Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

INTRODUCTION: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions. METHODS: This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups. RESULTS: A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01). DISCUSSION: Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.

Blue-light imaging or narrow-band imaging for proximal colonic lesions: a prospective randomized tandem colonoscopy study.

BACKGROUND AND AIMS: Blue-light imaging (BLI) is a new image-enhanced endoscopy with a wavelength filter similar to narrow-band imaging (NBI). We compared the 2 with white-light imaging (WLI) on proximal colonic lesion detection and miss rates. METHODS: In this 3-arm prospective randomized study with tandem examination of the proximal colon, we enrolled patients aged ≥40 years. Eligible patients were randomized in 1:1:1 ratio to receive BLI, NBI, or WLI during the first withdrawal from the proximal colon. The second withdrawal was performed using WLI in all patients. Primary outcomes were proximal polyp (pPDRs) and adenoma (pADRs) detection rates. Secondary outcomes were miss rates of proximal lesions found on tandem examination. RESULTS: Of 901 patients included (mean age, 64.7 years; 52.9% men), 48.1% underwent colonoscopy for screening or surveillance. The corresponding pPDRs of the BLI, NBI, and WLI groups were 45.8%, 41.6, and 36.6%, whereas the corresponding pADRs were 36.6%, 33.8%, and 28.3%. There was a significant difference in pPDR and pADR between BLI and WLI groups (difference, 9.2% [95% confidence interval {CI}, 3.3-16.9] and 8.3% [95% CI, 2.7-15.9]) and between NBI and WLI groups (difference, 5.0% [95% CI, 1.4-12.9] and 5.6% [95% CI, 2.1-13.3]). Proximal adenoma miss rates were significantly lower with BLI (19.4%) than with WLI (27.4%; difference, -8.0%; 95% CI, -15.8 to -.1) but not between NBI (27.2%) and WLI. CONCLUSIONS: Both BLI and NBI were superior to WLI on detecting proximal colonic lesions, but only BLI had lower proximal adenoma miss rates than WLI. (Clinical trial registration number: NCT03696992.).

Among Patients with Undetectable Hepatitis B Surface Antigen and Hepatocellular Carcinoma, a High Proportion Has Integration of HBV DNA into Hepatocyte DNA and No Cirrhosis.

BACKGROUND & AIMS: In some individuals with undetectable serum levels of hepatitis B surface antigen (HBsAg), hepatitis B virus (HBV) DNA can still be detected in serum or hepatocytes and HBV replicates at low levels-this is called occult HBV infection (OBI). OBI has been associated with increased risk of hepatocellular carcinoma (HCC). We investigated the incidence of OBI in patients with HCC and other liver diseases. We also investigated whether, in patients with OBI and HCC, HBV DNA has integrated into the DNA of hepatocytes. METHODS: We collected clinical information and liver tissues from 110 HBsAg-negative patients (90 with HCC and 20 without HCC; median ages at surgical resection and biopsy collection, 64.1 and 48.6 years, respectively) who underwent liver resection or liver biopsy from November 2002 through July 2017 in Hong Kong. HBV DNA and covalently closed circular DNA (cccDNA) were analyzed and quantified by PCR in liver tissues. Integration of HBV DNA into the DNA of liver cells was detected by Alu-PCR. RESULTS: Of the 90 HBsAg-negative patients with HCC, 18 had alcoholic liver disease (20%), 14 had non-alcoholic fatty liver disease or steatohepatitis (16%), 2 had primary biliary cholangitis, 2 had recurrent pyogenic cholangitis, 1 had autoimmune hepatitis, and 53 had none of these (59%). Among the 20 patients without HCC, 7 had non-alcoholic fatty liver disease or steatohepatitis, 7 had primary biliary cholangitis, and 6 had autoimmune hepatitis. OBI was detected in 62/90 patients with HCC (69%) and 3/20 patients without HCC (15%) (P < .0001). cccDNA was detectable in liver cells of 29 patients with HCC and OBI (47%) and HBV DNA had integrated into DNA of liver cells of 43 patients with HCC and OBI (69%); cccDNA and integrated HBV DNA were not detected in the 3 patients who had OBI without HCC. There were 29 patients with integration of HBV DNA among 33 patients with undetectable cccDNA in liver tissues (88%) and 14 patients with integration of HBV DNA among the 29 patients with cccDNA in liver tissues (48%) (P = .001). HBV DNA was found to integrate near genes associated with hepatocarcinogenesis, such as those encoding telomerase reverse transcriptase, lysine methyltransferase 2B, and cyclin A2. Among the 43 patients with integration of HBV DNA, 39 (91%) did not have cirrhosis. CONCLUSIONS: In an analysis of clinical data and liver tissues from 90 HBsAg-negative patients with HCC, we found that almost 70% had OBI, of whom 70% had integration of HBV DNA into liver cell DNA; 90% of these patients did not have cirrhosis. HBV DNA integrated near hepatic oncogenes; these integrations might promote development of liver cancer.

Linked color imaging versus narrow-band imaging for colorectal polyp detection: a prospective randomized tandem colonoscopy study.

BACKGROUND AND AIMS: Linked color imaging (LCI) is a newly available image-enhanced endoscopy (IEE) system that emphasizes the red mucosal color. No study has yet compared LCI with other available IEE systems. Our aim was to investigate polyp detection rates using LCI compared with narrow-band imaging (NBI). METHODS: This is a prospective randomized tandem colonoscopy study. Eligible patients who underwent colonoscopy for symptoms or screening/surveillance were randomized in a 1:1 ratio to receive tandem colonoscopy with both colonoscope withdrawals using LCI or NBI. The primary outcome was the polyp detection rate. RESULTS: Two hundred seventy-two patients were randomized (mean age, 62 years; 48.2% male; colonoscopy for symptoms, 72.8%) with 136 in each arm. During the first colonoscopy, the polyp detection rate (71.3% vs 55.9%; P = .008), serrated lesion detection rate (34.6% vs 22.1%; P = .02), and mean number of polyps detected (2.04 vs 1.35; P = .02) were significantly higher in the NBI group than in the LCI group. There was also a trend of higher adenoma detection rate in the NBI group compared with the LCI group (51.5% vs 39.7%, respectively; P = .05). Multivariable analysis confirmed that use of NBI (adjusted odds ratio, 1.99; 95% confidence interval, 1.09-3.68) and withdrawal time >8 minutes (adjusted odds ratio, 5.11; 95% confidence interval, 2.79-9.67) were associated with polyp detection. Overall, 20.5% of polyps and 18.1% of adenomas were missed by the first colonoscopy, but there was no significant difference in the miss rates between the 2 groups. CONCLUSION: NBI was significantly better than LCI for colorectal polyp detection. However, both LCI and NBI missed 20.5% of polyps. (Clinical trial registration number: NCT03336359.).

Serum Mac-2-binding protein glycosylation isomer and risk of hepatocellular carcinoma in entecavir-treated chronic hepatitis B patients.

BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) can still develop in chronic hepatitis B (CHB) patients receiving antiviral treatment. Serum Mac-2-binding protein glycosylation isomer (M2BPGi) is a novel marker for liver fibrosis. We investigated its role on incidence of HCC in entecavir (ETV)-treated CHB patients. METHODS: We identified HCC cases diagnosed at ≥ 1 year of ETV treatment. CHB patients without HCC (matched for age, gender, baseline hepatitis B virus-DNA, and duration of ETV treatment) were identified in approximately 1:2 ratio (HCC: non-HCC) for comparison. Serum samples were retrieved at baseline (initiation of ETV), 3, and 5 years of ETV for serum M2BPGi measurement (expressed in cut-off index [COI]). RESULTS: One hundred HCC cases were matched with 185 CHB patients without HCC (median age 56.7 years, 78.9% male, baseline hepatitis B virus-DNA 5.6 logIU/mL, and median follow-up 7.1 years). Median time from ETV initiation to incident HCC was 3.9 years. Serum M2BPGi levels were significantly higher in HCC cases compared with controls at baseline and year 3 (1.25 vs 0.98 [P = 0.004], 0.89 vs 0.74 [P = 0.018] COI, respectively). Multivariate analysis showed that baseline M2BPGi was the only independent factor associated with incident HCC (odds ratio 1.241, 95% confidence interval 1.039-1.482, P = 0.017). Using a cut-off value of 1.15 COI, the sensitivity, specificity, positive predictive value, and negative predictive value of baseline serum M2BPGi in cirrhotic patients to predict incident HCC were 90%, 53.8%, 69.6%, and 82.1%, respectively. CONCLUSIONS: Baseline and 3-year serum M2BPGi may be useful to identify high risk patients on antiviral treatment for subsequent HCC development.

Feedback from artificial intelligence improved the learning of junior endoscopists on histology prediction of gastric lesions.

Background and study aims Artificial intelligence (AI)-assisted image classification has been shown to have high accuracy on endoscopic diagnosis. We evaluated the potential effects of use of an AI-assisted image classifier on training of junior endoscopists for histological prediction of gastric lesions. Methods An AI image classifier was built on a convolutional neural network with five convolutional layers and three fully connected layers A Resnet backbone was trained by 2,000 non-magnified endoscopic gastric images. The independent validation set consisted of another 1,000 endoscopic images from 100 gastric lesions. The first part of the validation set was reviewed by six junior endoscopists and the prediction of AI was then disclosed to three of them (Group A) while the remaining three (Group B) were not provided this information. All endoscopists reviewed the second part of the validation set independently. Results The overall accuracy of AI was 91.0 % (95 % CI: 89.2-92.7 %) with 97.1 % sensitivity (95 % CI: 95.6-98.7%), 85.9 % specificity (95 % CI: 83.0-88.4 %) and 0.91 area under the ROC (AUROC) (95 % CI: 0.89-0.93). AI was superior to all junior endoscopists in accuracy and AUROC in both validation sets. The performance of Group A endoscopists but not Group B endoscopists improved on the second validation set (accuracy 69.3 % to 74.7 %; P  = 0.003). Conclusion The trained AI image classifier can accurately predict presence of neoplastic component of gastric lesions. Feedback from the AI image classifier can also hasten the learning curve of junior endoscopists in predicting histology of gastric lesions.