Evidence map›Paper›PMID 37650968›Full record

ArticleEuropean radiology2024

Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT.

Valerie Van Ballaer, Adriana Dubbeldam, Emanuele Muscogiuri, Lesley Cockmartin, Hilde Bosmans, Walter Coudyzer, Johan Coolen, Walter de Wever

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Article in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
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

15 citing papers in PubMed, 30 citations in OpenAlex.

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  15. Innovations in Chest Imaging: How Can Patients Benefit?Diagnostics (Basel, Switzerland) · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Valerie Van BallaerDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium. valerie.vanballaer@uzleuven.be.ORCID http://orcid.org/0000-0001-6881-7533
Adriana DubbeldamDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Emanuele MuscogiuriDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Lesley CockmartinDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Hilde BosmansDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Walter CoudyzerDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Johan CoolenDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
Walter de WeverDepartment of Radiology, University Hospitals Leuven, Herestraat 49 3000, Louvain, Belgium.
KU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND

methodsFifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level.

resultsAlmost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2.

conclusionUHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: • The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. • UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). • Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.

Indexed as

CystsLung DiseasesPulmonary EmphysemaBlisterHumansLungPhantoms, ImagingPhotonsTomography, X-Ray ComputedDiagnostic imagingInterstitial lung diseaseSpiral computed tomographyX-ray tomography

Identifiers

PMID37650968
OpenAlexW4386305906

What OpenQuestion holds

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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.