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Ultra-high resolution spectral photon-counting CT outperforms dual layer CT for lung imaging: Results of a phantom study - 02/10/24

Doi : 10.1016/j.diii.2024.09.011 
Hugo Lacombe a, b, 1, Joey Labour a, 1, Fabien de Oliveira c, Antoine Robert a, Angèle Houmeau a, Marjorie Villien b, Sara Boccalini a, d, Jean-Paul Beregi c, Philippe C. Douek a, d, Joël Greffier c, 2, Salim A. Si-Mohamed a, d, 2,
a Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, INSERM, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France 
b CT Clinical Science, Philips, 92150, Suresnes, France 
c IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France 
d Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69677, Bron, France 

Corresponding author.
Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Wednesday 02 October 2024

Highlights

Ultra high-resolution spectral photon-counting CT reduces image noise and improves detectability of lung lesions in an anthropomorphic phantom compared to dual-layer CT.
Image quality obtained with ultra-high resolution spectral photon-counting CT suggests greater potential for ultra-high-resolution dose optimization compared to dual-layer CT.
Lung images obtained with ultra-high resolution spectral photon-counting CT are better rated for clinical use by radiologists at all dose levels.

Le texte complet de cet article est disponible en PDF.

Abstract

Purpose

The purpose of this study was to compare lung image quality obtained with ultra-high resolution (UHR) spectral photon-counting CT (SPCCT) with that of dual-layer CT (DLCT), at standard and low dose levels using an image quality phantom and an anthropomorphic lung phantom.

Methods

An image quality phantom was scanned using a clinical SPCCT prototype and an 8 cm collimation DLCT from the same manufacturer at 10 mGy. Additional acquisitions at 6 mGy were performed with SPCCT only. Images were reconstructed with dedicated high-frequency reconstruction kernels, slice thickness between 0.58 and 0.67 mm, and matrix between 5122 and 10242 mm, using a hybrid iterative algorithm at level 6. Noise power spectrum (NPS), task-based transfer function (TTF) for iodine and air inserts, and detectability index (d’) were assessed for ground-glass and solid nodules of 2 mm to simulate highly detailed lung lesions. Subjective analysis of an anthropomorphic lung phantom was performed by two radiologists using a five-point quality score.

Results

At 10 mGy, noise magnitude was reduced by 29.1 % with SPCCT images compared to DLCT images for all parameters (27.1 ± 11.0 [standard deviation (SD)] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 6 mGy with SPCCT images, noise magnitude was reduced by 8.9 % compared to DLCT images at 10 mGy (34.8 ± 14.1 [SD] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 10 mGy and 6 mGy, average NPS spatial frequency (fav) was greater for SPCCT images (0.75 ± 0.17 [SD] mm-1) compared to DLCT images at 10 mGy (0.55 ± 0.04 [SD] mm-1) while remaining constant from 10 to 6 mGy. At 10 mGy, TTF at 50 % (f50) was greater for SPCCT images (0.92 ± 0.08 [SD] mm-1) compared to DLCT images (0.67 ± 0.06 [SD] mm-1) for both inserts. At 6 mGy, f50 decreased by 1.1 % for SPCCT images, while remaining greater compared to DLCT images at 10 mGy (0.91 ± 0.06 [SD] mm-1 vs. 0.67 ± 0.06 [SD] mm-1, respectively). At both dose levels, d’ were greater for SPCCT images compared to DLCT for all clinical tasks. Subjective analysis performed by two radiologists revealed a greater median image quality for SPCCT (5; Q1, 4; Q3, 5) compared to DLCT images (3; Q1, 3; Q3, 3).

Conclusion

UHR SPCCT outperforms DLCT in terms of image quality for lung imaging. In addition, UHR SPCCT contributes to a 40 % reduction in radiation dose compared to DLCT.

Le texte complet de cet article est disponible en PDF.

Keywords : Iterative reconstruction, Lung, Multidetector computed tomography, Spectral photon- counting CT, Task-based image quality assessment

Abbreviations : CT, CTDIvol, DECT, DLCT, EID, HU, iDose4, NPS, ROI, SD, SPCCT, TTF, UHR


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© 2024  Publié par Elsevier Masson SAS.
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