From the Journals

AI versus other interventions for colonoscopy: How do they compare?


 

FROM THE JOURNAL OF CLINICAL GASTROENTEROLOGY

No AI advantage for serrated polyps

Twenty-three studies evaluated detection for serrated polyps, including three AI studies. AI did not improve the serrated polyp detection rate (SPDR), compared with other interventions. However, several modalities did improve SPDR: G-EYE, compared with full-spectrum endoscopy (RR, 3.93), linked color imaging, compared with full-spectrum endoscopy (RR, 1.88), and HD colonoscopy (RR, 1.71), and Endocuff Vision, compared with HD colonoscopy (RR, 1.36). G-EYE had the highest P-score (0.93).

AI significantly improved adenomas per colonoscopy, compared with full-spectrum endoscopy (mean difference, 0.38), HD colonoscopy (MD, 0.18), and narrow-band imaging (MD, 0.13), the authors note. However, the number of adenomas detected per colonoscopy was significantly lower for AI, compared with Endocap (-0.13). Endocap had the highest P-score (0.92).

“The strengths of this study include the wide range of endoscopic add-ons included, the number of trials included, and the granularity of some of the reporting data,” Jeremy Glissen Brown, MD, a gastroenterologist and an assistant professor of medicine at Duke University, told this news organization.

Dr. Glissen Brown, who wasn’t involved with this study, researches AI tools for polyp detection. He and colleagues have found that AI decreases adenoma miss rates and increases the number of first-pass adenomas detected per colonoscopy.

“The limitations include significant heterogeneity among many of the comparisons, as well as a high risk of bias, as it is technically difficult to achieve blinding of provider participants in the device-based RCTs [randomized controlled trials] that this analysis was based on,” he said.

Additional considerations

Dr. Aziz and colleagues note the need for additional studies of AI-based detection, particularly for screening and surveillance. For widespread adoption into clinical practice, new systems must have higher specificity, sensitivity, accuracy, and efficiency, they write.

“AI technology needs further optimization, as there is still the aspect of having a lot of false positives – lesions detected but not necessarily adenomas that can turn into cancer,” Dr. Aziz said. “This decreases the efficiency of the colonoscopy and increases the anesthesia and sedation time. In addition, different AI systems have different diagnostic yield, as it all depends on the images that were fed to the system or algorithm.”

Dr. Glissen Brown also pointed to the low number of AI-based studies involving serrated polyp lesion detection. Future research could investigate whether computer-aided detection systems (CADe) decrease miss rates and increase detection rates for sessile serrated lesions, he said.

For practical clinical purposes, Dr. Glissen Brown highlighted the potential complementary nature of the various colonoscopy tools. When used together, for instance, AI and Endocuff may increase ADRs even further and decrease the number of missed polyps through different mechanisms, he said.

“It is also important in device research to interrogate the cost versus benefit of any intervention or combination of interventions,” he said. “I think with CADe this is still something that we are figuring out. We will need to find novel ways of making these technologies affordable, especially as the debate of which clinically meaningful outcomes we examine when it comes to AI continues to evolve.”

No funding source for the study was reported. Two authors have received grant support from or have consulted for several pharmaceutical and medical device companies. Dr. Glissen Brown has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

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