Search Results (54)

Background: Endoscopic assessment is central to the management of inflammatory bowel disease (IBD), particularly within treat-to-target strategies. However, conventional high-definition white-light endoscopy (HD-WLE) is limited by interobserver variability and its inability to reliably reflect microscopic inflammation or predict long-term outcomes. Over the last decade, multiple technological innovations have reshaped the role of endoscopy in both disease activity monitoring and dysplasia surveillance. Methods: This narrative review provides a comprehensive and clinically oriented overview of emerging endoscopic technologies in IBD, including image-enhanced endoscopy, ultra-high-magnification techniques, artificial intelligence (AI), and molecular imaging. We discuss their diagnostic performance, prognostic implications, and potential integration into clinical practice. Results: Image-enhanced endoscopy improves visualization of subtle mucosal and vascular alterations and demonstrates stronger correlation with histological activity compared with HD-WLE alone. Confocal laser endomicroscopy and endocytoscopy enable in vivo microscopic assessment of epithelial architecture and barrier integrity, redefining remission beyond macroscopic healing. AI systems have shown expert-level performance in grading inflammatory severity in ulcerative colitis and high sensitivity in capsule endoscopy for Crohn’s disease, supporting objective and reproducible assessment. In surveillance, targeted high-definition inspection has replaced random biopsies, while adjunctive optical and AI-based tools enhance lesion detection and characterization. Molecular imaging introduces a predictive dimension by enabling visualization of drug–target engagement and dysplasia-specific pathways. Conclusions: Endoscopy in IBD is evolving from a descriptive modality toward a multimodal precision tool integrating enhanced imaging, AI-driven standardization, and molecular profiling. Although further validation and cost-effectiveness studies are required, these innovations have the potential to improve therapeutic stratification, surveillance strategies, and long-term patient outcomes. Full article

Pancreatic neuroendocrine tumors (pNETs) are rare, clinically heterogeneous neoplasms with rising incidence linked to improved diagnostics. This review examines pNET management, addressing epidemiology, classification, diagnosis, treatment, and emerging therapies. Epidemiologically, pNETs show higher prevalence in Western populations, with emerging associations to metabolic disorders. The 2022 WHO classification highlights distinct prognoses for well-differentiated NETs versus poorly differentiated NECs, guided by Ki-67 and mitotic indices. Non-functional tumors often present late, while functional variants manifest hormonal syndromes, necessitating tailored approaches. Advanced imaging (contrast-enhanced CT/MRI, ⁶⁸Ga-DOTATATE PET) and endoscopic ultrasound-guided biopsy enable precise localization and grading. Surgical resection remains curative for localized disease, with minimally invasive techniques reducing morbidity. Active surveillance is favored for small (<2 cm), low-grade, non-functional tumors, while larger or aggressive lesions require resection. Systemic therapies, including mTOR inhibitors (everolimus), anti-angiogenics (surufatinib), and peptide receptor radionuclide therapy (PRRT), extend survival in advanced cases, though immunotherapy efficacy remains limited. Future strategies emphasize molecular profiling, biomarker development, and multidisciplinary integration to optimize outcomes. This evolving paradigm prioritizes precision medicine, balancing oncologic control with quality of life and functional preservation. Full article

Background: Odontogenic sinusitis (ODS) represents a distinct form of maxillary sinus inflammation arising from dental pathology and is most commonly unilateral. Despite its polymicrobial nature and predominance of anaerobic organisms, molecular characterization of the bacterial profile and its relationship to clinical severity remains limited. This study aimed to evaluate associations between targeted quantitative PCR (qPCR) findings from paired maxillary sinus and periapical lesion samples and clinical, endoscopic, and radiological features of disease. Additionally, the influence of oroantral communication on microbial concordance between odontogenic and sinus sites was examined. Methods: Twenty-eight patients with confirmed ODS were included for analytical cross-sectional study and underwent combined otolaryngological and dental assessment. During endoscopic sinus surgery with extraction of the causative tooth, paired specimens were collected from sinus mucosa and periapical lesions under sterile conditions and preserved for molecular analysis. Targeted qPCR assays using 16S rRNA–based primers were performed to detect predefined odontogenic pathogens. Associations between bacterial detection patterns and clinical, endoscopic, and imaging variables were analyzed. Results: Detection of Streptococcus anginosus group organisms was significantly associated with complete maxillary sinus opacification. Fusobacterium nucleatum and Porphyromonas endodontalis demonstrated higher detection rates in patients with more advanced radiological disease, although statistical significance was not reached. Purulent nasal discharge correlated with detection of Fusobacterium nucleatum, Porphyromonas endodontalis, and streptococcal species. Cases with intraoperative oroantral communication exhibited greater concordance between sinus and dental microbial profiles. Conclusions: ODS is characterized by a polymicrobial environment dominated by anaerobic bacteria, with specific organisms associated with markers of disease severity such as purulent secretion and extensive sinus opacification. Targeted molecular profiling may improve recognition of odontogenic origin and support individualized therapeutic strategies, although larger studies integrating clinical outcomes are required to clarify prognostic implications. Full article

Objectives: Pancreatic cystic lesions (PCLs) are increasingly detected due to the widespread use of imaging techniques. The identification of pancreatic mucinous cysts is especially important since these carry a risk of malignant transformation and require follow-up or surgical resection. The aim of this study was to determine the diagnostic yield of the molecular analysis of K-RAS (Kirsten RAt Sarcoma virus) and GNAS (Guanine Nucleotide-binding protein, Alpha Stimulating protein activity) gene mutations in pancreatic cyst fluid (PCF) obtained by endoscopic ultrasound (EUS)-guided fine needle aspiration (FNA). Methods: In this prospective trial, we assessed the sensitivity, specificity, and positive and negative predictive values of K-RAS and GNAS mutation analysis in differentiating mucinous versus non-mucinous cysts and the subsequent impact on decision-making in daily clinical practice. The reference standard used comprised the combination of morphology on cross-sectional imaging and EUS, string sign, cyst fluid cytology, intracystic carcinoembryonic antigen (CEA), and glucose levels, with subsequent correlation of surgical pathology in resected cases. Fluid samples of 47 cysts obtained by EUS-FNA over a 39-month period were analyzed. Mutation analysis of KRAS (exon 2) was performed in all cases, and additionally, GNAS (exon 8) in 28 cases using Sanger sequencing. Results: 33 out of 47 PCLs were classified as mucinous cysts and 14 as non-mucinous cysts defined using conventional standards, including morphological characteristics, string-sign, cytology, cyst fluid testing, and histology in resected cases. Of these 33 mucinous cysts, KRAS mutation was detected in 14 samples. A further 23 mucinous lesions were additionally tested for GNAS mutation, which was detected in 10 of the 23 cysts. A 42.4% sensitivity for KRAS and 43.5% for GNAS mutation analysis was calculated, with a specificity of 92.9% and 100%, respectively, for detecting mucinous lesions. The clinical management was altered through the genetic testing results in one single case. Conclusions: In this cohort, K-RAS and GNAS mutational analysis in cyst fluid did not improve the detection of mucinous pancreatic cysts significantly after conventional testing. However, the method may be useful due to its high specificity in uncertain cases. Full article

We report the case of a 42-year-old, non-smoking male admitted with right upper-lobe pneumonia. Chest computed tomography (CT) demonstrated findings consistent with an infectious process. For further evaluation, serial bronchoscopies with biopsy sampling were performed. Histopathological examination revealed moderate squamous dysplasia of the tracheal epithelium, and subsequent immunohistochemical testing detected human papillomavirus (HPV) genotype 45. This case underscores the value of integrating imaging, endoscopic assessment, and molecular diagnostic techniques in the evaluation of atypical pulmonary lesions and highlights the potential role of HPV infection in airway epithelial dysplastic changes. Full article

Only about 5% of colorectal cancers are hereditary, which is due to the low carrier rate of pathogenic gene mutations. The typical pattern of these cases is intergenerational aggregation within families and early onset. But public awareness of early diagnosis and intervention of HCRC is insufficient, resulting in most patients being diagnosed only after developing cancer, thereby missing the optimal window for treatment. This article reviews the latest developments in precision screening, treatment, evaluation and prevention strategies for HCRC, including innovative uses of artificial intelligence (AI) in molecular diagnostics, imaging technology advances, and potential application prospects. Regarding precision screening, tests of genomics, transcriptomics, microbiome, etc., combined with personalised risk stratification, can, respectively, effectively detect pathogenic mutations and “cancer-promoting” intestinal environments in the preclinical stage. AI combined with endoscopic and imaging tools has improved the accuracy of polyp detection and tumor profiling. Liquid biopsy and molecular marker detection provide new non-invasive monitoring solutions. In precision treatment, beyond traditional approaches like surgery and chemotherapy, immunotherapy with checkpoint inhibitors may be considered for HCRC patients with mismatch repair deficiency (dMMR). For patients harboring somatic mutations such as KRAS or BRAF V600E, targeted therapy can be guided by these specific mutations. Regarding precision assessment, AI incorporates microsatellite instability (MSI) detection and imaging diagnostic techniques, crucial for integrating genetic, environmental, and lifestyle data in follow-up. This helps assess the risk of recurrence and adjust the long-term medication regimens, as well as provide effective nutritional support and psychological counselling. In summary, the rapid development of precision medicine is driving the clinical management of HCRC into the era of tailored care, aiming to optimise patient outcomes. Full article

Early chronic pancreatitis (ECP) represents a potentially reversible stage in the natural history of chronic pancreatic disease. Timely diagnosis of ECP offers a possibility for intervention, yet its diagnosis remains challenging due to nonspecific symptoms, lack of standardized criteria, and the limited diagnostic sensitivity of conventional tools. This review aims to synthesize recent advancements in the understanding, detection, and management of ECP, with a focus on innovation in imaging techniques and biomarker profiling. The goal is to facilitate earlier diagnosis and more effective patient stratification. We reviewed the literature from the past five years, including original studies, meta-analyses, and expert consensus statements, to address the current evidence across genetic, inflammatory, imaging, and biochemical domains relevant to ECP. Endoscopic ultrasound and advanced magnetic resonance techniques offer high sensitivity in detecting early parenchymal changes, although inter-observer variability and lack of standardization persist. Biomarker discovery has focused on inflammatory (IL-6, sCD163), fibrotic (TGF-β1, TIMP-1), and oxidative markers, as well as novel candidates like microRNAs. Genetic predisposition (PRSS1, SPINK1, CTRC, CPA1, CLDN2) significantly influences disease onset and progression and could enable selection of high-risk individuals. Therefore, diagnosing ECP should involve a multidisciplinary precision-based approach integrating clinical, radiologic, molecular, serologic, and genetic data for individualized risk stratification. Full article

The accurate classification of pancreatic cystic lesions remains clinically challenging due to overlapping imaging features and variable malignant potential. Mucinous cystic neoplasms, in particular, require early identification given their premalignant nature. RNA profiling presents a promising alternative to current diagnostic limitations—a molecular lens sharpened by AI-driven pattern recognition. This study aimed to evaluate the diagnostic potential of RNA signatures for differentiating pancreatic cyst subtypes and to clarify their roles in their pathophysiology. The study included 31 patients with pancreatic lesions who underwent endoscopic ultrasound-guided fine-needle aspiration. RNA was extracted from cyst fluid, tissue, and peripheral blood. Expression of 17 target genes was analyzed using qPCR. Gene expression patterns were compared across mucinous cystic neoplasms, serous cystic neoplasms, pseudocysts, adenocarcinoma, and chronic pancreatitis cohorts. Diagnostic accuracy was evaluated via ROC analysis. Mucinous cysts exhibited significant overexpression of MUC1, ITGA2, ELOVL6, and MUC5AC genes compared to serous cysts and pseudocysts. PKM gene expression correlated with increasing malignant potential. In blood plasma, only MUC1, MUC4, and PYGL were elevated in adenocarcinoma compared to mucinous neoplasms. We identified a distinct RNA signature that can distinguish mucinous cystic neoplasms from benign cystic lesions (serous cysts and pseudocysts), which could be useful for guiding patient management and improving clinical outcomes. Validation in broader cohorts is essential for clinical implementation. Full article

Background/Objectives: Mass-forming chronic pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC) can present with overlapping radiological, clinical, and serological features in patients with underlying chronic pancreatitis (CP), making differential diagnosis particularly challenging. Current diagnostic tools, including CA19-9 and endoscopic ultrasound (EUS) imaging, often lack the specificity needed to reliably distinguish between these conditions. The objective of this study was to investigate whether the proteomic profiling of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) samples could provide molecular-level discrimination between MFP and PDAC in patients with CP. Methods: Thirty CP patients with solid pancreatic lesions were prospectively enrolled: 15 with histologically confirmed PDAC and 15 with MFP. Traditional diagnostic parameters, including CA19-9 levels and EUS characteristics, were recorded but found insufficient for differentiation. EUS-FNA samples were analyzed using label-free mass spectrometry. A total of 928 proteins were identified in PDAC samples and 555 in MFP samples. Differential abundance analysis and pathway enrichment were performed. Results: Overall, 88 proteins showed significant differential abundance between PDAC and MFP samples, of which 26 met stringent statistical thresholds. Among these, Carboxylesterase 2 (CES2), Carcinoembryonic Antigen-Related Cell Adhesion Molecule 1 (CEACAM1), Lumican (LUM), Transmembrane Protein 205 (TMEM205), and NAD(P)H Quinone Dehydrogenase 1 (NQO1) emerged as key discriminatory proteins. Pathway enrichment analysis revealed distinct biological processes between the groups, including mitochondrial fatty acid β-oxidation, Rho GTPase signaling, and platelet degranulation. Conclusions: Proteomic signatures derived from EUS-FNA samples offer a promising molecular approach to distinguish inflammatory pseudotumoral lesions from malignant pancreatic tumors in CP patients. This minimally invasive strategy could enhance diagnostic accuracy where current methods fall short. Further validation in larger, multicenter cohorts is warranted to confirm these findings and evaluate their clinical applicability. Full article

Background: Lung cancer remains the leading cause of cancer-related mortality worldwide. Timely and accurate diagnosis and staging are crucial for treatment decisions. Objective: To assess the feasibility, safety, and diagnostic/staging yield of a bronchoscopy-based pathway supported by EBUS-TBNA in a regional Romanian center. Bronchoscopy combined with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) may reduce the need for surgical confirmation, yet its implementation in regional centers is inconsistent. Materials and Methods: This retrospective study included 67 patients with suspected lung cancer evaluated at a regional oncology center between December 2023 and February 2024. All patients underwent bronchoscopy, and EBUS-TBNA was performed in those with mediastinal lymphadenopathy on imaging, with endoscopic tissue biopsies (endobronchial/EBUS-TBNA). Demographic, clinical, histological, and molecular data were collected and analyzed using descriptive statistics and chi-square/Fisher’s exact tests. Results: Among the 67 patients, 42 (62.7%) underwent EBUS-TBNA. The majority were diagnosed in advanced stages (stage III–IV: 83.6%), with adenocarcinoma being the most frequent histological subtype. PD-L1 expression was positive in 52.2% of cases, and p63 in 67.2%. No significant procedural complications occurred, and adequate tissue sampling for histopathological and molecular analyses was achieved in all cases. Associations were found between PD-L1 and advanced TNM stage (p = 0.026), as well as between p63 status and TNM stage (p = 0.002). Conclusions: This study supports the feasibility and safety of a bronchoscopy-based diagnostic and staging algorithm supported by EBUS-TBNA, achieving reliable sampling and avoiding surgical confirmation in a regional oncology setting. Further prospective studies are warranted to validate these findings. 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

Pancreatic ductal adenocarcinoma (PDAC) remains among the most lethal malignancies, with a five-year survival rate below 12%, largely attributable to its asymptomatic onset, late-stage diagnosis, and limited curative treatment options. Although PDAC accounts for approximately 3% of all cancers, it is projected to become the second leading cause of cancer-related mortality in the United States by 2030. A major contributor to its dismal prognosis is the lack of validated early detection strategies for asymptomatic individuals. In this review, we present a comprehensive synthesis of current advances in the early detection of PDAC, with a focus on the identification of high-risk populations, novel biomarker platforms, advanced imaging modalities, and artificial intelligence (AI)-driven tools. We highlight high-risk groups—such as those with new-onset diabetes after age 50, pancreatic steatosis, chronic pancreatitis, cystic precursor lesions, and hereditary cancer syndromes—as priority populations for targeted surveillance. Novel biomarker panels, including circulating tumor DNA (ctDNA), miRNAs, and exosomes, have demonstrated improved diagnostic accuracy in early-stage disease. Recent developments in imaging, such as multiparametric MRI, contrast-enhanced endoscopic ultrasound, and molecular imaging, offer improved sensitivity in detecting small or precursor lesions. AI-enhanced radiomics and machine learning models applied to prediagnostic CT scans and electronic health records are emerging as valuable tools for risk prediction prior to clinical presentation. We further refine the Define–Enrich–Find (DEF) framework to propose a clinically actionable strategy that integrates these innovations. Collectively, these advances pave the way for personalized, multimodal surveillance strategies with the potential to improve outcomes in this historically challenging malignancy. Full article

In the management of cholangiocarcinoma, effective biliary drainage and accurate diagnosis are vital to allow further treatment. Confirmation of tissue diagnosis and molecular characterization is also required to guide future treatment options including surgery and chemotherapy as well as the possible use of personalized treatments that target specific mutations present within individual tumours. Initial CT or MRI scans may be followed by endoscopic ultrasound (EUS) or endoscopic retrograde cholangiopancreatography (ERCP) to obtain tissue samples. However, these methods often fall short due to difficulty in accessing entire bile duct strictures. SpyGlass cholangioscopy can improve diagnosis, yet may fail to provide sufficient tissue for molecular characterization. Here we present a perspective on the development of snake-like agile robots with integrated optical imaging and Raman spectroscopy. These robots could improve the mapping of the biliary tree and the precision of biopsy collection and allow tissue analysis in situ, as well as facilitating stenting to restore the flow of bile. A multidisciplinary approach that brings together clinicians, pathologists, and engineers is required to develop these new robotic technologies and improve patient outcomes. Full article

(1) Background and Aims: Patients with inflammatory bowel disease (IBD) and primary sclerosing cholangitis (PSC) face a significantly increased risk of malignancies, including a 10-fold higher risk for colorectal cancer (CRC) and a lifetime risk for cholangiocarcinoma (CCA) exceeding 20%. The mechanisms underlying this elevated risk remain elusive. This review consolidates recent findings on cancer risk in PSC-IBD patients, focusing on molecular pathways, diagnostic innovations, and prevention strategies. (2) Methods: A comprehensive PubMed search was performed to identify studies published through to March 2025 on oncogenic processes, molecular mechanisms, and advancements in diagnostic and preventive strategies for CRC and CCA in PSC-IBD patients. (3) Results: Surveillance guidelines recommend an annual colonoscopy for CRC and imaging combined with CA 19-9 monitoring for CCA. Recent studies highlight the role of molecular alterations, including epigenetic modifications, in tumorigenesis. Advances in molecular diagnostics, imaging, and endoscopic technologies are improving the accuracy and timeliness of cancer detection. (4) Conclusions: PSC-IBD patients remain at high risk for CRC and CCA, emphasizing the need for vigilant surveillance and advanced prevention strategies. Advances in early detection and precision diagnostics offer new opportunities to reduce the cancer burden in this high-risk population. 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