Usefulness of Demarcation of Differentiated-Type Early Gastric Cancers after Helicobacter pylori Eradication by Magnifying Endoscopy with Narrow-Band Imaging

Photodynamic Diagnosis for the Identification of Intestinal-Type Gastric Cancers and High-Grade Adenomas

Gastric cancer is the second most common cancer in Japan. The incidence of gastric cancer remains high owing to the increase in the elderly population. Endoscopy outperforms radiography in identifying early gastric cancer (EGC). Furthermore, image-enhanced endoscopy (IEE) has been developed and implemented worldwide in clinical practice. Magnifying IEE images can help to visualize the microvascular pattern and microstructure architecture, which is used for the characterization of EGC. However, accurate endoscopic diagnosis requires the experience and skill of endoscopists, making an objective and simple diagnostic method desirable. In this retrospective study, we investigated the diagnostic yield of 5-aminolevulinic acid (5-ALA)-mediated photodynamic diagnosis (PDD) for identifying gastric cancers and high-grade adenomas. In total, 52 lesions from 43 patients were ultimately included in the study. We detected 5-ALA-mediated protoporphyrin IX fluorescence in 45 of the 52 lesions that were initially intended for PDD, resulting in a detection rate of 86.5%, whereas each signet ring cell carcinoma was negative using 5-ALA PDD. In eight of the patients with multiple lesions, 17 lesions were identified using 5-ALA PDD. Again, we took biopsies from six areas that we suspected as new lesions. While 4 lesions were gastric neoplasms resected by endoscopic submucosal dissection, two other lesions were normal. Preoperative 5-ALA-PDD could provide additional diagnostic yields to detect such multiple lesions simultaneously. No severe adverse events were observed. Prospective multicenter studies are warranted to confirm the usefulness of 5-ALA PDD for EGC identification.

Current Status of Photodynamic Diagnosis for Gastric Tumors

Although the recent development and widespread use of image-enhanced endoscopy and magnifying endoscopy have improved endoscopic diagnosis of gastric cancer, it is somewhat complicated, requires a higher level of expertise, and is still subjective. Photodynamic endoscopic diagnosis (PDED) is based on the fluorescence of photosensitizers that accumulate in tumors, which enables objective evaluation independent of the endoscopist’s experience, and is useful for tumor detection. The objective of this work was to perform a narrative review of PDED for gastric tumors and to introduce our approach to PDED in gastric tumors in our hospital. In our review there have been case reports of PDED for gastric cancer, but its usefulness has not been established because no prospective studies evaluating its usefulness have been performed. In our previous study, 85.7% (42/49) of gastric tumors exhibited fluorescence in PDED. PDED may be useful in the diagnosis of early gastric cancer. Our previous studies were pilot studies in cancer patients; therefore, future prospective studies are required to verify the usefulness of PDED.

ITIH4 is a novel serum biomarker for early gastric cancer diagnosis

BACKGROUND

Gastric cancer (GC) is one of the most lethal forms of cancer due to the absence of tools for its early detection. Here, we explored critical biomarkers for early diagnosis.

MATERIALS AND METHODS

Key biomarkers in serum from patients with early gastric cancer (EGC) and healthy controls (HCs) were identified via mass spectrometry and the expression of inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) was evaluated using several methods. Furthermore, ITIH4 expression in sera and exosomes from patients with EGC, advanced GC (AGC), low grade intraepithelial neoplasia (LGN), chronic superficial gastritis with Helicobacter pylori infection (Hpi), other systemic malignant tumors (OSTs), and healthy controls was also evaluated.

RESULTS

ITIH4 was identified as a key biomarker in patients with EGC. Its expression level in serum from the EGC group, which showed the highest specificity (94.44%), was significantly higher than those in sera from other GC groups as well as the control. Western blot analysis, immunohistochemical staining, and exosome analysis also confirmed ITIH4 expression in sera from patients with GC, but not in those from healthy individual.

CONCLUSION

ITIH4 is a key biomarker in serum from patients with EGC and has potential as a high value diagnostic marker for EGC.

Dynamic diagnosis of early gastric cancer with microvascular blood flow rate using magnifying endoscopy (with video): A pilot study

BACKGROUND AND AIM

Magnifying endoscopy (ME) diagnostic algorithm for early gastric cancer (EGC) relies on qualitative features such as microvascular (MV) architecture and microsurface structure; however, it is a "static" diagnostic algorithm that uses still images. ME can visualize red blood cell flow within subepithelial microvessels in real time. Here, we evaluated the utility of using the MV blood flow rate in combination with ME for the diagnosis of EGC as a retrospective study.

METHODS

Patients with differentiated-type EGC (n = 10) or patchy redness (n = 10) underwent ME with blue laser imaging. The mean MV blood flow rates of EGC, patchy redness, and background mucosa were calculated by the mean movement distance of one tagging red blood cell using split images of ME with blue laser imaging videos. We compared the mean MV blood flow rate between EGC, patchy redness, and background mucosa and also calculated the MV blood flow imaging ratio (inside lesion/background mucosa) between EGC and patchy redness.

RESULTS

Mean MV blood flow rate was significantly lower in EGC (1481 μm/s; range 1057-1762) than in patchy redness (3859 μm/s; 2435-5899) or background mucosa (4140.6 μm/s; 2820-6247) (P < 0.01). The MV blood flow imaging ratio was significantly lower in EGC (0.39; 0.27-0.62) than in patchy redness (0.90; 0.78-1.1) (P < 0.01).

CONCLUSIONS

Dynamic diagnosis with MV blood flow rate using ME may be useful for the differential diagnosis of EGC and patchy redness. Endoscopic assessment of dynamic processes within the gastric mucosa may facilitate the diagnosis of EGC.

Fundamentals, Diagnostic Capabilities and Perspective of Narrow Band Imaging for Early Gastric Cancer

The development of image-enhanced endoscopy has dramatically improved the qualitative and quantitative diagnosis of gastrointestinal tumors. In particular, narrow band imaging (NBI) has been widely accepted by endoscopists around the world in their daily practice. In 2009, Yao et al. proposed vessel plus surface (VS) classification, a diagnostic algorithm for early gastric cancer using magnifying endoscopy with NBI (ME-NBI), and in 2016, Muto et al. proposed a magnifying endoscopy simple diagnostic algorithm for early gastric cancer (MESDA-G) based on VS classification. In addition, the usefulness of ME-NBI in the differential diagnosis of gastric cancer from gastritis, diagnosis of lesion extent, inference of histopathological type, and diagnosis of depth has also been investigated. In this paper, we narrative review the basic principles, current status, and future prospects of NBI.

Characteristics and Early Diagnosis of Gastric Cancer Discovered after Helicobacter pylori Eradication

The prevalence of gastric cancer after eradication (GCAE) is increasing dramatically in Japan. GCAE has characteristic features, and we must understand these features in endoscopic examinations. Differentiated cancer types were frequently found after eradication and included characteristic endoscopic features such as reddish depression (RD). However, benign RD can be difficult to distinguish from gastric cancer because of histological alterations in the surface structures (nonneoplastic epithelium or epithelium with low-grade atypia [ELA]) as well as multiple appearances of RD. Recently, we clarified similar alterations in genetic mutations between ELA and gastric cancer, suggesting that ELA is derived from gastric cancer. Clinically, submucosal invasive cancer was frequently found in patients after eradication therapy even if they received annual endoscopic surveillance. We can improve the diagnostic ability using image-enhanced endoscopy with magnified observation.

Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging

BACKGROUND AND AIM

Magnifying endoscopy with narrow-band imaging (ME-NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. Recently, artificial intelligence (AI), using deep learning and a convolutional neural network (CNN), has made remarkable progress in various medical fields. Here, we constructed an AI-assisted CNN computer-aided diagnosis (CAD) system, based on ME-NBI images, to diagnose EGC and evaluated the diagnostic accuracy of the AI-assisted CNN-CAD system.

METHODS

The AI-assisted CNN-CAD system (ResNet50) was trained and validated on a dataset of 5574 ME-NBI images (3797 EGCs, 1777 non-cancerous mucosa and lesions). To evaluate the diagnostic accuracy, a separate test dataset of 2300 ME-NBI images (1430 EGCs, 870 non-cancerous mucosa and lesions) was assessed using the AI-assisted CNN-CAD system.

RESULTS

The AI-assisted CNN-CAD system required 60 s to analyze 2300 test images. The overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the CNN were 98.7%, 98%, 100%, 100%, and 96.8%, respectively. All misdiagnosed images of EGCs were of low-quality or of superficially depressed and intestinal-type intramucosal cancers that were difficult to distinguish from gastritis, even by experienced endoscopists.

CONCLUSIONS

The AI-assisted CNN-CAD system for ME-NBI diagnosis of EGC could process many stored ME-NBI images in a short period of time and had a high diagnostic ability. This system may have great potential for future application to real clinical settings, which could facilitate ME-NBI diagnosis of EGC in practice.

Review: Diagnosis of Helicobacter pylori infection

Endoscopic imaging of the stomach is improving. In addition to narrow band imaging, other methods, for example, blue light imaging and linked color imaging, are now available and can be combined with artificial intelligence systems to obtain information on the gastric mucosa and detect early gastric cancer. Immunohistochemistry is only recommended as an ancillary stain in case of chronic active gastritis without Helicobacter pylori detection by standard staining, and recommendations to exclude false negative H. pylori results have been made. Molecular methods using real-time PCR, droplet digital PCR, or amplification refractory mutation system PCR have shown a high accuracy, both for detecting H. pylori and for clarithromycin susceptibility testing, and can now be used in clinical practice for targeted therapy. The most reliable non-invasive test remains the ¹³ C-urea breath test. Large data sets show that DOB values are higher in women and that the cut-off for positivity could be decreased to 2.74 DOB. Stool antigen tests using monoclonal antibodies are widely used and may be a good alternative to UBT, particularly in countries with a high prevalence of H. pylori infection. Attempts to improve serology by looking at specific immunodominant antigens to distinguish current and past infection have been made. The interest of Gastropanel^® which also tests pepsinogen levels was confirmed.