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. 2024 Oct 17;14(20):2308.
doi: 10.3390/diagnostics14202308.

Image Quality and Lesion Detectability of Low-Concentration Iodine Contrast and Low Radiation Hepatic Multiphase CT Using a Deep-Learning-Based Contrast-Boosting Model in Chronic Liver Disease Patients

Yewon Lim  1 , Jin Sil Kim  1 , Hyo Jeong Lee  1 , Jeong Kyong Lee  1 , Hye Ah Lee  2 , Chulwoo Park  3
Affiliations

Image Quality and Lesion Detectability of Low-Concentration Iodine Contrast and Low Radiation Hepatic Multiphase CT Using a Deep-Learning-Based Contrast-Boosting Model in Chronic Liver Disease Patients

Yewon Lim et al. Diagnostics (Basel). .

Abstract

Background: This study investigated the image quality and detectability of double low-dose hepatic multiphase CT (DLDCT, which targeted about 30% reductions of both the radiation and iodine concentration) using a vendor-agnostic deep-learning-based contrast-boosting model (DL-CB) compared to those of standard-dose CT (SDCT) using hybrid iterative reconstruction.

Methods: The CT images of 73 patients with chronic liver disease who underwent DLDCT between June 2023 and October 2023 and had SDCT were analyzed. Qualitative analysis of the overall image quality, artificial sensation, and liver contour sharpness on the arterial and portal phase, along with the hepatic artery clarity was conducted by two radiologists using a 5-point scale. For quantitative analysis, the image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured. The lesion conspicuity was analyzed using generalized estimating equation analysis. Lesion detection was evaluated using the jackknife free-response receiver operating characteristic figures-of-merit.

Results: Compared with SDCT, a significantly lower effective dose (16.4 ± 7.2 mSv vs. 10.4 ± 6.0 mSv, 36.6% reduction) and iodine amount (350 mg iodine/mL vs. 270 mg iodine/mL, 22.9% reduction) were utilized in DLDCT. The mean overall arterial and portal phase image quality scores of DLDCT were significantly higher than SDCT (arterial phase, 4.77 ± 0.45 vs. 4.93 ± 0.24, AUCVGA 0.572 [95% CI, 0.507-0.638]; portal phase, 4.83 ± 0.38 vs. 4.92 ± 0.26, AUCVGA 0.535 [95% CI, 0.469-0.601]). Furthermore, DLDCT showed significantly superior quantitative results for the lesion contrast-to-noise ratio (7.55 ± 4.55 vs. 3.70 ± 2.64, p < 0.001) and lesion detectability (0.97 vs. 0.86, p = 0.003).

Conclusions: In patients with chronic liver disease, DLDCT using DL-CB can provide acceptable image quality without impairing the detection and evaluation of hepatic focal lesions compared to SDCT.

Keywords: deep learning; image reconstruction; low iodine concentration; multidetector computed tomography; radiation.

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Conflict of interest statement

Author Chulwoo Park was employed by the company Siemens Healthineers Ltd. All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Participant flowchart.
Figure 2
Figure 2
A 65-year-old man with a 0.8 cm sized hepatocellular carcinoma at segment 5 of the liver (arrows). Arterial phase (a), portal phase (b), and delayed phase (c) images of a double low-dose CT using a deep-learning-based contrast-boosting model show a well-enhancing nodule on the arterial phase (a), with washout on the portal phase (b) and the delayed phase (c).
Figure 3
Figure 3
A 53-year-old man with a 2 cm sized hepatocellular carcinoma at segment 2 of the liver (arrows). Arterial phase (a), portal phase (b), and delayed phase (c) images of a standard-dose CT using hybrid iterative reconstruction show a well-enhancing nodule in the arterial phase (a), with washout on the portal phase (b) and the delayed phase (c).
Figure 4
Figure 4
A 54-year-old man with a 0.4 cm sized small focal low density at segment 2 of the liver (arrows). A double low-dose CT using a deep-learning-based contrast-boosting model (a) shows better conspicuity (Reviewer 1, 4; Reviewer 2, 5) of the focal lesion (arrows) than standard-dose CT using hybrid iterative reconstruction (Reviewer 1, 2; Reviewer 2, 1) (b) at portal phase images (time interval: 11 months). Two reviewers evaluated the double low-dose CT using a deep-learning-based contrast-boosting model and standard-dose CT using hybrid iterative reconstruction. The results demonstrated no difference in overall image quality.
Figure 5
Figure 5
An 82-year-old man with a 0.5 cm sized enhancing nodule at segment 6 of the liver (arrows). A double low-dose CT using a deep-learning-based contrast-boosting model (a) shows better conspicuity (Reviewer 1, 5; Reviewer 2, 4) of the focal lesion (arrows) than standard-dose CT using hybrid iterative reconstruction (Reviewer 1, 5; Reviewer 2, 3) (b) at arterial phase images (time interval: 4 months). Two reviewers evaluated the double low-dose CT using deep-learning-based contrast-boosting model and standard-dose CT using hybrid iterative reconstruction. The results demonstrated no difference in overall image quality.
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