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. 2024 Nov 18;24(22):7341.
doi: 10.3390/s24227341.

Automatic Image Registration Provides Superior Accuracy Compared with Surface Matching in Cranial Navigation

Henrik Frisk  1   2 , Margret Jensdottir  1   2 , Luisa Coronado  3 , Markus Conrad  3 , Susanne Hager  3 , Lisa Arvidsson  1   2 , Jiri Bartek Jr  1   2 , Gustav Burström  1   2 , Victor Gabriel El-Hajj  1 , Erik Edström  1   4 , Adrian Elmi-Terander  1   4   5 , Oscar Persson  1   2
Affiliations

Automatic Image Registration Provides Superior Accuracy Compared with Surface Matching in Cranial Navigation

Henrik Frisk et al. Sensors (Basel). .

Abstract

Objective: The precision of neuronavigation systems relies on the correct registration of the patient's position in space and aligning it with radiological 3D imaging data. Registration is usually performed by the acquisition of anatomical landmarks or surface matching based on facial features. Another possibility is automatic image registration using intraoperative imaging. This could provide better accuracy, especially in rotated or prone positions where the other methods may be difficult to perform. The aim of this study was to validate automatic image registration (AIR) using intraoperative cone-beam computed tomography (CBCT) for cranial neurosurgical procedures and compare the registration accuracy to the traditional surface matching (SM) registration method based on preoperative MRI. The preservation of navigation accuracy throughout the surgery was also investigated.

Methods: Adult patients undergoing intracranial tumor surgery were enrolled after consent. A standard SM registration was performed, and reference points were acquired. An AIR was then performed, and the same reference points were acquired again. Accuracy was calculated based on the referenced and acquired coordinates of the points for each registration method. The reference points were acquired before and after draping and at the end of the procedure to assess the persistency of accuracy.

Results: In total, 22 patients were included. The mean accuracy was 6.6 ± 3.1 mm for SM registration and 1.0 ± 0.3 mm for AIR. The AIR was superior to the SM registration (p < 0.0001), with a mean improvement in accuracy of 5.58 mm (3.71-7.44 mm 99% CI). The mean accuracy for the AIR registration pre-drape was 1.0 ± 0.3 mm. The corresponding accuracies post-drape and post-resection were 2.9 ± 4.6 mm and 4.1 ± 4.9 mm, respectively. Although a loss of accuracy was identified between the preoperative and end-of-procedure measurements, there was no statistically significant decline during surgery.

Conclusions: AIR for cranial neuronavigation consistently delivered greater accuracy than SM and should be considered the new gold standard for patient registration in cranial neuronavigation. If intraoperative imaging is a limited resource, AIR should be prioritized in rotated or prone position procedures, where the benefits are the greatest.

Keywords: CBCT; accuracy; automatic image registration; neurosurgery; patient tracking; reference frame; surface matching; surgical navigation.

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Conflict of interest statement

None of the authors who are affiliated with clinical institutions (H.F., M.J., L.A., J.B.J., G.B., V.G.E.-H., E.E., A.E.-T. and O.P.) have financial interests in the subject matter, materials, or equipment or with any competing materials and did not receive any payments from Brainlab. A.E.-T. was a consultant for Brainlab during the data collection and until September 2022, when the consultancy was terminated. The other authors affiliated with Brainlab (L.C., M.C. and S.H.) have financial interests in the subject matter, materials, and equipment in the sense that they are employees of Brainlab. The extent of influence on the data, manuscript structure, and manuscript conclusions by these authors and/or Brainlab was limited to technical knowledge and support for the experiments as well as performing technical analysis of image data. Authors without conflicts of interest had full control of all data labeling, data analysis, information submitted for publication, and the overall conclusions drawn in the manuscript.

Figures

Figure 1
Figure 1
(A) Intraoperative setup with positioning of DRF, Universal AIR, and C-arm with patient in radiolucent head clamp. (B) Universal AIR matrix. (C) Schematic illustration of the scan volume with the Universal AIR radio-opaque markers included in the scan volume of the head.
Figure 2
Figure 2
Defining the screw head reference points at the center of the slit cross hairs on 3D reconstructed CBCT imaging data. Small picture shows close-up of screw head.
Figure 3
Figure 3
TRE calculated as mean of the difference between the acquired points using surface matching (SM) or automatic image registration (AIR) compared with the reference points for the four screws from the CBCT.
Figure 4
Figure 4
Mean difference of the calculated deviations at the four screws between AIR pre-drape and SM pre-drape registrations.
Figure 5
Figure 5
Boxplots of TRE calculated as mean of the difference between the acquired points at screw heads compared with the reference points for the four screws from the CBCT.
Figure 6
Figure 6
Boxplots of TRE of SM registration grouped by patient positioning.
Figure 7
Figure 7
Heatmap showing skin surface deformation between the preoperative MRI used for surface match registration and the intraoperative CBCT for two patients (ID19 and 20).
Figure 8
Figure 8
Boxplots of the TRE of the SM registration based on preoperative MRI compared with post hoc recalculated surface matching based on 3D reconstruction of the intraoperative CBCT.
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