Quantitative analysis of genicular nerve block spread and variability: Anatomical correlations and clinical implications

Background: Despite advancements in anaesthesiology and regional anaesthesia, the threedimensional spread of local anaesthetics is still poorly understood. This study investigates the pericapsular spread of radiopaque contrast after ultrasound-guided genicular nerve block in cadaveric knees using CT reconstruction. The aim is to assess the reproducibility, accuracy, and variability of this technique in order to improve safety and effectiveness. Methods: We used a four-stage methodology that involved performing genicular nerve block on cadaveric knees, acquiring data using high-resolution ultrasound and helical CT imaging, performing segmentation and surface reconstruction of the CT images, and analysing the data quantitively to determine the spread of the infiltrate in each genicular nerve region. Coefficients of variation were calculated to estimate the spread and reproducibility of each genicular nerve block. Results: Our results revealed significant variability in spread in all genicular nerve blocks, particularly around the recurrent genicular nerve. Despite this variability, the spread--particularly along the medial-lateral and anterior-posterior axes--showed moderate consistency. Furthermore, the regions covered by 80% of the spread closely matched the pericapsular distribution of the genicular nerves of the knee. Conclusions: Notable variability in spread was observed in genicular nerve blocks, particularly around the recurrent genicular nerve. However, the spread showed moderate consistency and aligns closely with the pericapsular nerve distribution of the knee. Future studies should combine quantitative analysis with anatomical dissection to further investigate the involvement of the deep peroneal motor branch. (c) 2024 Sociedad Espanola de Anestesiolog & imath;a, Reanimacion y Terapeutica del Dolor. Published by Elsevier Espana, S.L.U. All rights are reserved, including those for text and data mining, AI training, and similar technologies.