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Impact of Photon Counting Detector CT Derived Virtual Monoenergetic Images on the Diagnosis of Pulmonary Embolism

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Purpose: To assess the impact of virtual-monoenergetic-image (VMI) energies on the diagnosis of pulmonary embolism (PE) in photon-counting-detector computed-tomography (PCD-CT). Methods: Eighty patients (median age 60.4 years) with suspected PE… Click to show full abstract

Purpose: To assess the impact of virtual-monoenergetic-image (VMI) energies on the diagnosis of pulmonary embolism (PE) in photon-counting-detector computed-tomography (PCD-CT). Methods: Eighty patients (median age 60.4 years) with suspected PE were retrospectively included. Scans were performed on PCD-CT in the multi-energy mode at 120 kV. VMIs from 40–70 keV in 10 keV intervals were reconstructed. CT-attenuation was measured in the pulmonary trunk and the main branches of the pulmonary artery. Signal-to-noise (SNR) ratio was calculated. Two radiologists evaluated subjective-image-quality (noise, vessel-attenuation and sharpness; five-point-Likert-scale, non-diagnostic–excellent), the presence of hardening artefacts and presence/visibility of PE. Results: Signal was highest at the lowest evaluated VMI (40 keV; 1053.50 HU); image noise was lowest at the highest VMI (70 keV; 15.60 HU). Highest SNR was achieved at the lowest VMI (p < 0.05). Inter-reader-agreement for subjective analysis was fair to excellent (k = 0.373–1.000; p < 0.001). Scores for vessel-attenuation and sharpness were highest at 40 keV (both:5, range 4/3–5; k = 1.000); scores for image-noise were highest at 70 keV (4, range 3–5). The highest number of hardening artifacts were reported at 40 keV (n = 22; 28%). PE-visualization was rated best at 50 keV (4.7; range 4–5) and decreased with increasing VMI-energy (r = −0.558; p < 0.001). Conclusions: While SNR was best at 40 keV, subjective PE visibility was rated highest at 50 keV, potentially owing to the lower image noise and hardening artefacts.

Keywords: diagnosis pulmonary; pulmonary embolism; vmi; virtual monoenergetic; kev; image

Journal Title: Diagnostics
Year Published: 2022

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