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Article Dans Une Revue European Radiology Année : 2021

Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data

Résumé

To compare the spectral performance of dual-energy CT (DECT) platforms using task-based image quality assessment based on phantom data. Materials and methods: Two CT phantoms were scanned on four DECT platforms: fast kV-switching CT (KVSCT), split filter CT (SFCT), dual-source CT (DSCT), and dual-layer CT (DLCT). Acquisitions on each phantom were performed using classical parameters of abdomen-pelvic examination and a CTDIvol at 10 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 140 keV of virtual monoenergetic images. A detectability index (d') was computed to model the detection task of two contrast-enhanced lesions as function of keV. Results: The noise magnitude decreased from 40 to 70 keV for all DECT platforms, and the highest noise magnitude values were found for KVSCT and SFCT and the lowest for DSCT and DLCT. The average NPS spatial frequency shifted towards lower frequencies as the energy level increased for all DECT platforms, smoothing the image texture. TTF values decreased with the increase of keV deteriorating the spatial resolution. For both simulated lesions, higher detectability (d' value) was obtained at 40 keV for DLCT, DSCT, and SFCT but at 70 keV for KVSCT. The detectability of both simulated lesions was highest for DLCT and DSCT. Conclusion: Highest detectability was found for DLCT for the lowest energy levels. The task-based image quality assessment used for the first time for DECT acquisitions showed the benefit of using low keV for the detection of contrast-enhanced lesions.
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Dates et versions

hal-03623568 , version 1 (29-03-2022)

Identifiants

Citer

J. Greffier, S. Si-Mohamed, D. Dabli, H. de Forges, A. Hamard, et al.. Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data. European Radiology, 2021, 31 (7), pp.5324-5334. ⟨10.1007/s00330-020-07671-2⟩. ⟨hal-03623568⟩
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