Search Results (725)

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

Background: Abdominal wall endometriosis (AWE) is a rare pathological condition that mostly occurs in the post-cesarean section. This study aimed to describe the surgical approach employed in treating 31 patients at our center over the past decade and compare the outcomes with those reported in scientific literature. Methods: We retrospectively evaluated the data of 31 patients with a cesarean section history who underwent surgery for AWE excision between 1 November 2012, and 31 January 2023, at the University of Naples Federico II, Italy. Subsequently, we reviewed the scientific literature for all AWE-related studies published between 1 January 1995, and 31 July 2024. Results: Most women presented with a palpable abdominal mass (90.3%) at the previous surgical site associated with cyclic abdominal pain (80.6%) concomitant with menstruation. All patients underwent preoperative abdominal ultrasound and magnetic resonance imaging, 71% underwent computed tomography, and 32.2% received ultrasound-guided needle biopsies. Furthermore, 90.3% and 9.7% had previous Pfannenstiel and median vertical surgical incisions, respectively. All patients underwent laparotomic excision and abdominal wall reconstruction, with prosthetic reinforcement used in 73.5% of cases. No recurrent nodules were detected in any patient at the 12-month follow-up. Conclusions: AWE should be suspected in women with a history of cesarean section presenting with palpable, cyclically painful abdominal mass associated with the menstrual cycle. Preoperative ultrasound and magnetic resonance imaging are essential, and surgical excision must ensure clear margins. Abdominal wall reconstruction should include prosthetic reinforcement, except when the defect is minimal (≤1.5 cm). An ultrasound follow-up at 12 months is recommended to confirm the absence of recurrence. Full article

Tissue-engineered scaffolds, particularly composite scaffolds composed of polymers combined with ceramics, bioactive glasses, or nanomaterials, play a vital role in regenerative medicine by providing structural and biological support for tissue repair. As scaffold designs grow increasingly complex, the need for non-invasive imaging modalities capable of monitoring scaffold integration, degradation, and tissue regeneration in real-time has become critical. This review summarizes current non-invasive imaging techniques used to evaluate tissue-engineered constructs, including optical methods such as near-infrared fluorescence imaging (NIR), optical coherence tomography (OCT), and photoacoustic imaging (PAI); magnetic resonance imaging (MRI); X-ray-based approaches like computed tomography (CT); and ultrasound-based modalities. It discusses the unique advantages and limitations of each modality. Finally, the review identifies major challenges—including limited imaging depth, resolution trade-offs, and regulatory hurdles—and proposes future directions to enhance translational readiness and clinical adoption of imaging-guided tissue engineering (TE). Emerging prospects such as multimodal platforms and artificial intelligence (AI) assisted image analysis hold promise for improving precision, scalability, and clinical relevance in scaffold monitoring. Full article

Background/Objectives: In the era of treat-to-target strategies in inflammatory bowel disease (IBD), transmural healing (TH) is gaining recognition as a promising therapeutic goal. TH has been associated with significantly better long-term outcomes, including reduced rates of hospitalization, surgery, and the need for therapy escalation. Cross-sectional imaging techniques, such as intestinal ultrasound (IUS), magnetic resonance imaging (MRI), and computed tomography enterography (CTE), offer a comprehensive, non-invasive means to assess this deeper level of healing. This review explores how TH is currently defined across various imaging modalities and evaluates the feasibility and cost-effectiveness of achieving TH with available therapies. Methods: A literature search was conducted across PubMed, Scopus, and Embase using keywords, including “transmural healing”, “intestinal ultrasonography”, “magnetic resonance imaging”, “computed tomography enterography”, “Crohn’s disease”, “ulcerative colitis”, and “inflammatory bowel disease”. Only English-language studies were considered. Results: Despite growing interest, there is no standardized definition of TH across imaging platforms. Among the modalities, IUS emerges as the most feasible and cost-effective tool, owing to its accessibility, accuracy (sensitivity 62–95.2%, specificity 61.5–100%), and real-time capabilities, though it does have limitations. Current advanced therapies induce TH in roughly 20–40% of patients, with no consistent differences observed between biologics and small molecules. However, TH has only been evaluated as a formal endpoint in a single randomized controlled trial to date. Conclusions: A unified and validated definition of transmural healing is critically needed to harmonize research and guide clinical decision-making. While TH holds promise as a meaningful treatment target linked to improved outcomes, existing therapies often fall short of achieving complete transmural resolution. Further studies are essential to clarify its role and optimize strategies for deep healing in IBD. Full article

Background/Objectives: To assess quantitatively the correlation between the lung ultrasound severity scores (LUSSs) and chest CT severity scores (CTSSs) derived from low-dose computed tomography (LDCT) for evaluating pulmonary inflammation in COVID-19 patients. Methods: In this prospective observational study, from an initial cohort of 1000 patients, 555 adults (≥18 years) with confirmed COVID-19 were enrolled based on inclusion criteria. All underwent LDCT imaging, scored by the CTSS (0–25 points), quantifying involvement across five lung lobes. Lung ultrasound examinations using standardized semi-quantitative scales for the B-line (LUSS B) and consolidation (LUSS C) were performed in a subgroup of 170 patients; 110 had follow-up imaging after one week. Correlation analyses included Spearman’s and Pearson’s coefficients. Results: Significant positive correlations were found between the CTSS and both the LUSS B (r = 0.32; p < 0.001) and LUSS C (r = 0.24; p = 0.006), with the LUSS B showing a slightly stronger relationship. Each incremental increase in the LUSS B corresponded to an average increase of 0.18 CTSS points, whereas a one-point increase in the LUSS C corresponded to a 0.27-point CTSS increase. The mean influence of the LUSS on CTSS was 8.0%. Neither ultrasound score significantly predicted ICU admission or mortality (p > 0.05). Conclusion: Standardized lung ultrasound severity scores show a significant correlation with low-dose CT in assessing pulmonary involvement in COVID-19, particularly for the B-line artifacts. Lung ultrasound represents a valuable bedside tool, complementing—but not substituting—CT in predicting clinical severity. Integrating both imaging modalities may enable the acquisition of complementary bedside information and facilitate dynamic monitoring of disease progression. 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

Background: Migration of the peritoneal end of the ventriculoperitoneal shunt (VPS) into the scrotum is a rare but recognized complication. Inguinoscrotal migration typically occurs as a result of increased intra-abdominal pressure combined with a patent processus vaginalis. A 14-month-old pediatric patient presented to the emergency department with abdominal pain, vomiting, and swelling of the right scrotum that had persisted for two days. The patient had a history of a head injury that had resulted in a large secondary arachnoid cyst for which a VPS had been placed at eight months of age. Examination of the inguinoscrotal region revealed a swollen and painful right side of the scrotum with a hydrocele and a palpable distal portion of the ventriculoperitoneal catheter in the right groin extending to the scrotum. After a brief preoperative preparation, the patient underwent laparoscopic abdominal emergency exploration, during which shunt repositioning and laparoscopic closure of the patent processus vaginalis were performed. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A total of 30 case reports and six case series were included, analyzing 52 pediatric patients with scrotal migration of the VPS. The median age at presentation was 24 months (range: 1–169 months). The indication for VPS placement was hydrocephalus. Migration of the VPS catheter occurred on the right side in 34 cases. The median interval from VPS placement to the onset of symptoms was 9.0 months (range: 1 day–72 months). The most frequently reported symptoms were scrotal/inguinoscrotal swelling (n = 50), vomiting (n = 7), and fever (n = 3). Diagnostic methods included abdominal X-ray (n = 43), ultrasound (n = 5), scrotal transillumination test (n = 5), and computed tomography (n = 1). Regarding treatment, surgical repositioning of the VPS catheter into the peritoneal cavity was performed in 47 patients (90.4%), with no intraoperative or postoperative complications reported. Conclusions: Laparoscopic repositioning of the VPS into the peritoneal cavity, combined with closure of the processus vaginalis, appears to be a safe and effective treatment option for scrotal migration of the VPS. However, further well-designed studies are warranted to provide more comprehensive, generalizable, and unbiased evidence regarding this complication in the pediatric population. Full article

The rapid spread of COVID-19 increased the need for speedy diagnostic tools, which led scientists to conduct extensive research on deep learning (DL) applications that use chest imaging, such as chest X-ray (CXR) and computed tomography (CT). This review examines the development and performance of DL architectures, notably convolutional neural networks (CNNs) and emerging vision transformers (ViTs), in identifying COVID-19-related lung abnormalities. Individual ResNet architectures, along with CNN models, demonstrate strong diagnostic performance through the transfer protocol; however, ViTs provide better performance, with improved readability and reduced data requirements. Multimodal diagnostic systems now incorporate alternative methods, in addition to imaging, which use lung ultrasounds, clinical data, and cough sound evaluation. Information fusion techniques, which operate at the data, feature, and decision levels, enhance diagnostic performance. However, progress in COVID-19 detection is hindered by ongoing issues stemming from restricted and non-uniform datasets, as well as domain differences in image standards and complications with both diagnostic overfitting and poor generalization capabilities. Recent developments in COVID-19 diagnosis involve constructing expansive multi-noise information sets while creating clinical process-oriented AI algorithms and implementing distributed learning protocols for securing information security and system stability. While deep learning-based COVID-19 detection systems show strong potential for clinical application, broader validation, regulatory approvals, and continuous adaptation remain essential for their successful deployment and for preparing future pandemic response strategies. Full article

Background and Objectives: Acute appendicitis is a common cause of abdominal pain requiring surgery in pediatric patients. Given concerns regarding radiation exposure from computed tomography (CT), ultrasound (US) has become the first-line diagnostic modality. In many emergency and resource-limited settings, non-radiologist physicians often perform these examinations. This study aimed to evaluate the diagnostic accuracy of a non-radiologist-performed ultrasound in detecting acute appendicitis in children. Materials and Methods: We conducted a systematic review and meta-analysis according to the PRISMA guidelines. The literature was searched across PubMed, Ovid MEDLINE, EMBASE, the Cochrane Library, and Google Scholar through June 2024. Studies reporting on the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of non-radiologist-performed ultrasounds in pediatric appendicitis were included. Study quality was assessed using the QUADAS-2 tool, and a bivariate random-effects model was used for statistical analysis. Results: Eight studies, with a total of 1006 pediatric patients, were included. The pooled sensitivity and specificity were 0.87 (95% CI, 0.83–0.90) and 0.93 (95% CI, 0.91–0.95), respectively. The area under the SROC curve was 0.783 (95% CI, 0.708–0.853), suggesting moderate-to-good diagnostic accuracy. Substantial heterogeneity was observed across studies, possibly due to differences in operator training and ultrasound techniques. Conclusions: Non-radiologist-performed ultrasound demonstrates moderate-to-good diagnostic accuracy in identifying pediatric appendicitis. These findings support its implementation in emergency or resource-constrained settings and suggest that incorporating structured ultrasound training for non-radiologists may improve timely diagnosis and optimize clinical decision-making in pediatric emergency care. Full article

Coronary plaque vulnerability, more than luminal stenosis, drives acute coronary syndromes. Optical coherence tomography (OCT), intravascular ultrasound (IVUS), and coronary computed tomography angiography (CCTA) visualize plaque morphology in vivo, but manual interpretation is time-consuming and operator-dependent. We performed a narrative literature survey of artificial intelligence (AI) applications—focusing on machine learning (ML) architectures—for automated coronary plaque segmentation and risk characterization across OCT, IVUS, and CCTA. Recent ML models achieve expert-level lumen and plaque segmentation, reliably detecting features linked to vulnerability such as a lipid-rich necrotic core, calcification, positive remodelling, and a napkin-ring sign. Integrative radiomic and multimodal frameworks further improve prognostic stratification for major adverse cardiac events. Nonetheless, progress is constrained by small, single-centre datasets, heterogeneous validation metrics, and limited model interpretability. AI-enhanced plaque assessment offers rapid, reproducible, and comprehensive coronary imaging analysis. Future work should prioritize large multicentre repositories, explainable architectures, and prospective outcome-oriented validation to enable routine clinical adoption. 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

Coronary chronic total occlusions (CTOs) are diagnosed in a significant portion of patients undergoing coronary angiography and represent one of the most complex scenarios in contemporary percutaneous coronary interventions (PCI). This review systematically examines how adjunctive imaging modalities’—intravascular ultrasound (IVUS), optical coherence tomography (OCT), and coronary computed tomography angiography (CCTA)—co-registration enhances the precision and success rates of CTO-PCI during the procedure. The strategic integration of these technologies enables the development of patient-specific intervention strategies tailored to individual vascular architecture and lesion characteristics. This personalized approach marks a transition from standardized protocols to precision interventional cardiology, potentially optimizing procedural success rates while minimizing complications. Full article

Background: Liver cancer is a major health concern worldwide. Radiofrequency ablation is a safe treatment option that can be guided by either ultrasound, computer tomography (CT), or fluoroscopy. Although ultrasound-guided radiofrequency ablation is commonly used in clinical practice, radiofrequency ablation guided by CT is more precise but requires more time and does not offer real-time monitoring, which may result in complications such as pneumothorax or organ damage. Objectives: In this study, we investigated the effect of ultrasound, CT, and combined ultrasound/CT guidance on patient survival and complication development. Methods: A total of 982 radiofrequency ablation sessions conducted on 553 patients were analyzed. Clinical outcomes were assessed during follow-up to determine the survival and recurrence rates of malignant tumors. Results: Overall, the three guidance approaches exhibited significant differences in terms of tumor size, number, complication development, and treatment duration. However, no significant differences were observed in survival rate. A comparison of the effect of CT guidance and ultrasound guidance on complication development revealed a higher odds ratio for CT guidance in some cases. A comparison of combined ultrasound/CT guidance and ultrasound guidance revealed nonsignificant differences in complication development. A comparison of CT guidance and combined ultrasound/CT guidance revealed a higher odds ratio for CT guidance in some cases. Radiofrequency ablation is a safe and effective treatment for liver tumors. However, CT has an increased incidence of complications. Conclusions: Combined ultrasound/computer tomography guidance is recommended for patients with multiple or large tumors or tumors near the hepatic dome or diaphragm. Full article

Venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), is a life-threatening vascular disorder associated with significant morbidity and mortality. Prompt diagnosis is crucial for preventing fatal complications. Current clinical VTE diagnosis predominantly relies on imaging modalities such as compression ultrasound, computed tomography angiography (CTA), and magnetic resonance imaging (MRI). However, these techniques are resource-intensive, time-consuming, and may expose patients to radiation risks. Consequently, the development of highly sensitive and specific biomarkers is imperative to enhance early detection and guide therapeutic interventions. This review examines established and emerging biomarkers in venous thrombosis, evaluates current challenges, and outlines promising future directions for biomarker research in VTE. Full article

Contrast-enhanced ultrasound and elastography are two ultrasound technologies that are becoming increasingly popular in the evaluation of different abdominal pathologies in children. The use of these technologies has expanded the diagnostic scope of ultrasound into areas that were traditionally covered by advanced imaging modalities such as computed tomography, magnetic resonance imaging, and fluoroscopy. In this review, we summarize the use of contrast-enhanced ultrasound and elastography in the evaluation of hepatic, renal, pancreatic, splenic, urinary tract, and scrotal pathologies in children. We describe the technical aspects, applications, and limitations, intending to make readers more acquainted with the technologies. Full article