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Implications of computed tomography reconstruction algorithms on coronary atheroma composition: A head-to-head comparison with multimodality near-infrared spectroscopy intravascular ultrasound imaging.

October 21, 2025pubmed logopapers

Authors

Yap NAL,He X,Tanboga IH,Ramasamy A,Kyriakou S,Kitslaar P,Broersen A,Reiber JH,Dijkstra J,Mohammed ASA,Ozkor M,Serruys PW,Moon JC,Mathur A,Baumbach A,Torii R,Pugliese F,Bourantas CV

Affiliations (13)

  • Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University London, UK.
  • Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University London, UK; Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Department of Biostatistics and Cardiology, Nisantasi University Medical School, Istanbul, Turkey.
  • Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University London, UK; Department of Biostatistics and Cardiology, Nisantasi University Medical School, Istanbul, Turkey.
  • Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands; Medis Medical Imaging Systems, Leiden, the Netherlands.
  • Medis Medical Imaging Systems, Leiden, the Netherlands.
  • Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Department of Mechanical Engineering, University College London, London, UK.
  • Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, UK.
  • Faculty of Medicine, National Heart & Lung Institute, Imperial College London, UK; Department of Cardiology, National University of Ireland, Galway, Ireland.
  • Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, UK; Institute of Cardiovascular Sciences, University College London, London, UK.
  • Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University London, UK; Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, UK.
  • Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University London, UK; Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, UK. Electronic address: [email protected].

Abstract

To evaluate the performance of various computed tomography angiography (CTA) reconstruction methods in assessing coronary plaque composition using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) as the reference standard. Fifteen patients with chronic coronary syndrome underwent CTA and 3-vessel NIRS-IVUS imaging. CTA datasets were reconstructed using a medium-smooth b40f kernel with two slice thicknesses, 0.75 ​mm and 0.50 ​mm, and three strengths of advanced model-based iterative reconstruction (ADMIRE). Plaque components on CTA were classified using fixed and adaptive Hounsfield unit (HU) thresholds while NIRS-IVUS classification employed a deep learning method validated against histology. Matched CTA and NIRS-IVUS images were analyzed to quantify fibrotic tissue (FT), necrotic core (NC), and calcific (Ca) volumes and areas at both segment- and lesion-level. The intraclass correlation coefficient (ICC) and Surface Under the Cumulative Ranking Curve (SUCRA) scores were used to determine the best-performing reconstruction approach. Fifty vessels were included in the final analysis. CTA showed weak correlation with NIRS-IVUS for FT (ICC <0.43), good correlation for Ca (ICC 0.42-0.83), and poor correlation for NC, except when using reconstruction approach ADMIRE 2, 0.50 ​mm slice thickness, and fixed HU cutoffs, which demonstrated moderate correlation for NC (segment-level ICC ​= ​0.67; lesion-level ICC ​= ​0.61). This approach ranked highest on SUCRA plots. CTA reconstruction parameters influence plaque composition analysis. The combination of an intermediate-strength IR, thin slice thickness, and fixed HU cutoffs yields the most accurate tissue characterization compared to NIRS-IVUS as the reference standard.

Topics

Journal Article

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