The postoperative effectiveness of Roux-en-Y reconstruction may be superior to Billroth-II with Braun reconstruction after laparoscopic distal gastrectomy.

Background and Aims: Endoscopic ultrasonography (EUS) is a useful diagnostic modality for evaluating gastric mesenchymal tumors; however, differentiating gastrointestinal stromal tumors (GISTs) from benign mesenchymal tumors such as leiomyomas and schwannomas remains challenging. For this reason, we developed a convolutional neural network computer-aided diagnosis (CNN-CAD) system that can analyze gastric mesenchymal tumors on EUS images. Methods: A total of 905 EUS images of gastric mesenchymal tumors (pathologically confirmed GIST, leiomyoma, and schwannoma) were used as a training dataset. Validation was performed using 212 EUS images of gastric mesenchymal tumors. This test dataset was interpreted by three experienced and three junior endoscopists. Results: The sensitivity, specificity, and accuracy of the CNN-CAD system for differentiating GISTs from non-GIST tumors were 83.0%, 75.5%, and 79.2%, respectively. Its diagnostic specificity and accuracy were significantly higher than those of two experienced and one junior endoscopists. In the further sequential analysis to differentiate leiomyoma from schwannoma in non-GIST tumors, the final diagnostic accuracy of the CNN-CAD system was 72.5%, which was significantly higher than that of two experienced and one junior endoscopists. Conclusions: Our CNN-CAD system showed high accuracy in diagnosing gastric mesenchymal tumors on EUS images. It may complement the current clinical practices in the EUS diagnosis of gastric mesenchymal tumors.

Application of the open biopsy forceps method when measuring colon polyp size could help reduce inter-observer differences and error rates.

Background/AimsMagnifying endoscopy with narrow band imaging (ME-NBI) is a useful modality for the detailed visualization of microsurface (MS) and microvascular (MV) structures in the gastrointestinal tract. This study aimed to determine whether the MS and MV patterns in ME-NBI differ according to the histologic type, invasion depth, and mucin phenotype of early gastric cancers (EGCs).MethodsThe MS and MV patterns of 160 lesions in 160 patients with EGC who underwent ME-NBI before endoscopic or surgical resection were prospectively collected and analyzed. EGCs were categorized as either differentiated or undifferentiated and as either mucosal or submucosal, and their mucin phenotypes were determined via immunohistochemistry of the tumor specimens.ResultsDifferentiated tumors mainly displayed an oval and/or tubular MS pattern and a fine network or loop MV pattern, whereas undifferentiated tumors mainly displayed an absent MS pattern and a corkscrew MV pattern. The destructive MS pattern was associated with submucosal invasion, and this association was more prominent in the differentiated tumors than in the undifferentiated tumors. MUC5AC expression was increased in lesions with either a papillary or absent MS pattern and a corkscrew MV pattern, whereas MUC6 expression was increased in lesions with a papillary MS pattern and a loop MV pattern. CD10 expression was more frequent in lesions with a fine network MV pattern.ConclusionsME-NBI can be useful for predicting the histopathology and mucin phenotype of EGCs.

Background Rectal neuroendocrine tumors (NETs) < 10 mm in diameter, limited to the submucosa without local or distant metastasis, can be treated endoscopically. Endoscopic mucosal resection with a ligation band device (EMR-L) and endoscopic submucosal dissection (ESD) have been employed to resect rectal NETs. We evaluated and compared the clinical outcomes of EMR-L and ESD for endoscopic resection of rectal NETs G1 < 10 mm in diameter. Methods We conducted a retrospective study of 82 rectal NETs in 82 patients who underwent either EMR-L or ESD. Therapeutic outcomes (en bloc resection and complete resection rates), procedure time, and procedure-related adverse events were evaluated. Additionally, we measured the distance of the lateral and vertical margins from the border of the tumor in pathologic specimens and compared the resectability between EMR-L and ESD. Results Sixty-six lesions were treated using EMR-L and 16 using ESD. En bloc resection was achieved in all patients. The complete resection rate with EMR-L was significantly higher than that with ESD (95.5% vs.75.0%, p = 0.025). The prevalence of vertical margin involvement was significantly higher in the ESD group than in the EMR-L group (12.5% vs. 0%, p = 0.036), and ESD was more time consuming than EMR-L (24.21 ± 12.18 vs. 7.05 ± 4.53 min, p < 0.001). The lateral and vertical margins were more distant in the EMR-L group than in the ESD group (lateral margin distance, 1661 ± 849 vs. 1514 ± 948 μm; vertical margin distance, 277 ± 308 vs. 202 ± 171 μm). Conclusions EMR-L is more favorable for small rectal NETs with respect to therapeutic outcomes, procedure time, and technical difficulties. Additionally, EMR-L enables achievement of sufficient vertical margin distances.