Lesion Explorer: a comprehensive segmentation and parcellation package to obtain regional volumetrics for subcortical hyperintensities and intracranial tissue.

Subcortical hyperintensities (SH) are a commonly observed phenomenon on MRI of the aging brain (Kertesz et al., 1988). Conflicting behavioral, cognitive and pathological associations reported in the literature underline the need to develop an intracranial volumetric analysis technique to elucidate pathophysiological origins of SH in Alzheimer's disease (AD), vascular cognitive impairment (VCI) and normal aging (De Leeuw et al., 2001; Mayer and Kier, 1991; Pantoni and Garcia, 1997; Sachdev et al., 2008). The challenge is to develop processing tools that effectively and reliably quantify subcortical small vessel disease in the context of brain tissue compartments. Segmentation and brain region parcellation should account for SH subtypes which are often classified as: periventricular (pvSH) and deep white (dwSH), incidental white matter disease or lacunar infarcts and Virchow-Robin spaces. Lesion Explorer (LE) was developed as the final component of a comprehensive volumetric segmentation and parcellation image processing stream built upon previously published methods (Dade et al., 2004; Kovacevic et al., 2002). Inter-rater and inter-method reliability was accomplished both globally and regionally. Volumetric analysis showed high inter-rater reliability both globally (ICC=.99) and regionally (ICC=.98). Pixel-wise spatial congruence was also high (SI=.97). Whole brain pvSH volumes yielded high inter-rater reliability (ICC=.99). Volumetric analysis against an alternative kNN segmentation revealed high inter-method reliability (ICC=.97). Comparison with visual rating scales showed high significant correlations (ARWMC: r=.86; CHIPS: r=.87). The pipeline yields a comprehensive and reliable individualized volumetric profile for subcortical vasculopathy that includes regionalized (26 brain regions) measures for: GM, WM, sCSF, vCSF, lacunar and non-lacunar pvSH and dwSH.

Visual rating versus volumetry to detect frontotemporal dementia.

BACKGROUND/AIMS: Automated, volumetrically defined atrophy in the left anterior cingulate (LAC) and anterior temporal regions (LAT) on MRI can be used to distinguish most patients with frontotemporal dementia (FTD) from controls. FTD and Alzheimer's disease (AD) can differ in the degree of anterior temporal atrophy. We explored whether clinicians can visually detect this atrophy pattern and whether they can use it to classify the 2 groups of dementia patients with the same accuracy. METHODS: Four neurologists rated atrophy in the LAC and LAT regions on MRI slices from 21 FTD, 21 controls, and 14 AD participants. Inter-rater reliability and diagnostic accuracy were assessed. RESULTS: All 4 raters agreed on the presence of clinically significant atrophy, and their atrophy scoring correlated with the volumes, but without translation into high inter-rater diagnostic agreement. CONCLUSIONS: Volumetric analyses are difficult to translate into routine clinical practice.

Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients.

Depression is common in patients with multiple sclerosis, but to date no studies have explored diffusion tensor imaging indices associated with mood change. This study aimed to determine cerebral correlates of depression in multiple sclerosis patients using diffusion tensor imaging. Sixty-two subjects with multiple sclerosis were assessed for depression with the Beck Depression Inventory (BDI-II). All subjects underwent magnetic resonance imaging. Whole brain and regional volumes were calculated for lesions (hyper/hypointense) and normal-appearing white and grey matter. Fractional anisotropy and mean diffusivity were calculated for each brain region. Magnetic resonance imaging comparisons were undertaken between depressed (Beck Depression Inventory > or = 19) and non-depressed subjects. Depressed subjects (n = 30) had a higher hypointense lesion volume in the right medial inferior frontal region, a smaller normal-appearing white matter volume in the left superior frontal region, and lower fractional anisotropy and higher mean diffusivity in the left anterior temporal normal-appearing white matter and normal-appearing grey matter regions, respectively. Depressed subjects also had higher mean diffusivity in right inferior frontal hyperintense lesions. Magnetic resonance imaging variables contributed to 43% of the depression variance. We conclude that the presence of more marked diffusion tensor imaging abnormalities in the normal-appearing white matter and normal-appearing grey matter of depressed subjects highlights the importance of more subtle measures of structural brain change in the pathogenesis of depression.