AI Platform Doubles Detection Rates for Early-Stage Esophageal Cancer

Esophageal cancer is often asymptomatic, but experienced clinicians can detect tumors and precancerous lesions with endoscopies. The five-year survival rate is over 90 percent when the tumor is treated during the early stages while the clinical outcomes decline sharply once patients start experiencing symptoms. The study, published in the journal Science Translational Medicine, described an architecture driven by deep learning algorithms, which are trained via datasets of more than 190,000 esophageal images gathered from several clinics in China.

The clinical trial, run by researchers from Taizhou Hospital in Zhejiang Province and Wuhan University's Renmin Hospital, recruited more than 3,000 participants who underwent endoscopies. The AI system was used on half the volunteers.

This platform helps double the detection rate for high-risk esophageal lesions (1.8 percent) compared with that in the control group (0.9 percent), according to the study.

Also, the real-time AI tool has shown a high sensitivity and specificity of 89.7 percent and 98.5 percent, respectively, in the real world.

"The endoscopic assistance system, to a significant extent, enables endoscopists with less experience to enhance detection rates of high-risk esophageal lesions, thereby, reducing the frequency of missed diagnoses," said Mao Xinli, the corresponding author of the paper, from Taizhou Hospital.

4155/v