Comparison of piece-wise linear, linear, and nonlinear atlas-to-patient warping techniques: analysis of the labeling of subcortical nuclei for functional neurosurgical applications

Abstract

Digital atlases are commonly used in pre-operative planning in functional neurosurgical procedures performed to minimize the symptoms of Parkinson's disease. These atlases can be customized to fit an individual patient's anatomy through atlas-to-patient warping procedures. Once fitted to pre-operative magnetic resonance imaging (MRI) data, the customized atlas can be used to plan and navigate surgical procedures. Linear, piece-wise linear and nonlinear registration methods have been used to customize different digital atlases with varying accuracies. Our goal was to evaluate eight different registration methods for atlas-to-patient customization of a new digital atlas of the basal ganglia and thalamus to demonstrate the value of nonlinear registration for automated atlas-based subcortical target identification in functional neurosurgery. In this work, we evaluate the accuracy of two automated linear techniques, two piece-wise linear techniques (requiring the identification of manually placed anatomical landmarks), and four different automated nonlinear atlas-to-patient warping techniques (where two of the four nonlinear techniques are variants of the ANIMAL algorithm). Since a gold standard of the subcortical anatomy is not available, manual segmentations of the striatum, globus pallidus, and thalamus are used to derive a silver standard for evaluation. Four different metrics, including the kappa statistic, the mean distance between the surfaces, the maximum distance between surfaces, and the total structure volume are used to compare the warping techniques. The results show that nonlinear techniques perform statistically better than linear and piece-wise linear techniques. In addition, the results demonstrate statistically significant differences between the nonlinear techniques, with the ANIMAL algorithm yielding better results.

Figure 1

Example of pre‐operative MRI volume with headframe affixed to patient. Left: Sagittal view. Middle: Coronal view. Right: Axial view. Image volume shows lack of contrast in the subcortical nuclei. Surgical targeting is extremely difficult in these nuclei as a result. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 2

Coronal and axial representation of the atlas described in Atlas of the Basal Ganglia and Thalamus. A: Original coronal section from the histological dataset. B: Reconstructed transverse slice through the histological volume. C, D: Voxel‐label atlas representation of the atlas. E, F: Pseudo‐MRI representation of the atlas. G, H: Close‐up of the Colin27 MRI template in the region of the basal ganglia and thalamus. I–K: Coronal, sagittal, and axial views of the atlas warped to fit the Colin27 template. L: The geometric representation of the atlas that can be manipulated in 3D.

Figure 3

Left: The Talairach definition of the AC–PC line. Also shown are the divisions anteriorly and posteriorly and in the superior–inferior directions. Right: The 12 regions defined by the Talairach proportional grid system. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 4

Results of the atlas warping. From top to bottom: Original data unlabeled, result from the data labeled by the five manual raters, results from the linear (LSQ9, LSQ12) and piece‐wise linear (PFA, Talairach) atlas warping, and results from the nonlinear atlas warping (SPM, Romeo, ANIMAL‐1, ANIMAL‐2).

Figure 5

Summary of results from all metrics. From top to bottom: kappa, mean chamfer distance, maximum chamfer distance, and volume results for all methods tested for the globus pallidus (red), striatum (green), and thalamus (blue). Extents of each box represent the standard deviation and error bars represent the range of the data. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]