Optimized Intraoperative Imaging for Stereotactic Planning with a Multiaxial Robotic C-arm System: Technical Note and Case Series

Abstract

Background The preoperative preparation of the planning dataset for frame-based stereotactic brain biopsy is often associated with logistical effort and burden on the patient. Intraoperative imaging modalities need to be investigated to overcome these limitations.

Objective The objective of the study was to develop and apply a new method for the intraoperative acquisition of the planning dataset with the multiaxial robotic C-arm system Artis zeego.

Methods An indication-customized dose-reduced protocol for Artis zeego was developed and implemented into the workflow. A sample of 14 patients who had undergone intraoperative imaging with Artis zeego was analyzed. A sample of 10 patients with conventional preoperative imaging by cranial computed tomography (CT) was used as a control group. Outcomes were compared with regard to target deviation, diagnostic value of the biopsies, complications, and procedure time.

Results In all patients, a suitable intraoperative planning dataset could be acquired with Artis zeego. Total procedure time was shorter for the Artis zeego group (p = 0.01), whereas time in the operating room area was longer in the Artis zeego group (p = 0.04). Biopsy results were diagnostic in 12 patients (86%) in the Artis zeego group and in 8 patients (80%) in the control group. There were no significant differences in target size, trajectory length, or target deviation.

Conclusion Intraoperative imaging for frame-based stereotactic brain biopsy with Artis zeego is an easy and feasible method. Accuracy is comparable to conventional CT, whereas radiation exposure could be additionally reduced. It allows a significant reduction of the total procedure length and improves the comfort for the patient and staff.

Keywords

intraoperative imaging - stereotactic biopsy - workflow - cone beam CT

Publication History

Received: 21 August 2020

Accepted: 21 January 2021

Article published online:
15 November 2021

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