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Endoscopic resection (ER) of esophageal squamous cell carcinoma (ESCC) is evaluated pathologically, and additional treatment is recommended for cases resulting in non-curative resection, defined as pMM with lymphovascular invasion (LVI), pSM, or positive vertical margin. This study aimed to assess long-term outcomes and risk factors for recurrence in patients with ESCC treated with non-curative ER followed by additional chemoradiotherapy (CRT). We retrospectively reviewed the clinical courses of patients who underwent non-curative ER followed by additional CRT for ESCCs between August 2007 and December 2017. Recurrence rates and risk factors for recurrence were analyzed. Among 97 patients with non-curative ER, 73 underwent additional CRT. With a median follow-up period of 71 months, recurrences were observed in 10 (14%) of 73 patients, with a median interval of 24.5 (1–59 months). The 3- and 5-year recurrence-free survival were 89 and 85%, respectively, and the 3- and 5-year overall survival rates were 96 and 91%, respectively. Multivariate analysis showed that lymphatic invasion was an independent risk factor for recurrence in patients with non-curative ESCC receiving additional CRT. Among the 10 patients with recurrence, 4, 3, 2, and 1 underwent surgery, chemotherapy, supportive care, and CRT, respectively. Notably, all four patients who underwent surgery survived, regardless of regional and/or distant lymph node metastasis. Lymphatic invasion is an independent risk factor for the recurrence of non-curative ESCCs. Careful follow-up is required for at least 5 years after ER with additional CRT. [ABSTRACT FROM AUTHOR]

Objectives: A computer‐aided detection (CAD) system was developed to support the detection of colorectal lesions by deep learning using video images of lesions and normal mucosa recorded during colonoscopy. The study's purpose was to evaluate the stand‐alone performance of this device under blinded conditions. Methods: This multicenter prospective observational study was conducted at four Japanese institutions. We used 326 videos of colonoscopies recorded with patient consent at institutions in which the Ethics Committees approved the study. The sensitivity of successful detection of the CAD system was calculated using the target lesions, which were detected by adjudicators from two facilities for each lesion appearance frame; inconsistencies were settled by consensus. Successful detection was defined as display of the detection flag on the lesion for more than 0.5 s within 3 s of appearance. Results: Of the 556 target lesions from 185 cases, detection success sensitivity was 97.5% (95% confidence interval [CI] 95.8–98.5%). The "successful detection sensitivity per colonoscopy" was 93% (95% CI 88.3–95.8%). For the frame‐based sensitivity, specificity, positive predictive value, and negative predictive value were 86.6% (95% CI 84.8–88.4%), 84.7% (95% CI 83.8–85.6%), 34.9% (95% CI 32.3–37.4%), and 98.2% (95% CI 97.8–98.5%), respectively. Trial registration: University Hospital Medical Information Network (UMIN000044622). [ABSTRACT FROM AUTHOR]

Aim: Gastrectomy is recommended for patients with early gastric cancer (EGC) because the possibility of lymph node metastasis (LNM) cannot be completely denied. The aim of this study was to develop a discrimination model to select patients who do not require surgery using machine learning. Methods: Data from 382 patients who received gastrectomy for gastric cancer and who were diagnosed with pT1b were extracted for developing a discrimination model. For the validation of this discrimination model, data from 140 consecutive patients who underwent endoscopic resection followed by gastrectomy, with a diagnosis of pT1b EGC, were extracted. We applied XGBoost to develop a discrimination model for clinical and pathological variables. The performance of the discrimination model was evaluated based on the number of cases classified as true negatives for LNM, with no false negatives for LNM allowed. Results: Lymph node metastasis was observed in 95 patients (25%) in the development cohort and 11 patients (8%) in the validation cohort. The discrimination model was developed to identify 27 (7%) patients with no indications for additional surgery due to the prediction of an LNM‐negative status with no false negatives. In the validation cohort, 13 (9%) patients were identified as having no indications for additional surgery and no patients with LNM were classified into this group. Conclusion: The discrimination model using XGBoost algorithms could select patients with no risk of LNM from patients with pT1b EGC. This discrimination model was considered promising for clinical decision‐making in relation to patients with EGC. [ABSTRACT FROM AUTHOR]

The article discusses the use of endoscopic ultrasound (EUS) for diagnosing subepithelial lesions (SELs) and determining the management of gastrointestinal cancer. EUS-guided fine needle aspiration (EUS-FNA) is commonly used to obtain tissue samples from SELs, but the diagnostic yield is lower compared to pancreatic solid tumors. The article also mentions the development of minimally invasive treatments for SELs, such as endoscopic resection (ER), but highlights the challenges associated with these treatments. The study presented in the article evaluates an application system called SELERP for determining the management of SELs, and while the diagnostic results are somewhat inferior to previous studies, the application shows promise for predicting diagnosis and ER-related outcomes. The article concludes by emphasizing the importance of human training in performing EUS and making treatment decisions, despite the advancements in computer-aided diagnosis. [Extracted from the article]

Background and Aims: Noninvasive, imaging diagnosis of gastrointestinal mesenchymal tumors (GIMTs) is still difficult. This study aimed to develop a novel diagnostic method of GIMTs via endoscopic ultrasonography (EUS) using circularity. Methods: In a derivation series, we retrospectively collected 50 GIMTs 2–5 cm in diameter of two institutions. After selecting one EUS still image showing the maximal area per lesion, two endoscopists who were blind to the histological diagnosis assessed circularity, a surrogate indicator of roundness (range, 0–1; 1 = a true circle), with an image-analyzing software. Median circularity of three types of GIMT was compared, and the cutoff value to differentiate a group from other groups was presented by drawing a receiver operating characteristic curve. Subsequently, we assessed the diagnostic ability of circularity in 91 GIMTs which were retrospectively collected from the other two institutions by using the optimal cutoff value presented in the derivation series. Results: The circularity in leiomyomas indicated 0.70 and was significantly lower than that of gastrointestinal stromal tumors (0.89), schwannomas (0.90), and their combined group. When leiomyomas were diagnosed as the circularity of <0.8305, which was presented as the optimal cutoff value, the diagnostic accuracy, sensitivity, and specificity in the validation series were 73.6%, 80.0%, and 72.4%, respectively. Conclusion: The data demonstrated that leiomyomas significantly exhibited more distortion than other GIMTs. That implies that the difference in shape, which is objectively determined as circularity, is useful to noninvasively discriminate leiomyomas from other GIMTs. [ABSTRACT FROM AUTHOR]

Screening endoscopy improves detection and prognosis of patients with gastric cancer. However, even expert endoscopists can miss early gastric cancer under standard white light imaging. Texture and color enhancement imaging (TXI) is an image‐enhanced endoscopy that enhances brightness, surface irregularities such elevation or depression, and subtle color changes. A few image‐oriented studies have compared the gastric color differences between neoplastic and peripheral areas under both white light imaging and TXI. The results not only suggested that the overall color differences to be more pronounced in TXI, but also that TXI mode 1 was superior to white light imaging in the visibility of early gastric cancer. Despite the promising results in these initial studies, it is unclear whether the superiority of the image‐enhanced endoscopy will translate into an improvement in early gastric cancer detection in real practice. Therefore, large‐scale prospective studies are necessary to investigate the efficacy of this new technology in the evaluation of patients undergoing screening endoscopy. [ABSTRACT FROM AUTHOR]