A pilot study on the use of artificial intelligence in gastric cancer diagnosis with real endoscopic screening images (Preprint)
Authors: Furukawa Koichi 
Published: May 2023

BACKGROUND

Gastric cancer endoscopy is widely regarded as a highly accurate method of diagnosis, thanks to numerous advancements in recent years. These include quality control by secondary interpretation, efficiency improvements by transmission, and other attempts aimed at enhancing the accuracy and efficacy of the procedure. Despite these efforts, the field of endoscopy has faced challenges in recent years, as the increasing prevalence of gastric cancer has put greater pressure on medical professionals to develop more effective diagnostic tools. In particular, image analysis through computer-aided diagnosis (CAD) using artificial intelligence (AI) has emerged as a promising approach for improving the accuracy of endoscopic examination.

OBJECTIVE

The present study sought to investigate the potential benefits of introducing CAD into the secondary interpretation stage of gastric cancer endoscopy.

METHODS

By analyzing endoscopic images obtained from patients who underwent endoscopic submucosal dissection (ESD) of gastric cancer, the study aimed to assess the performance of AI in identifying and diagnosing lesions.

RESULTS

The results of the study demonstrate that introducing CAD into the current system could significantly improve the sensitivity of gastric cancer diagnosis in endoscopic examination. Specifically, the sensitivity of cancer detection during ESD and pre-ESD examination was found to be 93.2%, and 76.5% during cancer detection. Additionally, cancer was detected by AI in 75% of the images obtained before diagnosis, which did not ultimately lead to a cancer diagnosis.
These findings have important implications for the future of gastric cancer endoscopy. By highlighting the potential benefits of introducing CAD into the current system, the study underscores the importance of technological advancements in improving the accuracy and efficacy of endoscopic examination in clinical practice. In addition, the study suggests that continued efforts to develop and refine CAD systems for use in medical imaging could help to reduce the burden on medical professionals and improve patient outcomes.
It should be noted that this study is not without its limitations. For example, the sample size was relatively small, and the study was conducted at a single hospital. As such, further research is needed to confirm the effectiveness of CAD in gastric cancer endoscopy across a wider range of settings and patient populations.

CONCLUSIONS

In conclusion, the present study provides valuable insights into the potential effectiveness of CAD in gastric cancer endoscopy. By demonstrating the potential benefits of this approach for improving the accuracy and efficacy of endoscopic examination, the study offers important guidance for medical professionals and researchers seeking to enhance the diagnosis and treatment of gastric cancer.

CLINICALTRIAL

This study protocol was reviewed and approved by Niigata City General Hospital Clinical Research Ethics Committee, approval number 20-048. The committee could have given an exemption from the written request for informed consent because the study examined retrospectively anonymized images under the condition of complete personal information management.