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Prognostic Value of Right Ventricular 3D Trabecular Complexity in Arrhythmogenic right ventricular cardiomyopathy
Jin-Yu Zheng1, Bing-Hua chen1, Chong-Wen Wu1, Rui Wu1, Dong-Aolei An1, Ruo-Yang Shi1, Jingyu Xie2, Shan-shan Jiang3, Lian-Ming Wu1, and Lei Zhao4
1RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China, 2Philips Healthcare, shanghai, China, 3Philips Healthcare, Xi'an, Shaanxi, China, 4Beijing Anzhen Hospital, Capital Medical University, Beijing, China

Synopsis

Keywords: Myocardium, Cardiovascular

Motivation: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. The prognostic value of trabecular disorder assessed by three-dimensional (3D) fractal dimension (FD) measurement is unclear.

Goal(s): To investigate the prognostic value of 3D right ventricular trabecular complexity of ARVC.

Approach: Using cine images, trabecular complexity was measured with 3D fractal analysis to calculate 3D-FD in ARVC patients retrospectively. Cox regression analyses and Kaplan-Meier survival analysis were performed to identify the prognostic value of 3D-FD.

Results: RV 3D-FD was a significant risk predictor for MACE in ARVC and provided incremental prognostic value to conventional predictors.

Impact: Based on the results, we suggested 3D RV trabecular complexity, derived from non-invasive imaging examination, as a new biomarker for early clinical therapy in medication and ICD implantation in order to moderate the onset of adverse endpoints in ARVC patients.

Background

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. Two-dimensional (2D) fractal dimension (FD) analysis was conventionally utilized to evaluate trabecular disarray. While the prognostic value of trabecular disorder assessed by three-dimensional (3D) fractal dimension (FD) measurement is unclear.

Purpose

To investigate the prognostic value of right ventricular trabecular complexity using 3D fractal dimension analysis based on CMR cine images in participants with ARVC.

Materials and Methods

In this retrospective research, participants with ARVC who underwent CMR examination between May 2013 and May 2022 from2 sites were included. Using cine images, trabecular complexity was measured with three-dimensional (3D) fractal analysis to calculate 3D fractal dimension (FD). Major adverse cardiac events (MACE) were defined as a combination of aborted cardiac arrest, sudden cardiac arrest, and appropriate implantable cardioverter-defibrillator (ICD) intervention. Cox regression analyses and Kaplan-Meier survival analysis were performed to identify the prognostic value of 3D-FD.

Results

A total of 85 ARVC patients (median age: 49 years, interquartile range: 31–58 years; 52 male) were included, with 26 MACE recorded during the 60 month follow-up (interquartile range: 48- 67 months) after the CMR examination. RV 3D-FD differed between ARVC patients with and without MACE (2.67, interquartile range:2.51~2.81 vs 2.52, interquartile range:2.40~2.67, P<0.01). In multivariable Cox analysis, RV 3D-FD was suggested as a significant risk predictor for MACE in ARVC patients (hazard ratio, 1.02; 95% confidence interval:1.01, 1.04; P=0.01). In addition, prognostic model fitness was improved after adding 3D-FD to RV global longitudinal strain, LV involvement, and 5-year risk score separately (all P<0.05).

Conclusion

The myocardial trabecular complexity assessed through 3D fractal dimension analysis was found to be associated with MACE and provided incremental prognostic value beyond conventional ARVC risk predictors.

Acknowledgements

No acknowledgement found.

References

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Figures

Figure 1:Schematic representation of the specific approach to the development of 3D fractal dimension and 3D model visualization. Standard box-counting method was used for 3D FD value and surface rendering was applied for model visualization

Figure 3:Kaplan-Meier curve for MACE in ARVC patients according to the cut-off value (2.559) for RV FD. Patients with RVFD of ≥2.559 tend to display a higher risk of MACE

Figure 4:Comparisons for 3 nested models and models with RVFD addition. After adding RVFD to RV GLS(A), LV involvement(B), and 5-year risk score(C) separately, the model fitness and C- statistic improved significantly.

Figure 5:Time-dependent receiver operating characteristic analysis for 6 models. Compared with nested univariable model of RV GLS(A), LV involvement(B), and 5-year risk score(C), bivariable models with RVFD (D, E, F) respectively had increased Integrated areas under the receiver operating characteristic curve (AUCs).

Figure 2: Study inclusion flowchart.

Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)
4913
DOI: https://doi.org/10.58530/2024/4913