Evidence map›Paper›PMID 41238766›Full record

ArticleEuropean radiology2026

Comparative analysis of photon-counting and energy-integrating detector CT to identify obstructive coronary artery disease.

Melinda Boussoussou, Milán Vecsey-Nagy, Zsófia Jokkel, Borbála Vattay, Anikó Kubovje, Barbara Sipos, Márton Kolossváry, Anikó Ilona Nagy, Lili Száraz, Sámuel Beke and 8 more

Abstract readComparative Study
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

18 authors.

Melinda BoussoussouSemmelweis University Heart and Vascular Center, Budapest, Hungary.
Milán Vecsey-NagySemmelweis University Heart and Vascular Center, Budapest, Hungary.
Zsófia JokkelSemmelweis University Heart and Vascular Center, Budapest, Hungary.
Borbála VattaySemmelweis University Heart and Vascular Center, Budapest, Hungary.
Anikó KubovjeDepartment of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary.
Barbara SiposSemmelweis University Heart and Vascular Center, Budapest, Hungary.
Márton KolossváryGottsegen National Cardiovascular Center, Budapest, Hungary.
Anikó Ilona NagySemmelweis University Heart and Vascular Center, Budapest, Hungary.
Lili SzárazDepartment of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary.
Sámuel BekeDepartment of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary.
Bernard SchmidtSiemens Healthineers AG, Forchheim, Germany.
Máté KissSiemens Healthcare, Budapest, Hungary.
Béla MerkelySemmelweis University Heart and Vascular Center, Budapest, Hungary.
Josua A DeckerDepartment of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany.
Tilman EmrichDepartment of Radiology and Radiological Science29425, Medical University of South Carolina, Charleston, SC, USA.
Akos Varga-SzemesDepartment of Radiology and Radiological Science29425, Medical University of South Carolina, Charleston, SC, USA.
Pál Maurovich-HorvatDepartment of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary.
Bálint SzilveszterSemmelweis University Heart and Vascular Center, Budapest, Hungary. szilveszter.balint@semmelweis.hu.ORCID http://orcid.org/0000-0003-1530-4288

Funding

European Union RRF-2.3.1-21-2022-00003Magyar Tudományos Akadémia the János Bolyai Research ScholarshipMinistry of Culture and Innovation Hungary ÚNKP-23-3-5-OE-71Ministry of Culture and Innovation Hungary ÚNKP-23-5University Excellence Scholarship Program EKÖP-2024-187
6 · The paper itself

Abstract

objectiveTo evaluate the patient-, vessel- and segment-based diagnostic performance of photon-counting detector CT (PCD-CT) compared to energy-integrating detector CT (EID-CT) for detecting ≥ 50% or ≥ 70% stenosis using invasive coronary angiography (ICA) as a reference standard. MATERIALS AND

methodsPatients with stable chest pain and ≥ 50% stenosis detected on dual source PCD-CT who subsequently underwent ICA were prospectively enroled. Diagnostic accuracy was calculated for PCD-CT vs ICA and additionally for a patient cohort scanned with EID-CT with similar risk profiles and disease prevalence. A Monte Carlo simulation based on diagnostic accuracy parameters was performed to estimate the potential reduction in ICA referrals.

resultsA total of 143 patients (66 ± 9 years, 27.3% female) with 572 vessels and 2431 segments were evaluated with PCD-CT and ICA. Regarding EID-CT, 109 patients (65 ± 9 years, 31.0% female), 436 vessels and 1853 segments were assessed, with every patient undergoing ICA. PCD-CT demonstrated significantly higher accuracy than EID-CT in detecting ≥ 50% stenosis: 88.1% vs 77.9% (patient level), 91.6% vs 77.8% (vessel level), and 97.7% vs 92.4% (segment level) (p < 0.01 for all). For detecting ≥ 70% stenosis, PCD-CT also showed higher accuracy than EID-CT: 90.9% vs 70.6% (patient level), 94.6% vs 80.9% (vessel level), and 98.6% vs 94.1% (segment level) (p < 0.01 for all). We demonstrated a potential mean reduction of 14.8% in ICA referrals when utilising PCD-CT compared to EID-CT.

conclusionsPCD-CT provides improved per-patient, per-vessel and per-segment diagnostic performance in detecting obstructive CAD in symptomatic patients when compared to patients scanned on EID-CT. PCD-CT may lead to a significant decrease in ICA utilisation. KEY POINTS: Question Accurate coronary CT angiography guides treatment, but its diagnostic accuracy is limited by various factors. Findings Photon counting detector (PCD)-CT improved diagnostic performance in detecting ≥ 50% or ≥ 70% stenosis, potentially reducing unnecessary ICA referrals by 14.8%. Clinical relevance PCD-CT improves diagnostic accuracy over EID-CT and may reduce unnecessary ICA.

Indexed as

Computed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary StenosisTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedMonte Carlo MethodPhotonsProspective StudiesSensitivity and SpecificityCoronary stenosisDiagnostic accuracyDual source CTInvasive coronary angiographyPhoton-counting detector CT

Identifiers

PMID41238766
PMCPMC13035877

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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.