Probe-based confocal laser endomicroscopy (pCLE), also known as optical biopsy, is a new endoscopic technique that provides real-time magnification of 1000 × microscopic tissue information to diagnose indeterminate biliary strictures. Tissue sampling by endoscopic retrograde cholangiopancreatography (ERCP) is routinely performed to evaluate indeterminate biliary strictures. To evaluate the accuracy of pCLE and tissue sampling by ERCP in the diagnosis of indeterminate biliary strictures, 18 articles were included from 2008 to 2021 through Embase, PubMed, Web of Science, and Cochrane library databases. The summary estimates for the pCLE diagnosis of indeterminate biliary strictures were: sensitivity 0.88 (95% confidence interval (CI), 0.84–0.91); specificity 0.79 (95% CI 0.74–0.83); and Diagnostic Odds Ratio (DOR) 24.63 (95% CI 15.76–38.48). The summary estimates for tissue sampling by ERCP diagnosis for indeterminate biliary strictures were: sensitivity 0.54 (95% CI 0.49–0.59); specificity 0.96 (95% CI 0.94–0.98); and DOR 11.31 (95% CI 3.90–32.82). The area under the sROC curve of pCLE diagnosis of indeterminate biliary strictures is 0.90 higher than 0.65 of tissue sampling by ERCP. The pCLE is a better approach than tissue sampling by ERCP for the diagnosis of indeterminate biliary strictures by providing real-time microscopic images of the bile ducts.

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Background Selecting the appropriate patient for further treatment after surgery and adjuvant chemotherapy (ACT) for colorectal cancer (CRC) can improve the patient's prognosis. Circulating tumour DNA (ctDNA) has the potential to predict recurrence and prognosis after CRC surgery and ACT, but the results are still inconclusive. Objectives As the completed studies have small sample sizes and different experimental methods, a meta‐analysis was conducted to assess the ctDNA on recurrence and prognosis after CRC surgery and ACT. Methods PubMed, Embase, the Web of Science and the Cochrane Library were searched for potentially eligible studies published up to 6 March 2022. Pooled relative risk (RR) and pooled hazard ratio (HR) were calculated to evaluate recurrence and the prognosis of recurrence‐free survival (RFS) following CRC surgery and ACT. Results Fourteen studies published between 2014 and 2022 included 2393 patients, and 7189 serum samples were eventually included in the meta‐analysis. The pooled revealed that ctDNA‐positive patients were at high risk of recurrence after CRC surgery (RR = 4.43, 95% CI: 3.58–5.48, p < .05) and had a poorer prognosis for RFS (HR = 7.26, 95% CI: 5.48–9.62, p < .05). The pooled revealed that ctDNA‐positive patients were at high risk of recurrence after ACT (RR = 5.77 95% CI: 4.33–7.69, p < .05) and had a poorer prognosis for RFS (HR = 13.96, 95% CI: 8.71–22.4, p < .05). Conclusion ctDNA‐positive patients were at a high risk of recurrence after CRC surgery and ACT and had a poorer prognosis. Hence, ctDNA‐positive patients required close follow‐up and further treatments.

Aim. As the completed studies have small sample sizes and different algorithms, a meta-analysis was conducted to assess the accuracy of WCE in identifying polyps using deep learning. Method. Two independent reviewers searched PubMed, Embase, the Web of Science, and the Cochrane Library for potentially eligible studies published up to December 8, 2021, which were analysed on a per-image basis. STATA RevMan and Meta-DiSc were used to conduct this meta-analysis. A random effects model was used, and a subgroup and regression analysis was performed to explore sources of heterogeneity. Results. Eight studies published between 2017 and 2021 included 819 patients, and 18,414 frames were eventually included in the meta-analysis. The summary estimates for the WCE in identifying polyps by deep learning were sensitivity 0.97 (95% confidence interval (CI), 0.95–0.98); specificity 0.97 (95% CI, 0.94–0.98); positive likelihood ratio 27.19 (95% CI, 15.32–50.42); negative likelihood ratio 0.03 (95% CI 0.02–0.05); diagnostic odds ratio 873.69 (95% CI, 387.34–1970.74); and the area under the sROC curve 0.99. Conclusion. WCE uses deep learning to identify polyps with high accuracy, but multicentre prospective randomized controlled studies are needed in the future.