Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases

Abstract

Object: Fiducial-based registration (FBR) is used widely for patient registration in image-guided neurosurgery. The authors of this study have developed an automatic fiducial-less registration (FLR) technique to find the patient-to-image transformation by directly registering 3D ultrasound (3DUS) with MR images without incorporating prior information. The purpose of the study was to evaluate the performance of the FLR technique when used prospectively in the operating room and to compare it with conventional FBR.

Methods: In 32 surgical patients who underwent conventional FBR, preoperative T1-weighted MR images (pMR) with attached fiducial markers were acquired prior to surgery. After craniotomy but before dural opening, a set of 3DUS images of the brain volume was acquired. A 2-step registration process was executed immediately after image acquisition: 1) the cortical surfaces from pMR and 3DUS were segmented, and a multistart sum-of-squared-intensity-difference registration was executed to find an initial alignment between down-sampled binary pMR and 3DUS volumes; and 2) the alignment was further refined by a mutual information-based registration between full-resolution grayscale pMR and 3DUS images, and a patient-to-image transformation was subsequently extracted.

Results: To assess the accuracy of the FLR technique, the following were quantified: 1) the fiducial distance error (FDE); and 2) the target registration error (TRE) at anterior commissure and posterior commissure locations; these were compared with conventional FBR. The results showed that although the average FDE (6.42 ± 2.05 mm) was higher than the fiducial registration error (FRE) from FBR (3.42 ± 1.37 mm), the overall TRE of FLR (2.51 ± 0.93 mm) was lower than that of FBR (5.48 ± 1.81 mm). The results agreed with the intent of the 2 registration techniques: FBR is designed to minimize the FRE, whereas FLR is designed to optimize feature alignment and hence minimize TRE. The overall computational cost of FLR was approximately 4-5 minutes and minimal user interaction was required.

Conclusions: Because the FLR method directly registers 3DUS with MR by matching internal image features, it proved to be more accurate than FBR in terms of TRE in the 32 patients evaluated in this study. The overall efficiency of FLR in terms of the time and personnel involved is also improved relative to FBR in the operating room, and the method does not require additional image scans immediately prior to surgery. The performance of FLR and these results suggest potential for broad clinical application.

Keywords: 3DUS = 3D ultrasound; 3DUS-MR registration; AC = anterior commissure; FBR = fiducial-based registration; FDE = fiducial distance error; FLR = fiducial-less registration; FRE = fiducial registration error; OR = operating room; PC = posterior commissure; SBR = surface-based registration; TRE = target registration error; diagnostic and operative techniques; image-guided neurosurgery; pMR = preoperative MR images; patient registration; volumetric 3D ultrasound.

FIG. 1

FLRs from Cases 1, 16, and 24. A: Binary registration of cortical surfaces from down-sampled MR (red) and resliced US (green). B: Overlay of MR and US after binary registration. C: Overlay of MR and US after grayscale registration. Figure is available in color online only.

FIG. 2

Identification of AC (A and B) and PC (C and D) in MR and 3DUS independently. Magenta, blue, and cyan lines represent the coronal, axial, and sagittal cross-sections at the point of interest, respectively. Figure is available in color online only.

FIG. 3

Comparison of fiducial-less FDE (mean) with fiducial-based FRE (mean) for the 32 patients. The mean FDE (red crosses) and FRE (blue empty circles) for each patient are plotted (left), and a boxplot of these data is shown (right). Figure is available in color online only.

FIG. 4

Visual comparison of FLR (upper row) and FBR (lower row) for Cases 1, 16, and 24 by overlaying US (green) with MR (red) images. White arrows point to examples of internal features that are well aligned with FLR but misaligned with FBR. Figure is available in color online only.

FIG. 5

Comparison of TRE from FBR and FLR of the AC and PC for the 32 cases. Left: Image showing 3 plots—the TRE at AC, PC, and the overall TRE that combines both targets, respectively, where blue empty circles represent data from FBR, and red crosses represent data from FLR. Right: The corresponding boxplot. Figure is available in color online only.

FIG. 6

Example of visual assessment of accuracy by overlaying pMR (red) with different 3DUS images (green). FLR was performed based on panel A, and panels B and C were acquired immediately after A but with different scan-head positions. White arrows designate features that are well aligned in all 3 US acquisitions coregistered with FLR based only on panel A. Figure is available in color online only.