BM-BronchoLC - A rich bronchoscopy dataset for anatomical landmarks and lung cancer lesion recognition.

Flexible bronchoscopy has revolutionized respiratory disease diagnosis. It offers direct visualization and detection of airway abnormalities, including lung cancer lesions. Accurate identification of airway lesions during flexible bronchoscopy plays an important role in the lung cancer diagnosis. The application of artificial intelligence (AI) aims to support physicians in recognizing anatomical landmarks and lung cancer lesions within bronchoscopic imagery. This work described the development of BM-BronchoLC, a rich bronchoscopy dataset encompassing 106 lung cancer and 102 non-lung cancer patients. The dataset incorporates detailed localization and categorical annotations for both anatomical landmarks and lesions, meticulously conducted by senior doctors at Bach Mai Hospital, Vietnam. To assess the dataset's quality, we evaluate two prevalent AI backbone models, namely UNet++ and ESFPNet, on the image segmentation and classification tasks with single-task and multi-task learning paradigms. We present BM-BronchoLC as a reference dataset in developing AI models to assist diagnostic accuracy for anatomical landmarks and lung cancer lesions in bronchoscopy data.

Serum pepsinogen: A potential non-invasive screening method for moderate and severe atrophic gastritis among an asian population.

Background: Serum pepsinogen has been approved and used widely as an effective biomarker in diagnosis of atrophic gastritis and gastric cancer; however, its validity and appropriate cut-off values vary among different populations. This study aimed to initially assess the diagnostic value of the serum pepsinogen in diagnosis of moderate and severe atrophic gastritis for Vietnamese population. Materials and methods: A cross-sectional study enrolled 273 participants from June 2008 to November 2019. All participants underwent a gastroscopy procedure and three tests including serum PG test, pathology test, and Hp-Igg Elisa test. The Kimura-Takemoto classification and OLGA system were used to classify the mild versus moderate-severe atrophic gastritis. Receiver Operating Characteristic curve was used to assess the value of PGI, PGII and PGR. Results: Based on Kimura-Takemoto classification, the AUC of PGI and PGR was 0.635 (p = 0.008, 95% CI 0.554-0.716) and 0.766 (p < 0.001, 95% CI 0.676-0.857) respectively. The best cut-off values were PGI ≤69.0 and PGR ≤4.6 (sensitivity: 73%, specificity: 83.9%, positive predictive value: 41.5%, negative predictive value: 95.2%, accuracy: 82.4%). According to the OLGA system, the AUC of PGI and PGR was 0.612 (p = 0.004, 95% CI 0.540-0.684) and 0.689 (p < 0.001, 95% CI 0.621-0.758) respectively. The best cut-off values were PGI ≤63.5 and PGR ≤5.2 (sensitivity: 49.4%, specificity: 82.1%, positive predictive value: 52.1%, negative predictive value: 80.5%, accuracy: 72.9%). Conclusions: The serum pepsinogen II and pepsinogen I/II ratio had reliable diagnostic value for screening of moderate and severe atrophic gastritis among Vietnamese population. Further research was recommended to focus on larger scale to improve the diagnostic yield and to continue finding the cut-off values for diagnosis of gastric cancer among Vietnamese population.

Causes and Clinical Characteristics of Small Bowel Bleeding in Northern Vietnam.

Aim: Causes, clinical features, and diagnostic approaches for small bowel (SB) bleeding were analyzed to derive recommendations in dealing with this clinical condition. Methods: We included 54 patients undergoing surgical treatment for SB bleeding, from January 2009 to December 2019. Detailed clinical data, diagnosis procedures, and causes of bleeding were collected. Results: Among 54 cases with SB bleeding, the most common causes were tumors (64.8%), followed by angiopathy (14.8%), ulcers (9.3%), diverticula (5.6%), tuberculosis (3.7%), and enteritis (1.9%). Most tumors (32/35 cases, 91.4%) and vascular lesions (8/8 cases, 100%) were located in the jejunum. The incidence of tumors was higher in the older (30/41 cases, 73.1%) than that in patients younger than 40 years of age (5/13 cases, 38.5%, P < 0.01). Common initial findings were melena (68.5%) and hematochezia (31.5%). The overall diagnostic yield of computed tomographic enterography (CTE) was 57.4% (31/54 cases), with the figures for tumors, vascular lesions, and inflammatory lesions being 71.4% (25/35 cases), 62.5% (5/8 cases), and 12.5% (1/8 cases), respectively. Double-balloon enteroscopy (DBE) definitively identified SB bleeding sources in 16/22 (72.7%) patients. Conclusion: Tumors, angiopathy, ulcers, and diverticula were the most common causes of SB bleeding in Northern Vietnamese population. CTE has a high detection rate for tumors in patients with SB bleeding. CTE as a triage tool may identify patients before double-balloon enteroscopy because of the high prevalence of SB tumors.