The Effect of Using Ultrasonography Device Integrated with Artificial Intelligence on Imaging the Injection Area in Peripheral Nerve Block Applications

Abstract

Objective: New devices and software have brought about benefits such as easing the burden of clinicians, preventing time losses and increasing their professional satisfaction. In this study, we aimed to present the effect of the use of artificial intelligence integrated ultrasonography (USG) on the imaging of the injection site in peripheral nerve block applications and the point of view of the clinicians. Methods: In the study, following ethics committee’s approval, 40 volunteer Anesthesiology and Reanimation doctors working in Health Sciences University Dışkapı Yıldırım Beyazıt Education and Training Hospital performed selected regional blocks (infraclavicular and PECS) accompanied by conventional USG and artificial intelligence integrated-USG (Nerveblox), and the block area imaging times were recorded. Subsequently, questionnaires about these experiences were distributed and 14 closed-ended questions were asked. In the comparison made according to the physicians’ imaging times of the determined block areas, the t test for independent samples was used, and the statistical significance level was established as p<0.001. Results: There is a significant difference in favor of the use of artificial intelligence integrated-USG in the comparison of the time taken by the physicians participating in the survey to find infraclavicular and PECS blocks reference area with conventional and artificial intelligence integrated-USG (p<0.001). Conclusion: It has been proven in our study that artificial intelligence algorithms will continue to increase and will be one of the important components of diagnostic USG in the coming years. Keywords: Peripheral nerve blocks, ultrasonography, artificial intelligence