Endoscopic Detection Research Articles

Endoscopic ultrasound-guided detection and internal drainage of a pancreato-cutaneous fistula after acute pancreatitis.

Endoscopic ultrasound-guided detection and internal drainage of a pancreato-cutaneous fistula after acute pancreatitis.

Targeting c-MET for Endoscopic Detection of Dysplastic Lesions Within Barrett's Esophagus Using EMI-137 Fluorescence Imaging.

Esophageal cancer (EC) carries a poor prognosis with 5-year overall survival of less than 20%. Barrett's esophagus (BE) increases the risk of esophageal adenocarcinoma (EAC). The aim of this study was to investigate the ability of EMI-137, a mesenchymal-epithelial transition factor (c-MET)-targeting optical imaging tracer, to detect dysplasia in BE. c-MET expression in human esophageal tissue was investigated using Gene Expression Omnibus (GEO) datasets, tissue microarrays and BE biopsies. EMI-137 was tested in a dual xenograft mouse model bearing OE33 (c-MET high expression) and FLO-1 (c-MET low expression) tumors. Fluorescence molecular endoscopy (FME) was performed in a mouse model of Barrett's-like metaplasia and dysplasia (L2-IL1β). Tumors and organs-of-interest were evaluated through ex vivo fluorescence imaging. MET mRNA expression analyses and c-MET immunostaining confirmed upregulation of c-MET in BE and EAC compared to normal epithelium. There was strong accumulation of EMI-137 in OE33 xenografts 3 h post injection decreasing by more than 50% on co-injection of a 10-fold molar excess of unlabeled EMI-137. The target-to background ratio (TBR) at 3 h p.i. for OE33 and FLO-1 tumors was 10.08 and 1.42, respectively. FME of L2-IL1β mice showed uptake of EMI-137 in dysplastic lesions within BE with a TBR of 1.9 in vivo, and greater than 2 in ex vivo fluorescence imaging. EMI-137 accumulates in dysplastic lesions within BE and in c-MET positive EAC. EMI-137 imaging has potential as a screening and surveillance tool for patients with BE and as a means to detecting dysplasia and EAC.

Development of a prediction score for Barrett's esophagus in Japanese health checkup settings.

The incidence of esophageal adenocarcinoma has recently increased in Asia, including Japan. A system to identify individuals at high risk for Barrett's esophagus (BE), a pre-cancerous condition of esophageal adenocarcinoma, among the general population is needed to perform endoscopic surveillance appropriately. We therefore developed risk prediction scores for BE at health checkups in Japan. 4128 consecutive health checkup examinees were retrospectively enrolled from October 2021 to March 2022. A prediction score for BE was developed based on the linear transformation of β-regression coefficients in a multivariable regression model incorporating BE predictors. Internal validation was performed by evaluating discrimination and calibration of the prediction model. Three prediction scores corresponding to BE based on its length were developed: all lengths, ≥ 1cm, ≥ 2cm. All scores were internally validated, and the model calibration was excellent. The performance of the prediction models was better for longer BE, with a c-statistic of 0.70 for BE ≥ 2cm, than for shorter values. The prediction score for BE ≥ 2cm yielded sensitivity and specificity of 52.9% and 78.6% in high-risk subjects and 91.2% and 29.3% in intermediate- or high-risk subjects, respectively. This prediction score can potentially increase the endoscopic detection of BE by identifying potentially high-risk individuals from the general population. This is the first report on developing a prediction score for BE that may suit the Japanese population.

Endoscopic detection and diagnostic strategies for minute gastric cancer: A real-world observational study

BACKGROUND Minute gastric cancers (MGCs) have a favorable prognosis, but they are too small to be detected by endoscopy, with a maximum diameter ≤ 5 mm. AIM To explore endoscopic detection and diagnostic strategies for MGCs. METHODS This was a real-world observational study. The endoscopic and clinicopathological parameters of 191 MGCs between January 2015 and December 2022 were retrospectively analyzed. Endoscopic discoverable opportunity and typical neoplastic features were emphatically reviewed. RESULTS All MGCs in our study were of a single pathological type, 97.38% (186/191) of which were differentiated-type tumors. White light endoscopy (WLE) detected 84.29% (161/191) of MGCs, and the most common morphology of MGCs found by WLE was protruding. Narrow-band imaging (NBI) secondary observation detected 14.14% (27/191) of MGCs, and the most common morphology of MGCs found by NBI was flat. Another three MGCs were detected by indigo carmine third observation. If a well-demarcated border lesion exhibited a typical neoplastic color, such as yellowish-red or whitish under WLE and brownish under NBI, MGCs should be diagnosed. The proportion with high diagnostic confidence by magnifying endoscopy with NBI (ME-NBI) was significantly higher than the proportion with low diagnostic confidence and the only visible groups (94.19% > 56.92% > 32.50%, P < 0.001). CONCLUSION WLE combined with NBI and indigo carmine are helpful for detection of MGCs. A clear demarcation line combined with a typical neoplastic color using nonmagnifying observation is sufficient for diagnosis of MGCs. ME-NBI improves the endoscopic diagnostic confidence of MGCs.

Endoscopic detection and diagnosis of gastric cancer using image-enhanced endoscopy: A systematic review and meta-analysis.

We aimed to conduct a systematic review and meta-analysis to assess the value of image-enhanced endoscopy including blue laser imaging (BLI), linked color imaging, narrow-band imaging (NBI), and texture and color enhancement imaging to detect and diagnose gastric cancer (GC) compared to that of white-light imaging (WLI). Studies meeting the inclusion criteria were identified through PubMed, Cochrane Library, and Japan Medical Abstracts Society databases searches. The pooled risk ratio for dichotomous variables was calculated using the random-effects model to assess the GC detection between WLI and image-enhanced endoscopy. A random-effects model was used to calculate the overall diagnostic performance of WLI and magnifying image-enhanced endoscopy for GC. Sixteen studies met the inclusion criteria. The detection rate of GC was significantly improved in linked color imaging compared with that in WLI (risk ratio, 2.20; 95% confidence interval [CI], 1.39-3.25; p < 0.01) with mild heterogeneity. Magnifying endoscopy with NBI (ME-NBI) obtained a pooled sensitivity, specificity, and area under the summary receiver operating curve of 0.84 (95 % CI, 0.80-0.88), 0.96 (95 % CI, 0.94-0.97), and 0.92, respectively. Similarly, ME-BLI showed a pooled sensitivity, specificity, and area under the curve of 0.81 (95 % CI, 0.77-0.85), 0.85 (95 % CI, 0.82-0.88), and 0.95, respectively. The diagnostic efficacy of ME-NBI/BLI for GC was evidently high compared to that of WLI, However, significant heterogeneity among the NBI studies still existed. Our meta-analysis showed a high detection rate for linked color imagingand a high diagnostic performance of ME-NBI/BLI for GC compared to that with WLI.

Endoscopic approaches to the management of dysplasia in inflammatory bowel disease: A state-of-the-art narrative review.

Patients with inflammatory bowel disease (IBD) are at an increased risk of developing colitis-associated neoplasia (CAN), including colorectal cancer (CRC), through the inflammation-dysplasia-neoplasia pathway. Dysplasia is the most reliable, early and actionable marker for CAN in these patients. While such lesions are frequently encountered, adequate management depends on an accurate assessment, complete resection and close surveillance. With recent advances in endoscopic technologies and research in the field of CAN, the management of dysplastic lesions has significantly improved. The American Gastroenterology Association and Surveillance for Colorectal Endoscopic Neoplasia Detection (SCENIC) provide a guideline framework for approaching dysplastic lesions in patients with IBD. However, there are significant gaps in these recommendations and real-world clinical practice. Accurate lesion assessment remains pivotal for adequate management of CAN. Artificial intelligence-guided modalities are now increasingly being used to aid the detection of these lesions further. As the lesion detection technologies are improving, our armamentarium of resection techniques is also expanding and includes hot or cold polypectomy, endoscopic mucosal resection, endoscopic sub-mucosal dissection and full-thickness resection. With the broadened scope of endoscopic resection, the recommendations regarding surveillance after resection has also changed. Certain patient populations such as those with invisible dysplasia or with prior colectomy and ileal pouch anal anastomosis need special consideration. In the present review, we aim to provide a state-of-the-art summary of the current practice of endoscopic detection, resection and surveillance of dysplasia in patients with IBD and provide some perspective on the future directions based on the latest research.

The recovery of endoscopic activity and cancer detection after the COVID-19 pandemic

BackgroundThe COVID-19 pandemic had a substantial impact on cancer services. The aim of our study was to evaluate the recovery of endoscopic activity and cancer detection after the COVID-19 pandemic. MethodsEndoscopic data from January 2019 to December 2020 were retrospectively collected to assess the endoscopic activity and cancer detection during the COVID-19 peak period (February 2020) and the post-COVID-19 peak period (March to July 2020). ResultsThe COVID-19 pandemic almost brought endoscopic activity and cancer detection to a standstill. Diagnostic procedure and endoscopic resection showed the greatest reduction. With the decline in COVID-19 infections, endoscopic activity gradually returned to previous level in July. However, the detection rate of gastric cancer resumed in September, whereas colorectal cancer resumed in August. The monthly detection rates of gastric and colorectal cancers decreased from their initial peaks of 2.98 % and 6.45 %, respectively, and finally were even lower than the average in 2019. Similarly, the mean age of patients who received endoscopy also declined as the detection rates resumed. The increasing colonoscopies allowed the missing colorectal cancer patients to be caught up. In contrast, it was expected that 6.69 % of gastric cancer patients were missed and did not receive needed endoscopy. ConclusionsThe recovery of cancer detection occurred later than that of endoscopic activity, especially for gastric cancer. Older people were vulnerable to the continuous impact of COVID-19 pandemic than young people for seeking medical services. Urgent efforts are required to recover and maintain cancer services before subsequent waves of the COVID-19 pandemic.

Using Machine Learning for Endoscopic Detection of Low-Grade Subglottic Stenosis: A Proof of Principle.

The current study trains, tests, and evaluates a deep learning algorithm to detect subglottic stenosis (SGS) on endoscopy. A retrospective review of patients undergoing microlaryngoscopy-bronchoscopy was performed. A pretrained image classifier (Resnet50) was retrained and tested on 159 images of airways taken at the glottis, 106 normal-sized airways, and 122 with SGS. Data augmentation was performed given the small sample size to prevent overfitting. Overall model accuracy was 73.3% (SD: 3.8). Precision and recall for stenosis were 77.3% (SD: 4.0) and 72.7 (SD: 4.0). F1 score for the detection of stenosis was 0.75 (SD: 0.04). Precision and recall for normal-sized images were lower at 69% (SD: 4.35) and 74% (SD: 4), with an F1 score of 0.71 (SD: 0.04). This study demonstrates that an image classification algorithm can identify SGS on endoscopic images. Work is needed to improve diagnostic accuracy for eventual deployment of the algorithm into clinical care.

A Novel Characteristic Gastric Mucus Named "Web-like Mucus" Potentially Induced by Vonoprazan.

Background: In the absence of Helicobacter pylori (HP) infection, a characteristic gastric mucus adhesion may appear during the use of vonoprazan. We named this novel characteristic mucus "web-like mucus" (WLM). This study aimed to determine the incidence and risk factors for WLM. Methods: Between January 2017 and January 2022, 5665 patients were enrolled in this study. The patients were divided into a proton-pump inhibitor (PPI)-prescribed group (n = 2000), a vonoprazan-prescribed group (n = 268), and a no-PPI/vonoprazan-prescribed (n = 3397) group, and the presence of WLM was examined. After excluding four patients with autoimmune gastritis, the remaining 264 patients in the vonoprazan group were divided into WLM and non-WLM groups, and their clinical features were analyzed. Results: A total of 55 (21%) patients had WLM, all in the vonoprazan-prescribed group. There were no significant differences in factors such as, sex, age, chronic kidney disease, diabetes mellitus, HP eradication history, smoking, or alcohol consumption between the WLM and non-WLM groups. The median duration from the start of vonoprazan administration to the endoscopic detection of WLM was 2 (1-24) months. Conclusions: WLM appears to be a characteristic feature in patients treated with vonoprazan.

Parasitic Diseases of Upper Gastrointestinal Tract

Korea was a hotspot for parasitic infections until modern times. However, following economic development, improved health and hygiene and farming methods, and successful implementation of active deworming programs, human parasites are rare. Currently, medical and scientific advances have improved the survival rate of elderly and immunocompromised hosts, and immunosuppressants are widely administered for treatment, which may predispose patients to parasitic and various opportunistic infections. Furthermore, globalization has led to the entry of an increasing number of individuals from various countries into Korea, which increases the risk of transmission of parasites from foreign countries into Korea. However, parasitic diseases will tend to disappear in Korea, which may lead to reduced proficiency and diagnostic rate of existing stool tests, and new diagnostic methods tailored to Korea are unavailable. Currently, endoscopy is widely used as a standard method for gastrointestinal disease evaluation in Korea, and endoscopically detected parasites or parasite-induced abnormalities are useful to establish diagnosis in many cases. In this article, the author summarize the current status of endoscopic detection of parasitic diseases affecting the upper gastrointestinal tract.

Imaging and endoscopic tools in pediatric inflammatory bowel disease: What's new?

Pediatric inflammatory bowel disease (IBD) is a chronic inflammatory disorder, with increasing incidence and prevalence worldwide. There have been recent advances in imaging and endoscopic technology for disease diagnosis, treatment, and monitoring. Intestinal ultrasound, including transabdominal, transperineal, and endoscopic, has been emerging for the assessment of transmural bowel inflammation and disease complications (e.g., fistula, abscess). Aside from surgery, IBD-related intestinal strictures now have endoscopic treatment options including through-the-scope balloon dilatation, injection, and needle knife stricturotomy and new evaluation tools such as endoscopic functional lumen imaging probe. Unsedated transnasal endoscopy may have a role in patients with upper gastrointestinal Crohn's disease or those with IBD with new upper gastrointestinal symptoms. Improvements to dysplasia screening in pediatric patients with longstanding colonic disease or primary sclerosing cholangitis hold promise with the addition of virtual chromoendoscopy and ongoing research in the field of artificial intelligence-assisted endoscopic detection. Artificial intelligence and machine learning is a rapidly evolving field, with goals of further personalizing IBD diagnosis and treatment selection as well as prognostication. This review summarized these advancements, focusing on pediatric patients with IBD.

Latest Advances in Endoscopic Detection of Oesophageal and Gastric Neoplasia

Endoscopy is the gold standard for the diagnosis of cancers and cancer precursors in the oesophagus and stomach. Early detection of upper GI cancers requires high-quality endoscopy and awareness of the subtle features these lesions carry. Endoscopists performing surveillance of high-risk patients including those with Barrett’s oesophagus, previous squamous neoplasia or chronic atrophic gastritis should be familiar with endoscopic features, classification systems and sampling techniques to maximise the detection of early cancer. In this article, we review the current approach to diagnosis of these conditions and the latest advanced imaging and diagnostic techniques.

Сlinical case of visceral metastasis of cutaneous melanoma

Cutaneous melanoma is the most common tumor that metastasizes to the gastrointestinal tract, however, the diagnosis of visceral metastases remains difficult due to its low symptoms. Lifetime verification of melanoma metastases in the digestive tract is only 1–4%. Additional difficulties in verifying visceral melanoma metastases arise due to spontaneous regression of the primary tumor. The presented rare clinical case illustrates a variant of the course of disseminated melanoma of the skin with metastatic lesions of the gastrointestinal tract, while the dissemination was preceded by spontaneous regression of melanoma of the skin. Despite the lifetime endoscopic verification of multiple visceral metastases of cutaneous myeloma, the patient’s prognosis is unfavorable. The fact of spontaneous regression of cutaneous melanoma influenced the late diagnosis of melanoma dissemination, also due to the rarity of melanoma metastasis in the mucosa of the upper digestive tract, endoscopists are not sufficiently aware of endoscopic variants of melanoma metastases. It should be noted that endoscopic diagnostic methods must necessarily be included in the examination plan of a patient with melanoma, and when dynamically monitoring patients with melanoma after treatment, it is necessary to pay attention to non-specific signs of gastrointestinal tract damage (abdominal pain, anemia). In addition, in a patient with a history of melanoma, with endoscopic detection of an unpigmented neoplasm, it should be differentiated with a possible metastatic lesion, histological and immunohistochemical examination of the biopsy should be performed.

Investigation of the relationship between colonoscopy insertion difficulty factors and endoscope shape using an endoscopic position detection unit.

In this study, we investigated the relationship between the cecal intubation time (CIT) and the form and method used for passing through the sigmoid/descending colon junction (SDJ) and the hepatic flexure using an endoscopic position detection unit (UPD), with reference to various factors [age, sex, body mass index (BMI), history of abdominal and pelvic surgery, and diverticulum]. A total of 152 patients underwent colonoscopy with UPD. The mean age was 66.9 ± 12.4 years, and the male to female ratio was 3.6:1. The average CIT time was 14.3 ± 8.2 min. Age, number of experienced endoscopies, history of abdominal and pelvic surgery, BMI, and diverticulum were associated with prolonged CIT; SDJ passage pattern was straight: 8.6 ± 5.0, alpha loop: 11.8 ± 5.6, puzzle ring-like loop: 20.2 ± 5.0, reverse alpha loop: 22.4 ± 9.7, and other loop: 24.7 ± 10.5. The hepatic flexure passing method was in the following order: right rotation maneuver: 12.6 ± 6.6, push maneuver: 15.1 ± 5.9, and right rotation with positional change maneuver: 20.5 ± 7.2. In conclusion, colonoscopy with UPD revealed an association between CIT and SDJ passage pattern and hepatic flexure passing method.

Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.

Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images relayed through endoscopes. Moreover, works relying on supervised learning are powerless in the case of inadequate labeled samples. Therefore, for end-to-end medical image detection with overcritical efficiency and accuracy in endoscope detection, an ensemble-learning-based model with a semi-supervised mechanism is developed in this work. To gain a more accurate result through multiple detection models, we propose a new ensemble mechanism, termed alternative adaptive boosting method (Al-Adaboost), combining the decision-making of two hierarchical models. Specifically, the proposal consists of two modules. One is a local region proposal model with attentive temporal-spatial pathways for bounding box regression and classification, and the other one is a recurrent attention model (RAM) to provide more precise inferences for further classification according to the regression result. The proposal Al-Adaboost will adjust the weights of labeled samples and the two classifiers adaptively, and the nonlabel samples are assigned pseudolabels by our model. We investigate the performance of Al-Adaboost on both the colonoscopy and laryngoscopy data coming from CVC-ClinicDB and the affiliated hospital of Kaohsiung Medical University. The experimental results prove the feasibility and superiority of our model.

White-light endoscopic colorectal lesion detection based on improved YOLOv7

White-light endoscopy is an effective means of detecting colorectal lesions. Aiming at the phenomenon of misdetection and missed detection that are prone to occur in the detection process, this paper proposes an improved YOLOv7 model (CSS-YOLOv7) for lesion classification detection. First of all, the CNeB module is used to replace part of the ELAN module of the backbone and neck network, which can extract the features of the lesion area, reduce the number of network layers and model parameters, and improve the training speed. Second, colorectal lesion maps generated by white-light endoscopy have low resolution. Therefore, in response to this drawback, this study added the SPD-Conv module to the original model to effectively prevent fine-grained damage that may be caused by strided convolution. Finally, the SIOU loss function is used to enable the prediction frame to converge faster, and the precision and efficiency are effectively improved. The experimental results show that the recall rate of the model proposed in this paper is 92.3%, and mAP@.5 reaches 95.9%, which can promote the development of automatic detection of colorectal lesions.

Real time anatomical landmarks and abnormalities detection in gastrointestinal tract.

Gastrointestinal (GI) endoscopy is an active research field due to the lethal cancer diseases in the GI tract. Cancer treatments result better if diagnosed early and it increases the survival chances. There is a high miss rate in the detection of the abnormalities in the GI tract during endoscopy or colonoscopy due to the lack of attentiveness, tiring procedures, or the lack of required training. The procedure of the detection can be automated to the reduction of the risks by identifying and flagging the suspicious frames. A suspicious frame may have some of the abnormality or the information about anatomical landmark in the frame. The frame then can be analysed for the anatomical landmarks and the abnormalities for the detection of disease. In this research, a real-time endoscopic abnormalities detection system is presented that detects the abnormalities and the landmarks. The proposed system is based on a combination of handcrafted and deep features. Deep features are extracted from lightweight MobileNet convolutional neural network (CNN) architecture. There are some of the classes with a small inter-class difference and a higher intra-class differences, for such classes the same detection threshold is unable to distinguish. The threshold of such classes is learned from the training data using genetic algorithm. The system is evaluated on various benchmark datasets and resulted in an accuracy of 0.99 with the F1-score of 0.91 and Matthews correlation coefficient (MCC) of 0.91 on Kvasir datasets and F1-score of 0.93 on the dataset of DowPK. The system detects abnormalities in real-time with the detection speed of 41 frames per second.

Enhancing surgical precision: unveiling the impact of preoperative colonoscopy in anal fistula patients

BackgroundAnal fistula is a common benign anorectal disease that often requires surgical intervention for effective treatment. In recent years, preoperative colonoscopy as a diagnostic tool in patients with anal fistula has garnered increasing attention due to its potential clinical application value. By investigating underlying inflammatory bowel disease (IBD), polyps, and other abnormalities, preoperative colonoscopy can offer insights to refine surgical strategies and improve patient outcomes.MethodsThis retrospective study focused on 1796 patients with various benign anorectal diseases who underwent preoperative intestinal endoscopy and met surgical criteria within the preceding three years at the First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine. Among these patients, 949 diagnosed with anal fistula comprised group A, while 847 patients without anal fistula were assigned to group B for comparison. The investigation encompassed an analysis of general patient information, endoscopic findings, polyp histopathology, distribution of bowel inflammation sites, and results of inflammatory bowel disease assessments between the two patient cohorts. A subgroup analysis was also conducted on 2275 anal fistula patients with no surgical contraindications. This subgroup was categorized into Group A (949 patients who underwent preoperative intestinal endoscopy) and Group C (1326 patients who did not undergo preoperative colonoscopy). The study compared the rates of detecting endoscopic lesions and IBD-related findings between the two subgroups.ResultsThe study initially confirmed the comparability of general patient information between groups A and B. Notably, the abnormal detection rate in group A was significantly higher than in group B (P < 0.01). In terms of endoscopic findings, the anal fistula group (group A) exhibited higher rates of detecting bowel inflammation, inflammatory bowel disease, and polyps compared to the non-anal fistula group (group B) (P < 0.05). The distribution of inflammation locations indicated higher detection rates in the terminal ileum, ileocecal region, and ascending colon for group A compared to group B (P < 0.05). Although the incidence of IBD in group A was higher than in group B, this difference did not reach statistical significance (P > 0.05). Subsequently, the analysis of the subgroup (groups A and C) revealed a significant disparity in intestinal endoscopic detection rates (P < 0.01) and statistically significant differences in detecting IBD (P < 0.05) and Crohn's disease (P < 0.05) between the two anal fistula subgroups.ConclusionsThe findings of this study underscore the substantial clinical value of preoperative colonoscopy in the comprehensive evaluation of patients with anal fistula. Preoperative colonoscopy aids in ruling out localized perianal lesions caused by underlying inflammatory bowel disease, thereby mitigating the likelihood of missed diagnoses and enhancing treatment outcomes. This research highlights the importance of incorporating preoperative colonoscopy as a valuable diagnostic tool in managing anal fistula patients.

Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks.

The presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods. Each of the proposed feature descriptors outputs a feature activation map in the form of a grayscale image. Acquired feature maps can be appended in a straightforward way to the original color channels of the input image and passed to the input of a convolutional neural network during the training and inference steps. An experimental evaluation is conducted to compare the classification ROC AUC of feature-extended convolutional neural network models with baseline models using regular color image inputs. The advantage of feature-extended models is demonstrated for the Resnet and VGG convolutional neural network architectures.

Landscape of Innovative Methods for Early Diagnosis of Gastric Cancer: A Systematic Review.

From a global perspective, gastric cancer (GC) persists as a significant healthcare issue. In the Western world, the majority of cases are discovered at late stages, when the treatment is generally unsuccessful. There are no organized screening programs outside of Asia (Japan and Republic of Korea). Traditional diagnosis techniques (such as upper endoscopy), conventional tumor markers (CEA, CA19-9, and CA72-4), radiographic imaging, and CT scanning all have drawbacks. The gold standard for the earliest detection of cancer and related premalignant lesions is still endoscopy with a proper biopsy follow-up. Since there are currently no clinically approved biomarkers for the early diagnosis of GC, the identification of non-invasive biomarkers is expected to help improve the prognosis and survival rate of these patients. The search for new screening biomarkers is currently underway. These include genetic biomarkers, such as circulating tumor cells, microRNAs, and exosomes, as well as metabolic biomarkers obtained from biofluids. Meanwhile, cutting-edge high-resolution endoscopic technologies are demonstrating promising outcomes in the visual diagnosis of mucosal lesions with the aid of linked color imaging and machine learning models. Following the PRISMA guidelines, this study examined the articles in databases such as PubMed, resulting in 167 included articles. This review discusses the currently available and emerging methods for diagnosing GC early on, as well as new developments in the endoscopic detection of early lesions of the stomach.