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Updated: Jul 1, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Fat-Induced Signal-oscillation Analysis Enhances Myocardial Iron Deposition Detection in Myocardial Infarction on
Rui Chen1, Yuelong Yang1, Xinyi Wu2
1Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhong Shan Er Lu, Guangzhou 510080, Guangdong Province, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhong Shan Er Lu, Guangzhou 510080, Guangdong Province, China.
Background:
Accurate detection of myocardial iron deposition is essential for diagnosis, risk stratification and therapeutic decision-making. The black-blood cardiac T2* mapping is the guideline-recommended technique for detecting myocardial iron deposition. However, mixtures of fat (MF) can confound the results, because MF also reduces T2* values. The present study proposes a method that reduces MF-related overestimation of iron deposition in cardiac T2* mapping.
Method:
This secondary analysis of a prospective trial (clinicaltrials.gov, NCT04863677) included myocardial infarction participants from April 2022 to June 2025. The guideline method defines iron deposition based on reduced T2* values. The proposed method introduced fat-induced signal-oscillation analysis of T2* decay curves using Reduced Chi-squared (χν2). The χν2 is a metric that enabled to quantify the signal-oscillation characteristic of signal curves. Predictive performance for detecting iron deposition without MF was evaluated by area under the receiver operating characteristic curves (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy using DeLong's test or Z-test.
Results:
Totally 73 regions of interest (ROI) from 15 ex-vivo hearts (mean age, 56±6.6 years [SD], 15 males) and 115 ROIs from 35 in-vivo hearts (mean age, 52±11 years [SD], 33 males) were included. The χν2 elevated in MF relative to iron depositions, both ex-vivo (MF, 39±51, iron deposition, 0.20±0.12, P=.001) and in-vivo (MF, 10±9.8, iron deposition, 0.54±0.55, P<.001) hearts. The proposed method adding fat-induced signal-oscillation analysis to the guideline method achieved higher AUC than guideline method for identifying iron deposition without MF in ex-vivo [proposed method, 0.99 (95% CI, 0.97, 1.00), guideline method, 0.78 (95% CI, 0.71, 0.85), P<.001] and in-vivo hearts [proposed method, 0.94 (95% CI, 0.90, 0.99), guideline method, 0.79 (95% CI, 0.73, 0.84), P<.001]. Specificity, PPV and accuracy of proposed method also improved in both datasets (all P <.001).
Conclusion:
The proposed method effectively mitigated MF-related overestimation of myocardial iron deposition on cardiac T2* mapping, positioning it as a strong candidate for inclusion in future cardiac T2* mapping guidelines.
