# VERMONT non-optimised: Feasibility of angiography-derived vFFR using baseline diagnostic catheter images

## TL;DR

This study shows that vFFR calculated from standard angiogram images is accurate for identifying heart artery blockages, similar to using optimized images.

## Contribution

Demonstrates the feasibility of using baseline diagnostic catheter images for real-time vFFR with strong diagnostic accuracy.

## Key findings

- vFFR from baseline images had 94% sensitivity and 75% specificity for detecting significant lesions.
- Baseline and optimized vFFR showed strong correlation (R = 0.87) and excellent agreement (ICC = 0.93).
- vFFR from baseline images achieved an AUC of 0.91 for identifying lesions with FFR ≤ 0.80.

## Abstract

Vessel-fractional-flow-reserve (vFFR) estimates coronary physiology from the three-dimensional reconstruction of two angiographic projections using computational fluid dynamics. Although its diagnostic accuracy using optimised angiographic acquisitions is well established, evidence supporting its use with baseline diagnostic catheter images remains limited.

To evaluate the diagnostic performance of real-time vFFR derived from baseline diagnostic catheter images against wire-based FFR, and to compare its performance with vFFR computed from optimised angiographic projections.

VERMONT Non-Optimised was a prospective, single-centre, blinded study in which real-time vFFR derived from both baseline diagnostic and optimised images were measured and compared with simultaneous wire-based FFR. A wire-based FFR of ≤ 0.80 defined a physiologically significant lesion.

In 195 patients with 205 intermediate lesions, 56 (27.3%) lesions were excluded from vFFR analysis. vFFR derived from baseline diagnostic images demonstrated an AUC of 0.91 (95% CI,0.87–0.96) for detecting lesions with FFR ≤ 0.80, achieving 94% sensitivity, 75% specificity, a negative predictive value of 96%, and a positive predictive value of 67%. Baseline diagnostic and optimised vFFR were strongly correlated (R = 0.87,p < 0.001), with a mean bias of −0.0075 ± 0.0490 and an intraclass correlation coefficient of 0.93 (95% CI,0.90–0.95), indicating excellent agreement.

Real-time vFFR derived from judiciously selected baseline diagnostic catheter images demonstrated strong overall accuracy and high sensitivity for detecting physiologically significant lesions, with similar diagnostic performance to vFFR derived from optimised images. These findings support the use of vFFR as a reliable screening tool for intermediate lesions in both prospective and retrospective settings.