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The advent of robotic systems in interventional radiology marks a significant evolution in minimally invasive medical procedures, offering enhanced precision, safety, and efficiency. This review comprehensively analyzes the current state and applications of robotic system usage in interventional radiology, which can be particularly helpful for complex procedures and in challenging anatomical regions. Robotic systems can improve the accuracy of interventions like microwave ablation, radiofrequency ablation, and irreversible electroporation. Indeed, studies have shown a notable decrease of an average 30% in the mean deviation of probes, and a 40% lesser need for adjustments during interventions carried out with robotic assistance. Moreover, this review highlights a 35% reduction in radiation dose and a stable-to-30% reduction in operating time associated with robot-assisted procedures compared to manual methods. Additionally, the potential of robotic systems to standardize procedures and minimize complications is discussed, along with the challenges they pose, such as setup duration, organ movement, and a lack of tactile feedback. Despite these advancements, the field still grapples with a dearth of randomized controlled trials, which underscores the need for more robust evidence to validate the efficacy and safety of robotic system usage in interventional radiology.
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http://dx.doi.org/10.1016/j.bulcan.2024.06.004 | DOI Listing |
JAMA
September 2025
Division of Surgery and Interventional Science, UCL, London, United Kingdom.
Importance: Multiparametric magnetic resonance imaging (MRI), with or without prostate biopsy, has become the standard of care for diagnosing clinically significant prostate cancer. Resource capacity limits widespread adoption. Biparametric MRI, which omits the gadolinium contrast sequence, is a shorter and cheaper alternative offering time-saving capacity gains for health systems globally.
View Article and Find Full Text PDFPhys Eng Sci Med
September 2025
Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, 16424, Indonesia.
This study introduces a novel optimization framework for cranial three-dimensional rotational angiography (3DRA), combining the development of a brain equivalent in-house phantom with Figure of Merit (FOM) a quantitative evaluation method. The technical contribution involves the development of an in-house phantom constructed using iodine-infused epoxy and lycal resins, validated against clinical Hounsfield Units (HU). A customized head phantom was developed to simulate brain tissue and cranial vasculature for 3DRA optimization.
View Article and Find Full Text PDFCancer
September 2025
Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Tobacco use is the primary contributor to disease and death in the United States, and cigarette smoking is the leading risk factor for lung cancer. Safe and effective treatments for tobacco dependence exist; however, access to and use of tobacco treatment remains low. The most recent Centers for Medicare and Medicaid Services National Coverage Determination requires a shared decision-making visit for lung cancer screening that includes counseling on the importance of maintaining cigarette smoking abstinence if a person formerly smoked; or the importance of smoking cessation if a person currently smokes and, if appropriate, furnishing of information about tobacco-cessation interventions.
View Article and Find Full Text PDFCirc Cardiovasc Imaging
September 2025
Department of Cardiology, Amsterdam UMC, The Netherlands. (L.H.G.A.H., N.v.P., M.J.B.K., P.B., C.A., M.J.W.G.).
Radiol Adv
September 2024
Department of Radiology, Northwestern University and Northwestern Medicine, Chicago, IL, 60611, United States.
Background: In clinical practice, digital subtraction angiography (DSA) often suffers from misregistration artifact resulting from voluntary, respiratory, and cardiac motion during acquisition. Most prior efforts to register the background DSA mask to subsequent postcontrast images rely on key point registration using iterative optimization, which has limited real-time application.
Purpose: Leveraging state-of-the-art, unsupervised deep learning, we aim to develop a fast, deformable registration model to substantially reduce DSA misregistration in craniocervical angiography without compromising spatial resolution or introducing new artifacts.