The association between cardiac T2*BOLD and quantitative flow ratio (QFR) in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease.

BACKGROUND: T2*BOLD is based on myocardial deoxyhemoglobin content to reflect the state of myocardial oxygenation. Quantitative flow ratio is a tool for assessing coronary blood flow based on invasive coronary angiography. PURPOSE: This study aimed to evaluate the correlation between T2*BOLD and QFR in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. METHODS: Fifty patients with MVCAD with at least 1 significant coronary artery stenosis (diameter stenosis > 50%) and 21 healthy control subjects underwent coronary angiography combined with QFR measurements and cardiovascular magnetic resonance (CMR). QFR ≤ 0.80 was considered to indicate the presence of hemodynamic obstruction. RESULTS: Totally 60 (54%) obstructive vessels had hemodynamic change. Between stenotic coronary arteries (QFR ≤ 0.8) and normal vessels, T2*BOLD showed AUCs of 0.97, 0.69, and 0.91 for left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries and PI displayed AUCs of 0.89, 0.77 and 0.90 (all p > 0.05, except for LAD). The AUCs of T2*BOLD between stenotic coronary arteries (QFR > 0.8) and normal vessels were 0.86, 0.72, and 0.85 for LAD, LCX and RCA; while, PI showed AUCs of 0.93, 0.86, and 0.88, respectively (p > 0.05). Moreover, T2*BOLD displayed AUCs of 0.96, 0.74, and 0.91 for coronary arteries as before between coronary arteries with stenosis (QFR ≤ 0.8 and > 0.8), but the mean PI of LAD, LCX and RCA showed no significant differences between them. CONCLUSION: T2* BOLD and QFR have good correlation in diagnosing stenotic coronary arteries with hemodynamic changes in patients with stable multi-vessel CAD. T2* BOLD is superior to semi-quantitative perfusion imaging in analyzing myocardial ischemia without stress.

Fractal analysis of left ventricular trabeculae in heart failure with preserved ejection fraction patients with multivessel coronary artery disease.

OBJECTIVES: Endocardial trabeculae undergo varicose changes and hyperplasia in response to hemodynamic influences and are a variable phenotype reflecting changes in disease. Fractal analysis has been used to analyze the complexity of endocardial trabeculae in a variety of cardiomyopathies. The aim of this paper was to quantify the myocardial trabecular complexity through fractal analysis and to investigate its predictive value for the diagnosis of heart failure with preserved ejection fraction (HFpEF) in patients with multivessel coronary artery disease (CAD). METHODS: The retrospective study population consisted of 97 patients with multivessel CAD, 39 of them were diagnosed with HFpEF, while 46 healthy volunteers were recruited as controls. Fractal dimension (FD) was obtained through fractal analysis of endocardial trabeculae on LV short-axis cine images. Logistic regression analyses were used to confirm the predictors and compare different prediction models. RESULTS: Mean basal FD was significantly higher in patients with HFpEF than in patients without HFpEF or in the healthy group (median: 1.289; IQR: 0.078; p < 0.05). Mean basal FD was also a significant independent predictor in univariate and multivariate logistic regression (OR: 1.107 and 1.043, p < 0.05). Furthermore, adding FD to the prediction model improved the calibration and accuracy of the model (c-index: 0.806). CONCLUSION: The left ventricular FD obtained with fractal analysis can reflect the complexity of myocardial trabeculae and has an independent predictive value for the diagnosis of HFpEF in patients with multivessel CAD. Including FD into the diagnostic model can help improve the diagnosis. CRITICAL RELEVANCE STATEMENT: Differences show in the complexity of endocardial trabeculae in multivessel coronary artery disease patients, and obtaining fractal dimensions (FD) by fractal analysis can help identify heart failure with preserved ejection fraction (HFpEF) patients. KEY POINTS: The complexity of myocardial trabeculae differs among patients with multivessel coronary artery disease. Left ventricular fractal dimensions can reflect the complexity of the myocardial trabecular. Fractal dimensions have predictive value for the diagnosis of heart failure with preserved ejection fraction.

Late gadolinium enhancement entropy as a new measure of myocardial tissue heterogeneity for prediction of adverse cardiac events in patients with hypertrophic cardiomyopathy.

OBJECTIVES: Entropy is a new late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR)-derived parameter that is independent of signal intensity thresholds. Entropy can be used to measure myocardial tissue heterogeneity by comparing full pixel points of tissue images. This study investigated the incremental prognostic value of left ventricular (LV) entropy in patients with hypertrophic cardiomyopathy (HCM). METHODS: This study enrolled 337 participants with HCM who underwent 3.0-T CMR. The LV entropy was obtained by calculating the probability distribution of the LV myocardial pixel signal intensities of the LGE sequence. Patients who underwent CMR imaging were followed up for endpoints. The primary endpoint was defined as readmission to the hospital owing to heart failure. The secondary endpoint was the composite of the primary endpoint, sudden cardiac death and non-cardiovascular death. RESULTS: During the median follow-up of 24 months ± 13 (standard deviation), 43 patients who reached the primary and secondary endpoints had a higher entropy (6.20 ± 0.45, p < 0.001). The patients with increased entropy (≥ 5.587) had a higher risk of the primary and secondary endpoints, compared with HCM patients with low entropy (p < 0.001 for both). In addition, Cox analysis showed that LV entropy provided significant prognostic value for predicting both primary and secondary endpoints (HR: 1.291 and 1.273, all p < 0.001). Addition of LV entropy to the multivariable model improved model performance and risk reclassification (p < 0.05). CONCLUSION: LV entropy assessed by CMR was an independent predictor of primary and secondary endpoints. LV entropy assessment contributes to improved risk stratification in patients with HCM. CRITICAL RELEVANCE STATEMENT: Myocardial heterogeneity reflected by entropy the derived parameter of LGE has prognostic value for adverse events in HCM. The measurement of LV entropy helped to identify patients with HCM who were at risk for heart failure and sudden cardiac death. KEY POINTS: • Left ventricular entropy can reflect myocardial heterogeneity in HCM patients. • Left ventricular entropy was significantly higher in HCM patients who reached endpoint events. • Left ventricular entropy helps to predict the occurrence of heart failure and death in HCM patients.