# Comparative Analysis of the Feasibility of Myocardial Blood Flow Index Versus CT-FFR in the Diagnosis of Suspected Coronary Artery Disease

## TL;DR

This study compares two noninvasive methods, CT-FFR and MBFI, for diagnosing coronary artery disease and finds they are similarly effective.

## Contribution

The study introduces MBFI as a viable alternative to CT-FFR for diagnosing coronary artery disease.

## Key findings

- MBFI and CT-FFR both show strong correlation with invasive coronary angiography as a gold standard.
- The diagnostic performance of MBFI and CT-FFR is not significantly different.
- MBFI reflects myocardial mass remodeling, while CT-FFR is based on anatomical stenosis.

## Abstract

Using fluid dynamic modeling, noninvasive
fractional flow reserve (FFR) derived from coronary computed tomography
angiography (CCTA) data provides better anatomic and functional
information than CCTA, with a high diagnostic and discriminatory value for
diagnosing hemodynamically significant lesions. Myocardial blood flow index
(MBFI) based on CCTA is a physiological parameter that reflects myocardial
ischemia. Thus, exploring the relationship between computed tomography derived fractional flow reserve (CT-FFR) and MBFI could be
clinically significant. This study aimed to investigate the
relationship between CT-FFR and MBFI and to analyze the feasibility of MBFI
differing from CT-FFR in diagnosing suspected coronary artery disease (CAD).

Data from 61 patients (35 males, mean age: 59.2
± 10.02 years) with suspected CAD were retrospectively analyzed, including
the imaging data of CCTA, CT-FFR, and data of invasive coronary angiography
performed within one week after hospitalization. CT-FFR and MBFI were calculated,
and the correlation between MBFI or CT-FFR and invasive coronary angiography
(ICA) was evaluated. Using ICA (value ≥0.70) as the gold standard and
determining the optimal cutoff value via a diagnostic test, the diagnostic
performance of MBFI or CT-FFR was evaluated.

MBFI and CT-FFR
were negatively correlated with ICA (r = –0.3670 and –0.4922, p
= 0.0036 and 0.0001, respectively). Using ICA (value of ≥0.70) the gold
standard, the optimal cutoff value was 0.115 for MBFI, and the area under the curve (AUC) was 0.833
(95% confidence interval [CI]: 0.716–0.916, Z = 5.357, p
< 0.0001);
using ICA (value of ≥0.70) the gold standard, the optimal cutoff value was
0.80 for CT-FFR, and the area under the curve (AUC) was 0.759 (95% CI:
0.632–0.859, Z = 3.665, p = 0.0002). No significant difference was
observed between the AUCs of CT-FFR and MBFI (Z = 0.786, p = 0.4316).

MBFI based on CCTA can be used to evaluate myocardial
ischemia similar to CT-FFR in suspected CAD; however, it should be noted that
CT-FFR is a functional index based on the anatomical stenosis of the coronary
artery, whereas MBFI is a physiological index reflecting myocardial mass
remodeling.