A clinical study of deep learning image reconstruction algorithms in liver dual-energy CT with reduced radiation dose to further improve image quality and lesion diagnostic confidence
10.3760/cma.j.cn112149-20240327-00160
- VernacularTitle:应用深度学习图像重建算法提高低辐射剂量肝脏能谱CT图像质量和病灶诊断信心的临床研究
- Author:
Yuncheng LI
1
;
Yuguo LI
1
;
Junlin YANG
1
;
Jian SONG
1
;
Xing TANG
1
;
Wei DENG
1
;
Zhen WANG
1
;
Jinxiu YANG
1
;
Bin LIU
1
;
Yongqiang YU
1
;
Xiaohu LI
1
Author Information
1. 安徽医科大学第一附属医院医学影像科，合肥 230022
- Publication Type:Journal Article
- Keywords:
Tomography, X-ray computed;
Deep learning;
Image reconstruction;
Radiation dose
- From:
Chinese Journal of Radiology
2025;59(1):43-49
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the feasibility of applying deep learning image reconstruction (DLIR) in low-radiation dose liver dual-energy CT to further improve image quality, diagnostic confidence of lesion, and accuracy of iodine concentration (IC) measurement.Methods:This prospective cohort study enrolled 60 patients scheduled for enhanced liver CT at the First Affiliated Hospital of Anhui Medical University from June 2023 to January 2024. The participants were randomly assigned into the standard dose group and low radiation dose group with 30 cases in each using randomized block method. The standard radiation dose group underwent standard-radiation dose 120 kVp scans during the venous phase, while the low radiation dose group underwent low radiation dose scans with a rapid kVp-switching spectral scanning mode at 80 kVp and 140 kVp. The effective radiation dose (ED) was calculated for both groups. The standard radiation dose group was reconstructed using adaptive statistical iterative reconstruction-V (ASIR-V) algorithm 40% (AR40 120 kVp). The low radiation dose group using high-intensity DLIR (DLIR-H) to reconstructed 40 keV and 50 keV virtual monoenergetic images (VMI) (DH-VMI 40 keV, DH-VMI 50 keV). The image quality of the above three groups was objectively evaluated through the measurement of image noise and calculation of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the liver and portal vein; and the image quality was subjectively scored for image noise, contrast, lesion conspicuity, and diagnostic confidence. In the low radiation dose group, DLIR-H and ASIR-V40% reconstructed iodine maps were used to measure the liver and portal vein of IC values, standard deviations (SD), and coefficients of variation (CV). One-way analysis of variance or Kruskal-Wallis H test was used to compare the differences of subjective and objective image quality among the three groups, and paired t-test was used to compare the differences in measurement indexes between DLIR-H and ASIR-V40% reconstructed iodine maps. Results:The ED in the low radiation dose group [(2.2±0.5) mSv] was reduced by 56.8% compared to the conventional radiation dose group [(5.4±1.4) mSv]. Objective evaluations demonstrated that DH-VMI 40 keV had higher image noise, CNR, and SNR for liver and portal veins compared to AR40 120 kVp ( P<0.001). DH-VMI 50 keV had lower image noise ( P=0.200), with higher CNR and SNR for the liver and portal vein compared to AR40 120 kVp( P<0.001). In subjective evaluation, there was no statistically significant difference in image noise scores between DH-VMI 40 keV and AR40 120 kVp ( P>0.05), while the image noise score for DH-VMI 50 keV was lower than that of AR40 120 kVp ( P<0.05). Both DH-VMI 40 keV and DH-VMI 50 keV had higher scores for contrast, lesion conspicuity, and diagnostic confidence compared to those of AR40 120 kVp ( P<0.05). In the low radiation dose group, there was no statistically significant difference in IC values for the liver and portal vein between the ASIR-V40% and DLIR-H algorithm reconstructed iodine maps ( P>0.05). The SD and CV of liver and portal vein in the DLIR-H reconstructed iodine maps were lower than those in the ASIR-V40% reconstructed iodine maps ( P<0.001). Conclusions:DLIR can effectively reduce the image noise of low-energy (40, 50 keV) VMI, enhance lesion conspicuity and diagnostic confidence, and improve measurement accuracy without affecting IC values.
