Evidence map›Paper›PMID 39985506›Full record

ArticleJACC. Cardiovascular imaging2025

Benchmarking Photon-Counting Computed Tomography Angiography Against Invasive Assessment of Coronary Stenosis: Implications for Severely Calcified Coronaries.

Rafail A Kotronias, Giovanni L de Maria, Cheng Xie, Sheena Thomas, Kenneth Chan, Leonardo Portolan, Jeremy P Langrish, Jason Walsh, Thomas J Cahill, Andrew J Lucking and 11 more

Abstract readComparative Study
In one paragraph

Article in JACC. Cardiovascular imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. A scoping review of photon-counting detector computed tomography in cardiovascular imaging.Diagnostic and interventional radiology (Ankara, Turkey) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Cardiac imaging using photon counting CT - benefits, challenges and prospects.The international journal of cardiovascular imaging · 2026
    Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Article
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

21 authors.

Rafail A KotroniasAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Giovanni L de MariaAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Cheng XieAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Sheena ThomasAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Kenneth ChanAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Leonardo PortolanAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Jeremy P LangrishAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Jason WalshAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Thomas J CahillAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Andrew J LuckingAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Jonathan DentonAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Robyn FarrallAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Caroline TaylorAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Nikant SabharwalAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
David A HoldsworthAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Thomas HalborgAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Stefan NeubauerAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Adrian P BanningAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Keith M ChannonAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Charalambos AntoniadesAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom. Electronic address: charalambos.antoniades@cardiov.ox.ac.uk.
OxAMI and ORFAN InvestigatorsAcute Multidisciplinary Imaging and Interventional Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom.

Funding

British Heart Foundation CH/F/21/90009British Heart Foundation FS/CRTF/23/24460
6 · The paper itself

Abstract

backgroundClinical guidelines do not recommend coronary computed tomographic angiography (CTA) in elderly patients or in the presence of heavy coronary calcification. Photon-counting coronary computed tomographic angiography (PCCTA) introduces ultrahigh in-plane resolution and multienergy imaging, but the ability of this technology to overcome these limitations is unclear.

objectivesThe authors evaluate the ability of PCCTA to quantitatively assess coronary luminal stenosis in the presence and absence of calcification, comparing both the ultrahigh-resolution (UHR)-PCCTA and the multienergy standard-resolution (SR)-PCCTA with the criterion-standard 3-dimensional invasive quantitative coronary angiography (3D QCA).

methodsThe authors included 100 patients who had both PCCTA and invasive coronary angiography (ICA). They comparatively evaluated luminal diameter stenosis with PCCTA and 3D QCA, anatomic disease severity (according to CAD-RADS [Coronary Artery Disease-Reporting and Data System]) and the diagnostic performance of PCCTA in identifying coronary arteries with ≥50% diameter stenosis on 3D QCA requiring invasive hemodynamic severity evaluation and/or revascularization.

resultsThe authors analyzed 257 vessels and 343 plaques. UHR-PCCTA luminal evaluation relative to 3D QCA was more precise than SR-PCCTA (median difference: 3% [Q1-Q3: 1%-6%] vs 6% [Q1-Q3: 2%-11%]; P < 0.001), particularly in severely calcified arteries (median difference 3% [Q1-Q3: 1%-6%] vs 6% [Q1-Q3: 3%-13%]; P = 0.002). Per-vessel agreement for CAD-RADS between UHR-PCCTA and 3D QCA was near-perfect (κ = 0.90 [Q1-Q3: 0.84-0.95]; P < 0.001), and it was substantial for SR-PCCTA (κ = 0.63 [Q1-Q3: 0.54-0.71]; P < 0.001), especially in severely calcified arteries: κ = 0.90 (Q1-Q3: 0.83-0.97; P < 0.001) and κ = 0.67 (Q1-Q3: 0.56-0.77; P < 0.001), respectively. Per-vessel diagnostic performance of SR- and UHR-PCCTA was excellent: AUC: 0.94 (95% CI: 0.91-0.98; P < 0.001) and 0.99 (95% CI: 0.98-1.00; P < 0.001), respectively. UHR-PCCTA diagnostically outperformed SR-PCCTA: ΔAUC: 0.05 (95% CI: 0.01-0.08; P = 0.01).

conclusionsPCCTA compares favorably with ICA for lumen assessment and anatomic disease severity classification in patients presenting with acute coronary syndrome or patients referred for ICA. UHR-PCCTA luminal evaluation is superior to SR-PCCTA, especially in patients with heavy coronary calcification. UHR-PCCTA has excellent diagnostic performance in identifying coronary arteries with ≥50% luminal stenosis on 3D QCA, outperforming standard-resolution imaging.

Indexed as

BenchmarkingComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary StenosisCoronary VesselsMultidetector Computed TomographyPhotonsVascular CalcificationAgedAged, 80 and overFemaleHumansMaleMiddle AgedPredictive Value of Tests3D QCAcoronary CTAdiagnostic performancephoton-counting

Identifiers

PMID39985506
PMCPMC7618422

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Registered trials

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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 OpenQuestion graph.