Efficacy of 3D-nnU-Net model of CT virtual monoenergetic images,non-linear blending images and mixed-energy images for automatically segmenting advanced gastric cancer
10.13929/j.issn.1003-3289.2025.05.013
- VernacularTitle:CT虚拟单能量图、非线性融合图及混合能量图3D-nnU-Net模型自动分割进展期胃癌效能
- Author:
Bowen LIU
1
;
Xiaoxiao WANG
;
Chao LU
;
Zhixuan WANG
;
Jiulou ZHANG
;
Zehui WANG
;
Siyuan LU
;
Xiaoyue JIANG
;
Mingyao QI
;
Donggang PAN
;
Xiuhong SHAN
Author Information
1. 江苏大学附属人民医院医学影像科,江苏镇江 212002
- Publication Type:Journal Article
- Keywords:
stomach neoplasms;
artificial intelligence;
tomography,X-ray computed;
image segmentation
- From:
Chinese Journal of Medical Imaging Technology
2025;41(5):753-758
- CountryChina
- Language:Chinese
-
Abstract:
Objective To compare the segmenting efficacy of automatic segmentation models for advanced gastric cancer(AGC)on CT virtual monoenergetic images(VMI),non-linear blending images(NLBI)and mixed-energy images(MEI)based on 3D-nnU-Net.Methods Totally 216 cases of AGC were retrospectively enrolled,among them 185 cases were used to construct,train and validate models and divided into training set(n=154)and test set(n=31)at the ratio of 5∶1,while the other 31 cases were used as validation set to evaluate the generalization of the models.The 70 keV energy level VMI(VMI70 keV),NLBI and MEI were reconstructed with whole-abdominal dual-energy mode venous CT,and automatic segmentation models of AGC,including VMI70 keV,NLBI and MEI models were constructed using 3D-nnU-Net,respectively.Taken manually segmented results as golden standards,the efficacy of each model for segmenting all lesions and T2 stage lesions in test set and validation set were evaluated using Dice similarity coefficient(DSC),intersection over union(IoU)and average symmetric surface distance(ASSD).Results For all lesions in test and validation sets,DSC of 3 models were all＞0.80.DSC and IoU of VMI70 keV and NLBI models were both higher,while their ASSD was lower than those of MEI model(all P＜0.05).For T2 stage AGC in both test set and validation set(each n=5),DSC of MEI model was lower than that of VMI70 keV and NLBI models(both P＜0.05),while IoU of MEI model was lower than that of VMI70 keV model(P＜0.05),and its ASSD was higher than that of NLBI model(P＜0.05).Conclusion All 3D-nnU-Net-based VMI70 keV,NLBI and MEI models could effectively segment AGC on dual-energy CT images,and the segmentation efficacy of the former two were better.
