*3.4. Univariate and Multivariate Cox Analysis*

Among the evaluated parameters, in univariate analysis and multivariate Cox regression analysis, only four remained independent predictors for MACEs, namely LGE+ (HR = 1.77, 95%CI (2.79 to 12.51), *p* < 0.0001), reduced LAS (HR = 1.32, 95%CI (1.54 to 9.14), *p* < 0.001) and increased LVSI (HR = 1.17, 95%CI (1.45 to 7.19), *p* < 0.001) and LGE mass (HR = 1.43, 95%CI (1.01–6.12), *p* < 0.001) (Table 3).

**Figure 3.** Kaplan–Meier curves for event-free survival for (**A**) LGE+, (**B**) LAS, (**C**) LVSI. Abbreviations: LAS, long axis strain; LGE, left ventricular late gadolinium enhancement; LVSI, left ventricular sphericity index.



**Table3.**UnivariableandmultivariableCoxanalysistestingbetweenstudiedparametersandMACEs.

LVESV, left ventricular end-systolic volume; LVM, left ventricular mass; LVSI, left ventricular spherical index; *n*, number of patients; NT-proBNP, N-terminal pro-Brain Natriuretic Peptide;

RVEDV, right ventricular end-diastolic

 volume; RVEF, right ventricular ejection fraction; RVESV, right ventricular end-systolic volume; TAPSE, tricuspid annular plane systolic excursion.

## *3.5. Incremental Predictive Value of cMRI-Based LV Geometry and Strain for Outcomes*

Sequential Cox proportional-hazards models yielded significantly increased predictive power the combined outcome of MACEs when both LVSI and LAS were used in addition to LVEF and LGE+ (Chi-square = 24.52, *p* < 0.0001) (Figure 4). However, LAS did not provide incremental predictive power when used alone, in addition to LVEF and LGE+.

**Figure 4.** Incremental predictive value of LVSI and LAS added to LVEF and to LGE for outcome in patients with NIDCM. Abbreviations: LAS, left ventricular long axis strain; LGE, left ventricular late gadolinium enhancement; LVSI, left ventricular sphericity index; NIDCM, nonischemic dilated cardiomyopathy.

#### *3.6. Risk Stratification Scoring System*

The embedment of LVSI and LAS to LVEF and LGE allowed us to create a risk stratification score, using the following criteria: LVEF < 30%, LGE+, LVSI > 0.48 and LAS < −7.8%. These cut-off values were best correlated with outcome in our studied group. We created a scoring system and Kaplan–Meier curves based on the four parameters (Chi-square = 56.53, *p* < 0.0001) (Figure 5). We observed that patients with 3–4 points had significantly higher rates of MACEs during the follow-up period than others.

**Figure 5.** Kaplan-Meier curves for the risk stratification score. The scoring system ranges from 0 to 4 points: 1 point for each of the following LVEF < 30%, LGE+, LAS > −7.8% and LVSI > 0.48. Abbreviations: LAS, left ventricular long axis strain; LGE, left ventricular late gadolinium enhancement; LVSI, left ventricular sphericity index.

#### **4. Discussion**

This prospective study is the first to evaluate the association between cMRI-based LV geometry and strain and outcome, in a significant, well-diagnosed NIDCM cohort. LAS and LVSI were independent predictors of MACEs in patients with NIDCM and myocardial replacement fibrosis. These findings were independent of LVEF and other established prognostic factors in a multivariable analysis. We also demonstrated that the addition of both LAS and LVSI to LVEF and LGE was superior for the prediction of MACEs over those based only on LVEF and LGE. The incidence of MACEs was higher in those with myocardial replacement fibrosis and altered LV geometry and strain, therefore representing a group who may require more aggressive therapy and rigorous follow-up.

NIDCM is typically associated with LV mid-wall replacement fibrosis, which worsens its prognosis [21,22]. Furthermore, Lehrke et al. have shown that NIDCM can be confirmed by cMRI-determined LV midwall fibrosis [23]. In our study, the incidence of LGE in NIDCM was similar with other studies [8,24] and, in addition, we demonstrated that LGE was an independent predictor of MACEs. Similarly, in patients with NIDCM, Gulati et al. showed that the presence of mid-wall LGE was an independent predictor for outcome and improved risk stratification beyond LVEF [9]. Furthermore, several studies have confirmed that the presence LGE is independently associated with all-cause mortality, SCD and aborted SCD [25,26].

In our study, we confirmed the role of LVSI in predicting MACEs with a cut-off value of >0.43 (*p* < 0.001), similar with other published data. In patients with NIDCM, LVSI was initially evaluated in 2- and 3-dimensional echocardiography-based studies, which demonstrated that it was an independent predictor of MACEs, having a significant long-term prognostic impact [15,27]. Furthermore, in cMRI-based studies, it has been confirmed that LVSI is inversely correlated with LVEF in patients with NIDCM [28,29], while in a multi-ethnic study conducted on healthy subjects, lowest LVSI was an independent predictor for CHD, CVD and HF at 10-year follow-up and the highest LVSI was correlated with increased incidence of HF and atrial fibrillation [30]. Moreover, in a small study, LVSI was an independent predictor for correct ICD therapy [31]. Thereby, LVSI could become an important prediction parameter in this category of patients.

Furthermore, we demonstrated that LAS, a myocardial strain parameter, was an independent predictor for outcome in patients with NIDCM. cMRI-based myocardial strain has proved its utility in early diagnosing and predicting various cardiac diseases. In patients with myocardial infarction, Gjesdal et al. showed that LAS was progressively reduced in larger mitral insufficiency and was associated with the infarction mass [32], while Schuster et al. identified that the assessment of LAS provided incremental prognostic value for cardiovascular risk [33]. In a multi-ethnic study, LAS was also associated with LVEF and MACEs [34]. In a study conducted on patients with aortic stenosis, our research team identified that LAS was an independent predictor of outcome and provided incremental value beyond LVEF and LGE [35]. Lastly, in patients with NIDCM, a single study identified that LAS was an independent predictor for SCD, aborted SCD, heart transplantation and HF hospitalization [36].

The role of LVEF and LGE as independent predictors of MACEs in patients with NIDCM has been confirmed by recently published data. To our knowledge, only two studies have approached our goals, namely Kano et al. identified that the addition of LVSI to LGE significantly increased prognosis of MACEs [37], while Riffel et al. demonstrated that the addition of LAS to LGE provides incremental value for outcome prediction in patients with NIDCM [36]. Our investigation is the first to demonstrate that the combined addition of both LVSI and LAS to LVEF and LGE significantly increased the predictive power of outcome, thus conferring an incremental predictive value.

Based on these four parameters, we were able to create a risk stratification scoring system. Hitherto, a single study created a similar scoring system based on LAS, LVEF and LGE+ which provided significant predictive value [36]. We demonstrated that the addition of one point for each of these parameters (LVEF < 30%, LGE+, LAS > −7.8% and LVSI > 0.48) is highly correlated with MACEs. In patients without these risk features (score = 0), no MACEs were observed during follow-up. Thereby, we propose a combined risk score consisting of LVEF, LGE, LVSI and LAS in order to improved risk stratification.

Study limitations: Firstly, we conducted a single centre study. Secondly, we were unable to acquire T1 mapping sequences, and therefore extracellular volume and diffuse myocardial fibrosis could not be quantified. Additionally, the follow-up was, relatively speaking, not very long.
