# Fractal Laws for Bifurcation Quantitative Coronary Angiography to Assess Left Main Bifurcation Lesions

## TL;DR

This study compares methods for assessing heart artery blockages using angiography and fractal laws, finding that visual estimates are less accurate than quantitative methods.

## Contribution

The study evaluates the use of fractal laws in improving bifurcation lesion assessment compared to standard quantitative coronary angiography.

## Key findings

- Bif-QCA moderately correlates with pressure-wire functional assessment for left main bifurcation stenosis.
- Visual assessment leads to higher 1,1,1 and lower 1,0,0 MEDINA patterns compared to Bif-QCA and Finet-QCA.
- Fractal laws (Finet-QCA) did not improve reference diameter determination over conventional Bif-QCA.

## Abstract

Background: Visual angiographic assessment of left main (LM) bifurcation lesions is fraught with major limitations. Bifurcation-dedicated quantitative coronary angiography (Bif-QCA) assessment provides higher accuracy than standard QCA in bifurcation lesions. Fractal laws (e.g., Finet's and Murray's laws) can enhance the accuracy of reference diameter calculation when applied to angiography-derived algorithms and may serve as a surrogate for pressure-based assessment.

Aims: To investigate the correlation between Bif-QCA, Finet's law derived Bif-QCA (Finet-QCA) and pressure–wire functional assessment for LM bifurcation stenosis.

Methods: Using instantaneous wave-free ratio (iFR) as a reference standard (≤ 0.89), we compared the value of Bif-QCA and Finet-QCA (diameter stenosis ≥ 50%). Moreover, the differences in MEDINA classification according to site-reported visual assessment vs Bif-QCA or Finet-QCA were investigated.

Results: Eighty-four patients were included in the analysis, of which 72 (85.7%) presented an abnormal iFR. Bif-QCA derived %DS was moderately correlated with iFR values; however, implementing Finet's law in the correlation resulted weak. Site-reported MEDINA (visual assessment) resulted in significant higher rate of 1,1,1 and lower rate of 1,0,0 patterns compared to Bif-QCA MEDINA (9.5% vs. 1.2%, p < 0.001 and 33.3% vs. 46.4%, p < 0.001, respectively) and to Finet-QCA MEDINA (9.5% vs. 2.4%, p < 0.001 and 33.3% vs. 40%, p < 0.001, respectively).

Conclusions: The present study suggested that LM MEDINA bifurcation pattern should be based on QCA analysis rather than visual assessment, both in the context of clinical practice and clinical studies. Compared to conventional Bif-QCA, the implementation of fractal laws (Finet-QCA) did not appear to improve the determination of the reference diameters of the LM shaft.