Top Cats Often Begin as Underdogs: The Ascent of Trabecular Fractal Analysis with Cardiac MRI

Captur, Gabriella; Moon, James

doi:10.1148/radiol.2020203800

Cited by 1 publication

(1 citation statement)

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“…With cardiovascular magnetic resonance (CMR) short-axis cine sequences, the fractal dimension representing the complexity of the trabeculae can be calculated to determine their morphological changes. Several studies have applied the measurement of trabecular fractal dimension to investigate cardiac diseases [14,[19][20][21]. The aim of this study was to understand the complex changes in endocardial trabeculae with fractal analysis in the HFpEF patients with multivessel coronary artery disease.…”

Section: Introductionmentioning

confidence: 99%

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

Gu,

Chen,

Zhao

et al. 2024

Insights Imaging

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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. Graphical Abstract

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Section: Introductionmentioning

confidence: 99%