Impact of a real-time automatic quality control system on colorectal polyp and adenoma detection: a prospective randomized controlled study (with videos).

BACKGROUND AND AIMS: Quality control can decrease variations in the performance of colonoscopists and improve the effectiveness of colonoscopy to prevent colorectal cancers. Unfortunately, routine quality control is difficult to carry out because a practical method is lacking. The aim of this study was to develop an automatic quality control system (AQCS) and assess whether it could improve polyp and adenoma detection in clinical practice. METHODS: First, we developed AQCS based on deep convolutional neural network models for timing of the withdrawal phase, supervising withdrawal stability, evaluating bowel preparation, and detecting colorectal polyps. Next, consecutive patients were prospectively randomized to undergo routine colonoscopies with or without the assistance of AQCS. The primary outcome of the study was the adenoma detection rate (ADR) in the AQCS and control groups. RESULTS: A total of 659 patients were enrolled and randomized. A total of 308 and 315 patients were analyzed in the AQCS and control groups, respectively. AQCS significantly increased the ADR (0.289 vs 0.165, P < .001) and the mean number of adenomas per procedure (0.367 vs 0.178, P < .001) compared with the control group. A significant increase was also observed in the polyp detection rate (0.383 vs 0.254, P = .001) and the mean number of polyps detected per procedure (0.575 vs 0.305, P < .001). In addition, the withdrawal time (7.03 minutes vs 5.68 minutes, P < .001) and adequate bowel preparation rate (87.34% vs 80.63%, P = .023) were superior for the AQCS group. CONCLUSIONS: AQCS could effectively improve the performance of colonoscopists during the withdrawal phase and significantly increase polyp and adenoma detection. (Clinical trial registration number: NCT03622281.).

Three-dimensional cephalometric analysis of adolescents with cleft lip and palate using computed tomography-guided imaging.

OBJECTIVE: To propose landmarks and a new coordinate system to aid three-dimensional cephalometric analysis of adolescent cleft lip and palate (CLP) using computed tomography (CT) imaging. METHODS: Sixty-four-row CT images obtained from 52 adolescent patients were retrospectively analyzed with the MIMICS program (MIMICS 10.02; Materialise Technologies, Leuven, Belgium) to determine intrarater reliability of new landmarks for three-dimensional cephalometric analysis before surgery. RESULTS: Five points were located on each image including the midpoint between both uppermost external points of the external auditory meatus (EAM), the center of the sella turcica (sella, S), the most anterior point on the nasofrontal suture in the midline (nasion, N), and the right and left lowest points of the lower edge of the orbitale (r/l orbitale, r/l Or). The horizontal reference plane was then determined using EAM and bilateral Or. The sagittal reference plane was defined perpendicular to the horizontal plane, passing through N and S. The coronal reference plane included the EAM landmark and was perpendicular to the sagittal and horizontal planes. All 5 points had high intrarater reliability and proved easy to use in constructing the new coordinate system. The horizontal, sagittal, and coronal reference planes formed by these respective points improved the ease of performing three-dimensional cephalometric analysis of CLP adolescents with CT imaging. CONCLUSIONS: Our 5 landmarks provided reliable CT-guided three-dimensional cephalometric analysis of CLP, allowing for accurate quantitative assessment in adolescents before orthognathic surgery.

Development and Validation of an Automatic Image-Recognition Endoscopic Report Generation System: A Multicenter Study.

INTRODUCTION: Conventional gastrointestinal (GI) endoscopy reports written by physicians are time consuming and might have obvious heterogeneity or omissions, impairing the efficiency and multicenter consultation potential. We aimed to develop and validate an image recognition-based structured report generation system (ISRGS) through a multicenter database and to assess its diagnostic performance. METHODS: First, we developed and evaluated an ISRGS combining real-time video capture, site identification, lesion detection, subcharacteristics analysis, and structured report generation. White light and chromoendoscopy images from patients with GI lesions were eligible for study inclusion. A total of 46,987 images from 9 tertiary hospitals were used to train, validate, and multicenter test (6:2:2). Moreover, 5,699 images were prospectively enrolled from Qilu Hospital of Shandong University to further assess the system in a prospective test set. The primary outcome was the diagnosis performance of GI lesions in multicenter and prospective tests. RESULTS: The overall accuracy in identifying early esophageal cancer, early gastric cancer, early colorectal cancer, esophageal varices, reflux esophagitis, Barrett's esophagus, chronic atrophic gastritis, gastric ulcer, colorectal polyp, and ulcerative colitis was 0.8841 (95% confidence interval, 0.8775-0.8904) and 0.8965 (0.8883-0.9041) in multicenter and prospective tests, respectively. The accuracy of cecum and upper GI site identification were 0.9978 (0.9969-0.9984) and 0.8513 (0.8399-0.8620), respectively. The accuracy of staining discrimination was 0.9489 (0.9396-0.9568). The relative error of size measurement was 4.04% (range 0.75%-7.39%). DISCUSSION: ISRGS is a reliable computer-aided endoscopic report generation system that might assist endoscopists working at various hospital levels to generate standardized and accurate endoscopy reports (http://links.lww.com/CTG/A485).

Application of artificial intelligence in gastrointestinal endoscopy.

With recent significant improvements in artificial intelligence (AI), especially in the field of deep learning, an increasing number of studies have evaluated the use of AI in endoscopy to detect and diagnose gastrointestinal (GI) lesions. The present review summarizes current publications on the use of AI in GI endoscopy and focuses on the challenges and future of AI-aided systems. We expect AI to provide an effective and practical method for endoscopists in lesion detection and characterization as well as in quality control in endoscopy. However, so far, most studies have remained at the preclinical stage. More attention should be paid in the future to the use of AI in real-life clinical applications.

Atg5- and Atg7-dependent autophagy in dopaminergic neurons regulates cellular and behavioral responses to morphine.

The molecular basis of chronic morphine exposure remains unknown. In this study, we hypothesized that macroautophagy/autophagy of dopaminergic neurons would mediate the alterations of neuronal dendritic morphology and behavioral responses induced by morphine. Chronic morphine exposure caused Atg5 (autophagy-related 5)- and Atg7 (autophagy-related 7)-dependent and dopaminergic neuron-specific autophagy resulting in decreased neuron dendritic spines and the onset of addictive behaviors. In cultured primary midbrain neurons, morphine treatment significantly reduced total dendritic length and complexity, and this effect could be reversed by knockdown of Atg5 or Atg7. Mice deficient for Atg5 or Atg7 specifically in the dopaminergic neurons were less sensitive to developing a morphine reward response, behavioral sensitization, analgesic tolerance and physical dependence compared to wild-type mice. Taken together, our findings suggested that the Atg5- and Atg7-dependent autophagy of dopaminergic neurons contributed to cellular and behavioral responses to morphine and may have implications for the future treatment of drug addiction.

Smoc2 potentiates proliferation of hepatocellular carcinoma cells via promotion of cell cycle progression.

AIM: To determine the influence of Smoc2 on hepatocellular carcinoma (HCC) cell proliferation and to find a possible new therapeutic target for preventing HCC progression. METHODS: We detected expression of Smoc2 in HCC tissues and corresponding non-tumor liver (CNL) tissues using PCR, western blot, and immunohistochemistry methods. Subsequently, we down-regulated and up-regulated Smoc2 expression using siRNA and lentivirus transfection assay, respectively. Then, we identified the effect of Smoc2 on cell proliferation and cell cycle using CCK-8 and flow cytometry, respectively. The common cell growth signaling influenced by Smoc2 was detected by western blot assay. RESULTS: The expression of Smoc2 was significantly higher in HCC tissues compared with CNL tissues. Overexpression of Smoc2 promoted HCC cell proliferation and cell cycle progression. Down-regulation of Smoc2 led to inhibition of cell proliferation and cell cycle progression. Smoc2 had positive effect on ERK and AKT signaling. CONCLUSION: Smoc2 promotes the proliferation of HCC cells through accelerating cell cycle progression and might act as an anti-cancer therapeutic target in the future.

A novel inflammatory regulator TIPE2 inhibits TLR4-mediated development of colon cancer via caspase-8.

AIMS: TIPE2 is a novel inflammation regulator, and the role of TIPE2 in colitis-induced colon cancer is not clear. The aim of this study was to test whether TIPE2 inhibits TLR4 pathway in colon cancer patients and to explore potential mechanism of TIPE2 in colon cancer by caspase-8. METHODS: Expression of TIPE2 and TLR4 in human colon cancer tissues and cell line HT-29 was detected by immunohistochemistry or real-time PCR. TIPE2 mRNA was suppressed by siRNA transfection and the transfection efficiency was proved by fluorescence microscopy and real-time PCR. TLR4 pathway was activated by treating the cells with 1 µg/ml LPS for 4 h. Caspase-8 activities were tested by colorimetric assay in four HT-29 cell groups. RESULTS: TIPE2 was expressed in the cytoplasm of colon cancer tissues and HT-29 cells. TIPE2 expression was more pronounced in colon cancer tissues compared to normal controls and it was related with lymph node metastasis and Dukes stage of colon cancer. TIPE2 expression was positively correlated with that of TLR4 in colon cancer (r=0.7354). TIPE2 expression was knocked down successfully by siRNA transfection. Caspase-8 activity was elevated both in TIPE2 knockdown cells and in TLR4 activated cells compared to wild-type cells (P< 0.05). And the caspase-8 activity was further increased in TIPE2 knockdown cells after TLR4 was activated (P < 0.05). CONCLUSION: TIPE2 can inhibit caspase-8 activity in colon cancer cells. TIPE2 can regulate TLR4 inflammatory effect and inhibit further amplification of cascade reaction via caspase-8, which provides one new therapeutic target for clinical treatment schedule.