Search Results (55)

Background and Clinical Significance: Inherited thrombocytopenia (IT) is a heterogeneous group of disorders caused by mutations in over 45 genes. Among these, ANKRD26-related thrombocytopenia (ANKRD26-RT) accounts for a notable subset and is associated with variable bleeding tendencies and an increased risk of myeloid malignancies. However, the extent of this oncogenic risk appears to vary between specific gene variants. Understanding the genotype–phenotype relationship is essential for patient counseling and management. This report presents a multigenerational family carrying the rare c.−118C > G variant in the 5′ untranslated region of ANKRD26, contributing to the discussion on variant-specific cancer predisposition. Case Presentation: Two sisters aged 57 and 60 presented with lifelong bleeding diathesis and moderate thrombocytopenia. Their symptoms included easy bruising, menorrhagia, and excessive postoperative bleeding. Genetic testing confirmed heterozygosity for the ANKRD26 c.−118C > G variant. Bone marrow analysis revealed abnormal megakaryopoiesis without evidence of dysplasia or somatic mutations. One sister underwent major surgery without complications when managed with prophylactic hemostatic therapy. Their family history included multiple female relatives with similar symptoms, although formal testing was limited. Notably, none of the affected individuals developed hematologic malignancy, and only one developed esophageal cancer, with no current evidence linking this variant to solid tumors. Conclusions: This case underscores the importance of distinguishing between ANKRD26 variants when assessing malignancy risk. While ANKRD26-RT is associated with myeloid neoplasms, the c.−118C > G variant may confer a lower oncogenic potential. Variant-specific risk stratification and genetic counseling are crucial for optimizing surveillance and avoiding unnecessary interventions in low-risk individuals. Full article

Barrett’s esophagus (BE), a metaplastic transformation of an esophageal squamous epithelium into an intestinal-type columnar epithelium, is the primary precursor to esophageal adenocarcinoma (EAC). Traditional management strategies have relied heavily on selective screening, tailored surveillance intervals, and early dysplasia detection and treatment algorithms. However, the heterogeneity in progression risk among BE patients necessitates a more nuanced, personalized approach involving precision care, tailoring decisions to individual patient characteristics, promises to enhance outcomes in BE through more targeted screening, personalized surveillance intervals, and risk-based therapeutic strategies. This review explores the current landscape and emerging trends in precision medicine for Barrett’s esophagus, highlighting genomic markers, digital pathology, and AI-driven models as tools to transform how we approach this complex disease and prevent progression to EAC. Full article

Human papillomavirus (HPV) is a recognized oncogenic agent in several epithelial malignancies, though its role in esophageal squamous lesions remains unclear. Esophageal squamous papilloma and papillomatosis are rare, often benign lesions, but increasing evidence suggests possible associations with high-risk HPV genotypes and a non-negligible risk of dysplasia and malignant transformation. This narrative review summarizes current evidence on epidemiology, clinical features, histopathology, and diagnostic approaches, emphasizing advanced endoscopic imaging techniques that improve lesion detection and characterization. Management relies primarily on complete endoscopic resection with histological and virological evaluation. While small, non-dysplastic solitary lesions may not require routine surveillance, multifocal or high-risk HPV-positive cases warrant closer follow-up. Standardized HPV testing and long-term prospective studies are needed to better define the oncogenic potential and inform surveillance and treatment strategies. Full article

Objective: Esophageal cancer (EC) is difficult to visually identify, rendering early detection crucial to avert the advancement and decline of the patient’s health. Methodology: This work aimed to acquire spectral information from EC images via Spectrum-Aided Visual Enhancer (SAVE) technology, which improves imaging beyond the limitations of conventional White-Light Imaging (WLI). The hyperspectral data acquired using SAVE were examined utilizing sophisticated deep learning methodologies, incorporating models such as YOLOv8, YOLOv7, YOLOv6, YOLOv5, Scaled YOLOv4, and YOLOv3. The models were assessed to create a reliable detection framework for accurately identifying the stage and location of malignant lesions. Results: The comparative examination of these models demonstrated that the SAVE method regularly surpassed WLI for specificity, sensitivity, and overall diagnostic efficacy. Significantly, SAVE improved precision and F1 scores for the majority of the models, which are essential measures for enhancing patient care and customizing effective medicines. Among the evaluated models, YOLOv8 showed exceptional performance. YOLOv8 demonstrated increased sensitivity to squamous cell carcinomas (SCCs), but YOLOv5 provided reliable outcomes across many situations, underscoring its adaptability. Conclusions: These findings highlight the clinical importance of combining SAVE technology with deep learning models for esophageal cancer screening. The enhanced diagnostic accuracy provided by SAVE, especially when integrated with CAD models, offers potential for improving early detection, precise diagnosis, and tailored treatment approaches in clinically pertinent scenarios. Full article

Objective: Esophageal carcinoma (EC) is the eighth most prevalent cancer and the sixth leading cause of cancer-related mortality worldwide. Early detection is vital for improving prognosis, particularly for dysplasia and squamous cell carcinoma (SCC). Methods: This study evaluates a hyperspectral imaging conversion method, the Spectrum-Aided Vision Enhancer (SAVE), for its efficacy in enhancing esophageal cancer detection compared to conventional white-light imaging (WLI). Five deep learning models (YOLOv9, YOLOv10, YOLO-NAS, RT-DETR, and Roboflow 3.0) were trained and evaluated on a dataset comprising labeled endoscopic images, including normal, dysplasia, and SCC classes. Results: Across all five evaluated deep learning models, the SAVE consistently outperformed conventional WLI in detecting esophageal cancer lesions. For SCC, the F1 score improved from 84.3% to 90.4% in regard to the YOLOv9 model and from 87.3% to 90.3% in regard to the Roboflow 3.0 model when using the SAVE. Dysplasia detection also improved, with the precision increasing from 72.4% (WLI) to 76.5% (SAVE) in regard to the YOLOv9 model. Roboflow 3.0 achieved the highest F1 score for dysplasia of 64.7%. YOLO-NAS exhibited balanced performance across all lesion types, with the dysplasia precision rising from 75.1% to 79.8%. Roboflow 3.0 also recorded the highest SCC sensitivity of 85.7%. In regard to SCC detection with YOLOv9, the WLI F1 score was 84.3% (95% CI: 71.7–96.9%) compared to 90.4% (95% CI: 80.2–100%) with the SAVE (p = 0.03). For dysplasia detection, the F1 score increased from 60.3% (95% CI: 51.5–69.1%) using WLI to 65.5% (95% CI: 57.0–73.8%) with SAVE (p = 0.04). These findings demonstrate that the SAVE enhances lesion detectability and diagnostic performance across different deep learning models. Conclusions: The amalgamation of the SAVE with deep learning algorithms markedly enhances the detection of esophageal cancer lesions, especially squamous cell carcinoma and dysplasia, in contrast to traditional white-light imaging. This underscores the SAVE’s potential as an essential clinical instrument for the early detection and diagnosis of cancer. Full article

Esophageal cancer, primarily comprising the squamous cell carcinoma (ESCC) and adenocarcinoma (EAC) subtypes, is the sixth leading cause of cancer deaths globally. In addition to many well-established endogenous and exogenous risk factors, there is emerging evidence for the etiologic role of infectious agents in esophageal cancer, although these associations are incompletely understood. Here, we review the currently available literature on the relationship between infectious agents and esophageal cancer. By far, human papilloma virus (HPV), particularly HPV 16 and 18, have the strongest etiologic association with ESCC. Less robust is the association of high-risk HPV (hr-HPV) with EAC. Although H. pylori has been implicated in the development of EAC via increased acid reflux, decreased lower esophageal sphincter tone, and the resultant Barrett’s metaplasia–dysplasia–adenocarcinoma pathway, some hypothesize based on epidemiological trends that H. pylori may in fact be a protective factor. In rare cases, EBV can cause esophageal lymphoepithelial carcinoma. Several other agents including HSV, polyomaviruses, and Candida are associated with esophageal cancer to varying degrees. In summary, while several studies, including those conflicting with each other, implicate several infectious agents, the evidence is weak, at best. Clearly, further work is needed to help solidify clear etiologies that will help facilitate prevention and treatment. Full article

Background: Barrett’s esophagus (BE) is a known precursor to esophageal adenocarcinoma (EAC). However, reports on incidence and progression-to-neoplasm rates have been very variable and conflicting. The aims of the study were to evaluate the characteristics of BE and its progression to neoplasm in a large homogeneous population. Methods: This was a retrospective population-based study with patients identified from 11 institutions through the databases in two centralized pathology laboratories. Demographics and relevant clinicopathological features were obtained from medical records among patients with a pathologically confirmed BE by the presence of intestinal metaplasia between 2003 and 2022. Results: A total of 1388 patients were identified with BE: 948 were men (69%); the median age at diagnosis was 62 years (IQR, 53–72). The ratio of long-segment BE to short-segment BE was significantly higher in patients ≥ 60 years (1.15, 284/248) than those ≤ 60 years (0.77, 205/265) (p = 0.0025). At BE diagnosis, 9.4% had neoplasms: LGD (n = 65), HGD (n = 16), and EAC (n = 49). Among 1258 non-dysplastic BE (NDBE) patients, 4.6% developed a neoplasm—LGD (n = 35), HGD (n = 8), and EAC (n = 15)—with a median observation-period of 5 years (IQR, 3–7). Overall, 160 cases with neoplasms were diagnosed in this BE cohort; 130 (74%) were present at initial BE diagnosis, and 58 (26%) progressed to neoplasms from NDBE. Conclusions: The ratio of long-segment BE was found to be significantly higher in patients ≥ 60 years. Around 9% of the patients were diagnosed as harboring a neoplasm concomitantly with BE, accounting for approximately 74% of all neoplasms. After a median follow-up of 5 years, about 5% of BE showed dysplastic or malignant progression. Full article

Background: Barrett’s esophagus (BE) is described by the transformation of the normal squamous epithelium into metaplastic columnar epithelium, driven by chronic gastroesophageal reflux disease (GERD). BE is a recognized premalignant condition and the main precursor to esophageal adenocarcinoma (EAC). Understanding the molecular mechanisms underlying BE carcinogenesis is crucial for improving prevention, surveillance, and treatment strategies. Methods: This narrative review examines the molecular abnormalities associated with the progression of BE to EAC. Results: This study highlights inflammatory, genetic, epigenetic, and chromosomal alterations, emphasizing key pathways and biomarkers. BE progression follows a multistep process involving dysplasia and genetic alterations such as TP53 and CDKN2A (p16) mutations, chromosomal instability, and dysregulation of pathways like PI3K/AKT/mTOR. Epigenetic alterations, including aberrant microRNA expression or DNA methylation, further contribute to this progression. These molecular changes are stage-specific, with some alterations occurring early in BE during the transition to high-grade dysplasia or EAC. Innovations in chemoprevention, such as combining proton pump inhibitors and aspirin, and the potential of antireflux surgery to halt disease progression are promising. Incorporating molecular biomarkers into surveillance strategies and advancing precision medicine may enable earlier detection and personalized treatments. Conclusions: BE is the primary preneoplastic condition for EAC. A deeper understanding of its molecular transformation can enhance surveillance protocols, optimize the management of gastroesophageal reflux inflammation, and refine prevention and therapeutic strategies, ultimately contributing to a reduction in the global burden of EAC. Full article

Esopredict^TM is a prognostic assay that risk-stratifies Barrett’s esophagus patients to predict future progression to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC). Established based on foundational studies at Johns Hopkins University, a risk algorithm was developed and clinically validated in two independent studies (n = 320). Esopredict^TM is currently offered as a clinical test under the Clinical Laboratory Improvement Amendments (CLIA) guidelines. Here we present the analytical validation by repeated testing of FFPE tissues (n = 26 patients), cell lines, and contrived DNA controls to determine assay performance regarding analytical sensitivity (as defined by the limit of detection (LOD)), analytical specificity (as defined by the limit of blank (LOB)), accuracy as determined from the average positive and negative agreement, repeatability, and reproducibility. The LOD for the assay at 1.5% DNA methylation was significantly higher than the LOB, as determined by an unmethylated DNA control (0% methylated DNA). Inter- and intra-assay average positive agreement (APA) were 88% and 94%, respectively, while average negative agreement (ANA) values were 90% and 94%, respectively. Average inter- and intra-assay precision were <9% and <5% coefficient of variation (CV), respectively. These results confirm that Esopredict^TM is a highly reproducible, sensitive, and specific risk categorization assay for the prediction of progression to HGD or EAC within 5 years. Full article

Background: Although heartburn and reflux are frequently reported in ulcerative colitis [UC], the correlation between UC and gastroesophageal reflux disease [GERD], and its complications, esophageal stricture and Barrett’s esophagus [BE], is not well understood. This study aims to examine the prevalence and associated risk of GERD and its complications within the UC population. Methods: We analyzed the National Inpatient Sample (NIS) dataset, consisting of 7,159,694 patients, comparing GERD patients with and without UC to those without GERD. We assessed the degree of colonic involvement in UC and the occurrence of esophageal complications. Bivariate analyses were conducted using the chi-squared test or Fisher exact test (two-tailed). Results: A higher prevalence of GERD (23.0% vs. 16.5%) and GERD phenotypes, such as non-erosive reflux disease (NERD) (22.3% vs. 16%) and erosive esophagitis (EE) (1.2% vs. 0.6%), was found in UC patients (p < 0.01), including pancolitis, proctitis, proctosigmoiditis, left-sided colitis, and indetermined UC (with undefined colonic involvement). UC patients were more likely to develop GERD (1.421), NERD (1.407), and EE (1.681) (p < 0.01). A higher prevalence of esophageal stricture (16.9 vs. 11.4 per 10,000 patients) and BE without dysplasia (94.5 vs. 39.3 per 10,000 patients) was found in UC (p < 0.05). The odds of developing BE without dysplasia were higher (1.892) in patients with UC (p < 0.01), including ulcerative pancolitis, proctitis, and indeterminate UC (OR of 1.657, 3.328, and 1.996, respectively) (p < 0.05). Conclusions: Our study demonstrates an increased risk of developing GERD and its complications in UC. This highlights the importance of vigilant monitoring and early intervention to minimize associated GERD-related risks in patients with UC. Full article

Background: Barrett’s esophagus (BE) is a pre-neoplastic condition associated with an increased risk of esophageal adenocarcinoma (EAC). The accurate diagnosis of BE and grading of dysplasia can help to optimize the management of patients with BE. However, BE may be missed and the accurate grading of dysplasia based on a routine histology has a considerable intra- and interobserver variability. Thus, well-defined biomarker testing remains indispensable. The aim of our study was to identify routinely applicable and relatively specific biomarkers for an accurate diagnosis of BE, as well as determining biomarkers to predict the risk of progression in BE–dysplasia. Methods: Retrospectively, we performed immunohistochemistry to test mucin 2(MUC2), trefoil factor 3 (TFF3), p53, p16, cyclin D1, Ki-67, beta-catenin, and minichromosome maintenance (MCM2) in biopsies. Prospectively, to identify chromosomal alterations, we conducted fluorescent in situ hybridization testing on fresh brush samples collected at the time of endoscopy surveillance. Results: We discovered that MUC2 and TFF3 are specific markers for the diagnosis of BE. Aberrant expression, including the loss and strong overexpression of p53, Ki-67, p16, beta-catenin, cyclin D1, and MCM2, was significantly associated with low-grade dysplasia (LGD), high-grade dysplasia (HGD), and EAC histology, with a relatively high risk of neoplastic changes. Furthermore, the aberrant expressions of p53 and p16 in BE-indefinite dysplasia (IND) progressor cohorts predicted the risk of progression. Conclusions: Assessing the biomarkers would be a suitable adjunct to accurate BE histology diagnoses and improve the accuracy of BE–dysplasia grading, thus reducing interobserver variability, particularly of LGD and risk prediction. Full article

Esophageal carcinoma is the sixth-leading cause of cancer death worldwide. A precursor to esophageal adenocarcinoma (EAC) is Barrett’s Esophagus (BE). Early-stage diagnosis and treatment of esophageal neoplasia (Barrett’s with high-grade dysplasia/intramucosal cancer) increase the five-year survival rate from 10% to 98%. BE is a global challenge; however, current endoscopes for early BE detection are costly and require extensive infrastructure for patient examination and sedation. We describe the design and evaluation of the first prototype of ScanCap, a high-resolution optical endoscopy system with a reusable, low-cost tethered capsule, designed to provide high-definition, blue-green illumination imaging for the early detection of BE in unsedated patients. The tethered capsule (12.8 mm diameter, 35.5 mm length) contains a color camera and rotating mirror and is designed to be swallowed; images are collected as the capsule is retracted manually via the tether. The tether provides electrical power and illumination at wavelengths of 415 nm and 565 nm and transmits data from the camera to a tablet. The ScanCap prototype capsule was used to image the oral mucosa in normal volunteers and ex vivo esophageal resections; images were compared to those obtained using an Olympus CV-180 endoscope. Images of superficial capillaries in intact oral mucosa were clearly visible in ScanCap images. Diagnostically relevant features of BE, including irregular Z-lines, distorted mucosa, and dilated vasculature, were clearly visible in ScanCap images of ex vivo esophageal specimens. Full article

The early detection of esophageal cancer presents a substantial difficulty, which contributes to its status as a primary cause of cancer-related fatalities. This study used You Only Look Once (YOLO) frameworks, specifically YOLOv5 and YOLOv8, to predict and detect early-stage EC by using a dataset sourced from the Division of Gastroenterology and Hepatology, Ditmanson Medical Foundation, Chia-Yi Christian Hospital. The dataset comprised 2741 white-light images (WLI) and 2741 hyperspectral narrowband images (HSI-NBI). They were divided into 60% training, 20% validation, and 20% test sets to facilitate robust detection. The images were produced using a conversion method called the spectrum-aided vision enhancer (SAVE). This algorithm can transform a WLI into an NBI without requiring a spectrometer or spectral head. The main goal was to identify dysplasia and squamous cell carcinoma (SCC). The model’s performance was evaluated using five essential metrics: precision, recall, F1-score, mAP, and the confusion matrix. The experimental results demonstrated that the HSI model exhibited improved learning capabilities for SCC characteristics compared with the original RGB images. Within the YOLO framework, YOLOv5 outperformed YOLOv8, indicating that YOLOv5’s design possessed superior feature-learning skills. The YOLOv5 model, when used in conjunction with HSI-NBI, demonstrated the best performance. It achieved a precision rate of 85.1% (CI95: 83.2–87.0%, p < 0.01) in diagnosing SCC and an F1-score of 52.5% (CI95: 50.1–54.9%, p < 0.01) in detecting dysplasia. The results of these figures were much better than those of YOLOv8. YOLOv8 achieved a precision rate of 81.7% (CI95: 79.6–83.8%, p < 0.01) and an F1-score of 49.4% (CI95: 47.0–51.8%, p < 0.05). The YOLOv5 model with HSI demonstrated greater performance than other models in multiple scenarios. This difference was statistically significant, suggesting that the YOLOv5 model with HSI significantly improved detection capabilities. Full article

Esophageal carcinoma (EC) is a prominent contributor to cancer-related mortality since it lacks discernible features in its first phases. Multiple studies have shown that narrow-band imaging (NBI) has superior accuracy, sensitivity, and specificity in detecting EC compared to white light imaging (WLI). Thus, this study innovatively employs a color space linked to décor to transform WLIs into NBIs, offering a novel approach to enhance the detection capabilities of EC in its early stages. In this study a total of 3415 WLI along with the corresponding 3415 simulated NBI images were used for analysis combined with the YOLOv5 algorithm to train the WLI images and the NBI images individually showcasing the adaptability of advanced object detection techniques in the context of medical image analysis. The evaluation of the model’s performance was based on the produced confusion matrix and five key metrics: precision, recall, specificity, accuracy, and F1-score of the trained model. The model underwent training to accurately identify three specific manifestations of EC, namely dysplasia, squamous cell carcinoma (SCC), and polyps demonstrates a nuanced and targeted analysis, addressing diverse aspects of EC pathology for a more comprehensive understanding. The NBI model effectively enhanced both its recall and accuracy rates in detecting dysplasia cancer, a pre-cancerous stage that might improve the overall five-year survival rate. Conversely, the SCC category decreased its accuracy and recall rate, although the NBI and WLI models performed similarly in recognizing the polyp. The NBI model demonstrated an accuracy of 0.60, 0.81, and 0.66 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it attained a recall rate of 0.40, 0.73, and 0.76 in the same categories. The WLI model demonstrated an accuracy of 0.56, 0.99, and 0.65 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it obtained a recall rate of 0.39, 0.86, and 0.78 in the same categories, respectively. The limited number of training photos is the reason for the suboptimal performance of the NBI model which can be improved by increasing the dataset. Full article

Characterization of the Barrett’s esophagus (BE) microenvironment in patients with a known progression status, to determine how it may influence BE progression to esophageal adenocarcinoma (EAC), has been understudied, hindering both the biological understanding of the progression and the development of novel diagnostics and therapies. This study’s aim was to determine if a highly multiplex interrogation of the microenvironment can be performed on endoscopic formalin-fixed, paraffin-embedded (FFPE) samples, utilizing the NanoString GeoMx digital spatial profiling (GeoMx DSP) platform and if it can begin to identify the types of immune cells and pathways that may mediate the progression of BE. We performed a spatial proteomic analysis of 49 proteins expressed in the microenvironment and epithelial cells of FFPE endoscopic biopsies from patients with non-dysplastic BE (NDBE) who later progressed to high-grade dysplasia or EAC (n = 7) or from patients who, after at least 5 years follow-up, did not (n = 8). We then performed an RNA analysis of 1812 cancer-related transcripts on three endoscopic mucosal resections containing regions of BE, dysplasia, and EAC. Profiling with GeoMx DSP showed reasonable quality metrics and detected expected differences between epithelium and stroma. Several proteins were found to have an increased expression within NDBE biopsies from progressors compared to non-progressors, suggesting further studies are warranted. Full article