Plaque-Adapted Virtual Monoenergetic Image Selection for Carotid Plaque Visualization Using Photon-Counting CT
Objectives: The objective of this study was to evaluate the impact of virtual monoenergetic image (VMI) reconstructions derived from photon-counting computed tomography (PCCT) on the assessment of carotid arteries, with a focus on optimizing keV selection based on plaque composition. Methods: This retrospective study included 111 patients (mean age 80 ± 7.5 years; 64 men; 47 women) with carotid sclerosis who underwent PCCT between April 2022 and February 2023. One lesion was analyzed per patient, each containing both calcified and non-calcified components. Quantitative measurements were performed in calcified plaque across energy levels from 40 to 120 keV and comprised attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), corrected image noise (CIN) and artifact index (AIX). Two radiologists independently rated image quality, artifacts, and diagnostic assessability of both components using five-point scales. Results: Attenuation and CNR were highest at 40 to 50 keV, where CIN and AIX were also greatest. SNR followed a U-shaped course, lowest at 90 keV and highest at 110 to 120 keV, where intraluminal attenuation was too low for reliable luminal delineation. Reader ratings were highest at 40 to 50 keV for non-calcified components and at 70 to 80 keV for calcified plaque, with good interobserver agreement throughout (κ 0.74 to 0.92). After correction for multiple testing, adjacent energy levels were frequently indistinguishable. Conclusions: Optimal PCCT VMI energy levels depend on plaque composition. The findings support implementing standardized protocols with automatic dual-range reconstructions (40–50 keV and 70–80 keV) to enable efficient, individualized carotid plaque assessment in clinical practice.
Authors
- Scherwin Mahmoudi (ORCID: https://orcid.org/0000-0002-4020-1873)
- Mirela Dimitrova (ORCID: https://orcid.org/0000-0002-6905-8556)
- Tommaso D’Angelo (ORCID: https://orcid.org/0000-0003-0004-6378)
- Vitali Koch (ORCID: https://orcid.org/0000-0001-6915-5906)
- Thomas J. Vogl (ORCID: https://orcid.org/0000-0001-5218-1075)
- Leon D. Gruenewald (ORCID: https://orcid.org/0000-0001-7959-5008)
- İbrahim Yel (ORCID: https://orcid.org/0000-0002-3894-4782)
- Hanns Leonhard Kaatsch (ORCID: https://orcid.org/0000-0002-6208-3425)
- Leona S. Alizadeh (ORCID: https://orcid.org/0000-0001-8141-7454)
- Giuseppe M. Bucolo (ORCID: https://orcid.org/0000-0002-2076-5532)
- Katrin Eichler
- Aynur Goekduman
- Daniel Overhoff
- A I Nica
- Stephan Waldeck
- Christian Booz
- Lea B. Uebelacker
Institutions
- Goethe University Frankfurt (DE)
- University Hospital Frankfurt (DE)
- Azienda Ospedaliera Universitaria Policlinico "G. Martino" (IT)
- Bundeswehrzentralkrankenhaus Koblenz (DE)
Publication Details
- Journal
- Diagnostics
- Published
- 2026-08-28
- DOI
- https://doi.org/10.3390/diagnostics16172774
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00