Validity of modulation and optimal settings for advanced voxel-based morphometry

• Published in: NeuroImage (Orlando, Fla.) Vol. 86; pp. 81 - 90
• Main Authors: Radua, Joaquim, Canales-Rodríguez, Erick Jorge, Pomarol-Clotet, Edith, Salvador, Raymond
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.02.2014; Elsevier; Elsevier Limited
• Subjects: Adult; Algorithms; Biological and medical sciences; Brain; Brain - cytology; Cluster-based statistics; Diffeomorphic registration; Female; Fundamental and applied biological sciences. Psychology; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Magnetic Resonance Imaging - methods; Male; Medical imaging; Modulation; Neurons - cytology; Normalization; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Studies; Threshold-free cluster enhancement; Vertebrates: nervous system and sense organs; Voxel-based morphometry; Normalization; Threshold-free cluster enhancement; Cluster-based statistics; Diffeomorphic registration; Modulation; Voxel-based morphometry; Morphometry
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2013.07.084

Voxel-based morphometry (VBM) is a widely-used structural neuroimaging technique for comparing meso- and macroscopic regional brain volumes between patients and controls in vivo, but some of its steps, particularly the modulation, lack an experimental validation. The aims of this study were two-fold: a) to assess the effects of modulation to detect mesoscopic (i.e. between microscopic and macroscopic) abnormalities on published, classic VBM; and b) to suggest a set of potentially optimal settings for detecting mesoscopic abnormalities with new, advanced, high-resolution diffeomorphic VBM normalization algorithms. Sensitivity and false positive rate after modulating or not in classic VBM using different software packages and spatial statistics, and after setting a range of different parameters in advanced VBM (ANTS-SyN), were calculated in 10 VBM comparisons of 32 altered vs. 32 unaltered gray matter images from different healthy controls. Simulated brain abnormalities comprised mesoscopic volume differences mainly due to cortical thinning. In classic VBM, modulation was associated with a substantial decrease of the sensitivity to detect mesoscopic abnormalities (p<0.001). Optimal settings for advanced VBM included the omission of modulation, the use of large smoothing kernels, and the application of voxel-based or threshold-free cluster enhancement (TFCE) spatial statistics. The modulation-related decrease in sensitivity was due to an increase in variance, and it was more severe in higher-resolution normalization algorithms. Findings from this study suggest the use of unmodulated VBM to detect mesoscopic abnormalities such as cortical thinning. •Modulation in voxel-based morphometry (VBM) has not been experimentally validated.•We assessed the effects of modulation on the efficacy to detect cortical thinning.•Ten VBM comparisons and different software packages and statistics were used.•Modulation was associated to a decrease of the sensitivity to detect abnormalities.•Optimal settings also included large smoothing and voxel-based or TFCE statistics.