clinicaltbx:MainPage

Introduction

This toolbox is useful for normalizing data from older adults (with a mean age around 65). It includes a new template and routines for normalizing CT scans. It provides a simple method for lesion-masked normalization of MRI scans (using either the default SPM template or a new older adult template).

click here to download the latest version (place the ‘Clinical’ folder inside SPM’s toolbox folder, an included manual describes the features).

Functions

CT Template

These templates and toolbox are still under peer review, and potential users should read the manual carefully. As with any normalization routine, results should always be inspected visually to ensure accurate performance. Here are the available functions.

MR segment normalize: this function uses SPM8′s unified segmentation normalization (Ashburner and Friston, 2005) with lesion cost function masking (Brett et al., 2001), as validated by Andersen et al. (2010). In our experience, this option provides the best performance, but does require images with good spatial resolution and tissue contrast. While it has been validated for high quality T1 scans, in theory it can work well for high resolution images in different modalities. CT normalize: this option uses SPM8′s normalization routines (Ashburner and Friston, 1999) to warp computerized axial tomography (CT, CAT) images to standard space. This procedure uses an invertible transform to adjust image contrast (as Hounsfield units have little range of contrast for soft tissue, though modern scans have good SNR in this range) and a custom CT template developed by Rorden et al. (submitted). MR normalize: this option uses SPM8′s normalization routines (Ashburner and Friston, 1999) to warp magnetic resonance imaging (MR, MRI) data to standard space using lesion cost function masking (Brett et al., 2001). This method is generally less accurate than “MR segment-normalize” in situations where high-quality images are available (Crinion et al., 2007). However, this method tends to be robust for many clinical modalities and spatial resolutions. The routine allows you to normalize to a T1 template, a T2 template, a FLAIR template, or ‘other’ modality (where both the T1 and T2 templates are used to infer intensity distributions). The FLAIR template is provided with permission by the Glahn group and described here

Citations

Stroke lesion normalized with the clinical toolbox

1. Andersen SM, Rapcsak SZ, Beeson PM. (2010) Cost function masking during normalization of brains with focal lesions: still a necessity? Neuroimage. 53: 78-84.
2. Ashburner J, Friston KJ. (1999) Nonlinear spatial normalization using basis functions. Hum. Brain Mapp. 7: 254–266.
3. Ashburner J, Friston KJ. (2005) Unified segmentation. NeuroImage 26: 839–851.
4. Brett M, Leff AP, Rorden C, Ashburner J. (2001) Spatial normalization of brain images with focal lesions using cost function masking. NeuroImage 14: 486–500.
5. Crinion J, Ashburner J, Leff A, Brett M, Price C, Friston K. (2007) Spatial normalization of lesioned brains: performance evaluation and impact on fMRI analyses. Neuroimage. 37: 866-75.
6. Nachev P, Coulthard E, Jäger HR, Kennard C, Husain M. (2008) Enantiomorphic normalization of focally lesioned brains. Neuroimage. 39(3):1215-26.
7. Rorden C, Bonilha L, Fridriksson J, Bender B, Karnath HO (2012) Age-specific CT and MRI templates for spatial normalization. NeuroImage. 61(4):957-65.