Abstract
Endoscopic resection is recommended for gastric neoplasms confined to mucosa or superficial submucosa. The determination of invasion depth is based on gross morphology assessed in endoscopic images, or on endoscopic ultrasound. These methods have limited accuracy and pose an inter-observer variability. Several studies developed deep-learning (DL) algorithms classifying invasion depth of gastric cancers. Nevertheless, these algorithms are intended to be used after definite diagnosis of gastric cancers, which is not always feasible in various gastric neoplasms. This study aimed to establish a DL algorithm for accurately predicting submucosal invasion in endoscopic images of gastric neoplasms. Pre-trained convolutional neural network models were fine-tuned with 2899 white-light endoscopic images. The prediction models were subsequently validated with an external dataset of 206 images. In the internal test, the mean area under the curve discriminating submucosal invasion was 0.887 (95% confidence interval: 0.849–0.924) by DenseNet−161 network. In the external test, the mean area under the curve reached 0.887 (0.863–0.910). Clinical simulation showed that 6.7% of patients who underwent gastrectomy in the external test were accurately qualified by the established algorithm for potential endoscopic resection, avoiding unnecessary operation. The established DL algorithm proves useful for the prediction of submucosal invasion in endoscopic images of gastric neoplasms.
Highlights
Surgical resection has been the standard treatment method for gastric neoplasms
Consecutive patients who were found to have any type of gastric neoplasm during upper gastrointestinal endoscopy between 2010 and 2017 at Chuncheon Sacred Heart Hospital were enrolled
The external test set comprised 206 images from 197 patients, and the submucosa-invaded lesion images accounted for 38.8% (n = 80)
Summary
Surgical resection has been the standard treatment method for gastric neoplasms. the advancement of endoscopic techniques over recent years has led to a better understanding of various therapeutic indications and outcomes, allowing for the replacement of the classical surgery with endoscopic resection, in a subset of gastric cancer patients who meet certain specific criteria [1,2]. The commonly accepted consensus allows for endoscopic resection with curative intent, in cases of gastric neoplasms without lymph node metastasis (LNM). The indication for endoscopic resection is based on a combination of factors associated with a low LNM rate, which are retrospectively assessed in surgically resected specimens [3,4]. These factors include the depth of invasion, its specific size, and morphological and histological lesion properties [5]. The endoscopic resection is a greatly preferred method, owing to its minimal invasiveness and quick patient recovery [2]
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