure with preserved ejection fraction. Heart Fail. Rev.27 (1), 191–205. 10.1007/s10741-020-09998-w (2022). [DOI] [PubMed] [Google Scholar]

[CR27] 27.He, J. et al. Heart failure with preserved ejection fraction in hypertension patients: A myocardial MR strain study. J. Magn. Reson. Imaging. 53 (2), 527–539. 10.1002/jmri.27313 (2021). [DOI] [PubMed] [Google Scholar]

[CR28] 28.Liu, D., Qin, H., Gao, Y., Sun, M. & Wang, M. Cardiovascular disease: Mitochondrial dynamics and mitophagy crosstalk mechanisms with novel programmed cell death and macrophage polarisation. Pharmacol. Res.206 107258. (2024). [DOI] [PubMed]

[CR29] 29.Li, P. et al. Molecular mechanism and therapeutic targeting of necrosis, apoptosis, pyroptosis, and autophagy in cardiovascular disease. Chin. Med. J. (Engl). 134 (22), 2647–2655. 10.1097/CM9.0000000000001772 (2021). Published 2021 Oct 4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Sheng, S. Y., Li, J. M., Hu, X. Y. & Wang, Y. Regulated cell death pathways in cardiomyopathy. Acta Pharmacol. Sin. 44 (8), 1521–1535. 10.1038/s41401-023-01068-9 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Long, H. et al. Macrophages and fibrosis: how resident and infiltrating mononuclear phagocytes account for organ injury, regeneration or atrophy. Front. Immunol.14, 1194988. 10.3389/fimmu.2023.1194988 (2023). [DOI] [PMC free article] [PubMed]

[CR32] 32.Ito, H. et al. Cardiovascular magnetic resonance feature tracking for characterization of patients with heart failure with preserved ejection fraction: correlation of global longitudinal strain with invasive diastolic functional indices. J. Cardiovasc. Magn. Reson.22 (1), 42. 10.1186/s12968-020-00636-w (2020). Published 2020 Jun 4. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

CMR-LGE imaging features of dilated cardiomyopathy and relationship with left ventricular function

Baixiang Zhang

Zhongxiao Liu

Sidra Farooq

Mingchang Du

Peng Lu

Yu Yang

Wensu Chen

Abstract

Supplementary Information

Introduction

Materials and methods

Study population

CMR image acquisition and analysis

Clinical data collection

Clinical outcomes and follow-up

Statistical analyses

Results

Patients characteristics

Fig. 1.

Table 1.

Table 2.

The association between LGE and LV function

Table 3.

LGE distributions in patients with DCM

Fig. 2.

Different LGE distributions and left ventricular function

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

The impact of different LGE distribution patterns on the risk of MACE

Fig. 9.

Discussion

The characteristics of LGE distribution

Different LGE distributions and left ventricular function

Conclusions

Supplementary Information

Author contributions

Funding

Data availability

Declarations

Competing interests

Ethics approval and consent to participate

Footnotes

Contributor Information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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