Colorectal adenomas during colonoscopy can be automatically identified with the newly developed endoscopic system, which is powered by artificial intelligence (AI), reveals a new study.
The system, developed in Japan, has recently been tested in one of the first prospective trials of AI-assisted endoscopy in a clinical setting, with the results presented today at the 25th UEG Week in Barcelona, Spain.
Colo-rectal cancer - Management
Treatment for Colorectal Cancers may involve surgery,chemotherapy, radiation therapy or biological therapy. Some people require a combination of treatments.
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‘The endoscopic system powered by artificial intelligence can reduce the risk of colorectal cancer and cancer-related deaths.’
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AI-assisted endocytoscopy - how it works:
The new computer-aided diagnostic system uses an endocytoscopic image a 500-fold magnified view of a colorectal polyp to analyse approximately 300 features of the polyp after applying narrow-band imaging (NBI) mode or staining with methylene blue.
![Colorectal Cancer Screening]( "Colorectal Cancer Screening")
Colorectal screening is done using tests to detect blood in stool, colonoscopy or sigmoidoscopy ordouble contrast barium enema or CT colonography.
The system compares the features of each polyp against more than 30,000 endocytoscopic images that were used for machine learning, allowing it to predict the lesion pathology in less than a second.
Preliminary studies demonstrated the feasibility of using such a system to classify colorectal polyps, however, until today, no prospective studies have been reported.
Prospective study in routine practice:
The prospective study, led by Dr Yuichi Mori from Showa University in Yokohama, Japan, involved 250 men and women in whom colorectal polyps had been detected using endocytoscopy1.
The AI-assisted system was used to predict the pathology of each polyp and those predictions were compared with the pathological report obtained from the final resected specimens.
Overall, 306 polyps were assessed real-time by using the AI-assisted system, providing a sensitivity of 94 percent, specificity of 79 percent, accuracy of 86%, and positive and negative predictive values of 79 percent and 93 percent respectively, in identifying neoplastic changes.
Speaking at the Opening Plenary at UEG Week, Dr Mori explained; "The most remarkable breakthrough with this system is that artificial intelligence enables real-time optical biopsy of colorectal polyps during colonoscopy, regardless of the endoscopists' skill. This allows the complete resection of adenomatous polyps and prevents unnecessary polypectomy of non-neoplastic polyps."
"We believe these results are acceptable for clinical application and our immediate goal is to obtain regulatory approval for the diagnostic system" added Dr Mori.
Moving forwards, the research team is now undertaking a multicentre study for this purpose and the team are also working on developing an automatic polyp detection system.
"Precise on-site identification of adenomas during colonoscopy contributes to the complete resection of neoplastic lesions" said Dr Mori.
"This is thought to decrease the risk of colorectal cancer and, ultimately, cancer-related death."
Source: Eurekalert
Colorectal Cancer Screening
Colorectal screening is done using tests to detect blood in stool, colonoscopy or sigmoidoscopy ordouble contrast barium enema or CT colonography.
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The system compares the features of each polyp against more than 30,000 endocytoscopic images that were used for machine learning, allowing it to predict the lesion pathology in less than a second.
Preliminary studies demonstrated the feasibility of using such a system to classify colorectal polyps, however, until today, no prospective studies have been reported.
Prospective study in routine practice:
The prospective study, led by Dr Yuichi Mori from Showa University in Yokohama, Japan, involved 250 men and women in whom colorectal polyps had been detected using endocytoscopy1.
The AI-assisted system was used to predict the pathology of each polyp and those predictions were compared with the pathological report obtained from the final resected specimens.
Overall, 306 polyps were assessed real-time by using the AI-assisted system, providing a sensitivity of 94 percent, specificity of 79 percent, accuracy of 86%, and positive and negative predictive values of 79 percent and 93 percent respectively, in identifying neoplastic changes.
Speaking at the Opening Plenary at UEG Week, Dr Mori explained; "The most remarkable breakthrough with this system is that artificial intelligence enables real-time optical biopsy of colorectal polyps during colonoscopy, regardless of the endoscopists' skill. This allows the complete resection of adenomatous polyps and prevents unnecessary polypectomy of non-neoplastic polyps."
"We believe these results are acceptable for clinical application and our immediate goal is to obtain regulatory approval for the diagnostic system" added Dr Mori.
Moving forwards, the research team is now undertaking a multicentre study for this purpose and the team are also working on developing an automatic polyp detection system.
"Precise on-site identification of adenomas during colonoscopy contributes to the complete resection of neoplastic lesions" said Dr Mori.
"This is thought to decrease the risk of colorectal cancer and, ultimately, cancer-related death."
Source: Eurekalert
Colorectal Cancer Screening with Colonoscopy
Colonoscopy is a widely used endoscopic procedure to screen individuals for colorectal cancer. It is very sensitive in detecting colorectal cancers.
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 Colorectal Cancer Screening with Double-Contrast Barium EnemaDouble-contrast barium enema is a radiological technique that can be used to screen individuals for colorectal cancer and is performed when colonoscopy is not possible. | Advertisement
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