Author/Authors :
Wang, Yi School of Biomedical Engineering - Health Science Center - Shenzhen University - Shenzhen, China , Huang, Kun Department of Radiology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Chen, Jie Department of Gastroenterology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Luo, Yanji Department of Radiology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Zhang, Yu Department of Gastroenterology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Jia, Yingmei Department of Radiology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Xu, Ling Faculty of Medicine and Dentistry - University of Western Australia - Perth, Australia , Chen, Minhu Department of Gastroenterology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Huang, Bingsheng School of Biomedical Engineering - Health Science Center - Shenzhen University - Shenzhen, China , Ni, Dong School of Biomedical Engineering - Health Science Center - Shenzhen University - Shenzhen, China , Li, Zi-Ping Department of Radiology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China , Feng, Shi-Ting Department of Radiology - The First Affliated Hospital - Sun Yat-Sen University - Guangzhou, China
Abstract :
We propose a computer-aided method to assess response to drug treatment, using CT imaging-based volumetric and density
measures in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and difiuse liver metastases. Methods. Twenty-
ve patients with GEP-NETs with difiuse liver metastases were enrolled. Pre- and posttreatment CT examinations were retrospectively
analyzed. Total tumor volume (volume) and mean volumetric tumor density (density) were calculated based on tumor segmentation on
CT images. The maximum axial diameter (tumor size) for each target tumor was measured on pre- and posttreatment CT images
according to Response Evaluation Criteria In Solid Tumors (RECIST). Progression-free survival (PFS) for each patient was measured
and recorded. Results. Correlation analysis showed inverse correlation between change of volume and density (Δ(V + D)), change of
volume (ΔV), and change of tumor size (ΔS) with PFS (r = −0.653, P = 0.001; r = −0.617, P = 0.003; r = −0.548, P = 0.01, respectively).
There was no linear correlation between ΔD and PFS (r = −0.226, P = 0.325). Conclusion. THe changes of volume and density derived
from CT images of all lesions showed a good correlation with PFS and may help assess treatment response.
