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28.03.2023 | Computed Tomography

Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers

verfasst von: Jingyu Zhong, Lingyun Wang, Hailin Shen, Jianying Li, Wei Lu, Xiaomeng Shi, Yue Xing, Yangfan Hu, Xiang Ge, Defang Ding, Fuhua Yan, Lianjun Du, Weiwu Yao, Huan Zhang

Erschienen in: European Radiology | Ausgabe 8/2023

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Abstract

Objectives

To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V) at 50% blending (AV-50), and to identify potential factors impacting lesion conspicuity.

Methods

The portal-venous phase scans in abdominal DECT of 47 participants with 84 lesions were prospectively included. The raw data were reconstructed to virtual monoenergetic image (VMI) at 50 keV using filtered back-projection (FBP), AV-50, and DLIR at low (DLIR-L), medium (DLIR-M), and high strength (DLIR-H). A noise power spectrum (NPS) was generated. CT number and standard deviation values of eight anatomical sites were measured. Signal-to-noise (SNR), and contrast-to-noise ratio (CNR) values were calculated. Five radiologists assessed image quality in terms of image contrast, image noise, image sharpness, artificial sensation, and diagnostic acceptability, and evaluated the lesion conspicuity.

Results

DLIR further reduced image noise (p < 0.001) compared to AV-50 while better preserved the average NPS frequency (p < 0.001). DLIR maintained CT number values (p > 0.99) and improved SNR and CNR values compared to AV-50 (p < 0.001). DLIR-H and DLIR-M showed higher ratings in all image quality analyses than AV-50 (p < 0.001). DLIR-H provided significantly better lesion conspicuity than AV-50 and DLIR-M regardless of lesion size, relative CT attenuation to surrounding tissue, or clinical purpose (p < 0.05).

Conclusions

DLIR-H could be safely recommended for routine low-keV VMI reconstruction in daily contrast-enhanced abdominal DECT to improve image quality, diagnostic acceptability, and lesion conspicuity.

Key Points

• DLIR is superior to AV-50 in noise reduction, with less shifts of the average spatial frequency of NPS towards low frequency, and larger improvements of NPS noise, noise peak, SNR, and CNR values.

• DLIR-M and DLIR-H generate better image quality in terms of image contrast, noise, sharpness, artificial sensation, and diagnostic acceptability than AV-50, while DLIR-H provides better lesion conspicuity than AV-50 and DLIR-M.

• DLIR-H could be safely recommended as a new standard for routine low-keV VMI reconstruction in contrast-enhanced abdominal DECT to provide better lesion conspicuity and better image quality than the standard AV-50.

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Titel: Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers
verfasst von: Jingyu Zhong
Lingyun Wang
Hailin Shen
Jianying Li
Wei Lu
Xiaomeng Shi
Yue Xing
Yangfan Hu
Xiang Ge
Defang Ding
Fuhua Yan
Lianjun Du
Weiwu Yao
Huan Zhang
Publikationsdatum: 28.03.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 8/2023
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-023-09556-6

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Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers