Endoscopic three-categorical diagnosis of Helicobacter pylori infection using linked color imaging and deep learning: a single-center prospective study (with video)

BACKGROUND

Helicobacter pylori (H. pylori) eradication is required to reduce incidence related to gastric cancer. Recently, it was found that even after the successful eradication of H. pylori, an increased, i.e., moderate, risk of gastric cancer persists in patients with advanced mucosal atrophy and/or intestinal metaplasia. This study aimed to develop a computer-aided diagnosis (CAD) system to classify the status of H. pylori infection of patients into three categories: uninfected (with no history of H. pylori infection), currently infected, and post-eradication.

METHODS

The CAD system was based on linked color imaging (LCI) combined with deep learning (DL). First, a validation dataset was formed for the CAD systems by recording endoscopic movies of 120 subjects. Next, a training dataset of 395 subjects was prepared to enable DL. All endoscopic examinations were recorded using both LCI and white-light imaging (WLI). These endoscopic data were used to develop two different CAD systems, one for LCI (LCI-CAD) and one for WLI (WLI-CAD) images.

RESULTS

The diagnostic accuracy of the LCI-CAD system was 84.2% for uninfected, 82.5% for currently infected, and 79.2% for post-eradication status. Comparisons revealed superior accuracy of diagnoses based on LCI-CAD data relative based on WLI-CAD for uninfected, currently infected, and post-eradication cases. Furthermore, the LCI-CAD system demonstrated comparable diagnostic accuracy to that of experienced endoscopists with the validation data set of LCI.

CONCLUSIONS

The results of this study suggest the feasibility of an innovative gastric cancer screening program to determine cancer risk in individual subjects based on LCI-CAD.

Associations between interleukin-1 polymorphisms and gastric cancers among three ethnicities

AIM

To investigate the associations between interleukin (IL)-1B and IL-1RN polymorphisms and gastric cancers among the Tibet, Hui and Han ethnicities.

METHODS

Genomic DNA was extracted from peripheral blood of 210, 205, and 202 healthy volunteers and from 155, 158, and 197 gastric cancer patients from the Tibet, Hui, and Han populations, respectively. Polymorphisms in IL-1B and IL-1RN were analyzed by denaturing high-performance liquid chromatography.

RESULTS

Carriers of the IL-1B-31 CC genotype had an increased risk of intestinal type gastric cancer [odds ratio (OR) = 2.17, P = 0.037] in the Tibet ethnicity. Carriers of the IL-1B 2/L genotype had an increased risk of both intestinal and diffuse types of gastric cancer (OR = 2.08, 2.31, P = 0.007, 0.016, respectively) in the Hui ethnicity. In the Han population, carriers of the IL-1B-31 CC, IL-1B-511CT, TT genotypes had increased risk of intestinal type gastric cancer (OR = 2.51, 2.74, 5.66, P = 0.005, 0.002, 0.000, respectively).

CONCLUSION

IL-1B and IL-RN genotypes may differentially contribute to gastric cancer among the Tibet, Hui, and Han ethnicities in the Qinghai area of China.