Evidence mapPaperPMID 42188239Full record

ReviewJournal of imaging2026

FFR-CT: Technical Advances and Implementation in Clinical Practice.

Kamil Stankowski, Amedeo Pellizzon, Luca Signorelli, Andrea Baggiano, Nicola Cosentino, Alberico Del Torto, Fabio Fazzari, Daniele Junod, Maria Elisabetta Mancini, Riccardo Maragna and 5 more

Abstract readReview
In one paragraph

Review in Journal of imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Kamil StankowskiDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0001-7088-8509
Amedeo PellizzonDepartment of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy.ORCID 0009-0004-0603-5092
Luca SignorelliDepartment of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy.ORCID 0009-0007-1030-4939
Andrea BaggianoDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-8261-4529
Nicola CosentinoDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-8628-3106
Alberico Del TortoDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0001-5074-2078
Fabio FazzariDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Daniele JunodDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Maria Elisabetta ManciniDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Riccardo MaragnaDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Manuela MuratoriDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0003-4200-1362
Luigi TassettiDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
Alessandra VolpeDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-0624-0588
Saima MushtaqDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0003-4168-2207
Gianluca PontoneDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.ORCID 0000-0002-1339-6679

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fractional flow reserve derived from coronary computed tomography angiography (FFR-CT) has emerged as a non-invasive modality for the functional assessment of coronary artery disease. By using computational fluid dynamics, particularly in its most extensively validated off-site implementation, FFR-CT enables lesion-specific estimation of pressure gradients across coronary stenoses without the need for invasive catheterization. This narrative review summarizes the technical foundations of FFR-CT as well as the evidence demonstrating that FFR-CT enhances the diagnostic accuracy of coronary CT angiography alone by improving specificity for hemodynamically significant stenoses when compared with invasive fractional flow reserve. Beyond diagnosis, FFR-CT provides incremental prognostic information, supporting risk stratification and guiding revascularization decisions. Suggestions for clinical implementation of FFR-CT and guidance on interpreting results within the appropriate clinical context are provided. Despite these advantages, limitations remain, including dependence on image quality, reduced performance in heavily calcified vessels, assumptions regarding hyperemic flow conditions, and limited validation in certain populations. While computational fluid dynamics-based FFR-CT remains the most commonly adopted approach in clinical settings, machine learning-based on-site FFR-CT is rapidly evolving and is expected to become a reliable alternative. As technical refinements continue, FFR-CT is poised to play an expanding role in precision-guided management of coronary artery disease.

Indexed as

cardiac computed tomographychronic coronary syndromecomputational fluid dynamicscoronary artery diseasefractional flow reservemachine learning

Identifiers

PMID42188239
PMCPMC13208309

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.