Evidence map›Paper›PMID 38862843›Full record

ArticleEuropean radiology experimental2024

Virtual noncontrast images reveal gouty tophi in contrast-enhanced dual-energy CT: a phantom study.

Karim Khayata, Torsten Diekhoff, Jürgen Mews, Sydney Schmolke, Maximilian Kotlyarov

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Article in European radiology experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Karim KhayataDepartment of Radiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität Zu Berlin, Freie Universität Berlin, Charitéplatz 1, Berlin, 10117, Germany. ka.khayata@gmail.com.ORCID http://orcid.org/0009-0000-2369-7179
Torsten DiekhoffDepartment of Radiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität Zu Berlin, Freie Universität Berlin, Charitéplatz 1, Berlin, 10117, Germany.
Jürgen MewsCanon Medical Systems, Europe BV, Zoetermeer, The Netherlands.
Sydney SchmolkeDepartment of Radiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität Zu Berlin, Freie Universität Berlin, Charitéplatz 1, Berlin, 10117, Germany.
Maximilian KotlyarovDepartment of Radiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität Zu Berlin, Freie Universität Berlin, Charitéplatz 1, Berlin, 10117, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDual-energy computed tomography (DECT) is useful for detecting gouty tophi. While iodinated contrast media (ICM) might enhance the detection of monosodium urate crystals (MSU), higher iodine concentrations hamper their detection. Calculating virtual noncontrast (VNC) images might improve the detection of enhancing tophi. The aim of this study was to evaluate MSU detection with VNC images from DECT acquisitions in phantoms, compared against the results with standard DECT reconstructions.

methodsA grid-like and a biophantom with 25 suspensions containing different concentrations of ICM (0 to 2%) and MSU (0 to 50%) were scanned with sequential single-source DECT using an ascending order of tube current time product at 80 kVp (16.5-220 mAs) and 135 kVp (2.75-19.25 mAs). VNC images were equivalently reconstructed at 80 and 135 kVp. Two-material decomposition analysis for MSU detection was applied for the VNC and conventional CT images. MSU detection and attenuation values were compared in both modalities.

resultsFor 0, 0.25, 0.5, 1, and 2% ICM, the average detection indices (DIs) for all MSU concentrations (35-50%) with VNC postprocessing were respectively 25.2, 36.6, 30.9, 38.9, and 45.8% for the grid phantom scans and 11.7, 9.4, 5.5, 24.0, and 25.0% for the porcine phantom scans. In the conventional CT image group, the average DIs were respectively 35.4, 54.3, 45.4, 1.0, and 0.0% for the grid phantom and 19.4, 17.9, 3.0, 0.0, and 0.0% for the porcine phantom scans.

conclusionsVNC effectively reduces the suppression of information caused by high concentrations of ICM, thereby improving the detection of MSU. RELEVANCE STATEMENT: Contrast-enhanced DECT alone may suffice for diagnosing gout without a native acquisition. KEY POINTS: • Highly concentrated contrast media hinders monosodium urate crystal detection in CT imaging • Virtual noncontrast imaging redetects monosodium urate crystals in high-iodinated contrast media concentrations. • Contrast-enhanced DECT alone may suffice for diagnosing gout without a native acquisition.

Indexed as

Contrast MediaGoutPhantoms, ImagingTomography, X-Ray ComputedUric AcidAnimalsRadiography, Dual-Energy Scanned ProjectionSwineContrast MediaUric AcidContrast mediaGoutPhantoms (imaging)Tomography (x-ray computed)Uric acid

Identifiers

PMID38862843
PMCPMC11166610

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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.