Methods for quantitative measurement in the computed tomography images of Tusanqi related hepatic sinusoidal obstruction syndrome
10.3760/cma.j.issn.0254-1432.2018.10.008
- VernacularTitle:土三七相关肝窦阻塞综合征的计算机断层扫描图像定量测定方法
- Author:
Chao WANG
1
;
Xingwang WU
;
Wentao XIE
;
Xiaofei REN
;
Fen QI
;
Jianming XU
Author Information
1. 安徽医科大学第一附属医院消化内科
- Keywords:
Tusanqi;
Sinusoidal obstruction syndrome;
CT;
Volume measurement;
Stereology;
Threshold;
Region growing
- From:
Chinese Journal of Digestion
2018;38(10):687-690
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the feasibility of applying threshold and region-growing based algorithm in computed tomography (CT) images for the estimation of hepatic lesion volumes in patients with Tusanqi related hepatic sinusoidal obstruction syndrome (SOS).Methods From July 2012 to January 2015,at the First Affiliated Hospital of Anhui Medical University,20 patients who were diagnosed with SOS and had complete CT images were enrolled.Stereology and threshold and regiongrowing based algorithm were performed to estimate volumes of the low-density region in the liver,respectively,and then the measured volumes of hepatic lesion and operation time were compared.Paired samples t test and the Bland-Altman statistical test were performed for statistical analysis.Results The hepatic lesion volumes measured by stereology and threshold and region-growing based algorithm were (1.001±0.327) dm3 and (1.045±0.363) dm3,respectively,and the difference was not statistically significant (P＞0.05).The consistency between the two methods was good.The operation time of threshold and region-growing based algorithm was (597.55±52.86) s (minimum 500 s),which was less than that of stereology (1 251.60 ± 105.88) s (minimum 1 075 s),and the difference was statistically significant (t =32.808,P＜ 0.01).Conclusion There is no statistically significant difference in the measured hepatic lesion volume of patients with SOS between stereology and the threshold and regiongrowing based algorithm,but the operation time of threshold and region-growing based algorithm is shorter.
