Two-step artificial intelligence system for endoscopic gastric biopsy improves the diagnostic accuracy of pathologists.

Background: Endoscopic biopsy is the pivotal procedure for the diagnosis of gastric cancer. In this study, we applied whole-slide images (WSIs) of endoscopic gastric biopsy specimens to develop an endoscopic gastric biopsy assistant system (EGBAS). Methods: The EGBAS was trained using 2373 WSIs expertly annotated and internally validated on 245 WSIs. A large-scale, multicenter test dataset of 2003 WSIs was used to externally evaluate EGBAS. Eight pathologists were compared with the EGBAS using a man-machine comparison test dataset. The fully manual performance of the pathologists was also compared with semi-manual performance using EGBAS assistance. Results: The average area under the curve of the EGBAS was 0·979 (0·958-0·990). For the diagnosis of all four categories, the overall accuracy of EGBAS was 86·95%, which was significantly higher than pathologists (P< 0·05). The EGBAS achieved a higher κ score (0·880, very good κ) than junior and senior pathologists (0·641 ± 0·088 and 0·729 ± 0·056). With EGBAS assistance, the overall accuracy (four-tier classification) of the pathologists increased from 66·49 ± 7·73% to 73·83 ± 5·73% (P< 0·05). The length of time for pathologists to manually complete the dataset was 461·44 ± 117·96 minutes; this time was reduced to 305·71 ± 82·43 minutes with EGBAS assistance (P = 0·00). Conclusions: The EGBAS is a promising system for improving the diagnosis ability and reducing the workload of pathologists.

Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging.

BACKGROUND: Non-magnifying endoscopy with narrow-band imaging (NM-NBI) has been frequently used in routine screening of esophagus squamous cell carcinoma (ESCC). The performance of NBI for screening of early ESCC is, however, significantly affected by operator experience. Artificial intelligence may be a unique approach to compensate for the lack of operator experience. AIM: To construct a computer-aided detection (CAD) system for application in NM-NBI to identify early ESCC and to compare it with our previously reported CAD system with endoscopic white-light imaging (WLI). METHODS: A total of 2167 abnormal NM-NBI images of early ESCC and 2568 normal images were collected from three institutions (Zhongshan Hospital of Fudan University, Xuhui Hospital, and Kiang Wu Hospital) as the training dataset, and 316 pairs of images, each pair including images obtained by WLI and NBI (same part), were collected for validation. Twenty endoscopists participated in this study to review the validation images with or without the assistance of the CAD systems. The diagnostic results of the two CAD systems and improvement in diagnostic efficacy of endoscopists were compared in terms of sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. RESULTS: The area under receiver operating characteristic curve for CAD-NBI was 0.9761. For the validation dataset, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of CAD-NBI were 91.0%, 96.7%, 94.3%, 95.3%, and 93.6%, respectively, while those of CAD-WLI were 98.5%, 83.1%, 89.5%, 80.8%, and 98.7%, respectively. CAD-NBI showed superior accuracy and specificity than CAD-WLI (P = 0.028 and P ≤ 0.001, respectively), while CAD-WLI had higher sensitivity than CAD-NBI (P = 0.006). By using both CAD-WLI and CAD-NBI, the endoscopists could improve their diagnostic efficacy to the highest level, with accuracy, sensitivity, and specificity of 94.9%, 92.4%, and 96.7%, respectively. CONCLUSION: The CAD-NBI system for screening early ESCC has higher accuracy and specificity than CAD-WLI. Endoscopists can achieve the best diagnostic efficacy using both CAD-WLI and CAD-NBI.

PLAC8 overexpression correlates with PD-L1 upregulation and acquired resistance to chemotherapies in gallbladder carcinoma.

Gallbladder carcinoma (GBC) is always diagnosed at an advanced stage, and patients often miss the opportunity for surgery. Gemcitabine (GEM) and platinum-based drugs, including oxaliplatin (OXA), are mainstays of chemotherapy. However, drug resistance causes treatment failure. Hence, salvage mechanisms are critical to improve outcomes. This study revealed the positive correlation between placenta-specific protein 8 (PLAC8) overexpression and PD-L1 overexpression in GBC. Given the roles of PLAC8 and PD-L1 in chemotherapy resistance, GEM-resistant and OXA-resistant cell lines (SGC966GR and SGC966OR, respectively) were established to test whether and how PLAC8 and PD-L1 function in chemotherapy resistance. Drug-insensitive SGC966GR and SGC966OR cells upregulated MRP and MDR1 and had high expression of PLAC8. PLAC8 blockade using siRNA reversed chemotherapy resistance and downregulated MRP and MDR1 in SGC966GR and SGC966OR cells, suggesting that PLAC8 mediates chemotherapy resistance in GBC. Consistent with the increased mRNA levels of PD-L1 after the acquisition of resistance, PLAC8 knockdown reduced PD-L1 mRNA expression in SGC966GR and SGC966OR cells. In conclusion, PLAC8 overexpression in GBC patients positively correlated with PD-L1 expression. PLAC8 conferred resistance to GEM and OXA by upregulating PD-L1 expression, and PLAC8 or PD-L1 blockade may have potential for overcoming chemotherapy resistance, providing therapeutic options for chemotherapy-refractory GBC patients.