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📄 ResearchMay 26, 2026

Comparative Study on Image Quality of Deep Learning and Adaptive Statistical Iterative Reconstruction-V in Thin Layer CT of liver Lesions

Objective:This study aims to compare the advantages and disadvantages of DLIR and adaptive statistical iterative reconstruction-V (ASIR-V) in thin-slice (2.5 mm) CT images of hepatic lesions characterized by high and low contrast. Additionally, the study seeks to determine the optimal DLIR strength for the evaluation of liver lesions. Methods:A retrospective analysis was performed on 90 patients who underwent abdominal contrast-enhanced CT scans. Group A comprised 48 patients with low-contrast lesions, while Group B included 42 patients with high-contrast lesions. The acquired images were reconstructed using post-processing DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) strengths, all with a slice thickness of 2.5 mm (subgroups A1-A3, B1-B3). Furthermore, images were reconstructed with ASIR-V at 50% strength at slice thicknesses of 2.5 mm and 5 mm (subgroups A4/B4 and A5/B5, respectively). CT values and standard deviations (SD) of the liver and lesions were measured, and the corresponding signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The edge rise slope (ERS) was determined using ImageJ software by measuring CT values along a line from the liver parenchyma to the lesion. Objective metrics were compared using one-way ANOVA, with independent samples t-tests applied for inter-group differences. Subjective scoring, which encompassed noise level, diagnostic confidence, and lesion margin delineation, was conducted by two radiologists, with differences analyzed using the Kappa test. Results: Objective evaluation revealed a progressive decrease in lesion SD and a progressive increase in SNR and CNR from subgroups A1/B1 to A3/B3. The SD of Group A2 decreased by 57.4% compared to A4, while the SNR and CNR of A2 icreased by 19.3% and 24.6% compared to A4. Although subgroup B2 had a lower SNR than B5, the difference was not statistically significant. SNR and CNR in B2 increased by 24.1% and 11.9%, respectively, compared to B4. ERS gradually decreased from A1/B1 to A3/B3. ERS values in A2 and B2 increased by 27.0% and 39.4%, respectively, relative to A5 and B5. Although A3 had a lower ERS than A1 and A2, all DLIR subgroups exhibited higher ERS than A5; similar trends were observed in Group B. Subjective evaluation indicated good inter-reader agreement (Kappa > 0.61, p < 0.05). As DLIR strength increased, noise scores rose progressively in both groups. However, noise in A2 and B2 was lower than in A4/A5 and B4/B5. Diagnostic confidence and lesion margin delineation scores were highest in A2 and B2, while all subjective scores were lowest in A5 and B5. Discussion: Most prior studies evaluated the liver, vessels, or confirmed that image quality can be guaranteed at low doses. However, there are few studies on specific individual lesions. Therefore, this study aims to investigate specific individual lesions. The details and detection rate were analyzed separately to confirm the clinical acceptability of 2.5-mm DLIR image in different contrast lesions. Conclusion: For both high- and low-contrast hepatic lesions, DLIR provides superior image quality compared to ASIR-V, with the 2.5mm DLIR-M setting being optimal. DLIR-M reduces image noise, improves spatial resolution, and produces images more suitable for diagnostic purposes.

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Source

https://www.medrxiv.org/content/10.64898/2026.05.23.26353923v1?rss=1