Digestive and Liver Disease 相关网址

ALIMENTARY TRACT| VOLUME 54, ISSUE 9, P1202-1208, SEPTEMBER 2022

A computer-aided diagnosis system using white-light endoscopy for the prediction of conventional adenoma with high grade dysplasia

• Sijun Meng

• Yueping Zheng

• Wangyue Wang

• Wensheng Pan

• Shuisheng Wu

• Yiqun Hu

• Show all authors

Abstract

Objectives

We developed a computer-aided diagnosis system called ECRC CAD using standard white-light endoscopy (WLE) for predicting conventional adenomas with high-grade dysplasia (HGD) to optimise the patients' management decisions during colonoscopy.

Methods

Pretraining model was used to fine-tune the model parameters by transfer learning. 2,397 images of HGD and 2,487 low-grade dysplasia (LGD) images were randomly assigned (8:1:1) to the training, optimising, and internal validation dataset. The prospective validation dataset is the frames accessed from colonoscope videoes. One independent rural hospital provided an external validation dataset. Histopathological diagnosis was used as the standard criterion. The capability of the ECRC CAD to distinguish HGD was assessed and compared with two expert endoscopists.

Results

The accuracy, sensitivity and specificity for diagnosis of HGD in the internal validation set were 90.5%, 93.2%, 87.9%, respectively. While 88.2%, 85.4%, 89.8%, respectively, for the external validation set. For the prospective validation set, ECRC CAD achieved an AUC of 93.5% in diagnosing HGD. The performance of ECRC CAD in diagnosing HGD was better than that of the expert endoscopist in the external validation set (88.2% vs. 71.5%, P < 0.0001).

Conclusion

ECRC CAD had good diagnostic capability for HGD and enabled a more convenient and accurate diagnosis using WLE.