Key result
Compressed sensing cine CMR strain analysis matches conventional CMR for detecting MI.
Why the study?
This study aimed to examine the clinical feasibility of feature-tracking strain analysis on compressed sensing cine CMR imaging for detecting myocardial infarction using LGE-CMR.
Does feature-tracking strain analysis on compressed sensing cine CMR imaging accurately detect myocardial infarction compared to conventional cine CMR imaging?
Observational (n=37)
No
Does feature-tracking strain analysis on compressed sensing cine CMR imaging accurately detect myocardial infarction compared to conventional cine CMR imaging?
Feature-tracking strain analysis on compressed sensing cine CMR imaging is feasible and performs comparably to conventional cine CMR for detecting myocardial infarction.
Supports comparable MI detection via compressed sensing cine CMR strain; leaves open prospective validation before clinical use.
Purpose: This study aimed to use gadolinium-enhanced cardiovascular magnetic resonance (LGE-CMR) scanning to examine the clinical feasibility of feature-tracking strain (FT-strain) analysis on compressed sensing (CS) cine cardiovascular magnetic resonance (CMR) imaging for detecting myocardial infarction (MI). Methods: We enrolled 37 patients who underwent conventional cine CMR, CS cine CMR, and LGE-CMR scanning to assess cardiovascular disease. FT-strain analysis was used to assess peak circumferential strain (p-CS) based on an 18-segment model in both cine CMR imaging modalities. Based on LGE-CMR imaging findings, myocardial segments were classified as remote, adjacent, subendocardial infarcted, and transmural infarcted. The diagnostic performance of p-CS for detecting MI was compared between CS cine CMR imaging and conventional cine CMR imaging using the receiver operating characteristic (ROC) curve analysis. Results: A total of 440 remote, 85 adjacent, 76 subendocardial infarcted, and 65 transmural infarcted segments were diagnosed on LGE-CMR imaging. There were significant between-group differences in p-CS on both conventional and CS cine CMR (p < 0.05 in each) imaging. The sensitivity and specificity of p-CS for identifying MI were 85% and 79% for conventional cine CMR imaging, and 82% and 77% for CS cine CMR imaging, respectively. There was no significant difference between conventional and CS cine CMR imaging in the area under the curve of p-CS (0.89 vs. 0.87, p = 0.15). Conclusion: FT-strain analysis of CS cine CMR imaging may help identify MI; it may be used alongside or instead of conventional CMR imaging.
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Morikawa et al. (2021) conducted an observational in Myocardial infarction (n=37). Compressed sensing (CS) cine CMR imaging vs. Conventional cine CMR imaging was evaluated on Area under the curve (AUC) of peak circumferential strain for detecting myocardial infarction (p=0.15). Feature-tracking strain analysis of compressed sensing cine CMR imaging detected myocardial infarction with an AUC of 0.87, showing no significant difference from conventional cine CMR (AUC 0.89).
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