Background: In deep brain stimulation (DBS) for Parkinson's disease (PD), the clinical outcome largely depends on the appropriate position of the electrode implanted in the targeted structure. In intraoperative cone-beam computed tomography (CT) performed for the evaluation of the electrode position, the metal artifact induced by the implanted electrode can prevent the precise localization of the electrode. Metal artifact reduction (MAR) techniques have been recently developed that can dramatically improve the visualization of objects by reducing metal artifacts after performing cone-beam CT. Hence, in this case series, we attempted to clarify the usefulness and accuracy of intraoperative cone-beam CT with MAR (intraCBCTwM) by comparing with both intraoperative cone-beam CT without MAR (intraCBCTwoM) and conventional postoperative CT (post-CT) for the assessment of the implanted electrode position and the intracranial structures during DBS procedures.
Methods: Between November 2019 and December 2020, 10 patients with PD who underwent DBS at our institution were recruited, and the images of 9 patients (bilateral: n = 8, unilateral: n = 1) were analyzed. The artifact index (AI) in intraCBCTwM or intraCBCTwoM, and conventional post-CT were retrospectively assessed using the standard deviation of the region-of-interest around the implanted electrodes and background noise. Additionally, the Euclidean distances gap of electrode tip based on post-CT in each fusion image was compared between intraCBCTwM and intraCBCTwoM.
Results: The AI was significantly lower in intraCBCTwM than in intraCBCTwoM (P < 0.01). The mean Euclidean distance between the tip of the electrode in intraCBCTwM and in post-CT was significantly shorter compared to that in intraCBCTwoM (P < 0.05).
Conclusions: The results reported here suggest that intraCBCTwM is a more useful and accurate method than intraCBCTwoM to assess the implanted electrode position and intracranial structures during DBS.
Keywords: Cone-beam CT; Deep brain stimulation; Metal artifact.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.