A newly developed continuous zoom-focus endocytoscope

Quantitative diagnostic algorithm using endocytoscopy for superficial nonampullary duodenal epithelial tumors

BACKGROUND AND AIM

Optical biopsy using endocytoscopy for superficial nonampullary duodenal epithelial tumors (SNADETs) is practical; however, a diagnostic algorithm has not been established. The aim of this study was to determine correlations of endocytoscopic findings of SNADETs with histology using computer analysis and to establish an algorithm.

METHODS

Endocytoscopic images and histological images of duodenal lesions from 70 patients were retrospectively collected. The numbers of glands and densely stained areas with methylene blue (DSMs) per 1 mm2 and the percentage of DSMs per screen in endocytoscopy were determined. Moreover, correlations in DSMs and glands between endocytoscopy and histological images were analyzed. Histopathological diagnoses were assessed according to the revised Vienna classification. The primary outcome was correlation between the number of glands in endocytoscopy and that in histology. Finally, a diagnostic algorithm for endoscopic intervention of SNADETs with a statistical program command was established.

RESULTS

The number of glands in endocytoscopic images was correlated with that in histopathological images (ρ 0.64, P < 0.001). There were significant differences in the mean number of glands between category 4/5 and category 3 (P = 0.03) and the mean percentage of DSMs between category 4/5 and category 1 (P < 0.001). When the cutoffs for the number of glands and percentage of DSMs were set at 47 per 1 mm2 and 20.8% in one screen, respectively, the area under the ROC curve was 0.89.

CONCLUSIONS

Endocytoscopic images of SNADETs reflect histopathological atypia, and computer analysis provides a practical diagnostic algorithm for endoscopic intervention.

In Vivo Staging the Progression of Colitis and Associated Cancer by Concurrent Microimaging of Key Biomarkers

Currently colorectal cancer (CRC) staging (colitis, adenoma, and carcinoma) mainly relies on ex vivo pathologic analysis requiring an invasive surgical process with limited sample collection and increased metastatic risk. Thus, in vivo noninvasive pathological diagnosis is extremely demanded. By verifying the samples of clinical patients and CRC mouse models, it was found that vascular endothelial growth factor receptor 2 (VEGFR2) was barely expressed in the colitis stage and only appeared in adenoma and carcinoma stages with obvious elevation, while prostaglandin E receptor 4 (PTGER4) could be observed from colitis to adenoma and carcinoma stages with a gradient increase of expression. VEGFR2 and PTGER4 were further chosen as key biomarkers for molecular pathological diagnosis in vivo and corresponding molecular probes were constructed. The feasibility of in vivo noninvasive CRC staging by concurrent microimaging of dual biomarkers using confocal laser endoscopy (CLE) was verified in CRC mouse models and further confirmed by ex vivo pathological analysis. In vivo CLE imaging exhibited the correlation of severe colonic crypt structural alteration with a higher biomarker expression in adenoma and carcinoma stages. This strategy shows promise in benefiting patients undergoing CRC progression with in-time, noninvasive, and precise pathological staging, thus providing valuable guidance for selecting therapeutic strategies.

Endocytoscopic Observation of Esophageal Lesions: Our Own Experience and a Review of the Literature

This review outlines the process of the development of the endocytoscope (EC) with reference to previously reported studies including our own. The EC is an ultra-high-magnification endoscope capable of imaging at the cellular level. The esophagus is the most suitable site for EC observation because it is amenable to vital staining. The diagnosis of esophageal lesions using EC is based on nuclear density and nuclear abnormality, allowing biopsy histology to be omitted. The observation of nuclear abnormality requires a magnification of ×600 or higher using digital technology. Several staining methods have been proposed, but single staining with toluidine blue or methylene blue is most suitable because the contrast at the border of a cancerous area can be easily identified. A three-tier classification of esophageal lesions visualized by EC is proposed: Type 1 (non-cancerous), Type 2 (endocytoscopic borderline), and Type 3 (cancerous). Since characteristic EC images reflecting pathology can be obtained from non-cancerous esophageal lesions, a modified form of classification with four additional characteristic non-cancerous EC features has also been proposed. Recently, deep-learning AI for analysis of esophageal EC images has revealed that its diagnostic accuracy is comparable to that of expert pathologists.

Optical biopsy for esophageal squamous cell neoplasia by using endocytoscopy

BACKGROUND

Endocytoscopy (ECS) enables microscopic observation in vivo for the gastrointestinal mucosa; however, there has been no prospective study in which the diagnostic accuracy of ECS for lesions that have not yet undergone histological diagnosis was evaluated. We conducted a surveillance study for patients in a high-risk group of esophageal squamous cell carcinoma (ESCC) and evaluated the in vivo histological diagnostic accuracy of ECS.

METHODS

This study was a multicenter prospective study. We enrolled 197 patients in the study between September 1, 2019 and November 30, 2020. The patients first underwent white light imaging and narrow band imaging, and ultra-high magnifying observation was performed if there was a lesion suspected to be an esophageal tumor. Endoscopic submucosal dissection (ESD) was later performed for lesions that were diagnosed to be ESCC by ECS without biopsy. We evaluated the diagnostic accuracy of ECS for esophageal tumorous lesions.

RESULTS

ESD was performed for 37 patients (41 lesions) who were diagnosed as having ESCC by ECS, and all of them were histopathologically diagnosed as having ESCC. The sensitivity [95% confidence interval (CI)] was 97.6% (87.7-99.7%), specificity (95% CI) was 100% (92.7-100%), diagnostic accuracy (95% CI) was 98.9% (94.0-99.8%), positive predictive value (PPV) (95% CI) was 100% (91.4-100%) and negative predictive value (NPV) (95% CI) was 98.0% (89.5-99.7%).

CONCLUSIONS

ECS has a high diagnostic accuracy and there were no false positives in cases diagnosed and resected as ESCC. Optical biopsy by using ECS for esophageal lesions that are suspected to be tumorous is considered to be sufficient in clinical practice.

Convolutional neural network-based system for endocytoscopic diagnosis of early gastric cancer

Background

Endocytoscopy (ECS) aids early gastric cancer (EGC) diagnosis by visualization of cells. However, it is difficult for non-experts to accurately diagnose EGC using ECS. In this study, we developed and evaluated a convolutional neural network (CNN)-based system for ECS-aided EGC diagnosis.

Methods

We constructed a CNN based on a residual neural network with a training dataset comprising 906 images from 61 EGC cases and 717 images from 65 noncancerous gastric mucosa (NGM) cases. To evaluate diagnostic ability, we used an independent test dataset comprising 313 images from 39 EGC cases and 235 images from 33 NGM cases. The test dataset was further evaluated by three endoscopists, and their findings were compared with CNN-based results.

Results

The trained CNN required 7.0 s to analyze the test dataset. The area under the curve of the total ECS images was 0.93. The CNN produced 18 false positives from 7 NGM lesions and 74 false negatives from 28 EGC lesions. In the per-image analysis, the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 83.2%, 76.4%, 92.3%, 93.0%, and 74.6%, respectively, with the CNN and 76.8%, 73.4%, 81.3%, 83.9%, and 69.6%, respectively, for the endoscopist-derived values. The CNN-based findings had significantly higher specificity than the findings determined by all endoscopists. In the per-lesion analysis, the accuracy, sensitivity, specificity, PPV, and NPV of the CNN-based findings were 86.1%, 82.1%, 90.9%, 91.4%, and 81.1%, respectively, and those of the results calculated by the endoscopists were 82.4%, 79.5%, 85.9%, 86.9%, and 78.0%, respectively.

Conclusions

Compared with three endoscopists, our CNN for ECS demonstrated higher specificity for EGC diagnosis. Using the CNN in ECS-based EGC diagnosis may improve the diagnostic performance of endoscopists.

Evaluation of Microvascular Patterns Alone Using Endocytoscopy with Narrow-Band Imaging for Diagnosing Gastric Cancer

INTRODUCTION

Although endocytoscopy (EC) with narrow-band imaging (NBI) is effective in diagnosing gastric cancer, no diagnostic system has been validated. We explored a specific diagnostic system for gastric cancer using EC with NBI.

METHODS

Equal numbers of images from cancerous and noncancerous areas (114 images each) were assessed by endoscopists with (development group: 33) and without (validation group: 28) specific training in magnifying endoscopy with NBI. Microvascular and microsurface patterns (MS) in each image were evaluated. Lesions were diagnosed as cancerous when patterns were deemed "irregular." The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a diagnosis according to patterns on EC with NBI (microvascular pattern [MV] alone, MS alone, and both) were evaluated and compared between groups to determine the diagnostic performance.

RESULTS

In the development and validation groups, diagnoses based on the MV alone had significantly higher accuracy (91.7% vs. 76.3%, p < 0.0001 and 92.5% vs. 67.5%, p < 0.0001, respectively) and sensitivity (88.6% vs. 68.3%, p < 0.0001 and 89.5% vs. 38.6%, p < 0.0001, respectively) than those based on the MS alone. In both groups, there were no significant differences in diagnostic accuracy between using the MV alone and both patterns.

DISCUSSION/CONCLUSION

Evaluation of the MV alone is a simple and accurate diagnostic method for gastric cancer. This system could find widespread applications in clinical practice.

Molecular Imaging of Ulex Europaeus Agglutinin in Colorectal Cancer Using Confocal Laser Endomicroscopy (With Video)

Background and Study Aims

Previous studies have identified that colorectal cancer has different fucosylation levels compared to the normal colon. Ulex europaeus agglutinin-I (UEA-I), which specifically combines with α1-2 fucose glycan, is usually used to detect fucosylation levels. Therefore, we used confocal laser endomicroscopy (CLE) to investigate fluorescently labeled UEA-Fluorescein isothiocyanate (FITC) for detecting colonic cancer.

Patients and Methods

We stained frozen mouse colon tissue sections of normal, adenoma, and adenocarcinoma species with UEA-FITC to detect fucosylation levels in different groups. White light endoscopy and endocytoscopy were first used to detect the lesions. The UEA-FITC was then stained in the mice and human colon tissues in vitro. The CLE was used to detect the UEA-FITC levels of the corresponding lesions, and videos were recorded for quantitation analysis. The diagnostic accuracy of UEA-FITC using CLE was evaluated in terms of sensitivity and specificity.

Results

The UEA expression level in colorectal cancer was lower than that in normal intestinal epithelium. The fluorescence intensity ratio of UEA-FITC in colorectal cancer was significantly lower than that in normal tissue detected by CLE in both mice and humans. The combination of UEA-FITC and CLE presented a good diagnostic accuracy with a sensitivity of 95.6% and a specificity of 97.7% for detecting colorectal cancer. The positive and negative predictive values were 91.6% and 95.6%, respectively. Overall, 95.6% of the sites were correctly classified by CLE.

Conclusions

We developed a new imaging strategy to improve the diagnostic efficacy of CLE by using UEA-FITC.

Application of artificial intelligence-assisted endoscopic detection of early esophageal cancer

In recent years, artificial intelligence (AI) combined with endoscopy has made an appearance in the diagnosis of early esophageal cancer (EC) and achieved satisfactory results. Due to the rapid progression and poor prognosis of EC, the early detection and diagnosis of EC are of great value for patient prognosis improvement. AI has been applied in the screening of early EC and has shown advantages; notably, it is more accurate than less-experienced endoscopists. In China, the detection of early EC depends on endoscopist expertise and is inevitably subject to interobserver variability. The excellent imaging recognition ability of AI is very suitable for the diagnosis and recognition of EC, thereby reducing the missed diagnosis and helping physicians to perform endoscopy better. This paper reviews the application and relevant progress of AI in the field of endoscopic detection of early EC (including squamous cell carcinoma and adenocarcinoma), with a focus on diagnostic performance of AI to identify different types of endoscopic images, such as sensitivity and specificity.

Application of Current Image-Enhanced Endoscopy in Gastric Diseases

Image-enhanced endoscopy (IEE) plays an integral role in endoscopic diagnosis and treatment. IEE enables an early and accurate detection of cancer and characterization of lesions prior to therapeutic decisions. Ideal IEE can serve as an optical or digital chromoscopic endoscopy, as well as an optical biopsy that predicts exact histopathology. Several IEE modalities have recently been developed and are used in the clinical field. The stomach is a challenging organ for imaging because of its complex secretion function and status of Helicobacter pylori infection. Therefore, understanding the current IEE modalities for their clinical applicability in an evidence-based approach is warranted. Along with technology refinements, the new paradigm will be available for the diagnosis of gastric cancer or other conditions in the stomach in the near future.

Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?

Esophageal cancer (EC) is a common malignant tumor of the digestive tract and originates from the epithelium of the esophageal mucosa. It has been confirmed that early EC lesions can be cured by endoscopic therapy, and the curative effect is equivalent to that of surgical operation. Upper gastrointestinal endoscopy is still the gold standard for EC diagnosis. The accuracy of endoscopic examination results largely depends on the professional level of the examiner. Artificial intelligence (AI) has been applied in the screening of early EC and has shown advantages; notably, it is more accurate than less-experienced endoscopists. This paper reviews the application of AI in the field of endoscopic detection of early EC, including squamous cell carcinoma and adenocarcinoma, and describes the relevant progress. Although up to now most of the studies evaluating the clinical application of AI in early EC endoscopic detection are focused on still images, AI-assisted real-time detection based on live-stream video may be the next step.

Diagnostic performance in gastric cancer is higher using endocytoscopy with narrow-band imaging than using magnifying endoscopy with narrow-band imaging

BACKGROUND

For diagnosing gastric cancer, differences in the diagnostic performance between endocytoscopy with narrow-band imaging and magnifying endoscopy with narrow-band imaging have not been reported. We aimed to clarify these differences by analyzing diagnoses made by endoscopists in Japan.

METHODS

This single-center retrospective cohort study used 106 cancerous and 106 non-cancerous images obtained via both modalities (total, 424 images) for diagnosis. Sixty-one endoscopists with varying experience levels from 45 institutions were included. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated to determine the diagnostic performance of each modality and compared using the Mann-Whitney U test.

RESULTS

Among all endoscopists, diagnostic accuracy, sensitivity, positive predictive value, and negative predictive value were higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging (percentage [95% confidence interval]: 78.8% [76.4-83.0%] versus 72.2% [69.3-73.6%], p < 0.0001; 82.1% [78.3-85.9%] versus 64.2% [60.4-69.8%], p < 0.0001; 88.7% [82.6-90.7%] versus 78.5% [75.4-85.1%], p = 0.0023; 79.0% [75.3-80.5%] versus 68.5% [66.4-71.6%], p < 0.0001, respectively). In the magnifying endoscopy with narrow-band imaging-trained group, these values were also higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging (p < 0.0001, p = 0.0001, p = 0.0143, and p < 0.0001, respectively). Diagnostic accuracy, sensitivity, and negative predictive value were higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging in the magnifying endoscopy with narrow-band imaging-untrained group (p = 0.0041, p = 0.0049, and p = 0.0098, respectively).

CONCLUSIONS

Diagnostic performance was higher using endocytoscopy with narrow-band imaging than using magnifying endoscopy with narrow-band imaging. Our results may help change the technique used to diagnose gastric cancer.

Artificial intelligence assisted endocytoscopy: A novel eye in endoscopy

Over the past few years, emerging new approaches in endoscopic imaging technologies facilitate a high-quality assessment of lesions found in the gastrointestinal (GI) tract. Endocytoscopy (EC), as a novel tool in endoscopy, aids the more accurate evaluation of superficial mucosal surface. This review article aims to represent the most relevant information related to the latest EC technology and its clinical application in the lower GI tract diagnostic. We discuss EC-computer-aided diagnosis capability to differentiate between non-neoplastic and neoplastic lesion that offers a closer look to in-vivo assessment and diagnosis of cancerous tissue. Nevertheless, artificial-assisted EC diagnostics could also be employed with benefits in patients with inflammatory bowel disease (IBD) by accurately highlighting the presence of mucosal injury. In our review we included those studies comprising data about colonoscopy with narrow banding imaging and computer-aided diagnosis, as well as EC. Last but not least, artificial-assisted EC facilitates in-vivo diagnosis of the lower GI tract and may, in the future, remodel the field of in-vivo endoscopic diagnosis of colorectal lesions, representing another step towards the so-called optical biopsy.

Endocytoscopic observation with methylene blue staining for duodenal neoplasms associated with familial adenomatous polyposis

Duodenal cancer is a leading cause of death after colectomy in patients with familial adenomatous polyposis (FAP). Detailed endoscopic evaluation of duodenal lesions with potential for carcinoma development is therefore mandatory. Here we investigated the features of duodenal lesions in FAP patients using an endocytoscopy system (ECS). We retrospectively reviewed duodenal lesions in 15 cases of FAP using an ECS (GIF-H290EC) with methylene blue (MB) as the vital dye. With reference to the Spigelman classification, we investigated the number of lesions using white light (WL), narrow-band imaging (NBI), and MB staining. Using the maximum magnification power of the ECS we investigated the histology (duct openings or finger-like projections) and grade of dysplasia (presence or absence of enlarged oval-shaped nuclei) of the lesions. The number of duodenal lesions increased in ascending order of WL, NBI, and MB (P < 0.05). Among 51 MB-unstained lesions, 46 (90.2%) were proven to be duodenal neoplasms histologically. Duct openings were seen in 90.2% of tubular adenomas and tubulovillous adenomas. Finger-like projections were seen in 33.3% of tubular adenomas and in 88.2% of tubulovillous adenomas. Enlarged oval-shaped nuclei were observed in 100% of duodenal cancers, 33.3% of high-grade adenomas, and 9.4% of low-grade adenomas. MB staining allows more accurate detection of duodenal neoplasms in comparison to conventional WL and NBI observation. In cases of FAP, use of the maximum magnification power of the ECS may allow selection of lesions with high malignant potential.

In vivo optical cellular diagnosis for uterine cervical or vaginal intraepithelial neoplasia using flexible gastrointestinal endocytoscopy -a prospective pilot study

Backgrouund

For patients with any kind of atypical squamous intraepithelial lesion of the uterine cervix or vagina, colposcopy and punch biopsy are common procedures for histological determination following cytology. However, colposcopy-guided biopsy does not provide a high level of diagnostic accuracy. The aim of this study was to determine the usefulness of optical biopsy in vivo using endocytoscopy compared with conventional procedures using colposcopy.

Methods

Between May 2018 and March 2019, patients who were scheduled for cervical conization or mapping biopsies of the vagina were prospectively enrolled. Endocytoscopy was performed by senior endoscopists prior to scheduled procedures, and endocytoscopic images and biopsy samples were taken from the most prominent site and surrounding area of the cervical or vaginal lesions. The collection process of images was randomized and anonymous, and three doctors separately evaluated the images according to the ECA classification. ECA 4 and 5 are indicative of endoscopic malignancy. The primary endpoint was diagnostic accuracy (benign or malignant: cervical intraepithelial neoplasia (CIN) 3 or vaginal intraepithelial neoplasia (VAIN) 3 or worse) of cell images at the most prominent site in each patient.

Results

A total of 28 consecutive patients were enrolled. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of endocytoscopic images were 95.0% (84.8–98.6%), 87.5% (61.9–96.5%), 95.0% (84.8–98.6%), 87.5% (61.9–96.5%) and 92.9% (78.2–98.0%), respectively. Inter-observer agreement among three reviewers was 0.78 (0.08–9.88, P < 0.01). On the other hand, the accuracy of colposcopy-guided biopsy was 74.1% (64.0–84.0%).

Conclusions

Optical cell diagnosis of cervical or vaginal intraepithelial neoplasia using endocytoscopy provides a high level of diagnostic accuracy.

Trial registration

The study was registered with the UMIN database (ID: 000031712).

UMIN000031712. Registered 16 March 2017,

The Impact of Artificial Intelligence in the Endoscopic Assessment of Premalignant and Malignant Esophageal Lesions: Present and Future

In the gastroenterology field, the impact of artificial intelligence was investigated for the purposes of diagnostics, risk stratification of patients, improvement in quality of endoscopic procedures and early detection of neoplastic diseases, implementation of the best treatment strategy, and optimization of patient prognosis. Computer-assisted diagnostic systems to evaluate upper endoscopy images have recently emerged as a supporting tool in endoscopy due to the risks of misdiagnosis related to standard endoscopy and different expertise levels of endoscopists, time-consuming procedures, lack of availability of advanced procedures, increasing workloads, and development of endoscopic mass screening programs. Recent research has tended toward computerized, automatic, and real-time detection of lesions, which are approaches that offer utility in daily practice. Despite promising results, certain studies might overexaggerate the diagnostic accuracy of artificial systems, and several limitations remain to be overcome in the future. Therefore, additional multicenter randomized trials and the development of existent database platforms are needed to certify clinical implementation. This paper presents an overview of the literature and the current knowledge of the usefulness of different types of machine learning systems in the assessment of premalignant and malignant esophageal lesions via conventional and advanced endoscopic procedures. This study makes a presentation of the artificial intelligence terminology and refers also to the most prominent recent research on computer-assisted diagnosis of neoplasia on Barrett’s esophagus and early esophageal squamous cell carcinoma, and prediction of invasion depth in esophageal neoplasms. Furthermore, this review highlights the main directions of future doctor–computer collaborations in which machines are expected to improve the quality of medical action and routine clinical workflow, thus reducing the burden on physicians.

Endocytoscopic Observation of Non-Ampullary Mucosal Duodenal Cancer

Our previous study of duodenal adenoma using an endocytoscopy system (ECS) demonstrated that disappearance of goblet cells and spindle-shaped nuclei with loss of polarity were characteristic features. In addition, round duct openings and finger-like projections were observed in tubular adenoma and villous adenoma, respectively. Here, we retrospectively investigated six cases of histologically proven sporadic non-ampullary mucosal duodenal cancer (NAMDC) using ECS. Immunohistochemistry for CD10, MUC2, MUC5AC, and MUC6 was employed to determine the mucin phenotype in addition to conventional HE histology. Immunohistochemistry revealed one case involving the duodenal bulb that was considered to be the mixed type. The other five cases, located in the second or third portion, were considered to be the intestinal type. Vital staining of the mixed-type case was considered insufficient for ECS observation because of surface mucus. However, all five cases of intestinal-type duodenal cancer demonstrated a villous structure, disappearance of goblet cells and enlarged nuclei with loss of polarity. Tubular structures were admixed in four of those cases. Four cases demonstrated oval-shaped nuclei, and one case had spindle-shaped nuclei. Cases showing spindle-shaped nuclei in most of the lesion were diagnosed histologically as cancer in adenoma where the adenomatous component of the tumor was dominant. Oval-shaped nuclei and nuclear enlargement are the characteristic features of NAMDC revealed by ECS and are included among the histological criteria used for diagnosis. ECS offers the potential to perform real-time histological diagnosis of NAMDC in vivo.

Endocytoscopy: technology and clinical application in upper gastrointestinal tract

Over the past few years, the innovative field of magnifying endoscopy has been expanding with various cutting-edge technologies, one of which is endocytoscopy, to facilitate improvement in the detection and diagnosis of gastrointestinal lesions. Endocytoscopy is a novel ultra-high magnification endoscopic technique enabling high-quality in-vivo assessment of lesions found in the gastrointestinal tract with the use of intraprocedural stains. The main scope of this review article is to offer a closer look at the latest endocytoscopic technology and its clinical application in the upper gastrointestinal tract, especially in the esophagus and stomach, as well as to introduce readers to our simplified and up-to-date endocytoscopic classification, specifically developed for the esophagus and stomach, for the in-vivo assessment and diagnosis of esophageal and gastric lesions. Despite the good accuracy of endocytoscopy in the diagnosis of esophageal and gastric lesions in recent studies, some challenges still remain (e.g., staining method and standardized endocytoscopic classification). Through continuous evaluation and improvement of methods and skills, these challenges may be overcome thus establishing current techniques and classification, paving the way for further advances in the field of endocytoscopy and magnifying endoscopy. In all, endocytoscopy seems to aid in the in-vivo diagnosis of gastrointestinal tract lesions and may, in the future, revolutionize the field of in-vivo endoscopic diagnosis of gastrointestinal cancer, representing another step towards the so-called optical biopsy.

Utilizing fourth-generation endocytoscopy and the 'enlarged nuclear sign' for in vivo diagnosis of early gastric cancer

Background and study aims  Fourth-generation endocytoscopy is an ultra-high magnification endoscopic technique designed to provide excellent quality in vivo histologic assessment of gastrointestinal lesions. This study aims to evaluate the diagnostic accuracy of endocytoscopy in early gastric cancer diagnosis. Patients and methods  A single-center, retrospective analysis of prospectively collected data from all gastric endocytoscopic examinations was conducted. Two expert endoscopists, blinded to white-light and narrow-band imaging findings as well as histopathologic diagnosis, independently reviewed and diagnosed all endocytoscopic images. A newly recognized "enlarged nuclear sign" was detected, and its implication in early gastric cancer diagnosis was evaluated. The diagnostic performance of fourth-generation endocytoscopy was assessed while using the gold standard histopathology as a reference. Results  Forty-three patients (mean age±SD, 72.6 ± 12.1 years; 31 males) were enrolled. Based on histopathology, 23 had well-differentiated adenocarcinomas, four adenomas, and 16 non-neoplastic lesions. The sensitivity, specificity, and accuracy of fourth-generation endocytoscopy for gastric cancer diagnosis were 87.0 % (95 % CI: 67.9 - 95.5), 80.0 % (95 % CI: 58.4 - 91.9), and 83.7 % (95 % CI: 70.0 - 91.9) by endoscopist A; and 91.3 % (95 % CI: 73.2 - 97.6), 75.0 % (95 % CI: 53.1 - 88.8), and 83.7 % (95 % CI: 70.0 - 91.9) by endoscopist B. The inter-observer agreement, Kappa statistic = 0.71 (95 % CI: 0.50 - 0.93), was good. The sensitivity, specificity, and accuracy of the enlarged nuclear sign for early gastric cancer diagnosis were 87.0 % (95 % CI: 67.9 - 95.5), 95.0 % (95 % CI: 76.4 - 99.1), and 90.7 % (95 % CI: 78.4 - 96.3) by endoscopist A; and 82.6 % (95 % CI: 62.9 - 93.0), 85.0 % (95 % CI: 64.0 - 94.8), and 83.7 % (95 % CI: 70.0 - 91.9) by endoscopist B. The inter-observer agreement, Kappa statistic = 0.68 (95 % CI: 0.51 - 0.89) was good. Conclusion: Fourth-generation endocytoscopy appears to aid in the diagnosis of early gastric cancer, particularly well-differentiated adenocarcinomas, due to its good diagnostic accuracy and identification of the "enlarged nuclear sign," and deserves further evaluation in future studies.

Advanced Imaging for Barrett's Esophagus and Early Neoplasia: Surface and Subsurface Imaging for Diagnosis and Management

PURPOSE OF REVIEW

Esophageal adenocarcinoma bears one of the fastest rising incidence of any cancers and generally arises in the setting of gastroesophageal reflux and Barrett's esophagus. However, early detection of neoplasia can be challenging since most patients are asymptomatic until they progress to more advanced and less curable stages, and early dysplastic lesions can be small, multifocal, and difficult to detect. Clearly, new imaging tools are needed in light of sampling error associated with random biopsies, the current standard of practice.

RECENT FINDINGS

Advances in endoscopic imaging including virtual chromoendoscopy, confocal laser endomicroscopy, and subsurface imaging with optical coherence tomography have ushered in a new era for detecting subtle neoplastic lesions. Moreover, in light of esophagus-sparing treatments for neoplastic lesions, such tools are likely to guide ablation and follow-up management. While there is no ideal single imaging modality to facilitate improved detection, staging, ablation, and follow-up of patients with dysplastic Barrett's esophagus, new advances in available technology, the potential for multimodal imaging, and the use of computer-aided diagnosis and biomarkers all hold great promise for improving detection and treatment.

In vivo histological diagnosis for gastric cancer using endocytoscopy

AIM

To examine usefulness of virtual biopsy using endocytoscopy by comparing the in vivo endocytoscopic and histopathological images of gastric cancers.

METHODS

Endocytoscopy was performed in 30 patients with early gastric cancer. Of these, 26 patients showed well differentiated adenocarcinomas, while 4 patients showed poorly differentiated adenocarcinomas (including one signet ring cell carcinoma). Cancerous and non-cancerous areas were observed after double staining with 0.05% crystal violet and 0.1% methylene blue. The endocytoscopic images obtained were evaluated by an expert endoscopist and an expert pathologist without knowledge of patient clinical data, and endocytoscopic and histopathological diagnoses were compared.

RESULTS

The endocytoscopic images of the cancerous area were assessed as evaluable in 25 (83.3%) and 27 (90%) patients by endoscopist A and pathologist B, respectively, and those of the non-cancerous area as evaluable in 28 (93.3%) and 23 (76.7%) patients by the endoscopist and pathologist, respectively. The sensitivity, specificity, and diagnostic accuracy of gastric cancer diagnosis using evaluable endocytoscopic images were 88.0% and 92.9%, and 90.6% by endoscopist A, and 88.9% and 91.3%, and 90.0% by pathologist B, respectively. Evaluation of the diagnostic concordance rate between the endoscopist and the pathologist by inter-observer agreement calculation revealed no significant difference between the two observers. The inter-observer agreement (κ-value) for endocytoscopic diagnosis was 0.745.

CONCLUSION

Endocytoscopy is useful for the differentiation of cancerous from non-cancerous gastric mucosa, making it a promising tool for virtual biopsy.