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Background: Stereoelectroencephalography (SEEG) is an effective presurgical invasive evaluation for drug-resistant epilepsies. The introduction of robotic devices provides a simplified, accurate, and safe alternative to the conventional SEEG technique. We report our institutional experience with robot-assisted SEEG and compare its in vivo accuracy, operation efficiency, and safety with the more traditional SEEG workflow.
Methods: All patients with medically refractory focal epilepsy who underwent SEEG depth electrode implantation between 2014 and 2022 were included in this study. Technical advancements of the robot-assisted technique are described. Analyses of patient demographics, electrode implantation accuracy, operation time, and procedure-related complications were performed.
Results: One hundred and sixty-six patients underwent 167 SEEG procedures. The first 141 procedures were performed using a conventional approach involving a Leksell stereotactic system, and the last 26 procedures were robot-assisted. Among the 1726 depth electrodes that were inserted, the median entry point localization error was as follows: conventional (1.0 mm; range, 0.1-33.5 mm) and robot-assisted (1.1 mm; range, 0-4.8 mm) (P = 0.17). The median target point localization error was as follows: conventional (2.8 mm; range, 0.1-49 mm) and robot-assisted (1.8 mm; range, 0-30.3 mm) (P < 0.001). The median operation time was significantly reduced with the robot-assisted workflow (90 min vs. 77.5 min; P < 0.01). Total complication rates were as follows: conventional (17.7%) and robot-assisted (11.5%) (P = 0.57). Major complication rates were 3.5% and 7.7% (P = 0.77), respectively.
Conclusions: SEEG is a safe and highly accurate method that provides essential guidance for epilepsy surgery. Implementing SEEG in conjunction with multimodal planning systems and robotic devices can further increase safety margin, surgical efficiency, and accuracy.
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http://dx.doi.org/10.1007/s00701-024-05983-6 | DOI Listing |
Multimed Man Cardiothorac Surg
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Department of Thoracic Surgery, New Cross Hospital, Royal Wolverhampton NHS Trust, Wolverhampton, UK
Three-dimensional (3D) guided robotic-assisted thoracic surgery is increasingly recognized as the pioneering approach for the most complex of pulmonary resections, offering high-definition 3D visualization, enhanced instrument augmentation and tremor-free tissue articulation. Compared with open thoracotomy, the robotic platform is associated with reduced peri-operative morbidity, shorter hospital admissions and faster patient recovery. However, sublobar resections such as segmentectomies remain anatomically and technically demanding, particularly in the context of resecting multiple segments, as showcased in this right S1 and S2 segmentectomy.
View Article and Find Full Text PDFMed Biol Eng Comput
September 2025
Department of Computer Science, Università degli Studi di Bari Aldo Moro, Bari, Italy.
Fetal standard plane detection is essential in prenatal care, enabling accurate assessment of fetal development and early identification of potential anomalies. Despite significant advancements in machine learning (ML) in this domain, its integration into clinical workflows remains limited-primarily due to the lack of standardized, end-to-end operational frameworks. To address this gap, we introduce FetalMLOps, the first comprehensive MLOps framework specifically designed for fetal ultrasound imaging.
View Article and Find Full Text PDFTechnol Cancer Res Treat
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Department of Nephrology, Dongyang People's Hospital, Dongyang, China.
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View Article and Find Full Text PDFTurk Kardiyol Dern Ars
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Department of Cardiology, Muğla Sıtkı Koçman University, School of Medicine, Muğla, Türkiye.
Objective: Management of aortic stenosis (AS) requires integrating complex clinical, imaging, and risk stratification data. Large language models (LLMs) such as ChatGPT and Gemini AI have shown promise in healthcare, but their performance in valvular heart disease, particularly AS, has not been thoroughly assessed. This study systematically compared ChatGPT and Gemini AI in addressing guideline-based and clinical scenario questions related to AS.
View Article and Find Full Text PDFInt J Oral Implantol (Berl)
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Purpose: To compare the accuracy of static guided surgery using a pilot drill guide and dynamic guided surgery for dental implant placement.
Materials And Methods: Partially edentulous adult patients requiring implant placement were randomly assigned to either the static guided surgery group using a pilot drill guide or the dynamic guided surgery group. Digital implant planning was conducted using intraoral scans and CBCT with planning software to determine the optimal prosthetic position.