Lipiodol Versus Imipenem/Cilastatin in Genicular Artery Embolization: A Retrospective Study on Safety and Clinical Success.

Purpose: This study aims to evaluate the safety and effectiveness of genicular artery embolization (GAE) using lipiodol in comparison to imipenem/cilastatin (IPM-CS).

Materials And Methods: This retrospective study screened patients who underwent GAE between January 2022 and February 2023 for inclusion. Clinical outcomes were assessed at 1, 3, and 6 months post-procedure using the Visual Analog Scale (VAS) for pain and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for pain, stiffness, functional capacity, and total scores.

Microwave ablation of synovial hypertrophy in recurrent monoarthritis: The results of extended cohort and long-term follow-up.

Objectives: Recurrent monoarthritis (RM) is a major challenge of many rheumatic diseases. Ablation is a well-known technique in the treatment of benign or malign lesions of different etiologies. We aimed to to investigate the success and safety of microwave ablation (MWA) as an adjunctive therapy in a cohort of medical treatment-resistant RM.

Comparative Analysis of Transpedal and Transfemoral Access During Genicular Artery Embolization for Knee Osteoarthritis.

Purpose: This retrospective study aimed to compare the efficacy and safety of transpedal access (TPA) with transfemoral access (TFA) in Genicular Artery Embolization (GAE).

Materials And Methods: 60 patients who underwent GAE between January and June 2023, were recruited and outcomes were compared between the TFA (n = 37) and TPA (n = 23) groups. Technical and clinical success rates, complications, and patient-reported outcomes were assessed.

A Comparative Analysis of Erector Spinae Plane Block Versus Conscious Sedation in Managing Percutaneous Cholecystostomy Pain.

Purpose: This study investigates the efficacy of erector spinae plane block (ESPB) for managing perioperative and postoperative pain in patients undergoing percutaneous cholecystostomy (PC) for acute cholecystitis, particularly in high-risk elderly patients with extensive comorbidities and limited functional status.

Methods: In a retrospective single-center study, 58 high-risk patients scheduled for PC were assessed. ESPB was administered to 23 patients, while 22 received conscious sedation.

Percutaneous CT-Guided Microwave Ablation for the Treatment of Osteoid Osteomas: A Single Center Experience.

Rationale And Objectives: The aim of the current study was to evaluate the feasibility and effectiveness of CT-guided microwave ablation (MWA) in the treatment of osteoid osteomas (OO).

Materials And Methods: Data from 59 consecutive patients who underwent percutaneous CT-MWA for OO treatment were examined in the current retrospective study. The period of this study spanned from January 2021 to May 2023 at a single institution.

Effectiveness of polidocanol sclerotherapy in alleviating symptoms in patients with venous malformations.

Objective: The objective of this study was to retrospectively evaluate the effectiveness of polidocanol in managing pain, swelling, functional limiting and cosmetic disorders in patients with venous malformations (VMs).

Methods: This retrospective study included patients who underwent sclerotherapy with polidocanol for VMs between 2020 and 2022. Patient records, imaging findings, and evaluation questionnaires used in the preprocedure and follow-up phases were reviewed.

Development of subcapsular hematoma in the pelvic kidney during peripheral angioplasty.

Pelvic kidney is a mostly asymptomatic pathology resulting from failure of the kidneys to superior migration in fetal development. Herein, we report a 47-year-old female patient who presented with intermittent claudication in her right leg at 100 m. Significant stenosis was detected in the right superficial femoral artery and popliteal artery by computed tomography angiography.

Efficacy of Middle Meningeal Artery Embolization in Treatment Resistant Spontaneous Intracranial Hypotension Caused Subdural Hematoma : Report of Two Cases and Review of the Literature.

Spontaneous intracranial hypotension (SIH) most commonly manifests as bilateral subdural hematoma (SH). SIH cases mostly resolve spontaneously but further treatment would be needed via blind epidural blood patch (EBP). Cerebrospinal fluid (CSF) leakage in EBP-refractory cases can be treated surgically only if the localization of CSF leakage is detectable but it cannot be possible in most of the cases.

Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI.

Purpose: Variable response to neoadjuvant chemoradiotherapy (nCRT) is observed among individuals with locally advanced rectal cancer (LARC), having a significant impact on patient management. In this work, we aimed to investigate the potential value of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics in predicting therapeutic response to nCRT in patients with LARC.

Materials And Methods: Seventy-six patients with LARC were included in this retrospective study.

A surgical method to be reminded for the treatment of symptomatic ipsilateral central venous occlusions in patients with hemodialysis access: Axillo-axillary venous bypass case report and review of the literature.

Background: In this case report, we present two chronic hemodialysis patients with upper extremity swelling due to central venous occlusions together with their clinical presentation, surgical management and brief review of the literature.

Methods: The first patient who was a 63-year-old female patient with a history of multiple bilateral arteriovenous fistulas (AVFs) was referred to our clinic. Physical examination demonstrated a functioning right brachio-cephalic AVF, with severe edema of the right arm, dilated venous collaterals, facial edema, and unilateral breast enlargement.

Ga-PSMA PET/CT Versus F-FDG PET/CT for Imaging of Hepatocellular Carcinoma.

Objectives: This study aimed to compare the metabolic parameters obtained from fluorine-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET/CT) and gallium-68 (Ga)-prostate-specific membrane antigen (PSMA) PET/CT and investigate the relationship between serum alpha-fetoprotein and PET scan parameters in patients with hepatocellular carcinoma.

Methods: Fourteen patients were recruited after dynamic magnetic resonance imaging (MRI) of the upper abdomen, and F-FDG and Ga-PSMA PET/CT imaging studies were conducted. Regions of interest (ROIs) were drawn from lesion-free liver tissue, abdominal aorta (A), and right medial gluteal muscle (G) for the background activity.

Comparison of functional patency rates between paclitaxel-eluting versus plain balloon angioplasty in hemodialysis patients with central venous stenosis: An intra-individual comparison study.

Central venous stenosis (CVS) is usually a late-diagnosed clinical entity that is common in hemodialysis patients. It causes various problems ranging from hemodialysis difficulty to loss of the arterio-venous (A-V) fistula. In the present study, we aimed to determine the effect of drug eluting balloon while excluding the influence of other variable factors by evaluating the same individuals with plain and paclitaxel-eluting balloons.

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts.

In recent years, there has been a dramatic increase in research papers about machine learning (ML) and artificial intelligence in radiology. With so many papers around, it is of paramount importance to make a proper scientific quality assessment as to their validity, reliability, effectiveness, and clinical applicability. Due to methodological complexity, the papers on ML in radiology are often hard to evaluate, requiring a good understanding of key methodological issues.

Tubular gastric adenocarcinoma: machine learning-based CT texture analysis for predicting lymphovascular and perineural invasion.

Purpose: Lymphovascular invasion (LVI) and perineural invasion (PNI) are associated with poor prognosis in gastric cancers. In this work, we aimed to investigate the potential role of computed tomography (CT) texture analysis in predicting LVI and PNI in patients with tubular gastric adenocarcinoma (GAC) using a machine learning (ML) approach.

Methods: Sixty-eight patients who underwent total gastrectomy with curative (R0) resection and D2-lymphadenectomy were included in this retrospective study.

Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency.

The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. A systematic literature search was conducted using PubMed to identify original research studies about the application of AI to renal mass characterization. Besides baseline study characteristics, a total of 15 methodologic quality items were extracted and evaluated on the basis of the following four main categories: modeling, performance evaluation, clinical utility, and transparency items.

Machine Learning in Radiomic Renal Mass Characterization: Fundamentals, Applications, Challenges, and Future Directions.

The purpose of this study is to provide an overview of the traditional machine learning (ML)-based and deep learning-based radiomic approaches, with focus placed on renal mass characterization. ML currently has a very low barrier to entry into general medical practice because of the availability of many open-source, free, and easy-to-use toolboxes. Therefore, it should not be surprising to see its related applications in renal mass characterization.

Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment.

Purpose: The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative period.

Materials And Methods: CT images of 114 patients with GC were included in this retrospective study. Following pre-processing steps, textural features were extracted using MaZda software in the portal venous phase.

Prediction of Benign and Malignant Solid Renal Masses: Machine Learning-Based CT Texture Analysis.

Rationale And Objectives: This study aimed to investigate whether benign and malignant renal solid masses could be distinguished through machine learning (ML)-based computed tomography (CT) texture analysis.

Materials And Methods: Seventy-nine patients with 84 solid renal masses (21 benign; 63 malignant) from a single center were included in this retrospective study. Malignant masses included common renal cell carcinoma (RCC) subtypes: clear cell RCC, papillary cell RCC, and chromophobe RCC.

Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.

Objective: To evaluate the potential value of the machine learning (ML)-based MRI texture analysis for predicting 1p/19q codeletion status of lower-grade gliomas (LGG), using various state-of-the-art ML algorithms.

Materials And Methods: For this retrospective study, 107 patients with LGG were included from a public database. Texture features were extracted from conventional T2-weighted and contrast-enhanced T1-weighted MRI images, using LIFEx software.

Radiomics with artificial intelligence: a practical guide for beginners.

Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high number of quantitative features from medical images. Artificial intelligence (AI) is broadly a set of advanced computational algorithms that basically learn the patterns in the data provided to make predictions on unseen data sets. Radiomics can be coupled with AI because of its better capability of handling a massive amount of data compared with the traditional statistical methods.