Voxel-based morphometry: current perspectives

Abstract

Voxel-based morphometry (VBM) is a widely used automated technique for the analysis of neuroanatomical images. This work, which reviews important VBM clinical findings of the last few years, is divided into two main sections. After briefly introducing VBM methodology, in the first part, VBM findings on neurological and psychiatric diseases have been discussed separately. The reported studies were divided into studies that examine the diagnostic value of VBM results and their usefulness for the differential diagnosis between two disorders; studies investigating the potential of VBM for the diagnosis in an early stage of the illness, and studies that examine the utility of VBM for predicting the transition from prodromal phase to full-blown disease. In the second part, this review focuses on the most recent findings on the single-case approach. This analysis is useful for promoting the translational impact of VBM results in clinical practice, where clinicians need to make inferences at the level of the individual patient. Finally, within the single-case approach, a paragraph is dedicated to the potential forensic applications of VBM. Indeed, if used to support and integrate results obtained with classical forensic evaluations, VBM may provide objective data that could be used to reduce controversy in forensic psychiatric evaluations of mental insanity. In this second part, particular emphasis is given to the problem of results interpretation, which should be based mainly on the presence of anatomoclinical correlation. The review finishes with a provocative note reporting an interesting result of a single-case VBM analysis that highlights the risk to fall into the "reverse inference" reasoning. This example has been chosen because it effectively highlights the risks that are encountered when this technique is inappropriately used.

Neurostructural correlates of optimism: Gray matter density in the putamen predicts dispositional optimism in late adolescence

“…To achieve these goals, we performed S-MRI scans on participants and assessed their levels of dispositional optimism and extraversion with standard measures. Here, the brain GM structure was estimated using a VBM method (Ashburner & Friston, 2001;Scarpazza & De Simone, 2016). Specifically, we used a VBM approach to assess regional GM density/concentration (rGMD, i.e., the proportion of GM relative to other tissue types in a brain region; Mechelli, Price, Friston, & Ashburner, 2005) as this index is frequently used in developmental studies because maturational changes in GMD in some brain regions (e.g., the frontal and striatum regions) occur at a certain age (Gogtay et al, 2004;Paus, 2005;Sowell et al, 2003;Sowell, Thompson, Tessner, & Toga, 2001), and this index is also often adopted to detect the GM correlates of a personality trait (Omura, Todd Constable, & Canli, 2005;Takeuchi et al, 2011Takeuchi et al, , 2014.…”

The charm of structural neuroimaging in insanity evaluations: guidelines to avoid misinterpretation of the findings

“…As additional premises, we would like to underline that (i) this paper is focused on the use of structural images only. The introduction of functional images is further complicated by high between-subject variability in the blood oxygenation level-dependent (BOLD) signal, the ecological validity of task performance 43 and the absence of false-positive distribution maps that can guide result interpretation (this map is available for sNI 4 , 5 ). Thus, the potential application of functional imaging is a topic that falls outside the aims of the current paper.…”

Changing landscapes in the neuroimaging of dementia

“…In the behavioral variant of frontotemporal lobar degeneration, the gray matter loss will be more in the orbitofrontal cortex, inferior frontal gyrus, and the anterior cingulate cortex. [ 9 ]…”