Diagnostic value of endoscopic ultrasonography for the depth of gastric cancer suspected of submucosal invasion: a multicenter prospective study

Prediction of the invasion depth of superficial nonampullary duodenal adenocarcinoma

OBJECTIVES

Distinguishing between intramucosal cancer and submucosal invasive cancer is vital for optimal treatment selection for patients with superficial nonampullary duodenal adenocarcinoma (SNADAC); however, standard diagnostic systems for diagnosing invasion depth are as yet undetermined.

METHODS

Of 205 patients with SNADAC who underwent treatment at our institution between 2006 and 2022, 188 had intramucosal cancer and 17 had submucosal invasive cancer. The clinical, endoscopic, and pathological features used in the preoperative diagnosis of invasion depth and the diagnostic performance of endoscopic ultrasonography (EUS) were retrospectively analyzed in 85 patients.

RESULTS

The oral side of the papilla tumor location, protruded or mixed macroscopic type, and moderately-to-poorly differentiated adenocarcinoma based on biopsy specimens were significantly more frequent in submucosal invasive cancer than in intramucosal cancer (88% vs. 48%; 94% vs. 42%; 47% vs. 0%, respectively). From the relationship between the endoscopic features and the submucosal invasive cancer incidence, submucosal invasion risk was stratified as: (i) low-risk (risk, 2%), all lesions located on the anal side of the papilla and superficial macroscopic type on the oral side of the papilla; and (ii) high-risk (risk, 23%), protruded or mixed macroscopic type on the oral side of the papilla. Based on the biopsy specimens, all eight patients with moderately-to-poorly differentiated adenocarcinoma had submucosal invasive cancer. Furthermore, EUS was not associated with invasion depth's diagnostic accuracy improvements.

CONCLUSION

Optimal treatment indications for SNADAC can be selected based on the risk factors of submucosal invasion by tumor location, macroscopic type, and biopsy diagnosis.

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.

Endoscopic Diagnosis of Superficial Gastrointestinal Cancer

White light image (WLI) findings are important for detection and characterization in the GI tract. However, magnified endoscopic examination with image enhanced endoscopy (IEE-NE) is becoming increasingly important for qualitative diagnosis of GI neoplastic lesions. IEE-ME is extremely useful for diagnosis of invasion depth in esophageal squamous cell cancer (ESCC) and colorectal cancer, whereas macroscopic findings of WLI are still useful in Barrett's adenocarcinoma (BAC) and gastric cancer. IEE-ME is also useful for diagnosis of tumor extent in BAC and gastric cancer, whereas chromoendoscopy with indigo carmine is useful in colorectal cancer and iodine staining is indispensable in ESCC.

Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases

Endoscopic ultrasound (EUS) has emerged as a widely utilized tool in the diagnosis of digestive diseases. In recent years, the potential of artificial intelligence (AI) in healthcare has been gradually recognized, and its superiority in the field of EUS is becoming apparent. Machine learning (ML) and deep learning (DL) are the two main AI algorithms. This paper aims to outline the applications and prospects of artificial intelligence-assisted endoscopic ultrasound (EUS-AI) in digestive diseases over the past decade. The results demonstrated that EUS-AI has shown superiority or at least equivalence to traditional methods in the diagnosis, prognosis, and quality control of subepithelial lesions, early esophageal cancer, early gastric cancer, and pancreatic diseases including pancreatic cystic lesions, autoimmune pancreatitis, and pancreatic cancer. The implementation of EUS-AI has opened up new avenues for individualized precision medicine and has introduced novel diagnostic and treatment approaches for digestive diseases.

Early Gastric Cancer: Update on Prevention, Diagnosis and Treatment

Gastric cancer (GC) is a relevant public health issue as its incidence and mortality rates are growing worldwide. There are recognized carcinogen agents, such as obesity, tobacco, meat, alcohol consumption and some dietary protective factors. Strategies of early diagnosis through population-based surveillance programs have been demonstrated to be effective in lowering the morbidity and mortality related to GC in some countries. Indeed, the detection of early lesions is very important in order to offer minimally invasive treatments. Endoscopic resection is the gold standard for lesions with a low risk of lymph node metastasis, whereas surgical mini-invasive approaches can be considered in early lesions when endoscopy is not curative. This review outlines the role of lifestyle and prevention strategies for GC, in order to reduce the patients' risk factors, implement the surveillance of precancerous conditions and, therefore, improve the diagnosis of early lesions. Furthermore, we summarize the available treatments for early gastric cancer.