The potential role of computed blood flow in the management of patients with acute coronary syndrome (ACS)

ABSTRACT Background Acute coronary syndromes (ACS) are one of the leading causes of hospitalization and death. Patients with non-ST elevation ACS (NSTE-ACS) undergo coronary angiography (CAG). However, identifying the lesions which are physiologically significant is difficult based upon CAG alone. Fractional flow reserve (FFR) measured with a pressure wire is used in a few and produces a 25% change in management compared with visual assessment. Virtual (computed) FFR (vFFR), which uses a 3D model of the coronary arteries constructed from the invasive angiogram, and application of the physical laws of fluid flow, has the potential to be used more widely. Its practicability and impact in the acute setting need to be tested. Hypothesis vFFR leads to a change in planned treatment in >10% cases compared with angiographic assessment. Methods This was a prospective, observational study of patients with NSTE-ACS undergoing coronary angiography. Clinical data, demographics, CAG result and the initial management (medical therapy, PCI, coronary artery bypass grafting (CABG) or multidisciplinary team (MDT)) were recorded. The vFFRs were calculated and the cardiologist was asked for any change in decision. Study meetings were also convened, and their decisions recorded. The primary endpoint was the number of patients in whom management changes. Results Two hundred and ninety-four patients were screened, 208 were recruited and 335 vessels were processed. vFFR resulted in an hypothetical change of management in 22% [95% CI: 15% to 25%, p <0.001] and increased the confidence level of the decisions in 126/208 (61%) cases and reduced it in 12/208 (6%). At six months, 6/208 (3%) of patients experienced a MACE; one death, two MIs, two unplanned revascularisations and one bleed. Conclusion vFFR is feasible and leads to an hypothetical change in management in 22% of cases. It may have the potential impact to augment simple, angiography-based decision making in ACS.