Evidence map›Paper›PMID 41944834›Full record

ArticleEuropean radiology2026

Photon-counting CT characterization of carotid perivascular adipose tissue: a layer-by-layer quantitative analysis. A preliminary analysis in an asymptomatic population.

Luca Saba, Hatem Alkadhi, Erica Maffei, Roberta Sciciolone, Mahmud Mossa-Basha, Lorenzo Mannelli, Gennaro D'Anna, Antonella Balestrieri, Jasjit S Suri, Filippo Cademartiri

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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. Not yet cited 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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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Luca SabaDepartment of Radiology, University of Cagliari, Cagliari, Italy. lucasaba@tiscali.it.ORCID http://orcid.org/0000-0003-2870-3771
Hatem AlkadhiDiagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Erica MaffeiIRCCS SYNLAB SDN, Naples, Italy.
Roberta ScicioloneDepartment of Radiology, University of Cagliari, Cagliari, Italy.
Mahmud Mossa-BashaDepartment of Radiology, University of Washington, Seattle, WA, USA.
Lorenzo MannelliIRCCS SYNLAB SDN, Naples, Italy.
Gennaro D'AnnaStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.
Antonella BalestrieriDepartment of Radiology, University of Cagliari, Cagliari, Italy.
Jasjit S SuriStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.
Filippo CademartiriIRCCS SYNLAB SDN, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCarotid atherosclerosis is a major contributor to ischemic stroke. While luminal stenosis has historically guided treatment decisions, growing evidence indicates that plaque composition, vascular inflammation and perivascular adipose tissue (PVAT) may be more closely linked to clinical outcomes and plaque vulnerability. This study aimed to characterize carotid PVAT using photon-counting computed tomography (PCCT) and to evaluate its spatial behavior and variability in a cohort of asymptomatic patients. MATERIALS AND

methodsWe retrospectively analyzed PCCT angiography data from 20 asymptomatic patients. A custom-developed Python algorithm was used to segment concentric perivascular layers from 1 mm to 5 mm around the carotid artery. For each layer, we quantified attenuation values in Hounsfield Units (HU) and voxel counts. Statistical comparisons were performed across layers and between sides.

resultsMean PVAT attenuation decreased progressively with increasing distance from the carotid wall. Significant differences were observed between inner and outer layers, particularly between the 1 mm and 3-5 mm annuli. Circle-by-circle analysis revealed substantial inter-individual variability in HU trends. Voxel count increased with annular thickness, but variability (SD and CV) also rose in outer layers. No significant differences were found between left and right carotid arteries in either attenuation or voxel distribution.

conclusionPhoton-counting CT enables detailed, layer-specific assessment of carotid PVAT. The observed attenuation patterns and inter-individual variability suggest that PVAT profiling may provide valuable insights into local vascular inflammation and plaque vulnerability. These findings support the potential of PCCT as a noninvasive tool for vascular risk stratification beyond luminal stenosis. KEY POINTS: Question Can photon-counting CT enable a reliable, layer-by-layer quantitative characterization of carotid perivascular adipose tissue in asymptomatic patients beyond luminal stenosis assessment? Findings Photon-counting CT demonstrated a progressive decrease in PVAT attenuation with increasing distance from the carotid wall and marked inter-individual variability across concentric layers. Clinical relevance Layer-specific PVAT profiling with photon-counting CT may provide a noninvasive imaging marker of local vascular inflammation, supporting improved carotid risk stratification beyond stenosis severity, even in asymptomatic individuals.

Indexed as

Adipose TissueCarotid ArteriesCarotid Artery DiseasesCarotid StenosisComputed Tomography AngiographyTomography, X-Ray ComputedAgedAlgorithmsFemaleHumansMaleMiddle AgedPhotonsRetrospective StudiesCarotidComputed tomography angiographyPerivascular adipose tissuePhoton-counting computed tomographyPlaque

Identifiers

PMID41944834
PMCPMC13342122

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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.