Domenico Laganà

Background: Percutaneous transhepatic biliary drainage (PTBD) remains a cornerstone in managing obstructive jaundice, particularly when endoscopic retrograde cholangiopancreatography (ERCP) is unsuccessful or contraindicated. This study aims to compare ultrasound-guided (US-PTBD) and fluoroscopy-guided (F-PTBD) techniques regarding procedural time, radiation exposure, technical success, and complication rates. Methods: This retrospective, single-center study included patients with malignant obstructive jaundice who underwent PTBD between January 2018 and December 2025. Patients were stratified based on the imaging modality used for the bile duct puncture (US-PTBD vs. F-PTBD). Procedural characteristics, including dose–area product (DAP), fluoroscopy time, complication rates, and technical success, were analyzed using statistical methods appropriate for continuous and categorical data. Results: A total of 133 patients (163 PTBD procedures) were included. US-PTBD demonstrated significantly lower DAP (4.1 ± 1.9 Gy·cm² vs. 6.2 ± 1.5 Gy·cm²; p < 0.001) and shorter procedure time (42 ± 7 min vs. 56.6 ± 6 min; p < 0.001) compared to F-PTBD. Both techniques had comparable technical success rates (91.1% vs. 82.2%; p = 0.158). Complications occurred in 10.2% of patients in the F-PTBD group and 6.7% in the US-PTBD group, with no statistically significant difference between groups (p = 0.489). Major complications, including bleeding and cholangitis, occurred exclusively in the F-PTBD cohort. US-PTBD resulted in fewer Glisson capsule punctures, suggesting reduced procedural trauma. Conclusions: Although a significant access side imbalance was present between cohorts, US-PTBD offers distinct advantages over F-PTBD, including reduced radiation exposure, shorter procedure times, and a comparable safety profile. These findings highlight the potential of US guidance as a safer alternative for PTBD, particularly in patients with coagulopathy or complex anatomy. Further multicenter studies with larger populations are warranted to confirm these benefits and refine patient selection criteria.

Introduction: Cholecystocolonic fistula (CCF) represents the second most frequent type of biliary-enteric fistula, following cholecystoduodenal fistula. It occurs more frequently in older women, especially those with chronic cholelithiasis, but its overall incidence remains low. CCF is characterized by a pathological communication between the gallbladder and the colon, allowing the direct passage of bile and, eventually, stones into the colonic lumen. Since its typical symptoms, including diarrhea, right upper quadrant pain, and cholangitis, can be vague, the diagnosis often occurs intraoperatively, which can complicate surgical intervention, particularly in elderly patients with multiple comorbidities. Due to its rarity, variable clinical presentation, and diagnostic and therapeutic challenges, CCF stands out as a distinctive surgical condition. This study aims to improve clinical practice by highlighting the importance of the early diagnosis of CCF through the presentation of an atypical case report. The approach is supported by recent literature (not older than 10 years), selected based on diagnostic relevance and clinical outcomes. Case presentation: We present the case of a 77-year-old man who arrived at the hospital with a fever of unknown origin, resistant to antibiotic therapy. Abdominal ultrasound raised suspicion of a cholecystocolonic fistula, requiring a contrast-enhanced CT scan, which ultimately confirmed the diagnosis of a cholecystocolonic fistula that originated subsequently to gallbladder carcinoma. Conclusions: Cholecystocolonic fistula is a rare but significant complication of gallbladder disease, which in some cases may present with atypical symptoms. Clinical practice, exemplified by this case report, demonstrates that the presence of a cholecystocolonic fistula should be suspected when heterogeneous masses and abnormal connections between the gallbladder and colon are detected by diagnostic imaging, even in the absence of specific symptoms. Moreover, its association with biliary neoplasia, although uncommon, must always be considered to guide appropriate treatment planning.

Cesarean scar pregnancy (CSP) carries a high risk of severe hemorrhage and potential loss of fertility. This narrative review summarizes current evidence on uterine artery embolization (UAE) using absorbable gelatin sponge (GS), focusing on GS preparation, procedural approaches, and reported outcomes. PubMed/MEDLINE, Scopus, and Google Scholar were searched from January 2015 to 31 December 2024 for peer-reviewed studies reporting UAE with GS for CSP (GS alone or combined with intra-arterial methotrexate and/or adjunct particles). Fifty studies (N = 3139) were included. Technical success was 3133/3139 (~99.8%) and clinical success was 2975/3139 (~94.8%), with most cohorts reporting high clinical control. Severe complications were infrequently reported (typically ~2–4% in most series). Menstrual function, when assessed, generally recovered within ~1–2 months. Subsequent pregnancy outcomes were inconsistently reported and follow-up durations were heterogeneous, predominantly in retrospective designs. Overall, UAE with GS appears effective for hemostasis in CSP and may reduce escalation to hysterectomy in appropriately selected patients. Standardized reporting of GS preparation and outcomes, as well as prospective multicenter registries/studies, are needed to refine best practices.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide, representing a major public health challenge. Despite advances in screening strategies, surgical techniques, and systemic therapies, patient prognosis is often compromised by late diagnosis, tumor heterogeneity, and therapeutic resistance. In recent years, the integration of advanced imaging analytics and artificial intelligence (AI) has opened new avenues for precision oncology. Radiomics, defined as the high-throughput extraction of quantitative features from medical images, has emerged as a promising tool to capture intratumoral heterogeneity and predict clinical outcomes in a non-invasive manner. When combined with AI, particularly machine learning and deep learning approaches, radiomics enables the development of predictive and prognostic models that may support treatment personalization. This narrative review provides a comprehensive overview of CRC epidemiology and risk factors, summarizes current diagnostic and clinical management strategies, and focuses extensively on radiomics and AI applications in CRC, including workflow standardization, feature extraction, clinical applications, and challenges for implementation in daily practice.

Background and Objectives: Progressive pulmonary fibrosis (PPF) presents significant clinical challenges due to irreversible lung damage and declining respiratory function. Nintedanib has demonstrated antifibrotic effects, yet there is a lack of sensitive tools to assess treatment efficacy quantitatively. This study evaluated the potential of artificial intelligence (AI)-powered quantitative computed tomography (QCT) to monitor lung changes and predict treatment outcomes in patients with PPF undergoing nintedanib therapy. Materials and Methods: This retrospective study analysed 37 patients diagnosed with PPF who were treated with nintedanib for one year. AI-powered QCT was performed using the 3D Slicer software version 5.2.2, which quantified lung infiltration, collapse, and vessel volumes. These data were then correlated with pulmonary function tests. Receiver operating characteristic (ROC) analysis was used to assess baseline AI-powered QCT predictors for progression. Results: AI-powered QCT demonstrated a significant reduction in post-treatment right lung infiltration (5.56 ± 3.08 cm³ to 4.88 ± 2.77 cm³, p = 0.041), whereas total lung infiltration decreased non-significantly. Functional parameters, including forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLCO), showed no significant changes. ROC analysis identified a baseline infiltrated lung volume greater than 21.90% as predictive of continued disease progression (AUC = 0.767; sensitivity, 91.70%; specificity, 68.00%). Conclusions: AI-powered QCT identified diverse parenchymal responses to nintedanib in PPF and showed preliminary prognostic value for clinical trajectory. Imaging biomarkers enhance functional measures and may reveal early treatment effects. Prospective, multicentre validation is necessary to confirm usefulness and establish actionable thresholds for clinical application.

Background/Objectives: Although MRI with fat-suppression sequences is the gold standard for diagnosis of bone marrow edema (BME), Dual-Layer Spectral CT (DL-SCT) with electron density (ED) provides a viable alternative, particularly in situations where an MRI is not accessible. Using MRI as the reference standard, this study analyzed how DL-SCT with ED reconstructions may be a valid alternative in the detection of BME. Methods: This retrospective study included 28 patients with a suspected diagnosis of BME via MRI conducted between March and September 2024. Patients underwent DL-SCT using ED reconstructions obtained through IntelliSpace software v. 12.1. Images were evaluated by two experienced radiologists and one young radiologist in a blinded way, giving a grade from 0 to 3 to classify BME (0 absence; 1 mild; 2 moderate; 3 severe). To reduce the recall bias effect, the order of image evaluations was set differently for each reader. p-Values were considered significant when p-value < 0.001); for grade 1: 0.21 (p-value < 0.001); for grade 2: 0.197 (p-value < 0.001); and for grade 3: 0.515 (p-value < 0.001). Conclusions: ED reconstructions allowed the identification of BME presence or absence in all analyzed cases, thus suggesting DL-SCT as a potentially effective method for its detection.

Background/Objectives: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality and often develops in the context of liver cirrhosis (LC). Its detection remains a clinical challenge, particularly with limited sensitivity of the current serum biomarkers and qualitative imaging tools. The aim of this pilot study is to evaluate the application of a combined model based on the use of Liver to Spleen Volume Ratio (LSVR), a score of regional liver remodeling, and Liver Vein to Cava Attenuation (LVCA), a computed tomography (CT)-based perfusion-related parameter, to diagnose HCC in patients with LC. Methods: In this observational retrospective pilot study, 36 patients with LC, with or without HCC, were enrolled from a single tertiary care center between 2021 and 2024. Demographic, clinical, biochemical, and imaging data were collected. LSVR and LVCA were calculated from contrast-enhanced CT scans. Predictors of HCC were assessed using conditional inference trees and multivariate logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). A p-value < 0.05 was considered statistically significant. Results: LVCA and LSVR levels were significantly higher in the HCC group (p < 0.001). In multivariate analysis, LVCA was significantly associated with HCC onset (Odds Ratio = 2.88, p = 0.0075). The final model incorporating both LVCA and LSVR achieved excellent discrimination (AUC = 0.967), with 91% sensitivity and 88% specificity. The combined model outperformed LSVR alone (p = 0.030), though not LVCA alone. Conclusions: Our pilot study suggests the utility of LVCA and LSVR as potential non-invasive imaging tools for HCC diagnosis. External validation in multicenter cohorts and longitudinal studies assessing the temporal evolution of LSVR and LVCA are necessary to better evaluate their application in clinical practice.

Background/Objectives: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality and often develops in the context of liver cirrhosis (LC). Early detection remains a clinical challenge, particularly with limited sensitivity of current se-rum biomarkers and qualitative imaging tools. This pilot study aimed to evaluate the diagnostic utility of two computed tomography (CT)-derived metrics, Liver Segmental Volume Ratio (LSVR) and Liver Vein to Cava Attenuation (LVCA), as non-invasive im-aging predictors of HCC in cirrhotic patients. Methods: In this observational retrospective pilot study, 36 patients with LC, with or without HCC, were enrolled from a single tertiary care center between 2021 and 2024. Demographic, clinical, biochemical, and imaging data were collected. LSVR and LVCA were calculated from contrast-enhanced CT scans. Predictors of HCC were assessed using conditional inference trees and multivariate logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). P-value < 0.05 was considered statistically significant Results: LVCA and LSVR levels were significantly higher in the HCC group (p< 0.001). In multivariate analysis, LVCA was significantly associated with HCC onset (Odds Ratio=2.88, p=0.0075). The final model incorporating both LVCA and LSVR achieved excellent discrimination (AUC=0.967), with 91% sensitivity and 88% specificity. The combined model outperformed LSVR alone (p=0.030), though not LVCA alone. Conclusions: LVCA and LSVR represent promising quantitative imaging biomarkers for non-invasive HCC detection in cirrhotic patients. External validation in multicenter co-horts and longitudinal studies assessing the temporal evolution of LSVR and LVCA are necessary to confirm their application in clinical practice.

Background/Objectives: To evaluate dual-energy computed tomography (DECT) in comparison with conventional CT for periprosthetic bone and surrounding soft tissues in total hip arthroplasty (THA). Methods: Two authors independently screened titles and abstracts for eligibility, discussing any disagreements with a third author for final decisions. The articles were categorized into two main groups: those focusing on periprosthetic bone and those on blood vessels or pelvic organs. Results: A total of 37 articles were selected to be included in this systematic review. Conclusions: Our systematic review reveals significant variability in the use of DECT for periprosthetic bone and soft tissue imaging, due to differences in equipment, protocols, and clinical settings. While many studies indicate that virtual monochromatic imaging (VMI), especially when combined with metal artifact reduction (MAR), improves image quality, there is no consensus on optimal energy levels. Future research should focus on large-scale, multicenter studies with standardized protocols to compare reconstruction techniques, energy levels, and combined MAR-VMI use.

Magnetic resonance imaging (MRI) is routinely used to confirm the suspected diagnosis of anterior cruciate ligament (ACL) injury. Recently, many studies explored the role of artificial intelligence (AI) and deep learning (DL), a sub-category of AI, in the musculoskeletal field and medical imaging. The aim of this study was to review the current applications of DL models to detect ACL injury on MRI, thus providing an updated and critical synthesis of the existing literature and identifying emerging trends and challenges in the field. A total of 23 relevant articles were identified and included in the review. Articles originated from 10 countries, with China having the most contributions (n = 9), followed by the United State of America (n = 4). Throughout the article, we analyzed the concept of DL in ACL tears and provided examples of how these tools can impact clinical practice and patient care. DL models for MRI detection of ACL injury reported high values of accuracy, especially helpful for less experienced clinicians. Time efficiency was also demonstrated. Overall, the deep learning models have proven to be a valid resource, although still requiring technological developments for implementation in daily practice.