Search Results (34)

Background: Endoscopic Electroporation (EE) is an innovative minimally invasive therapy that utilises short electrical pulses combined with intratumoural (IT) calcium or IT/intravenous (IV) chemotherapy to induce tumour cell death in colorectal cancer (CRC). Based on electrochemotherapy protocols developed for the treatment of skin cancers, EE has shown promising results in salvage therapy, local tumour control, and symptom palliation, particularly in patients who are unsuitable for surgery or standard treatments. Objective: To establish, for the first time, a comprehensive and standardised protocol for setting up a Salvage Endoscopic Electroporation (SEE) service in CRC clinical practice, covering multidisciplinary patient selection, procedural steps, equipment needs, and follow-up care. Methods: Drawing from the European Standard Operating Procedures of Electrochemotherapy (ESOPE) and emerging clinical evidence on EE from King’s College London, we detail infrastructure, treatment delivery, and monitoring for CRC. Key procedural elements, safety considerations, and patient management strategies are outlined. Electroporation pulses were delivered using the Conformité Européenne (CE) approved ePORE^® electroporation generator and single-use CE-marked EndoVE^® probe (Mirai Medical, Galway, Ireland). Results: Tumour assessment involves both clinical evaluation and endoscopic imaging, with radiological correlation. EE treatment has been safely carried out under sedation using specialised endoscopic probes, leading to effective local tumour response, symptomatic relief, and improved quality of life. Follow-up schedules allow for timely assessment of treatment response and enable repeat treatments if needed. Conclusions: This novel protocol provides a practical framework for centres aiming to implement SEE services, promoting consistency, safety, and better patient outcomes. Future prospective studies will refine indications and improve integration of this approach into colorectal cancer management pathways. Full article

Background: Computed tomography (CT)-based image-guided surgery (IGS) is of great importance in functional endoscopic sinus surgery (FESS) and requires IGS-specific imaging protocols to ensure high intraoperative accuracy. This study aimed to compare photon-counting CT (PCCT), dual-energy dual-source CT (DECT), and spectral detector CT (SDCT) of the paranasal sinuses with respect to image quality, IGS accuracy and radiation dose. Methods: A formalin-fixed cadaver skull was examined using PCCT, DECT and SDCT at 100 kV tube voltage with descending tube currents (mAs). The setup of electromagnetic IGS was evaluated using a visual analog scale. Accuracy was analyzed endoscopically using defined anatomical landmarks. Diagnostic image quality as well as bone and soft tissue noise were assessed qualitatively using a 5-point Likert scale and quantitatively by determination of signal-to-noise ratio. Radiation dose was evaluated using the dose length product. Results: While PCCT datasets could be registered and navigated accurately down to 10 mAs (1.5 mm error at 10 mAs), both DECT and SDCT exhibited significantly increased inaccuracies below 40 mAs (4.35/5.15 mm for DECT/SDCT at 25 mAs). Using PCCT therefore enabled a 45% radiation dose reduction at the minimally required dose length product using PCCT. Quantitative and qualitative image quality were superior for PCCT compared to DECT and SDCT. Conclusions: PCCT provides excellent accuracy of anatomical landmarks in IGS with superior image quality of the paranasal sinuses in low-mA scans and substantially reduced radiation exposure. Full article

Background: Lumbar foraminal stenosis (LFS) is a prevalent degenerative condition associated with significant radicular pain and impaired quality of life. Advances in minimally invasive and fusion-based surgical techniques have introduced new strategies for decompressing the neural elements. However, comparative data correlating volumetric foraminal expansion with functional outcomes remain limited. Methods: This retrospective cohort study analyzed 256 patients treated surgically for symptomatic LFS between December 2017 and December 2023. Patients were categorized into four surgical subgroups: endoscopic decompression, anterior lumbar interbody fusion (ALIF), microsurgical decompression, and transforaminal lumbar interbody fusion (TLIF). Preoperative and postoperative assessments included magnetic resonance imaging (MRI) to calculate foraminal volume and standardized clinical scales: the Oswestry Disability Index (ODI), Visual Analogue Scale (VAS) for back and leg pain, and SF-36 health-related quality-of-life scores. Statistical significance was determined using p-values, and inter-observer agreement was evaluated via κ-statistics. Results: Postoperative imaging demonstrated a significant increase in foraminal canal volume across all surgical groups: endoscopy (29.9%), ALIF (71.8%), microsurgery (48.06%), and TLIF (67.0%). ODI scores improved from a preoperative mean of 55.25 to 18.27 at 24 months post-surgery (p < 0.001). VAS scores for back pain decreased from 6.37 to 2.1 (p < 0.001), while leg pain scores declined from 6.85 to 2.05 (p < 0.001). Functional improvement reached or exceeded the minimal clinically important difference (MCID) threshold in over 66% of patients. Conclusions: Modern surgical strategies for LFS, particularly fusion-based techniques, yield significant volumetric decompression and durable clinical improvement. Volumetric gain in the foraminal canal is closely associated with pain reduction and enhanced functional outcomes. These findings support a tailored surgical approach based on anatomical pathology and segmental stability. Full article

Diagnosing gastrointestinal disorders (GIDs) remains a significant challenge, particularly when relying on wireless capsule endoscopy (WCE), which lacks advanced imaging enhancements like Narrow Band Imaging (NBI). To address this, we propose a novel framework, the Spectrum-Aided Vision Enhancer (SAVE), especially designed to transform standard white light (WLI) endoscopic images into spectrally enriched representations that emulate both hyperspectral imaging (HSI) and NBI formats. By leveraging color calibration through the Macbeth Color Checker, gamma correction, CIE 1931 XYZ transformation, and principal component analysis (PCA), SAVE reconstructs detailed spectral information from conventional RGB inputs. Performance was evaluated using the Kvasir-v2 dataset, which includes 6490 annotated images spanning eight GI-related categories. Deep learning models like Inception-Net V3, MobileNetV2, MobileNetV3, and AlexNet were trained on both original WLI- and SAVE-enhanced images. Among these, MobileNetV2 achieved an F1-score of 96% for polyp classification using SAVE, and AlexNet saw a notable increase in average accuracy to 84% when applied to enhanced images. Image quality assessment showed high structural similarity (SSIM scores of 93.99% for Olympus endoscopy and 90.68% for WCE), confirming the fidelity of the spectral transformations. Overall, the SAVE framework offers a practical, software-based enhancement strategy that significantly improves diagnostic accuracy in GI imaging, with strong implications for low-cost, non-invasive diagnostics using capsule endoscopy systems. Full article

This study investigates the real-time monitoring of 3D printing using an endoscopic camera system integrated directly into the print head. The embedded endoscope enables continuous observation of the area surrounding the extruder, facilitating real-time inspection of the currently printed layers. A convolutional neural network (CNN) is employed to analyse captured images in the direction of print progression, enabling the detection of common defects such as stringing, layer shifting, and inadequate first-layer adhesion. The primary innovation of this work lies in its capacity for online quality assessment and immediate classification of print integrity within predefined thresholds. This system allows for the prompt termination of printing in the case of critical faults or dynamic adjustment of printing parameters in response to minor anomalies. The proposed solution offers a novel pathway for optimising additive manufacturing through real-time feedback on layer formation. Full article

Background: Pancreatic cystic lesions (PCLs), including intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), pose a diagnostic challenge due to their variable malignant potential. Current guidelines, such as Fukuoka and American Gastroenterological Association (AGA), have moderate predictive accuracy and may lead to overtreatment or missed malignancies. Artificial intelligence (AI), incorporating machine learning (ML) and deep learning (DL), offers the potential to improve risk stratification, diagnosis, and management of PCLs by integrating clinical, radiological, and molecular data. This is the first systematic review to evaluate the application, performance, and clinical utility of AI models in the diagnosis, classification, prognosis, and management of pancreatic cysts. Methods: A systematic review was conducted in accordance with PRISMA guidelines and registered on PROSPERO (CRD420251008593). Databases searched included PubMed, EMBASE, Scopus, and Cochrane Library up to March 2025. The inclusion criteria encompassed original studies employing AI, ML, or DL in human subjects with pancreatic cysts, evaluating diagnostic, classification, or prognostic outcomes. Data were extracted on the study design, imaging modality, model type, sample size, performance metrics (accuracy, sensitivity, specificity, and area under the curve (AUC)), and validation methods. Study quality and bias were assessed using the PROBAST and adherence to TRIPOD reporting guidelines. Results: From 847 records, 31 studies met the inclusion criteria. Most were retrospective observational (n = 27, 87%) and focused on preoperative diagnostic applications (n = 30, 97%), with only one addressing prognosis. Imaging modalities included Computed Tomography (CT) (48%), endoscopic ultrasound (EUS) (26%), and Magnetic Resonance Imaging (MRI) (9.7%). Neural networks, particularly convolutional neural networks (CNNs), were the most common AI models (n = 16), followed by logistic regression (n = 4) and support vector machines (n = 3). The median reported AUC across studies was 0.912, with 55% of models achieving AUC ≥ 0.80. The models outperformed clinicians or existing guidelines in 11 studies. IPMN stratification and subtype classification were common focuses, with CNN-based EUS models achieving accuracies of up to 99.6%. Only 10 studies (32%) performed external validation. The risk of bias was high in 93.5% of studies, and TRIPOD adherence averaged 48%. Conclusions: AI demonstrates strong potential in improving the diagnosis and risk stratification of pancreatic cysts, with several models outperforming current clinical guidelines and human readers. However, widespread clinical adoption is hindered by high risk of bias, lack of external validation, and limited interpretability of complex models. Future work should prioritise multicentre prospective studies, standardised model reporting, and development of interpretable, externally validated tools to support clinical integration. Full article

Gastric cancer remains the fourth leading cause of cancer-related mortality worldwide. Advanced disease is associated with a poor prognosis, emphasizing the critical importance of early diagnosis through endoscopy. In addition to prognosis, disease extent also plays a pivotal role in guiding management strategies. Therefore, accurate locoregional staging (T and N staging) is vital for optimal prognostic and therapeutic planning. Endoscopic ultrasound (EUS) has long been an essential tool in this regard, with computed tomography (CT) and, more recently, positron emission tomography–computed tomography (PET–CT) serving as alternative imaging modalities. EUS is particularly valuable in the assessment of early gastric cancer, defined as tumor invasion confined to the mucosa or submucosa. These tumors are increasingly managed by endoscopic resection techniques offering improved post-treatment quality of life. EUS has also recently been utilized in the restaging process after neoadjuvant chemotherapy, aiding in the evaluation of tumor resectability and prognosis. Its performance may be further enhanced through the application of emerging techniques such as contrast-enhanced endosonography, EUS elastography, and artificial intelligence systems. In advanced, unresectable disease, complications such as gastric outlet obstruction (GOO) severely impact patient quality of life. In this setting, EUS-guided gastroenterostomy (EUS-GE) offers a less invasive alternative to surgical gastrojejunostomy. This review summarizes and critically analyzes the role of EUS in the context of gastric cancer, highlighting its applications across different stages of the disease and evaluating its performance relative to other diagnostic modalities. Full article

Rectal cancer management necessitates a rigorous multidisciplinary strategy, emphasizing precise staging and detailed risk stratification to inform optimal therapeutic decision-making. Obtaining an accurate histological diagnosis before initiating treatment is essential. Comprehensive staging integrates clinical evaluation, thorough medical history analysis, assessment of carcinoembryonic antigen (CEA) levels, and computed tomography (CT) imaging of the abdomen and thorax. High-resolution pelvic magnetic resonance imaging (MRI), utilizing dedicated rectal protocols, is critical for identifying recurrence risks and delineating precise anatomical relationships. Endoscopic ultrasound further refines staging accuracy by determining the tumor infiltration depth in early-stage cancers, while preoperative colonoscopy effectively identifies synchronous colorectal lesions. In early-stage rectal cancers (T1–T2, N0, and M0), radical surgical resection remains the standard of care, although transanal local excision can be selectively indicated for certain T1N0 tumors. In contrast, locally advanced rectal cancers (T3, T4, and N+) characterized by microsatellite stability or proficient mismatch repair are optimally managed with total neoadjuvant therapy (TNT), which combines chemoradiotherapy with oxaliplatin-based systemic chemotherapy. Additionally, tumors exhibiting high microsatellite instability or mismatch repair deficiency respond favorably to immune checkpoint inhibitors (ICIs). The evaluation of tumor response following neoadjuvant therapy, utilizing MRI and endoscopic assessments, facilitates individualized treatment planning, including non-operative approaches for patients with confirmed complete clinical responses who comply with rigorous follow-up. Recent advancements in molecular characterization, targeted therapies, and immunotherapy highlight a significant evolution towards personalized medicine. The effective integration of these innovations requires enhanced interdisciplinary collaboration to improve patient prognosis and quality of life. Full article

Background: Idiopathic normal pressure hydrocephalus (iNPH) is a progressive neurological disorder characterized by cognitive decline, gait disturbances, and urinary incontinence. Surgical interventions such as ventriculoperitoneal shunt (VPS) and endoscopic third ventriculostomy (ETV) are the primary treatment options. While VPS is the standard of care, ETV offers a minimally invasive alternative with potentially fewer complications. However, comparative evidence regarding their impact on cognitive, motor, and structural outcomes remains limited. This study, titled ENVENTOR-iNPH (endoscopic ventriculostomy versus shunt on neuropsychological and motor performance in patients with iNPH), aims to address this gap through a rigorously designed comparative protocol. Methods: This protocol is designed as a multicenter, randomized, controlled trial (ENVENTOR-iNPH) to compare the effects of ETV and VPS in patients diagnosed with iNPH. The study will enroll 100 patients aged 60 years or older, randomly assigned to undergo ETV (n = 50) or VPS (n = 50). Preoperative and postoperative evaluations will include comprehensive cognitive and motor assessments, standardized quality-of-life instruments, and advanced neuroimaging techniques such as MRI with flowmetry and diffusion tensor imaging (DTI). Functional outcomes will also be evaluated using navigated transcranial magnetic stimulation (nTMS) and wearable motion analysis systems. The objective of this study is to compare the efficacy and safety of ETV versus VPS in restoring cognitive and motor performance in patients with iNPH. Results: Primary outcomes include cognitive and motor function improvements. Secondary endpoints are surgical complications, hospital stay duration, and changes in quality of life. Neuroimaging will assess changes in white matter integrity and cerebrospinal fluid dynamics, while nTMS will provide insights into neuroplasticity and motor pathway recovery. ETV is hypothesized to demonstrate clinical outcomes comparable or superior to VPS, particularly in terms of complication reduction and hospital recovery metrics. Conclusions: The ENVENTOR-iNPH protocol establishes the framework for a comprehensive, multicenter study comparing ETV and VPS in iNPH patients. The findings from this initial study will inform the design of larger-scale multicenter trials, guide clinical decision making, and potentially position ETV as a preferred treatment option for eligible patients. Full article

This review provides an in-depth analysis and comprehensive overview of recent advancements in MRI techniques for evaluating esophageal cancer (EC). It discusses the specific MRI acquisition protocols and parameters that enhance image quality and diagnostic accuracy. The review highlights MRI’s role and performance in the initial TNM staging and its potential to refine treatment strategies by improving tumor delineation and characterization. Additionally, the paper explores MRI utility in restaging after NAT, focusing on its accuracy in assessing treatment response and detecting residual or recurrent disease. Comparisons with other imaging modalities currently used—such as endoscopic ultrasound (EUS), contrast-enhanced computed tomography (CE-CT), and ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/CT (PET/CT)—are included to highlight the strengths and limitations of each method. Illustrated with numerous Figures, this article proposes a novel MRI-based strategy for EC staging and restaging. It aims to integrate MRI into clinical practice by leveraging its superior soft-tissue contrast and functional imaging capabilities to enhance diagnostic precision and improve patient outcomes. Through this comprehensive evaluation, the review underscores the potential of MRI to become a cornerstone in the precision diagnosis and management of EC. Full article

Portal hypertension (PH) is a complication of advanced liver diseases, including cirrhosis and hepatocellular carcinoma, often leading to unfavorable outcomes. Endo-hepatology, particularly endoscopic ultrasound (EUS) has revolutionized the assessment of PH. Notably, EUS-guided portal pressure gradient (EUS-PPG) enables measurement of portal and hepatic venous pressures, offering diagnostic precision for both cirrhotic and non-cirrhotic forms of PH, including porto-sinusoidal vascular disorder (PSVD). EUS-based assessment of PH in advanced liver disease can refine diagnostic workup and prognostication, supporting therapeutic decisions. Additionally, EUS-guided liver biopsy (EUS-LB) achieves high-quality histological samples with fewer complications compared to percutaneous techniques, enabling thorough evaluation of chronic liver diseases and vascular abnormalities. EUS-shear wave elastography (EUS-SWE) further refines stiffness measurements where standard imaging fails. Moreover, EUS plays a major role in controlling variceal hemorrhage, a severe PH complication. EUS-guided coil and cyanoacrylate injection for gastric varices demonstrate a great efficacy, often surpassing conventional endoscopy. Similarly, EUS-based identification and treatment of perforator vessels feeding esophageal varices reduce rebleeding risks, particularly in challenging patients. The combination of these state-of-the-art interventions supports a “one-stop strategy”, integrating variceal screening, biopsy, and portal pressure measurement within a single procedure. Despite these advancements, refinements in sedation protocols, patient selection, and cost-effectiveness data are necessary. While noninvasive tools remain central in guidelines, EUS-based methods continue to expand their role, especially in complex cases. This review summarizes the applications and impact of EUS in evaluating PH, emphasizing its importance in contemporary hepatology and its potential as a pivotal diagnostic modality in cirrhosis complicated by PH. Full article

Rectal cancer is a significant global health concern, particularly amongst the elderly population, with rectal cancer accounting for approximately one-third of cancer cases in this population. Older adults often present with advanced disease stages and unique clinical manifestations, such as tumors closer to the anal verge and with greater size. Diagnosis typically involves a series of screening and imaging strategies, culminating in accurate staging through pelvic MRI, endoscopic ultrasound, and CT scan. Management of rectal cancer in older adults emphasizes individualized treatment plans that consider both the cancer stage and the patient’s overall health status, including frailty and comorbidities. A multidisciplinary approach, including a mandatory geriatric assessment, is essential for optimizing outcomes, in order to improve survival and quality of life for elderly patients with rectal cancer. Full article

Background/objectives:To date, no studies have evaluated Chat Generative Pre-Trained Transformer (ChatGPT) as a large language model chatbot in optical applications for digestive endoscopy images. This study aimed to weigh the performance of ChatGPT-4 in assessing bowel preparation (BP) quality for colonoscopy. Methods: ChatGPT-4 analysed 663 anonymised endoscopic images, scoring each according to the Boston BP scale (BBPS). Expert physicians scored the same images subsequently. Results: ChatGPT-4 deemed 369 frames (62.9%) to be adequately prepared (i.e., BBPS > 1) compared to 524 frames (89.3%) assessed by human assessors. The agreement was slight (κ: 0.099, p = 0.0001). The raw human BBPS score was higher at 3 (2–3) than that of ChatGPT-4 at 2 (1–3), demonstrating moderate concordance (W: 0.554, p = 0.036). Conclusions: ChatGPT-4 demonstrates some potential in assessing BP on colonoscopy images, but further refinement is still needed. Full article

Chronic inflammatory bowel diseases, such as Crohn’s disease and ulcerative colitis, present diagnostic challenges due to their complex and heterogeneous nature. While histology remains fundamental for accurate diagnosis, a multidisciplinary approach incorporating clinical, endoscopic, and imaging modalities is increasingly recognized as essential for comprehensive evaluation. This article delves into the importance of integrating various diagnostic techniques in the assessment of IBD. Colonoscopy and histology, with its ability to directly visualize the intestinal mucosa, play a central role in the diagnostic process. However, histological analysis alone may not suffice, necessitating the inclusion of advanced imaging techniques, such as magnetic resonance enterography (MRE), computed tomography enterography (CTE), and intestinal ultrasound (IUS). These techniques provide valuable insights into the disease’s extent, severity, and complications, and should be used in conjunction with biochemical parameters. These modalities complement traditional endoscopic and histological findings, offering a more holistic understanding of the disease process. A multidisciplinary approach that incorporates clinical, endoscopic, histological, serological, and imaging assessments enables clinicians to achieve a more accurate and timely diagnosis of IBD. Moreover, this integrated approach facilitates personalized treatment strategies tailored to individual patient needs, ultimately improving clinical outcomes and quality of life for those affected by chronic inflammatory bowel diseases. Full article

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice. Full article