Screening for precancerous lesions of upper gastrointestinal tract: from the endoscopists' viewpoint

Advanced Endoscopic Techniques to Detect Prevalence of Synchronous Oesophageal Cancers in Patients with Head and Neck Cancers

Objective

To study the prevalence of synchronous oesophageal cancer in patients with head and neck cancers using Narrow Band Imaging and Lugol's chromoendoscopy.

Materials and methods

Study design: Prospective cross sectional diagnostic study. Method: 63 recruited patients with head and neck cancers, underwent haematologic evaluation, histological confirmation, imaging which included contrast enhanced computerised tomography(CECT) of the Neck and when indicated an additional Magnetic Resonance Imaging(MRI) scan followed by UGI endoscopy using white light followed by Narrow Band Imaging(NBI) and Lugol's chromoendoscopy(LCE).

Results

Oesophageal examination picked up a gastric inlet patch in 5 subjects and epithelial hyperplasia in one while the remaining 57 were normal on using White Light Endoscopy (WLE). NBI identified an abnormal pattern in 4 patients in whom WLE was normal (3 - Type II Intra Papillary Capillary Loop (IPCL) pattern, 1- Type III IPCL pattern). LCE showed unstained mucosa of < 10 mm in six patients, the histopathology reported were normal tissue in two patients, mild chronic oesophagitis in two and, gastric metaplasia and high grade dysplasia in one each respectively. Unstained mucosa of > 10 mm in one subject showed epithelial hyperplasia. Two patients had an abnormal NBI and LCE pattern although the WLE were normal.

Conclusion

By utilizing NBI and LCE, although oesophageal cancer was not detected, premalignant pathology like high grade dysplasia, as well as gastric metaplasia, epithelial hyperplasia, esophagitis were detected. Using both NBI and LCE along with WLE would be complimentary to detect early pathological lesions. Capturing the lesions in the window period that exists between the transformation of epithelial dysplasia to carcinoma and treating them early will reduce the morbidity and also improve the outcome in oesophageal malignancy.

Screening and surveillance of esophageal cancer by magnifying endoscopy with narrow band imaging improves the survival of hypopharyngeal cancer patients

Introduction

Patients with head and neck cancer may develop a second primary neoplasm (SPN) of the esophagus due to field cancerization. This study investigated the impacts of esophageal cancer screening using magnifying endoscopy with narrow-band imaging (ME-NBI) on the outcomes of hypopharyngeal cancer patients.

Methods

Patients with hypopharyngeal cancer diagnosed from 2008 to 2021 in a tertiary hospital were reviewed retrospectively. Screening and surveillance using ME-NBI examination of the esophagus were divided into three patterns: (1) ME-NBI never performed or more than 6 months after diagnosis of index primary hypopharyngeal cancer, (2) ME-NBI within 6 months only, and (3) ME-NBI within 6 months and regular surveillance.

Results

A total of 261 were reviewed and 21 (8%) patients were in stage I, 20 (8%) in stage II, 27 (10%) in stage III, 116 (44%) in stage IVA, 65 (25%) in stage IVB, and 12 (5%) in stage IVC. Sixty-seven (26%) patients had SPN (50 esophagus, 10 oral cavity, 3 oropharynx, 2 nasopharynx, 1 larynx and 1 lung). Among esophageal SPN, 35 (70%) and 15 (30%) patients developed synchronous and metachronous neoplasia, respectively. In multivariate Cox regression analysis, advanced stages III and IV (compared with stages I and II, HR: 1.86, 1.18-2.95, p=0.008), ME-NBI examination of the esophagus received within 6 months and regular surveillance (HR: 0.53, 0.36-0.78, p=0.001) were independent factors affecting the overall survival of patients with hypopharyngeal cancer.

Discussion

Our findings demonstrated that screening and surveillance of esophageal SPN by ME-NBI improves the survival of patients with hypopharyngeal cancer.

Guide mapping for effective superficial photothermal coagulation of the esophagus using computer simulations with ex vivo sheep model validation study

OBJECTIVES

The transfer and widespread acceptance of laser-induced thermal therapy into gastroenterology remain a topic of interest. However, a practical approach to the quantitative effect of photothermal injury in the esophagus needs further investigation. Here, we aim to perform computer simulations that simulate laser scanning and calculate the laser-induced thermal damage area. The simulation engine offers the results in a guide map for laser coagulation with a well-confined therapeutic area according to laser irradiance and surface scanning speed. The study also presents validation experiments that include histology analyses in an ex vivo sheep esophagus model.

METHODS

The simulation engine was developed based on the Monte-Carlo method and the Arrhenius damage integral. The computational model mimicked laser scanning by shifting the position of the calculated heat source in the grating system along the axis to be scanned. The performance of the simulations was tested in an ex vivo sheep esophagus model at a laser wavelength of 1505 nm. Histological analysis, hematoxylin-eosin staining, light microscope imaging, and block-face scanning electron microscopy were used to assess thermal damage to the tissue model.

RESULTS

The developed simulation engine estimated the photothermal coagulation area for a surface scanning speed range of 0.5-8 mm/second and laser power of up to 0.5 W at a 0.9-nm laser diameter in a tissue model with a volume of 4 × 4 × 4 mm³ . For example, the optimum laser irradiation for effective photothermal coagulation in the mucosa and superficial submucosa depths was estimated to be between 16.4 and 31.8 W/cm² , 23.2 and 38.1 W/cm² at 0.5 and 1 mm/second, respectively. The computational results, summarized as a guide map, were directly compared with the results of ex vivo tissue experiments. In addition, it was pointed out that the comparative theoretical and experimental data overlap significantly in terms of energy density.

CONCLUSIONS

Our results suggest that the developed simulation approach could be a seed algorithm for further preclinical and clinical trials and a complementary tool to the laser-induced photothermal coagulation technique for superficial treatments in the gastrointestinal tract. In future preclinical studies, it is thought that the simulation engine can be enriched by combining it with an in vivo model for different laser wavelengths.

Endoscopic Screening for Second Primary Tumors of the Esophagus Among Head and Neck Cancer Patients

Malignancies of the head and neck (HN) region and esophagus are among the most common cancers worldwide. Due to exposure to common carcinogens and the theory of field cancerization, HN cancer patients have a high risk of developing second primary tumors (SPTs). In our review of 28 studies with 51,454 HN cancer patients, the prevalence of SPTs was 12%. The HN area is the most common site of SPTs, followed by the lungs and esophagus, and 13% of HN cancer patients have been reported to have esophageal high-grade dysplasia or invasive carcinoma. The prognosis of HN cancer patients with concomitant esophageal SPTs is poor, and therefore identifying esophageal SPTs as early as possible is of paramount importance for risk stratification and to guide the treatment strategy. Image-enhanced endoscopy, especially using narrow-band imaging endoscopy and Lugol’s chromoendoscopy, has been shown to improve the diagnostic performance in detecting esophageal neoplasms at an early stage. Moreover, the early detection and minimally invasive endoscopic treatment of early esophageal neoplasm has been shown to improve the prognosis. Well-designed prospective studies are warranted to establish appropriate treatment and surveillance programs for HN cancer patients with esophageal SPTs.

Artificial Intelligence for Upper Gastrointestinal Endoscopy: A Roadmap from Technology Development to Clinical Practice

Stomach cancer is the third deadliest type of cancer in the world (0.86 million deaths in 2017). In 2035, a 20% increase will be observed both in incidence and mortality due to demographic effects if no interventions are foreseen. Upper GI endoscopy (UGIE) plays a paramount role in early diagnosis and, therefore, improved survival rates. On the other hand, human and technical factors can contribute to misdiagnosis while performing UGIE. In this scenario, artificial intelligence (AI) has recently shown its potential in compensating for the pitfalls of UGIE, by leveraging deep learning architectures able to efficiently recognize endoscopic patterns from UGIE video data. This work presents a review of the current state-of-the-art algorithms in the application of AI to gastroscopy. It focuses specifically on the threefold tasks of assuring exam completeness (i.e., detecting the presence of blind spots) and assisting in the detection and characterization of clinical findings, both gastric precancerous conditions and neoplastic lesion changes. Early and promising results have already been obtained using well-known deep learning architectures for computer vision, but many algorithmic challenges remain in achieving the vision of AI-assisted UGIE. Future challenges in the roadmap for the effective integration of AI tools within the UGIE clinical practice are discussed, namely the adoption of more robust deep learning architectures and methods able to embed domain knowledge into image/video classifiers as well as the availability of large, annotated datasets.

hERG1 Potassium Channel Expression in Colorectal Adenomas: Comparison with Other Preneoplastic Lesions of the Gastrointestinal Tract

Preneoplastic lesions represent a useful target for early diagnosis and follow-up of gastrointestinal malignancies. hERG1 channel expression was tested by immunohistochemistry (IHC) in a cohort of colorectal adenoma samples belonging to Italian subjects. Overall, hERG1 was expressed in 56.5% of cases with both high staining intensity and a high percentage of positive cells. Moreover, hERG1 was expressed in a higher percentage of dysplastic adenomas with respect to hyperplastic lesions, and the proportion of positive samples further increased in patients with high-grade dysplasia. Comparing hERG1 expression in other preneoplastic lesions of the GI tract (gastric dysplasia and Barrett’s esophagus), it emerged that in all the conditions, hERG1 was expressed with a diffused pattern, throughout the cell, with variable staining intensity within the samples. The highest expression was detected in gastric dysplasia samples and the lowest in Barrett’s esophagus at similar levels observed in colorectal adenomas. Our results show that hERG1 is aberrantly expressed in human preneoplastic lesions of the gastrointestinal tract and has a different pattern of expression and role in the different sites. Overall, the detection of hERG1 expression in preneoplastic lesions could represent a novel diagnostic or prognostic marker of progression in the gastrointestinal tract.

Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A review

Upper gastrointestinal (GI) cancers are the leading cause of cancer-related deaths worldwide. Early identification of precancerous lesions has been shown to minimize the incidence of GI cancers and substantiate the vital role of screening endoscopy. However, unlike GI cancers, precancerous lesions in the upper GI tract can be subtle and difficult to detect. Artificial intelligence techniques, especially deep learning algorithms with convolutional neural networks, might help endoscopists identify the precancerous lesions and reduce interobserver variability. In this review, a systematic literature search was undertaken of the Web of Science, PubMed, Cochrane Library and Embase, with an emphasis on the deep learning-based diagnosis of precancerous lesions in the upper GI tract. The status of deep learning algorithms in upper GI precancerous lesions has been systematically summarized. The challenges and recommendations targeting this field are comprehensively analyzed for future research.

Development and validation of a classification and scoring system for the diagnosis of oral squamous cell carcinomas through confocal laser endomicroscopy

Background

Confocal laser endomicroscopy (CLE) is an optical biopsy method allowing in vivo microscopic imaging at 1000-fold magnification. It was the aim to evaluate CLE in the human oral cavity for the differentiation of physiological/carcinomatous mucosa and to establish and validate, for the first time, a scoring system to facilitate CLE assessment.

Methods

The study consisted of 4 phases: (1) CLE-imaging (in vivo) was performed after the intravenous injection of fluorescein in patients with histologically confirmed carcinomatous oral mucosa; (2) CLE-experts (n = 3) verified the applicability of CLE in the oral cavity for the differentiation between physiological and cancerous tissue compared to the gold standard of histopathological assessment; (3) based on specific patterns of tissue changes, CLE-experts (n = 3) developed a classification and scoring system (DOC-Score) to simplify the diagnosis of oral squamous cell carcinomas; (4) validation of the newly developed DOC-Score by non-CLE-experts (n = 3); final statistical evaluation of their classification performance (comparison to the results of CLE-experts and the histopathological analyses).

Results

Experts acquired and edited 45 sequences (260 s) of physiological and 50 sequences (518 s) of carcinomatous mucosa (total: 95 sequences/778 s). All sequences were evaluated independently by experts and non-experts (based on the newly proposed classification system). Sensitivity (0.953) and specificity (0.889) of the diagnoses by experts as well as sensitivity (0.973) and specificity (0.881) of the non-expert ratings correlated well with the results of the present gold standard of tissue histopathology. Experts had a positive predictive value (PPV) of 0.905 and a negative predictive value (NPV) of 0.945. Non-experts reached a PPV of 0.901 and a NPV of 0.967 with the help of the DOC-Score. Inter-rater reliability (Fleiss` kappa) was 0.73 for experts and 0.814 for non-experts. The intra-rater reliability (Cronbach’s alpha) of the experts was 0.989 and 0.884 for non-experts.

Conclusions

CLE is a suitable and valid method for experts to diagnose oral cancer. Using the DOC-Score system, an accurate chair-side diagnosis of oral cancer is feasible with comparable results to the gold standard of histopathology—even in daily clinical practice for non-experienced raters.

Prevention strategies for esophageal cancer: Perspectives of the East vs. West

Esophageal cancer is the eighth most common cancer worldwide. Esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) are the two major phenotypes in Western and Eastern countries, respectively. Because of different pathways in carcinogenesis, the risk factors and effective steps for prevention of esophageal cancer are different between EAC and ESCC. The carcinogenesis of EAC is initiated by the acid exposure of the esophageal mucosa from stomach while that of the ESCC are related to the chronic irritation of carcinogens mainly by the alcohol, cigarette, betel quid, and hot beverage. To eliminate the burden of esophageal cancer on the global health, the effective strategy should be composed of the primary, secondary, and tertiary prevention. In this article, we perform a systematic review of the preventive strategies for esophageal cancer with special emphasis on the differences from the perspectives of Western and Eastern countries.