The utility of customised tissue probability maps and templates for patients with idiopathic normal pressure hydrocephalus: a computational anatomy toolbox (CAT12) study

Abstract

Background: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is one of the neuroradiological characteristics of idiopathic normal pressure hydrocephalus (iNPH), which makes statistical analyses of brain images difficult. This study aimed to develop and validate methods of accurate brain segmentation and spatial normalisation in patients with DESH by using the Computational Anatomy Toolbox (CAT12).

Methods: Two hundred ninety-eight iNPH patients with DESH and 25 healthy controls (HCs) who underwent cranial MRI were enrolled in this study. We selected the structural images of 169 patients to create customised tissue probability maps and diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) templates for patients with DESH (DESH-TPM and DESH-Template). The structural images of 38 other patients were used to evaluate the validity of the DESH-TPM and DESH-Template. DESH-TPM and DESH-Template were created using the 114 well-segmented images after the segmentation processing of CAT12. In the validation study, we compared the accuracy of brain segmentation and spatial normalisation among three conditions: customised condition, applying DESH-TPM and DESH-Template to CAT12 and patient images; standard condition, applying the default setting of CAT12 to patient images; and reference condition, applying the default setting of CAT12 to HC images.

Results: In the validation study, we identified three error types during segmentation. (1) The proportions of misidentifying the dura and/or extradural structures as brain structures in the customised, standard, and reference conditions were 10.5%, 44.7%, and 13.6%, respectively; (2) the failure rates of white matter hypointensity (WMH) cancellation in the customised, standard, and reference conditions were 18.4%, 44.7%, and 0%, respectively; and (3) the proportions of cerebrospinal fluid (CSF)-image deficits in the customised, standard, and reference conditions were 97.4%, 84.2%, and 28%, respectively. The spatial normalisation accuracy of grey and white matter images in the customised condition was the highest among the three conditions, especially in terms of superior convexity.

Conclusions: Applying the combination of the DESH-TPM and DESH-Template to CAT12 could improve the accuracy of grey and white matter segmentation and spatial normalisation in patients with DESH. However, this combination could not improve the CSF segmentation accuracy. Another approach is needed to overcome this challenge.

Keywords: Brain tissue segmentation; CAT12 = computational anatomy toolbox; DESH = disproportionately enlarged subarachnoid space hydrocephalus; INPH = idiopathic normal pressure hydrocephalus; Spatial normalisation; Template.

Fig. 1

Flow chart of the process of creating the DESH-TPM and DESH-Template CSF: cerebrospinal fluid; DESH: disproportionately enlarged subarachnoid space hydrocephalus; and TPM: tissue probability map

Fig. 2

DESH-TPM and SPM12-TPM. a DESH-TPM. b SPM12-TPM. Red area: grey matter; yellow area: white matter; blue area: CSF; white area: bone; and yellow–green area: soft tissues. DESH disproportionately enlarged subarachnoid space hydrocephalus, SPM12 statistical parametric mapping 12, TPM tissue probability map

Fig. 3

Error types of brain image segmentation in each condition. a demonstrates the misidentification of dural and extradural structures as the grey or white matter or CSF in the superior convexity (yellow arrowhead) and the CSF image deficits in the infratentorial region (white arrowhead). The segmented CSF images are coloured light blue. b shows the misidentification of dura as the grey or white matter in the posterior cranium (red arrowhead). This type of error was observed in all conditions. c demonstrates the errors of WMH cancellation. The errors in the periventricular white matter were frequently observed in the standard condition (yellow green arrowhead). Errors in the frontal subcortical white matter were identified in both the customised and standard conditions (pink arrowhead). d shows the CSF image deficits in the superior convexity and Sylvian fissures (light blue arrowhead). The segmented CSF images are coloured light blue. The CSF image deficits in the superior convexity were observed in all conditions. CSF image deficits in the Sylvian fissures were not identified; only in the reference condition

Fig. 4

Overlapped maps of normalised grey and white matter images in three conditions. a shows the overlapped normalised grey matter image. b shows the overlapped normalised white matter image. Coloured maps demonstrate the overlap rates of each structural images outside the voxels of which probability values were above 0.5 in each structural template, which indicates the magnitude of spatial normalisation inaccuracy