Long-term outcomes of endoscopic submucosal dissection for undifferentiated type early gastric cancer over 2 cm with R0 resection.

BACKGROUND: Endoscopic submucosal dissection (ESD) for over 2 cm in size undifferentiated type (UD type) early gastric cancer (EGC) confined to the mucosa is not only challenging, but also long-term outcomes are not well known. AIM: To evaluate the long-term outcomes of ESD done for UD type EGCs confined to the mucosa over 2 cm in size and compare the results with those where the lesions were less than 2 cm. METHODS: 143 patients with UD type EGC confirmed on histology after ESD at a tertiary hospital were reviewed. Cases with synchronous and metachronous lesions and a case with emergency surgery after ESD were excluded. A total of 137 cases were enrolled. 79 cases who underwent R0 resection were divided into 2 cm or less (group A) and over 2 cm (group B) in size. RESULTS: Among 79 patients who underwent R0 resection, the number in group A and B were 51 and 28, respectively. The mean follow-up period (SD) was 79.71 ± 45.42 months. There was a local recurrence in group A (1/51, 2%) and group B (1/28, 3.6%) respectively. This patient in group A underwent surgery while the patient in group B underwent repeated ESD with no further recurrences in both patients. There was no regional lymph node metastasis, distant metastasis, and deaths in both groups. With R0 resection strategy for ESD on lesions over 2 cm, 20.4% (28/137) of patients were able to avoid surgery compared with expanded indication. CONCLUSION: If R0 resection is achieved by ESD, UD type EGCs over 2 cm also showed good and similar clinical outcomes as compared to lesions less than 2 cm when followed for over 5 years. With R0 resection strategy, several patients can avoid surgery.

Mucin phenotype and microvessels in early gastic cancer: Magnifying endoscopy with narrow band imaging.

Backgrounds: In order to detect early gastric cancer (EGC), this research sought to assess the diagnostic utility of magnifying endoscopy (ME) as well as the significance of mucin phenotype and microvessel features. Methods: 402 individuals with an EGC diagnosis underwent endoscopic submucosal dissection (ESD) at the Department of ME between 2012 and 2020. After adjusting for image distortion, high-magnification endoscopic pictures were taken and examined to find microvessels in the area of interest. The microvessel density was measured as counts per square millimeter (counts/mm2) after segmentation, and the vascular bed's size was computed as a percentage of the area of interest. To identify certain properties of the microvessels, such as end-points, crossing points, branching sites, and connection points, further processing was done using skeletonized pixels. Results: According to the research, undifferentiated tumors often lacked the MS pattern and showed an oval and tubular microsurface (MS) pattern, but differentiated EGC tumors usually lacked the MS pattern and presented a corkscrew MV pattern. Submucosal invasion was shown to be more strongly associated with the destructive MS pattern in differentiated tumors as opposed to undifferentiated tumors. While lesions with a corkscrew MV pattern and an antrum or body MS pattern revealed greater MUC5AC expression, lesions with a loop MV pattern indicated higher MUC2 expression. Furthermore, CD10 expression was higher in lesions with a papillary pattern and an antrum or body MS pattern. Conclusion: These results imply that evaluating mucin phenotype and microvessel features in conjunction with magnifying endoscopy (ME) may be a useful diagnostic strategy for early gastric cancer (EGC) detection. Nevertheless, further investigation is required to confirm these findings and identify the best course of action for EGC diagnosis.

Non-inferiority of additional gastrectomy after endoscopic submucosal dissection compared with surgery alone on long-term prognosis: A propensity score-matching analysis.

BACKGROUND: Patients in whom endoscopic submucosal dissection (ESD) has resulted in non-curative resection need further surgical treatment. However, the oncological outcome of additional gastrectomy after ESD compared with surgery alone remains unclear. METHODS: The clinical data of 778 patients who underwent gastrectomy for early gastric cancer from January 2008 to December 2019 in Ishikawa Prefectural Central Hospital were retrospectively analyzed. Of these 778 patients, 187 underwent additional gastrectomy after ESD (ESD (+) group) and 591 underwent surgery alone (ESD (-) group). We compared the overall survival and disease-free survival between the ESD (+) and ESD (-) groups, using propensity score matching to adjust for baseline characteristics. We also assessed early postoperative outcomes. RESULTS: After propensity score matching based on sex, age, tumor diameter, tumor gross type, and operative procedure, each group comprised 144 patients with no significant differences in clinical background characteristics. After matching, the 5-year overall survival rate in the ESD (+) and ESD (-) group was 90.9% and 87.8%, respectively, with no significant difference (P = 0.470). In addition, there was no significant difference in the disease-free survival rate (97.6% vs. 95.8%, respectively; P = 0.504). The postoperative complication rate was similar in both groups. CONCLUSION: Additional gastrectomy for patients in whom ESD resulted in non-curative resection did not adversely affect the long-term prognosis. Additional gastrectomy after ESD is oncologically acceptable for early gastric cancer.

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to assess comprehensive pathologic characteristics of EGC using white-light endoscopic images and videos. METHODS: To train the model, we retrospectively collected 4,336 images and prospectively included 153 videos from patients with EGC who underwent endoscopic or surgical resection. The performance of the model was tested and compared to that of 16 endoscopists (nine experts and seven novices) using a mutually exclusive set of 260 images and 10 videos. Finally, we conducted external validation using 436 images and 89 videos from another institution. RESULTS: After training, the model achieved predictive accuracies of 89.7% for undifferentiated histology, 88.0% for submucosal invasion, 87.9% for lymphovascular invasion (LVI), and 92.7% for lymph node metastasis (LNM), using endoscopic videos. The area under the curve values of the model were 0.992 for undifferentiated histology, 0.902 for submucosal invasion, 0.706 for LVI, and 0.680 for LNM in the test. In addition, the model showed significantly higher accuracy than the experts in predicting undifferentiated histology (92.7% vs. 71.6%), submucosal invasion (87.3% vs. 72.6%), and LNM (87.7% vs. 72.3%). The external validation showed accuracies of 75.6% and 71.9% for undifferentiated histology and submucosal invasion, respectively. CONCLUSIONS: AI may assist endoscopists with high predictive performance for differentiation status and invasion depth of EGC. Further research is needed to improve the detection of LVI and LNM.

Predictive efficacy of combined tumor markers and gastrin for recurrence after endoscopic submucosal dissection in early gastric cancer patients.

OBJECTIVE: This study aims to evaluate the predictive value of tumor markers combined with gastrin for tumor recurrence after endoscopic submucosal dissection (ESD) in patients with early gastric cancer. METHODS: The clinicopathological data of 169 patients with early gastric cancer treated with ESD between March 2019 and January 2021 were retrospectively analyzed. The patients were divided into a relapse group (n=45) and a non-recurrence group (n=124). Clinical data such as carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), alpha-fetoprotein (AFP), gastrin 17, pepsinogen I and pepsinogen II, as well as tumor size and degree of infiltration were examined to construct a recurrence prediction model using lasso regression. RESULTS: The comprehensive model showed superior predictive power (AUC=0.958, C-index=0.966) over biomarker-only models (AUC=0.925), indicating a significant improvement in the prediction of recurrence risk. Decision curve analysis confirmed the clinical utility of the model with a maximum net benefit of 73.37%. Key indicators such as CEA, CA19-9, AFP, gastrin 17 and pepsinogens I and II were statistically significant in predicting recurrence with P values < 0.01. CONCLUSION: The comprehensive model combining tumor markers with clinical data provides a more accurate and clinically valuable tool for predicting recurrence in early gastric cancer patients after ESD. This approach facilitates personalized risk assessment and may significantly improve prognostic management, emphasizing the importance of a multifaceted strategy in the management of early gastric cancer.

Risk factors of missed early gastric cancer in endoscopic resected population: a retrospective, case-control study.

BACKGROUND: Missed early gastric cancer (MEGC) is prevalent during esophagogastroduodenoscopy (EGD), which is the first-line recommended strategy for detecting early gastric cancer (EGC). Hence, we explored the risk factors for MEGC and different types of MEGC, based on the endoscopic resected population. METHODS: This retrospective, case-control study was conducted at Nanjing Drum Tower Hospital (NJDTH). We included patients who were diagnosed with EGC during screening EGD, underwent endoscopic resection, and were confirmed by postoperative pathology at the NJDTH from January 2014 to December 2021, and classified them into different types according to the different root causes of misses. Univariable, multivariable, subgroup and propensity score analyses were used to explore the risk factors for MEGC and different types of MEGC. RESULTS: A total of 447 patients, comprising 345 with initially detected early gastric cancer (IDEGC) and 102 with MEGC, were included in this study. Larger size (≥ 1 cm) (OR 0.45, 95% CI 0.27-0.74, P = 0.002) and invasion depth of submucosa (OR 0.26, 95% CI 0.10-0.69, P = 0.007) were negatively associated with MEGC. Use of sedation (OR 0.32, 95% CI 0.20-0.52, P < 0.001) and longer observation time (OR 0.60, 95% CI 0.37-0.96, P = 0.034) exhibited protective effect on MEGC. CONCLUSIONS: Smaller and more superficial EGC lesions are more susceptible to misdiagnosis. The use of sedation and prolonged observation time during EGD could help reduce the occurrence of MEGC.

Optical enhancement mode 2 improves the detection rate of gastric neoplastic lesion in high-risk populations: A multicenter randomized controlled clinical study.

OBJECTIVES: Detection of early neoplastic lesions is crucial for improving the survival rates of patients with gastric cancer. Optical enhancement mode 2 is a new image-enhanced endoscopic technique that offers bright images and can improve the visibility of neoplastic lesions. This study aimed to compare the detection of neoplastic lesions with optical enhancement mode 2 and white-light imaging (WLI) in a high-risk population. METHODS: In this prospective multicenter randomized controlled trial, patients were randomly assigned to optical enhancement mode 2 or WLI groups. Detection of suspicious neoplastic lesions during the examinations was recorded, and pathological diagnoses served as the gold standard. RESULTS: A total of 1211 and 1219 individuals were included in the optical enhancement mode 2 and WLI groups, respectively. The detection rate of neoplastic lesions was significantly higher in the optical enhancement mode 2 group (5.1% vs. 1.9%; risk ratio, 2.656 [95% confidence interval, 1.630-4.330]; p < 0.001). The detection rate of neoplastic lesions with an atrophic gastritis background was significantly higher in the optical enhancement mode 2 group (8.6% vs. 2.6%, p < 0.001). The optical enhancement mode 2 group also had a higher detection rate among endoscopists with different experiences. CONCLUSIONS: Optical enhancement mode 2 was more effective than WLI for detecting neoplastic lesions in the stomach, and can serve as a new method for screening early gastric cancer in clinical practice. CLINICAL REGISTRY: United States National Library of Medicine (https://www. CLINICALTRIALS: gov), ID: NCT040720521.

A machine learning model for predicting the lymph node metastasis of early gastric cancer not meeting the endoscopic curability criteria.

BACKGROUND: We developed a machine learning (ML) model to predict the risk of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) who did not meet the existing Japanese endoscopic curability criteria and compared its performance with that of the most common clinical risk scoring system, the eCura system. METHODS: We used data from 4,042 consecutive patients with EGC from 21 institutions who underwent endoscopic submucosal dissection (ESD) and/or surgery between 2010 and 2021. All resected EGCs were histologically confirmed not to satisfy the current Japanese endoscopic curability criteria. Of all patients, 3,506 constituted the training cohort to develop the neural network-based ML model, and 536 constituted the validation cohort. The performance of our ML model, as measured by the area under the receiver operating characteristic curve (AUC), was compared with that of the eCura system in the validation cohort. RESULTS: LNM rates were 14% (503/3,506) and 7% (39/536) in the training and validation cohorts, respectively. The ML model identified patients with LNM with an AUC of 0.83 (95% confidence interval, 0.76-0.89) in the validation cohort, while the eCura system identified patients with LNM with an AUC of 0.77 (95% confidence interval, 0.70-0.85) (P = 0.006, DeLong's test). CONCLUSIONS: Our ML model performed better than the eCura system for predicting LNM risk in patients with EGC who did not meet the existing Japanese endoscopic curability criteria. We developed a neural network-based machine learning model that predicts the risk of lymph node metastasis in patients with early gastric cancer who did not meet the endoscopic curability criteria.

Endoscopic Features of Synchronous Multiple Early Gastric Cancers: Findings from a Nationwide Cohort.

INTRODUCTION: We investigated the factors associated with synchronous multiple early gastric cancers and determined their localization. METHODS: We analyzed 8,191 patients who underwent endoscopic submucosal dissection for early gastric cancers at 33 hospitals in Japan from November 2013 to October 2016. Background factors were compared between single-lesion (n = 7,221) and synchronous multi-lesion cases (n = 970) using univariate and multivariate analyses. We extracted cases with two synchronous lesions (n = 832) and evaluated their localization. RESULTS: Significant independent risk factors for synchronous multiple early gastric cancer were older age (≥75 years old) (odds ratio [OR] = 1.257), male sex (OR = 1.385), severe mucosal atrophy (OR = 1.400), tumor localization in the middle (OR = 1.362) or lower region (OR = 1.404), and submucosal invasion (OR = 1.528 [SM1], 1.488 [SM2]). Depressed macroscopic type (OR = 0.679) and pure undifferentiated histology OR = 0.334) were more common in single early gastric cancers. When one lesion was in the upper region, the other was more frequently located in the lesser curvature of the middle region. When one lesion was in the middle region, the other was more frequently located in the middle region or the lesser curvature of the lower region. When one lesion was in the lower region, the other was more frequently located in the lesser curvature of the middle region or the lower region. CONCLUSION: Factors associated with synchronous multiple early gastric cancer included older age, male sex, severe mucosal atrophy, tumor localization in the middle or lower region, and tumor submucosal invasion. Our findings provide useful information regarding specific areas that should be examined carefully when one lesion is detected.

A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer.

BACKGROUND: We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) system for diagnosing the invasion depth of early gastric cancer (EGC), and we evaluated the performance of this system. METHODS: A total of 8280 EUS images from 559 EGC cases were collected from 11 institutions. Within this dataset, 3451 images (285 cases) from one institution were used as a development dataset. The AI model consisted of segmentation and classification steps, followed by the CycleGAN method to bridge differences in EUS images captured by different equipment. AI model performance was evaluated using an internal validation dataset collected from the same institution as the development dataset (1726 images, 135 cases). External validation was conducted using images collected from the other 10 institutions (3103 images, 139 cases). RESULTS: The area under the curve (AUC) of the AI model in the internal validation dataset was 0.870 (95% CI: 0.796-0.944). Regarding diagnostic performance, the accuracy/sensitivity/specificity values of the AI model, experts (n = 6), and nonexperts (n = 8) were 82.2/63.4/90.4%, 81.9/66.3/88.7%, and 68.3/60.9/71.5%, respectively. The AUC of the AI model in the external validation dataset was 0.815 (95% CI: 0.743-0.886). The accuracy/sensitivity/specificity values of the AI model (74.1/73.1/75.0%) and the real-time diagnoses of experts (75.5/79.1/72.2%) in the external validation dataset were comparable. CONCLUSIONS: Our AI model demonstrated a diagnostic performance equivalent to that of experts.

Early gastric cancer with RhoGAP fusion is linked to frequent nodal metastasis and a part of microtubular-mucocellular histology.

INTRODUCTION: Gastric cancer with fusion genes involving the Rho GTPase-activating protein domain (RhoGAP-GC) is mainly included in the genomically stable type of The Cancer Genome Atlas classification. Clinical implications and histological characteristics of RhoGAP-GC in the early phase remain unclear. METHODS: We analyzed 878 consecutive pT1b GCs for RhoGAP and its partner genes using fluorescence in situ hybridization assay. RESULTS: RhoGAP fusion was detected in 57 (6.5%) GCs. Univariate analysis revealed that female sex, middle-lower third tumor location, advanced macroscopic type, tumor diameter > 2 cm, pT1b2, lymphatic invasion, venous invasion, negative EBER-ISH, and RhoGAP fusion were significantly associated with lymph node metastasis (LNM). Multivariate analysis presented RhoGAP fusion, lymphatic invasion, tumor diameter > 2 cm, advanced macroscopic type, venous invasion, and middle-lower third tumor location as independent risk factors for LNM. Notably, RhoGAP fusion had the highest odds ratio (3.92) for LNM among analyzed parameters (95% CI 2.12-7.27; p < 0.001). Compared to non-RhoGAP-GCs, RhoGAP-GCs were significantly frequent in younger females and showed the highest incidence of lymphatic invasion (56.2%) and LNM (49.1%) (p < 0.001). Histologically, microtubular architecture with pseudo-trabecular interconnection and small aggregations of tumor cells with a varied amount of cytoplasmic mucin, named "microtubular-mucocellular (MTMC) histology," was found in 93.0% (53 of 57) of RhoGAP-GCs in the intramucosal area. MTMC histology showed high sensitivity and negative predictive value (93.0% and 99.4%, respectively) for RhoGAP fusion, albeit positive predictive value is low (34.9%). CONCLUSION: RhoGAP-GC is linked to a characteristic MTMC histology and a high incidence of LNM.

Artificial Intelligence Model for a Distinction between Early-Stage Gastric Cancer Invasive Depth T1a and T1b.

Background: Endoscopic submucosal dissection (ESD) is a widely accepted treatment for patients with mucosa (T1a) disease without lymph node metastasis. However, the inconsistency of inspection quality of tumor staging under the standard tool combining endoscopic ultrasound (EUS) with computed tomography (CT) scanning makes it restrictive. Methods: We conducted a study using data augmentation and artificial intelligence (AI) to address the early gastric cancer (EGC) staging problem. The proposed AI model simplifies early cancer treatment by eliminating the need for ultrasound or other staging methods. We developed an AI model utilizing data augmentation and the You-Only-Look-Once (YOLO) approach. We collected a white-light image dataset of 351 stage T1a and 542 T1b images to build, test, and validate the model. An external white-light images dataset that consists of 47 T1a and 9 T1b images was then collected to validate our AI model. The result of the external dataset validation indicated that our model also applies to other peer health institutes. Results: The results of k-fold cross-validation using the original dataset demonstrated that the proposed model had a sensitivity of 85.08% and an average specificity of 87.17%. Additionally, the k-fold cross-validation model had an average accuracy rate of 86.18%; the external data set demonstrated similar validation results with a sensitivity of 82.98%, a specificity of 77.78%, and an overall accuracy of 82.14%. Conclusions: Our findings suggest that the AI model can effectively replace EUS and CT in early GC staging, with an average validation accuracy rate of 86.18% for the original dataset from Linkou Cheng Gun Memorial Hospital and 82.14% for the external validation dataset from Kaohsiung Cheng Gun Memorial Hospital. Moreover, our AI model's accuracy rate outperformed the average EUS and CT rates in previous literature (around 70%).

Risk Factors for Lymph Node Metastasis in a Western Series of Patients with Distal Early Gastric Cancer.

Background: Assessment of potential lymph node metastasis is mandatory in the appropriate treatment of early gastric cancers. This study analysed factors associated with lymph node metastasis to identify differences between node-negative and node-positive patients and between T1a and T1b cancers. Methods: The clinicopathological features of 129 early gastric cancer patients who had undergone radical gastrectomy were analysed to identify predictive factors for lymph node metastasis. Results: Lymph node metastasis was detected in 76 (59.0%) patients. Node-positive patients were younger (58.1 ± 11.3 years) than those without metastasis (61.9 ± 9.6 years, p = 0.02). Greater tumour sizes were observed in patients with lymph node metastasis (3.6 ± 1.0 cm) compared to node-negative patients (1.9 ± 0.5 cm, p = 0.00001). Depressed form, ulceration, diffuse histological type, and undifferentiated lesions were more frequent in node-positive patients than in the node-negative group. Tumour size > 3.0 cm showed a correlation with lymph node metastasis in both T1a (p = 0.0001) and T1b (p = 0.006) cancer. The male sex (p = 0.006) had a significant correlation with lymph node metastasis in T1a cancer. Depressed appearance (p = 0.02), ulceration (p = 0.03), differentiation (p = 0.0001), diffuse type (p = 0.0002), and lower third location (p = 0.005) were associated with lymph node metastasis in T1b cancer. Conclusions: Tumour size > 3 cm, undifferentiated lesions, ulceration, diffuse type, lower third location, and submucosal invasion are risk factors for lymph node metastasis in early gastric cancer.

Low prognostic nutrition index as a prognostic biomarker in elderly patients with early gastric cancer after gastrectomy.

Purpose Non-invasive biomarkers including systemic inflammatory or nutrition-based index including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) lymphocyte to monocyte ratio (LMR), and prognostic nutritional index (PNI) can be useful in determining treatment strategies for elderly patients with early gastric cancer (EGC). The aim of this study was to investigate the significance of these index for predicting the long-term survival of EGC patients aged 80 years over. Methods This study included 80 elderly EGC patients with pStageIA after gastrectomy. Optimal cutoff value for PNI, NLR, PLR and LMR were set by using receiver operating curve analysis. The long-term outcomes after gastrectomy were analyzed by univariate and multivariate Cox regression analyses. Results Cut-off value for PNI, NLR, PLR and LMR was set at 46.5, 2.8, 210 and 4.6, respectively. By univariate analyses, low PNI, high NLR, high PLR and low LMR were significantly associated with worse prognosis. By multivariate analysis, low PNI was confirmed as an independent prognostic factor after gastrectomy (HR 0.17 ; 95% CI 0.03-0.91 ; P = 0.04). 5-year overall survival rate of patients with low PNI (≤ 46.5) were 52.4%. Conclusion Low PNI might be useful biomarker to predict worse prognosis of elderly EGC patients after gastrectomy. J. Med. Invest. 71 : 113-120, February, 2024.

Clinical outcome of non-curative endoscopic submucosal dissection for early gastric cancer.

Background: Early gastric cancer (EGC) is defined as cancer cells confined to the mucosal or submucosal layer, irrespective of size or presence of lymph node metastasis. The recent EGC endoscopic submucosal dissection (ESD) and endoscopic mucosal resection (EMR) guidelines (2021 Japan Gastroenterological Endoscopy Society (JGES) guidelines, 2nd edition) revised the concept from "endoscopic curative/non-curative resection" (NCR) to "endoscopic curability (eCura)". Under this, eCuraA and eCuraB signify curative resections (CRs), while eCuraC (including eCuraC-1 and eCura-C2) indicate NCRs. This study retrospectively analyzes clinical and pathological data from EGC patients who underwent endoscopic resection, assessing the long-term clinical outcomes in a substantial cohort after undergoing NCR. Methods: We retrospectively analyzed clinical and pathological data from 443 EGC patients, encompassing 478 lesions, who received endoscopic treatment. The long-term clinical outcomes of patients who underwent NCR were statistically evaluated. Characteristics of the NCR group were compared with those of the surgical group, employing single- and multi-factor logistic regression analyses to identify risk factors that necessitate further surgical intervention. Prognostically, the Kaplan-Meier method and Log-Rank test determined the impact of risk factors on recurrence-free survival post-surgery in NCR patients. Differences were assessed using a method incorporating statistically significant differences in the multi-factor Cox regression analysis, evaluating the hazard ratio (HR) for disease recurrence following NCR. Results: In this study, 443 EGC cases were pathologically diagnosed, comprising a total of 478 lesions. Of these, 127 cases underwent non-curative endoscopic resection, resulting in a NCR rate of 24.4%. Long-term follow-up was achieved for 117 (92.12%) patients. The metastasis/recurrence rate at 6 months stood at 23.1%. Multivariate Cox regression analysis identified lesion size ≥2.0 and <3 cm [P=0.02, HR =0.12, 95% confidence interval (CI): 0.02-0.67], presence of ulceration (P=0.03, HR =5.48, 95% CI: 1.23-24.33), lymphatic invasion (P=0.05, HR =17.51, 95% CI: 1.07-286.23), positive vertical margins (P=0.09, HR =3.77, 95% CI: 0.81-17.53), and flat macroscopic morphology (P=0.048, HR =4.8, 95% CI: 1.01-22.73) as independent risk factors for recurrence-free survival post non-curative endoscopic resection in EGC patients. Conclusions: The recurrence/metastasis rate in patients who underwent NCR is notably higher compared to the control group. Significant prognostic risk factors include tumor size ≥2.0 and <3 cm, positive vertical margins, lymphatic invasion, and flat type (one of pathological gross classification). Patients in the eCuraC-2 category of NCR should consider further surgical intervention. The necessity for additional surgical intervention in these patients warrants further investigation.

Clip-and-snare method with a pre-looping technique versus conventional method in the treatment of precancerous lesion and early gastric cancer: a retrospective study.

BACKGROUND: Low grade intraepithelial neoplasia (LGIN) and high grade intraepithelial neoplasia (HGIN) are potential precancerous lesion of gastric neoplasms. Endoscopic submucosal dissection (ESD) is the first option for the treatment of precancerous lesion and early gastric cancer (EGC). Traction is an effective method to improve efficiency, and reduce complications during ESD. In this study, we shared a useful traction method using the clip-and-snare method with a pre-looping technique (CSM-PLT) for precancerous lesion and EGC. METHODS: We retrospectively analyzed patients received ESD combined with CSM-PLT or conventional ESD from June 2018 to December 2021 in Shenzhen People's hospital. The primary outcome was resection speed. RESULTS: Forty-two patients were enrolled in ESD combined with CSM-PLT group and sixty-five patients in conventional ESD group respectively. Baseline characteristics were comparable among two groups (P>0.05). There were no significant differences in terms of R0 resection rate, en bloc resection rate (97.6% vs. 98.5%, P = 1.000 and 97.6% vs. 96.9%, P = 1.000, respectively), operation costs (933.7 (644.1-1102.4) dollars vs. 814.7 (614.6-988.3) dollars, P = 0.107), and hospital stays (8.0 ± 3.1 days vs. 7.3 ± 3.2 days, P = 0.236). In addition, no significant difference was observed with respect to complications (P>0.05). However, the resection speed of ESD combined with CSM-PLT was faster than that of conventional ESD (11.3 (9.4-14.9) mm2/min vs. 8.0 (5.8-10.9) mm2/min, P < 0.001), particularly lesions located in anterior wall and lesser curvature. In addition, the association between ESD combined with CSM-PLT and resection speed was still supported after propensity matching scores (PMS). CONCLUSIONS: CSM-PLT can help to improve ESD efficiency without reducing the en bloc resection rate or increasing the incidence of complications.

Chronic active and atrophic gastritis as significant contributing factor to the development of gastric cystica profunda.

Gastric cystica profunda (GCP) is an uncommon but underestimated gastric lesion. Its precancerous potential determines its significance. In addition to previous mucosa injury due to operations, biopsy or polypectomy, chronic active and atrophic gastritis may also lead to the development of GCPs. By carefully examining the stomach and taking biopsy samples from the susceptible regions, the stage of atrophy can be determined. Chronic atrophic gastritis is a risk factor for cancer evolvement and it can also contribute to GCPs formation. GCPs frequently occur close to early gastric cancers (EGCs) or EGC can arise from the cystic glands. Endoscopic resection is an effective and minimally invasive treatment in GCP.

New Proposal Strategy of Sentinel Lymph Node Navigation Surgery for Endoscopic Curability C-2: A Retrospective Study.

BACKGROUND/AIM: The purpose of this study was to evaluate the outcomes of the sentinel node navigation surgery (SNNS) followed by limited gastrectomy for early gastric cancer (EGC) with Endoscopic Curability C-2 (eCuraC-2). PATIENTS AND METHODS: Between 2001 and 2018, 33 patients were included in this study. Following sentinel node (SN) biopsy using indocyanine green combined with an infrared ray laparoscopic system, limited gastrectomy (LG) [wedge resection (WR), or segmental gastrectomy (SG)] was performed without extended lymphadenectomy. RESULTS: SN detection rate was 97% (32/33). The mean number of SNs per case was 7.8. Three patients (9.1%) with lymph node metastasis (LNM) had a positive SN identified by intraoperative pathological examination. When intraoperative pathologic examination showed SN to be LNM negative, 11 patients underwent WR, and seven were subjected to SG. Postoperative pathological examinations showed no false negatives for LNM, and four patients (12%) had residual cancer in their resected stomachs. Overall survival and disease-specific survival five years after SNNS were 87.9% and 100%, respectively. CONCLUSION: SNNS followed by LG with lymphatic basin resection may be one of the ideal procedures for patients with eCuraC-2 due to the accurate diagnosis of LNM and favorable disease-specific prognosis.