Intra-individual radiomic analysis of pericoronary adipose tissue: Photon-counting detector vs energy-integrating detector CT angiography

Dmitrij Kravchenko; Milan Vecsey-Nagy; Akos Varga-Szemes; Muhammad Taha Hagar; U Joseph Schoepf; Chiara Gnasso; Emese Zsarnóczay; Jim O'Doherty; Damiano Caruso; Andrea Laghi; Tilman Emrich; Giuseppe Tremamunno

doi:10.1016/j.ijcard.2024.132749

Intra-individual radiomic analysis of pericoronary adipose tissue: Photon-counting detector vs energy-integrating detector CT angiography

Int J Cardiol. 2025 Feb 1:420:132749. doi: 10.1016/j.ijcard.2024.132749. Epub 2024 Nov 21.

Authors

Affiliations

¹ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany; Quantitative Imaging Laboratory Bonn (QILaB), Bonn, Germany. Electronic address: [email protected].
² Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Heart and Vascular Centre, Semmelweis University, Budapest, Hungary. Electronic address: [email protected].
³ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: [email protected].
⁴ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Freiburg, Germany. Electronic address: [email protected].
⁵ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: [email protected].
⁶ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, Italy. Electronic address: [email protected].
⁷ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; MTA-SE Cardiovascular Imaging Research Group, Department of Radiology, Medical Imaging Centre, Semmelweis University, Hungary. Electronic address: [email protected].
⁸ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Siemens Medical Solutions, Malvern, PA, USA. Electronic address: [email protected].
⁹ Department of Medical Surgical Sciences and Translational Medicine, Sapienza University of Rome, Italy. Electronic address: [email protected].
¹⁰ Department of Medical Surgical Sciences and Translational Medicine, Sapienza University of Rome, Italy. Electronic address: [email protected].
¹¹ Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany; German Center for Cardiovascular Research (DZHK), Partner-Site Rhine-Main, Mainz, Germany. Electronic address: [email protected].
¹² Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Medical Surgical Sciences and Translational Medicine, Sapienza University of Rome, Italy. Electronic address: [email protected].

PMID: 39579791
DOI: 10.1016/j.ijcard.2024.132749

Abstract

Background: The impact of novel photon-counting detector (PCD)-CT technology on in-vivo radiomics is not fully understood. This study aimed to compare the intra-individual stability and reproducibility of pericoronary adipose tissue (PCAT) radiomic features between PCD-CT and energy-integrating detector (EID)-CT in patients undergoing coronary CT angiography (CCTA) on both systems.

Methods: Patients undergoing clinically indicated CCTA on an EID-CT were prospectively enrolled for research PCD-CCTA within 30 days. Image acquisition parameters were standardized; PCD-CT datasets were reconstructed both down-sampled to 0.6 mm to match the clinical scan (PCD-CT_DS) and at 0.2 mm ultrahigh-resolution mode (PCD-CT_UHR). Automatic PCAT segmentation was performed; a total of 110 radiomic feature classes were extracted and compared across the three datasets (EID-CT, PCD-CT_DS, and PCD-CD_UHR). Feature stability was assessed using paired t-test filtered for false discoveries using Benjamini-Hochberg method, and reproducibility using intraclass correlation coefficient (ICC).

Results: A total of 42 patients (34 male [81.0 %]; 67.9 ± 7.6 years) were included. Feature stability was 91 % for EID-CT vs. PCD-CT_DS, but decreased for UHR datasets (EID-CT vs. PCD-CT_UHR: 55 %; PCD-CT_DS vs. PCD-CT_UHR: 51 %). However, inter-scanner reproducibility was poor in both comparisons (EID-CT vs. PCD-CT_DS median ICC: 0.43 [0.03-0.69]; EID-CT vs. PCD-CT_UHR: 0.29 [0.01-0.51]). Nevertheless, reproducibility improved within PCD-CT datasets (PCD-CT_DS vs. PCD-CT_UHR: 0.72 [0.48-0.83]), regardless of the difference in slice thickness.

Conclusions: Most PCAT radiomic features remained stable between EID-CT and PCD-CT_DS, although inter-scanner reproducibility was poor, emphasizing the significant impact of detector technology. Conversely, reproducibility of features within PCD-CT datasets showed more consistent results, even when comparing standard to UHR.

Keywords: Computed tomography angiography; Energy-integrating detector; Pericoronary adipose tissue, photon-counting detector; Radiomics; Reproducibility of results.

Publication types

Comparative Study

MeSH terms

Adipose Tissue* / diagnostic imaging
Aged
Computed Tomography Angiography* / instrumentation
Computed Tomography Angiography* / methods
Computed Tomography Angiography* / standards
Coronary Angiography / instrumentation
Coronary Angiography / methods
Coronary Artery Disease / diagnostic imaging
Epicardial Adipose Tissue
Female
Humans
Male
Middle Aged
Pericardium / diagnostic imaging
Photons
Prospective Studies
Radiomics
Reproducibility of Results