Quantitative MRI of Perivascular Spaces at 3T for Early Diagnosis of Mild Cognitive Impairment

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The authors automated the identification of enlarged perivascular spaces in brain MR images using a custom quantitative program designed with Matlab. They quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n=14) and age-matched cognitively healthy controls (n=15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis. The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects.

Abstract

BACKGROUND AND PURPOSE

Early Diagnosis of Mild Cognitive Impairment
Representative multislice MIP projections of EPVS in the subcortical brain structures and the basal ganglia of a control and a subject with aMCI. A, MIP image of subcortical structures within the middle of the brain of a control subject. B, The MIP image of subcortical structures within the middle of the brain of a subject with aMCI. C, MIP image of the basal ganglia of a control subject. D, MIP image of the basal ganglia of a subject with aMCI.

The limitations inherent in the current methods of diagnosing mild cognitive impairment have constrained the use of early therapeutic interventions to delay the progression of mild cognitive impairment to dementia. This study evaluated whether quantifying enlarged perivascular spaces observed on MR imaging can help differentiate those with mild cognitive impairment from cognitively healthy controls and, thus, have an application in the diagnosis of mild cognitive impairment.

MATERIALS AND METHODS

We automated the identification of enlarged perivascular spaces in brain MR Images using a custom quantitative program designed with Matlab. We then quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n = 14) and age-matched cognitively healthy controls (n = 15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis.

RESULTS

Quantified as a percentage of volume fraction (v/v%), densities of enlarged perivascular spaces were calculated to be 2.82 ± 0.40 v/v% for controls and 4.17 ± 0.57 v/v% for the mild cognitive impairment group in the subcortical brain (P < .001), and 2.74 ± 0.57 v/v% for the controls and 3.90 ± 0.62 v/v% for the mild cognitive impairment cohort in the basal ganglia (P < .001). Maximum intensity projections exhibited a visually conspicuous difference in the distributions of enlarged perivascular spaces for a patient with mild cognitive impairment and a control patient. By means of receiver operating characteristic curve analysis, we determined the sensitivity and specificity of using enlarged perivascular spaces as a differentiating biomarker between mild cognitive impairment and controls to be 92.86% and 93.33%, respectively.

CONCLUSIONS

The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects. The density of enlarged perivascular spaces, therefore, may be a useful imaging biomarker for the diagnosis of mild cognitive impairment.

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Quantitative MRI of Perivascular Spaces at 3T for Early Diagnosis of Mild Cognitive Impairment
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Jeffrey Ross
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