Header

UZH-Logo

Maintenance Infos

Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience


Eberhard, Matthias; Nadarevic, Tin; Cousin, Andrej; von Spiczak, Jochen; Hinzpeter, Ricarda; Euler, Andre; Morsbach, Fabian; Manka, Robert; Keller, Dagmar I; Alkadhi, Hatem (2020). Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience. Cardiovascular Diagnosis and Therapy, 10(4):820-830.

Abstract

Background

Computed tomography (CT)-derived fractional flow reserve (FFR$_{CT}$) enables the non-invasive functional assessment of coronary artery stenosis. We evaluated the feasibility and potential clinical role of FFR$_{CT}$ in patients presenting to the emergency department with acute chest pain who underwent chest-pain CT (CPCT).

Methods

For this retrospective IRB-approved study, we included 56 patients (median age: 62 years, 14 females) with acute chest pain who underwent CPCT and who had at least a mild (≥25% diameter) coronary artery stenosis. CPCT was evaluated for the presence of acute plaque rupture and vulnerable plaque features. FFR$_{CT}$ measurements were performed using a machine learning-based software. We assessed the agreement between the results from FFR$_{CT}$ and patient outcome (including results from invasive catheter angiography and from any non-invasive cardiac imaging test, final clinical diagnosis and revascularization) for a follow-up of 3 months.

Results

FFR$_{CT}$ was technically feasible in 38/56 patients (68%). Eleven of the 38 patients (29%) showed acute plaque rupture in CPCT; all of them underwent immediate coronary revascularization. Of the remaining 27 patients (71%), 16 patients showed vulnerable plaque features (59%), of whom 11 (69%) were diagnosed with acute coronary syndrome (ACS) and 10 (63%) underwent coronary revascularization. In patients with vulnerable plaque features in CPCT, FFRCT had an agreement with outcome in 12/16 patients (75%). In patients without vulnerable plaque features (n=11), one patient showed myocardial ischemia (9%). In these patients, FFR$_{CT}$ and patient outcome showed an agreement in 10/11 patients (91%).

Conclusions

Our preliminary data show that FFR$_{CT}$ is feasible in patients with acute chest pain who undergo CPCT provided that image quality is sufficient. FFR$_{CT}$ has the potential to improve patient triage by reducing further downstream testing but appears of limited value in patients with CT signs of acute plaque rupture.

Abstract

Background

Computed tomography (CT)-derived fractional flow reserve (FFR$_{CT}$) enables the non-invasive functional assessment of coronary artery stenosis. We evaluated the feasibility and potential clinical role of FFR$_{CT}$ in patients presenting to the emergency department with acute chest pain who underwent chest-pain CT (CPCT).

Methods

For this retrospective IRB-approved study, we included 56 patients (median age: 62 years, 14 females) with acute chest pain who underwent CPCT and who had at least a mild (≥25% diameter) coronary artery stenosis. CPCT was evaluated for the presence of acute plaque rupture and vulnerable plaque features. FFR$_{CT}$ measurements were performed using a machine learning-based software. We assessed the agreement between the results from FFR$_{CT}$ and patient outcome (including results from invasive catheter angiography and from any non-invasive cardiac imaging test, final clinical diagnosis and revascularization) for a follow-up of 3 months.

Results

FFR$_{CT}$ was technically feasible in 38/56 patients (68%). Eleven of the 38 patients (29%) showed acute plaque rupture in CPCT; all of them underwent immediate coronary revascularization. Of the remaining 27 patients (71%), 16 patients showed vulnerable plaque features (59%), of whom 11 (69%) were diagnosed with acute coronary syndrome (ACS) and 10 (63%) underwent coronary revascularization. In patients with vulnerable plaque features in CPCT, FFRCT had an agreement with outcome in 12/16 patients (75%). In patients without vulnerable plaque features (n=11), one patient showed myocardial ischemia (9%). In these patients, FFR$_{CT}$ and patient outcome showed an agreement in 10/11 patients (91%).

Conclusions

Our preliminary data show that FFR$_{CT}$ is feasible in patients with acute chest pain who undergo CPCT provided that image quality is sufficient. FFR$_{CT}$ has the potential to improve patient triage by reducing further downstream testing but appears of limited value in patients with CT signs of acute plaque rupture.

Statistics

Citations

Altmetrics

Downloads

4 downloads since deposited on 17 Nov 2020
4 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Cardiology and Cardiovascular Medicine
Language:English
Date:August 2020
Deposited On:17 Nov 2020 11:30
Last Modified:01 Dec 2020 14:20
Publisher:AME Publishing Company
ISSN:2223-3652
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.21037/cdt-20-381
PubMed ID:32968637

Download

Hybrid Open Access

Download PDF  'Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience'.
Preview
Content: Published Version
Filetype: PDF
Size: 773kB
View at publisher
Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)