J Zeng1, W L Sun, G Y Chen, Q Pan, S Y Yan, C Sun, Z J Xu, J G Fan. 1. Department of Gastroenterology, Center for Fatty Liver, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China.
Abstract
Objective: To investigate the efficiency of FibroScan(FS)and FibroTouch(FT)in liver stiffness measurement(LSM)and fat quantification through a comparative analysis. Methods: The outpatients or hospitalized patients who underwent LSM and fat quantification using FS and FT were enrolled. The differences in success rate and detecting parameters between FS and FT were analyzed, as well as the correlation between FS and FT values. The t-test was used for comparison of normally distributed continuous data between groups, and a one-way analysis of variance or the Kruskal-Wallis test was used for comparison between multiple groups. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. Results: A total of 1621 patients were enrolled. The success rates of FT and FS were 100% and 94.96%, respectively, and the success rate of FS was influenced by sex, age, body mass index, and biochemical markers of liver function. FT has a significantly shorter duration of single detection and a significantly lower number of times of single detection than FS(duration of single detection: 190.21±38.78 s vs 220.89±68.36 s, P < 0.01; number of single detection times: 10.31±1.32 vs 11.81±3.76, P < 0.01), as well as a significantly lower ratio of interquartile range to median of fat quantification in the same patient(5.39%±4.81% vs 17.18%±14.07%, P < 0.01). The LSM and fat quantification of FS were significantly correlated with those of FT(r = 0.645 and 0.620, both Based on the duration and number of times of single detection, success rate, and stability of fat quantification, FT seems to have a better detection efficiency than FS. The detection values of FT and FS can be calculated with regression equations < 0.01). The equations of linear regression were LSM(FT)= 4.435+0.477×LSM(FS); CAP(FT)= 134.71+0.456×CAP(FS). Conclusion: Based on the duration and number of times of single detection, success rate, and stability of fat quantification, FT seems to have a better detection efficiency than FS. The detection values of FT and FS can be calculated with regression equations.
Objective: To investigate the efficiency of FibroScan(FS)and FibroTouch(FT)in liver stiffness measurement(LSM)and fat quantification through a comparative analysis. Methods: The outpatients or hospitalized patients who underwent LSM and fat quantification using FS and FT were enrolled. The differences in success rate and detecting parameters between FS and FT were analyzed, as well as the correlation between FS and FT values. The t-test was used for comparison of normally distributed continuous data between groups, and a one-way analysis of variance or the Kruskal-Wallis test was used for comparison between multiple groups. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. Results: A total of 1621 patients were enrolled. The success rates of FT and FS were 100% and 94.96%, respectively, and the success rate of FS was influenced by sex, age, body mass index, and biochemical markers of liver function. FT has a significantly shorter duration of single detection and a significantly lower number of times of single detection than FS(duration of single detection: 190.21±38.78 s vs 220.89±68.36 s, P < 0.01; number of single detection times: 10.31±1.32 vs 11.81±3.76, P < 0.01), as well as a significantly lower ratio of interquartile range to median of fat quantification in the same patient(5.39%±4.81% vs 17.18%±14.07%, P < 0.01). The LSM and fat quantification of FS were significantly correlated with those of FT(r = 0.645 and 0.620, both Based on the duration and number of times of single detection, success rate, and stability of fat quantification, FT seems to have a better detection efficiency than FS. The detection values of FT and FS can be calculated with regression equations < 0.01). The equations of linear regression were LSM(FT)= 4.435+0.477×LSM(FS); CAP(FT)= 134.71+0.456×CAP(FS). Conclusion: Based on the duration and number of times of single detection, success rate, and stability of fat quantification, FT seems to have a better detection efficiency than FS. The detection values of FT and FS can be calculated with regression equations.