Search Results (563)

Accurate diagnosis of gastrointestinal (GI) diseases typically requires invasive procedures or imaging studies that pose the risk of various post-procedural complications or involve radiation exposure. Bowel sounds (BSs), though typically described during a GI-focused physical exam, are highly inaccurate and variable, with low clinical value in diagnosis. Interpretation of the acoustic characteristics of BSs, i.e., using a phonoenterogram (PEG), may aid in diagnosing various GI conditions non-invasively. Use of artificial intelligence (AI) and improvements in computational analysis can enhance the use of PEGs in different GI diseases and lead to a non-invasive, cost-effective diagnostic modality that has not been explored before. The purpose of this work was to develop an automated AI model, You Only Listen Once (YOLO), to detect prominent bowel sounds that can enable real-time analysis for future GI disease detection and diagnosis. A total of 110 2-minute PEGs sampled at 44.1 kHz were recorded using the Eko DUO^® stethoscope from eight healthy volunteers at two locations, namely, left upper quadrant (LUQ) and right lower quadrant (RLQ) after IRB approval. The datasets were annotated by trained physicians, categorizing BSs as prominent or obscure using version 1.7 of Label Studio Software^®. Each BS recording was split up into 375 ms segments with 200 ms overlap for real-time BS detection. Each segment was binned based on whether it contained a prominent BS, resulting in a dataset of 36,149 non-prominent segments and 6435 prominent segments. Our dataset was divided into training, validation, and test sets (60/20/20% split). A 1D-CNN augmented transformer was trained to classify these segments via the input of Mel-frequency cepstral coefficients. The developed AI model achieved area under the receiver operating curve (ROC) of 0.92, accuracy of 86.6%, precision of 86.85%, and recall of 86.08%. This shows that the 1D-CNN augmented transformer with Mel-frequency cepstral coefficients achieved creditable performance metrics, signifying the YOLO model’s capability to classify prominent bowel sounds that can be further analyzed for various GI diseases. This proof-of-concept study in healthy volunteers demonstrates that automated BS detection can pave the way for developing more intuitive and efficient AI-PEG devices that can be trained and utilized to diagnose various GI conditions. To ensure the robustness and generalizability of these findings, further investigations encompassing a broader cohort, inclusive of both healthy and disease states are needed. Full article

Timely and accurate diagnosis of gastrointestinal diseases (GIDs) remains a critical bottleneck in clinical endoscopy, particularly due to the limited contrast and sensitivity of conventional white light imaging (WLI) in detecting early-stage mucosal abnormalities. To overcome this, this research presents Spectrum Aided Vision Enhancer (SAVE), an innovative, software-driven framework that transforms standard WLI into high-fidelity hyperspectral imaging (HSI) and simulated narrow-band imaging (NBI) without any hardware modification. SAVE leverages advanced spectral reconstruction techniques, including Macbeth Color Checker-based calibration, principal component analysis (PCA), and multivariate polynomial regression, achieving a root mean square error (RMSE) of 0.056 and structural similarity index (SSIM) exceeding 90%. Trained and validated on the Kvasir v2 dataset (n = 6490) using deep learning models like ResNet-50, ResNet-101, EfficientNet-B2, both EfficientNet-B5 and EfficientNetV2-B0 were used to assess diagnostic performance across six key GI conditions. Results demonstrated that SAVE enhanced imagery and consistently outperformed raw WLI across precision, recall, and F1-score metrics, with EfficientNet-B2 and EfficientNetV2-B0 achieving the highest classification accuracy. Notably, this performance gain was achieved without the need for specialized imaging hardware. These findings highlight SAVE as a transformative solution for augmenting GI diagnostics, with the potential to significantly improve early detection, streamline clinical workflows, and broaden access to advanced imaging especially in resource constrained settings. Full article

Sensorimotor integration along the gastrointestinal (GI) tract is crucial for normal gut function yet remains poorly understood in the context of neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD). The genetic tractability of zebrafish allows investigators to generate molecularly defined models that provide a means of studying the functional circuits of digestion in vivo. Optical transparency during development allows for the use of optogenetics and calcium imaging to elucidate the mechanisms underlying GI-related symptoms associated with ASD. The array of commonly reported symptoms implicates altered sensorimotor integration at various points along the GI tract, from the pharynx to the anus. We will examine the reflex arcs that facilitate swallowing, nutrient-sensing, absorption, peristalsis, and evacuation. The high level of conservation of these processes across vertebrates also enables us to explore potential therapeutic avenues to mitigate GI distress in ASD and other NDDs. Full article

Gastrointestinal signals present a major challenge in magnetic particle imaging (MPI) because of their strong background interference. This study aimed to evaluate and compare the gut MPI signal in mice fed six commercially available diets in Australia, including Gordon’s Specialty Stock Feeds (normal and low iron), Specialty Feeds (normal and low iron), a Western diet, and Gubra-Amylin NASH (GAN diet). We also assessed the impact of 24 h fasting on gut signal reduction. Each diet group included three mice, and the gut signal intensity was monitored over seven days. The results indicated that the standard diet produced signal intensities approximately eight times greater than those of the low-iron diet from specialty feeds and over eleven times greater than those of the GAN or Western diets. Notably, switching to GAN or Western diets led to a tenfold reduction in the gut signal within 24 h, a decrease comparable to that achieved by fasting. These findings suggest that dietary modification—particularly the use of low-iron diets—can effectively minimize gastrointestinal signals in MPI, reducing background interference by up to 90%. This simple dietary adjustment offers a practical and noninvasive method for improving image clarity and experimental reliability in preclinical MPI studies. Full article

Background: Gastric cancer (GC) is a malignant tumor of the gastrointestinal tract, characterized by high mortality rates and responsible for about one million new cases each year globally. Surgery is the main treatment, but achieving radical resection remains a relevant intraoperative challenge. Fluorescence-guided surgery offers clinicians greater capabilities for real-time detection of tumor nodules and visualization of tumor margins. In this field, the main challenge remains the development of fluorescent dyes that can selectively target tumor tissues. Methods: we examined the expression of the most suitable GC markers, including carcinoembryonic antigen cell adhesion molecule-5 (CEACAM5) and Claudin-4 (CLDN4), in GC cell lines. To further evaluate their expression, we performed immunohistochemistry (IHC) on tumor and healthy tissue samples from 30 GC patients who underwent partial gastrectomy at the Digestive System Surgery Unit, AOU Careggi, Florence. Additionally, we validated anti-CEACAM5 expression on patient-derived organoids. Furthermore, we developed a fluorescent molecule targeting CEACAM5 on the surface of GC cells and assessed its binding properties on patient tissue slices and fragments. Results: in this work, we first identified CEACAM5 as an optimal GC biomarker, and then we developed a fluorescent antibody specific for CEACAM5. We also evaluated its binding specificity for GC cell lines and patient-derived tumor tissue, achieving an optimal ability to discriminate tumor tissue from healthy mucosa. Conclusions: Overall, our results support the development of our fluorescent antibody as a promising tumor-specific imaging agent that, after further in vivo validation, could improve the accuracy of complete tumor resection. Full article

Background: Necrotizing enterocolitis (NEC) is a severe gastrointestinal disease and a major cause of morbidity and mortality among preterm infants. Traditional diagnostic methods such as abdominal radiography have limited sensitivity in early disease stages, prompting interest in bowel ultrasound (BUS) as a complementary imaging modality. Objective: This scoping review aims to synthesize existing literature on the role of ultra sound in the early detection, diagnosis, and management of NEC, with emphasis on its diagnostic performance, integration into clinical care, and technological innovations. Methods: Following PRISMA-ScR guidelines, a systematic search was conducted across PubMed, Embase, Cochrane Library, and Google Scholar for studies published between January 2000 and December 2025. Inclusion criteria encompassed original research, reviews, and clinical studies evaluating the use of bowel, intestinal, or Doppler ultrasound in neonates with suspected or confirmed NEC. Data were extracted, categorized by study design, population characteristics, ultrasound features, and diagnostic outcomes, and qualitatively synthesized. Results: A total of 101 studies were included. BUS demonstrated superior sensitivity over radiography in detecting early features of NEC, including bowel wall thickening, portal venous gas, and altered peristalsis. Doppler ultrasound, both antenatal and postnatal, was effective in identifying perfusion deficits predictive of NEC onset. Neonatologist-performed ultrasound (NEOBUS) showed high interobserver agreement when standardized protocols were used. Emerging tools such as ultra-high-frequency ultrasound (UHFUS) and artificial intelligence (AI)-enhanced analysis hold potential to improve diagnostic precision. Point-of-care ultrasound (POCUS) appears feasible in resource-limited settings, though implementation barriers remain. Conclusions: Bowel ultrasound is a valuable adjunct to conventional imaging in NEC diagnosis. Standardized protocols, validation of advanced technologies, and out come-based studies are essential to guide its broader clinical adoption. Full article

Background and Objectives: Visceral arterial pseudoaneurysms (VAPAs) are rare vascular lesions characterized by the disruption of partial disruption of the arterial wall, most commonly involving the intima and media. They have an estimated incidence of 0.1–0.2%, with the splenic artery most commonly affected. Their management poses unique challenges due to the high risk of rupture. Timely recognition is crucial, as unmanaged pseudoaneurysms have a mortality rate of 90%. This narrative review aims to synthesize current knowledge regarding the epidemiology, etiology, clinical presentation, diagnostic methods, and management strategies for VAPAs. Materials and Methods: A literature search was performed across Pubmed for articles reporting on VAPAs, including case reports, review articles, and cohort studies, with inclusion of manuscripts that were up to (date). VAPAs are grouped by embryological origin—foregut, midgut, and hindgut. Results: Chronic pancreatitis is a primary cause of VAPAs, with the splenic artery being involved in 60–65% of cases. Other causes include acute pancreatitis, as well as iatrogenic trauma from surgeries, trauma, infections, drug use, and vascular diseases. VAPAs often present as abdominal pain upon rupture, with symptoms like nausea, vomiting, and gastrointestinal hemorrhage. Unruptured pseudoaneurysms may manifest as pulsatile masses or bruits but are frequently asymptomatic and discovered incidentally. Diagnosis relies on both non-invasive imaging techniques, such as CT angiography and Doppler ultrasound, and invasive methods like digital subtraction angiography, which remains the gold standard for detailed evaluation and treatment. A range of management options exists that are tailored to individual cases based on the aneurysm’s characteristics and patient-specific factors. This encompasses both surgical and endovascular approaches, with a growing preference for minimally invasive techniques due to lower associated morbidity. Conclusions: VAPAs are a critical condition requiring prompt early recognition and intervention. This review highlights the need for ongoing research to improve diagnostic accuracy and refine treatment protocols, enhancing patient outcomes in this challenging domain of vascular surgery. Full article

Accurate analysis of medical videos remains a major challenge in deep learning (DL) due to the need for effective spatiotemporal feature mapping that captures both spatial detail and temporal dynamics. Despite advances in DL, most existing models in medical AI focus on static images, overlooking critical temporal cues present in video data. To bridge this gap, a novel DL-based framework is proposed for spatiotemporal feature extraction from medical video sequences. As a feasibility use case, this study focuses on gastrointestinal (GI) endoscopic video classification. A 3D convolutional neural network (CNN) is developed to classify upper and lower GI endoscopic videos using the hyperKvasir dataset, which contains 314 lower and 60 upper GI videos. To address data imbalance, 60 matched pairs of videos are randomly selected across 20 experimental runs. Videos are resized to 224 × 224, and the 3D CNN captures spatiotemporal information. A 3D version of the parallel spatial and channel squeeze-and-excitation (P-scSE) is implemented, and a new block called the residual with parallel attention (RPA) block is proposed by combining P-scSE3D with a residual block. To reduce computational complexity, a (2 + 1)D convolution is used in place of full 3D convolution. The model achieves an average accuracy of 0.933, precision of 0.932, recall of 0.944, F1-score of 0.935, and AUC of 0.933. It is also observed that the integration of P-scSE3D increased the F1-score by 7%. This preliminary work opens avenues for exploring various GI endoscopic video-based prospective studies. Full article

Prompt and accurate identification of liver metastases from neuroendocrine tumors, arising from the gastrointestinal system and from the pancreas, through the means of both anatomical and functional diagnostic imaging techniques is mandatory. A patient’s prognosis and treatment planning are dependent on these diagnostic procedures. The aim of this narrative review is to depict the common appearance of liver metastases, as well as to depict atypical imaging patterns. Moreover, this review will cover the differential diagnosis between liver metastases from neuroendocrine tumors and other primary and secondary malignant liver lesions, as well as benign liver lesions. Full article

A young adult patient presented to the gastrointestinal outpatient department with a suspected hepatic tumor. The patient was in a traffic accident ten years ago and underwent splenectomy and distal pancreatectomy at another medical institution. The physical examination was unremarkable. The liver function tests and tumor markers were within normal limits, with the alpha-fetoprotein level at 1.38 ng/mL. Both hepatitis B surface antigen and anti-HCV were negative. Based on the clinical history, intrahepatic splenosis was suspected first. Dynamic computed tomography revealed a 2.3 cm lesion exhibiting suspicious early wash-in and early wash-out enhancement patterns. As previous studies have reported, this finding makes hepatocellular carcinoma and metastatic lesions the major differential diagnoses. For further evaluation, dynamic magnetic resonance imaging was performed, and similar enhancing features were observed, along with restricted diffusion. As hepatocellular carcinoma still could not be confidently ruled out, the patient underwent an ultrasound-guided biopsy. The diagnosis of intrahepatic splenosis was confirmed by the pathologic examination. Intrahepatic splenosis is a rare condition defined as an acquired autoimplantation of splenic tissue within the hepatic parenchyma. Diagnosis can be challenging due to its ability to mimic liver tumors in imaging studies. Therefore, in patients with a history of splenic trauma and/or splenectomy, a high index of suspicion and awareness is crucial for accurate diagnosis and for prevention of unnecessary surgeries or interventions. Full article

Rare presentations are surprising and may disturb the day-to-day routine of a medical unit; however, they are expected (not as individual entities, but as a group of “uncommon causes”). While reviewing the literature in relation to three clinical cases of upper gastrointestinal bleeding (UGIB) encountered in our institution—gastric metastases of breast cancer (GMB), pyloric gland adenoma, and gastrointestinal stromal tumor (GIST)—we identified seven and 29 case reports for the first two entities, and over 100 publications addressing GIST. This prompted a shift in focus from novel reporting to diagnostic contextualization. We found it difficult to obtain an overview of the spectrum of UGIB etiologies, as most publications refer to a few individual entities or to a subgroup of rare causes. The narrative review we conducted arose from this particular research methodology. Based on a broad literature search, UGIB etiologies were organized in five categories (lesions of the mucosa, neoplasms, vascular causes, bleeding predisposition, and external sources of bleeding). In the management of patients with UGIB, the underlying etiology deviates from the classic peptic ulcer disease/esophageal varices dyad in approximately half of the cases. This underscores the need for heightened clinical vigilance, particularly in complex scenarios, where endoscopic findings, imaging results, and histopathological interpretations may be unexpected or prone to misinterpretation. As an illustration, we conducted two systematic reviews of case reports of bleeding GMB and PGA. Our findings support a proactive diagnostic and research mindset and advocate for improved awareness of uncommon UGIB etiologies. Full article

Background/Objectives: A 2-year-old male presented to the emergency department (ED) with vomiting and abdominal discomfort following ingestion of multiple magnets from a sibling’s bracelet. This case highlights the risks associated with magnet ingestion and the need for coordinated multidisciplinary care and public health intervention. Methods: Radiographs revealed magnets in the oropharynx, stomach, and small bowel. Emergency physicians coordinated care with otolaryngology, gastroenterology, and general surgery. Results: Laryngoscopy successfully removed two magnets from the uvula, and endoscopy retrieved 30 magnets from the stomach. General surgery performed a diagnostic laparoscopy, identifying residual magnets in the colon. Gastroenterology attempted a colonoscopy but was unable to retrieve magnets due to formed stool, leading to bowel preparation and serial imaging. The patient eventually passed 12 magnets per rectum without surgical intervention. Conclusions: This case emphasizes the importance of multidisciplinary collaboration in managing magnet ingestion, a preventable cause of serious gastrointestinal injury. Recent studies highlight the increasing incidence and severity of such cases due to accessibility and inadequate regulation. These findings underscore the need for public awareness and adherence to management protocols to mitigate morbidity and mortality in pediatric patients. Full article

Sweet sensing is a fundamental sensory experience that plays a critical role not only in food preference, reward and dietary behaviour but also in glucose metabolism. Sweet taste receptors (STRs), composed of a heterodimer of taste receptor type 1 member 2 (T1R2) and member 3 (T1R3), are now recognised as being widely distributed throughout the body, including the gastrointestinal tract. Preclinical studies suggest these receptors are central to nutrient and glucose sensing, detecting energy availability and triggering metabolic and behavioural responses to maintain energy balance. Both internal and external factors tightly regulate their signalling pathways, and dysfunction within these systems may contribute to the development of metabolic disorders such as obesity and type 2 diabetes (T2D). Functional magnetic resonance imaging (fMRI) has provided valuable insights into the neural mechanisms underlying sweet sensing by mapping brain responses to both lingual/oral and gastrointestinal sweet stimuli. This review highlights key findings from fMRI studies and explores how these neural responses are modulated by metabolic state and individual characteristics such as body mass index, habitual intake and metabolic health. By integrating current evidence, this review advances our understanding of the complex interplay between sweet sensing, brain responses, and health and identifies key gaps and directions for future research in nutritional neuroscience. Full article

The neural network-based classification of endoscopy images plays a key role in diagnosing gastrointestinal diseases. However, current models for estimating ulcerative colitis (UC) severity still lack high performance, highlighting the need for more advanced and accurate solutions. This study aims to apply a state-of-the-art hybrid neural network architecture—combining convolutional neural networks (CNNs) and transformer models—to classify intestinal endoscopy images, utilizing the largest publicly available annotated UC dataset. A 10-fold cross-validation is performed on the LIMUC dataset using CoAtNet models, combined with the Class Distance Weighted Cross-Entropy (CDW-CE) loss function. The best model is compared against pure CNN and transformer baselines by evaluating performance metrics, including quadratically weighted kappa (QWK) and macro F1, for full Mayo score classification, and kappa and F1 scores for remission classification. The CoAtNet models outperformed both pure CNN and transformer models. The most effective model, CoAtNet_2, improved classification accuracy by $1.76\%$ and QWK by $1.46\%$ over the previous state-of-the-art models on the LIMUC dataset. Other metrics, including F1 score, also showed clear improvements. Experiments show that the CoAtNet model, which integrates convolutional and transformer components, improves UC assessment from endoscopic images, enhancing AI’s role in computer-aided diagnosis. Full article

Primary hepatic gastrointestinal stromal tumours (PHGISTs) are rare and frequently misdiagnosed due to their atypical presentation and uncertain origin. The purpose of this article is to present the case of a 79-year-old female patient with a gigantic PHGIST characterized by a predominantly cystic nature—an extremely rare presentation, as most cases of PHGIST are solid. Despite extensive imaging and exploratory laparotomy, the primary origin remained uncertain, leading to questioning about whether it was a true primary hepatic GIST or an atypical metastatic lesion. The initial therapeutic approach involved a surgical procedure aimed to confirm the diagnosis and achieve reductive tumourectomy. Following the surgery, the patient was administered imatinib with a favourable clinical response for four and a half years—an atypical pattern of resistance, as most patients typically develop therapeutic resistance within two to three years. A second surgical intervention was performed to address a cystic lesion localized in the left hepatic lobe, followed by an atypical segment III hepatectomy to achieve macroscopic resection. Subsequently, the patient received sunitinib for two and a half years, which resulted in temporary disease stabilization. However, the sunitinib treatment was associated with hypertension and leukopenia. The patient’s overall survival was 8 years, suggesting that individualized therapeutic strategies and close monitoring might be the key in such cases. Furthermore, this case confirms the role of surgical intervention even in advanced disease stages, with multiple major resections contributing significantly to prolonged survival. The interplay between surgical and oncologic therapies remains essential to guiding clinical decisions. Given the unusual cystic presentation, this case highlights the necessity to expand the pathological and molecular profiling of PHGISTs. Furthermore, the atypical timeline of resistance development and treatment-related toxicity emphasizes the importance of further research into the genetic and pharmacological determinants of PHGISTs. These findings advocate for the refinement of diagnostic, therapeutic, and surveillance protocols tailored to rare GIST subtypes. Full article