Regional impact of field strength on voxel‐based morphometry results

Abstract

The objective of this study was to characterize the sensitivity of voxel-based morphometry (VBM) results to choice field strength. We chose to investigate the two most widespread acquisition sequences for VBM, FLASH and MP-RAGE, at 1.5 and 3 T. We first evaluated image quality of the four acquisition protocols in terms of SNR and image uniformity. We then performed a VBM study on eight subjects scanned twice using the four protocols to evaluate differences in grey matter (GM) density and corresponding scan-rescan variability, and a power analysis for each protocol in the context a longitudinal and cross-sectional VBM study. As expected, the SNR increased significantly at 3 T for both FLASH and MP-RAGE. Image non-uniformity increased as well, in particular for MP-RAGE. The differences in CNR and contrast non-uniformity cause regional biases between protocols in the VBM results, in particular between sequences at 3 T. The power analysis results show an overall decrease in the number of subjects required in a longitudinal study to detect a difference in GM density at 3 T for MP-RAGE, but an increase for FLASH. The number of subjects required in a cross-sectional VBM study is higher at 3 T for both sequences. Our results show that each protocol has a distinct regional sensitivity pattern to morphometric change, which goes against the classical view of VBM as an unbiased whole brain analysis technique, complicates the combination of data within a VBM study and the direct comparison of VBM studies based on different protocols.

Power estimation for non-standardized multisite studies

“…For a given region of interest (ROI), two mechanisms simultaneously impact the final boundary definition: (1) gradient nonlinearities cause distortion and (2) hardware (including scanner, field strength, and coils) and acquisition parameters modulate tissue contrast. Based on the results of Tardiff and colleagues, who found that contrast-to-noise ratio and contrast inhomogeneity from various pulse sequences and scanner strengths cause regional biases in VBM[11, 12], we hypothesized that each ROI will scale differently at each site. Evidence for this scaling property can also be seen in the overall increase of gray matter volume and decrease of white matter volume of the ADNI-2 compared to the ADNI-1 protocols despite attempts to maintain compatibility between these protocols [13].…”

An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry

“…All the OASIS images included in this study were acquired on the same scanner with identical imaging parameters, thus preventing possible systematic variations in the image acquisition system to be erroneously interpreted as group variations (Good et al, 2001b; Mechelli et al, 2005; Tardif et al, 2010). In particular, it has been shown that the acquisition protocol and the magnetic field strength have a substantial impact on the image quality characteristics that in turn affect the sensitivity and specificity of VBM measures (Tardif et al, 2010).…”

“…In particular, it has been shown that the acquisition protocol and the magnetic field strength have a substantial impact on the image quality characteristics that in turn affect the sensitivity and specificity of VBM measures (Tardif et al, 2010). Although not tested, we have no reason to believe that our automatic framework cannot be applied for validating the accuracy of VBM measures of brain asymmetry for a 3 T image acquisition system.…”

Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review

“…To author's knowledge, gray matter probability and gray matter PV-coefficient based VBM methods have not been directly compared. Tardif et al [48] examined two pipelines resulting in GM probability based VBM and PVC based VBM but the main focus of the work was on a comparison of 1.5T and 3T imaging protocols. The VBM8 software package (http://dbm.…”