| Title: |
Fractal Analysis of Left Ventricular Trabeculae in Patients with End‐Stage Renal Disease: A Random Survival Tree Analysis. |
| Authors: |
Zhang, Tian‐yi, An, Dong‐Aolei, Yan, Hao, Wang, Jieying, Zhou, Hang, Chen, Binghua, Lu, Renhua, Fang, Wei, Wang, Qin, Che, Xiajing, Huang, Jiaying, Jin, Haijiao, Shen, Jianxiao, Zhou, Yin, Mou, Shan, Chen, Jie, Fang, Yan, Wu, Lian‐Ming |
| Source: |
Journal of Magnetic Resonance Imaging; Nov2024, Vol. 60 Issue 5, p1948-1961, 14p |
| Subject Terms: |
MAJOR adverse cardiovascular events, RECEIVER operating characteristic curves, FRACTAL analysis, FRACTAL dimensions, RANDOM forest algorithms |
| Abstract: |
Background: The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. Purpose: To evaluate the prognostic value of LV trabecular complexity in patients with end‐stage renal disease (ESRD). Study Type: Prospective outcome study. Population: 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. Field Strength: 3.0T, steady‐state free precession (SSFP) and modified Look‐Locker imaging sequences. Assessment: All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low‐ and high‐risk groups based on scores derived from the RF model and survival compared. Statistical Tests: Receiver operating characteristic curve analysis; Kaplan–Meier survival analysis with log rank tests; Harrel's C‐index to assess model performance. A P value <0.05 was considered statistically significant. Results: Fifty‐five patients (26.57%) experienced MACE during a median follow‐up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C‐index: 0.81) had significantly better discrimination than the Cox regression model (C‐index: 0.74). Participants of the external validation dataset classified into the high‐risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low‐risk group. Data Conclusion: LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. Level of Evidence: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Magnetic Resonance Imaging is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |
