Current Status of Image-Enhanced Endoscopy for Early Identification of Esophageal Neoplasms

Current status and perspectives of esophageal cancer: a comprehensive review

Esophageal cancer (EC) continues to be a significant global health concern, with two main subtypes: esophageal squamous cell carcinoma and esophageal adenocarcinoma. Prevention and changes in etiology, improvements in early detection, and refinements in the treatment have led to remarkable progress in the outcomes of EC patients in the past two decades. This seminar provides an in-depth analysis of advances in the epidemiology, disease biology, screening, diagnosis, and treatment landscape of esophageal cancer, focusing on the ongoing debate surrounding multimodality therapy. Despite significant advancements, EC remains a deadly disease, underscoring the need for continued research into early detection methods, understanding the molecular mechanisms, and developing effective treatments.

Image-enhanced endoscopy in upper gastrointestinal disease: focusing on texture and color enhancement imaging and red dichromatic imaging

Endoscopic examination plays a crucial role in the diagnosis of upper gastrointestinal (UGI) tract diseases. Despite advancements in endoscopic imaging, the detection of subtle early cancers and premalignant lesions using white-light imaging alone remains challenging. This review discusses two novel image-enhanced endoscopy (IEE) techniques-texture and color enhancement imaging (TXI) and red dichromatic imaging (RDI)-and their potential applications in UGI diseases. TXI enhances texture, brightness, and color tone, which improves the visibility of mucosal irregularities and facilitates earlier detection of neoplastic lesions. Studies have suggested that TXI enhances the color differences between lesions and the surrounding mucosa and improves the visibility of the lesion. TXI aids in the diagnosis of various UGI diseases, including early gastric cancer, esophageal cancer, premalignant conditions such as atrophic gastritis and Barrett's esophagus, and duodenal tumors. RDI utilizes specific wavelengths to enhance the visualization of deep blood vessels or bleeding points, aiding in the rapid and accurate identification of bleeding sources during endoscopic procedures. Although promising, TXI and RDI require further large-scale studies across diverse populations to establish their clinical utility, diagnostic performance, and cost-effectiveness before integration into the guidelines. Standardized training is also required for effective utilization. Overall, these IEE techniques has the potential to improve the diagnosis and management of UGI.

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.

An umbrella-inspired snap-on robotic 3D photoacoustic endoscopic probe for augmented intragastric sensing: Proof of concept study

In this paper, we present a novel on-demand modular robotic photoacoustic tomography (PAT) probe integrated into an endoscopic device, potentially for deep intragastric sensing. The proposed solution offers a plug-and-play approach through the use of meso-scale steerable endoscopy and a new 'snap-on' 3D robotic PAT probe that can reconfigure the geometry of the intracorporeal light delivery, inspired by an umbrella structure. Specifically, using the limited esophageal access, steerable endoscopy allows navigation and advancement of a distally mounted robotic add-on for PAT that is folded until it reaches the deep-seated gastric lesion. Once the tip is positioned near the lesion site in the gastric cavity, there is ample working space for the robotic probe to adjust its umbrella-like unfolded shape. This allows fine-tuning of the laser delivery orientation of the fiber bundles to achieve the lesion-specific light delivery scheme. This design allows volumetric imaging of the intragastric PAT with enhanced sensitivity. To evaluate the performance of the modular robotic PAT probe, we performed a simulation analysis of the light intensity and ultrasound field distribution. The simulation results show that the robotic probe is feasible for intracorporeal PAT imaging. In addition, we printed a 3D model of a human stomach containing a simulated gastric tumour. Both the phantom and ex vivo experimental results validate the feasibility of the proposed robotic PAT probe.

Curative criteria for endoscopic treatment of oesophageal adenocarcinoma

The incidence of oesophageal adenocarcinoma has been increasing rapidly in the Western world. A well-known risk factor for developing this type of tumour is reflux disease, which can cause metaplasia from the squamous cell mucosa to columnar epithelium (Barrett's Oesophagus) which can progress to dysplasia and eventually adenocarcinoma. With the rise of the incidence of oesophageal adenocarcinoma, research on the best way to manage this disease is of great importance and has changed treatment modalities over the last decades. The gold standard for superficial adenocarcinoma has shifted from surgical to endoscopic management when certain criteria are met. This review will discuss the different curative criteria for endoscopic treatment of oesophageal adenocarcinoma.

Analysis of Colorectal and Gastric Cancer Classification: A Mathematical Insight Utilizing Traditional Machine Learning Classifiers

Cancer remains a formidable global health challenge, claiming millions of lives annually. Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored cancer classification using machine learning and deep learning techniques, scant literature focuses on traditional ML methods. In this manuscript, we undertake a comprehensive review of colorectal and gastric cancer detection specifically employing traditional ML classifiers. This review emphasizes the mathematical underpinnings of cancer detection, encompassing preprocessing techniques, feature extraction, machine learning classifiers, and performance assessment metrics. We provide mathematical formulations for these key components. Our analysis is limited to peer-reviewed articles published between 2017 and 2023, exclusively considering medical imaging datasets. Benchmark and publicly available imaging datasets for colorectal and gastric cancers are presented. This review synthesizes findings from 20 articles on colorectal cancer and 16 on gastric cancer, culminating in a total of 36 research articles. A significant focus is placed on mathematical formulations for commonly used preprocessing techniques, features, ML classifiers, and assessment metrics. Crucially, we introduce our optimized methodology for the detection of both colorectal and gastric cancers. Our performance metrics analysis reveals remarkable results: 100% accuracy in both cancer types, but with the lowest sensitivity recorded at 43.1% for gastric cancer.

Role of linked color imaging for upper gastrointestinal disease: present and future

Techniques for upper gastrointestinal endoscopy are advancing to facilitate lesion detection and improve prognosis. However, most early tumors in the upper gastrointestinal tract exhibit subtle color changes or morphological features that are difficult to detect using white light imaging. Linked color imaging (LCI) has been developed to overcome these shortcomings; it expands or reduces color information to clarify color differences, thereby facilitating the detection and observation of lesions. This article summarizes the characteristics of LCI and advances in LCI-related research in the upper gastrointestinal tract field.

Magnifying Endoscopy with Narrow-Band Imaging for Duodenal Neuroendocrine Tumors

Duodenal neuroendocrine tumors (NETs) are rare subepithelial tumors that arise from the neuroendocrine cells beneath the epithelial layer. However, an accurate histopathological diagnosis is difficult when tissue samples are obtained using conventional endoscopic forceps biopsy alone. This study aimed to evaluate the magnifying endoscopy with narrow-band imaging (ME-NBI) findings of duodenal NETs. We retrospectively analyzed a database of 22 duodenal NETs from 21 patients who underwent ME-NBI between January 2011 and June 2022. The ME-NBI, endosonographic, and histopathologic findings of duodenal NETs were analyzed. Nineteen lesions were located in the bulb, two were located in the superior duodenal angle, and one was located in the second portion of the duodenum. Eighteen lesions (82%) had IIa morphology, and nine (41%) had central depression on the surface. On endoscopic ultrasonography, almost all lesions (20/22, 91%) were located in the second and/or third layers, and the median tumor size was 6 mm. During ME-NBI, the microsurface pattern was regular in 18 lesions (82%) and absent in 4 (18%). The microvascular pattern was regular in 17 lesions (77%), irregular in 4 (18%), and absent in 1 (5%). Thickened subepithelial vessels were observed in 15 (68%) lesions. There was no difference in tumor size according to the presence or absence of thickened subepithelial vessels (6.1 ± 1.8 mm vs. 5.9 ± 3.8 mm, p = 0.860). In conclusion, the characteristic ME-NBI findings of duodenal NETs were regular microsurface and microvascular patterns and the presence of thickened subepithelial vessels. These ME-NBI features may be useful for differentiating duodenal NETs from other duodenal subepithelial lesions.

Biomarkers for Early Detection, Prognosis, and Therapeutics of Esophageal Cancers

Esophageal cancer (EC) is the deadliest cancer worldwide, with a 92% annual mortality rate per incidence. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two major types of ECs, with EAC having one of the worst prognoses in oncology. Limited screening techniques and a lack of molecular analysis of diseased tissues have led to late-stage presentation and very low survival durations. The five-year survival rate of EC is less than 20%. Thus, early diagnosis of EC may prolong survival and improve clinical outcomes. Cellular and molecular biomarkers are used for diagnosis. At present, esophageal biopsy during upper endoscopy and histopathological analysis is the standard screening modality for both ESCC and EAC. However, this is an invasive method that fails to yield a molecular profile of the diseased compartment. To decrease the invasiveness of the procedures for diagnosis, researchers are proposing non-invasive biomarkers for early diagnosis and point-of-care screening options. Liquid biopsy involves the collection of body fluids (blood, urine, and saliva) non-invasively or with minimal invasiveness. In this review, we have critically discussed various biomarkers and specimen retrieval techniques for ESCC and EAC.

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.