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Schifitto, G.

Publications and source records attributed to Schifitto, G..

3 recordsLinked to original sources

Brain Iron Imaging Markers in the Presence of White Matter Hyperintensities

PurposeTo investigate the relationship between pathological brain iron deposition and white matter hyperintensities (WMHs) in cerebral small vessel disease (CSVD), via Monte Carlo simulations of magnetic susceptibility imaging and a novel imaging marker called the Expected Iron Coefficient (EIC). MethodsA synthetic pathological model of a different number of impenetrable spheres at random locations was employed to represent pathological iron deposition. The diffusion process was simulated with a Monte Carlo method with adjustable parameters to manipulate sphere size, distribution, and extracellular properties. Quantitative susceptibility mapping (QSM) was performed in a clinical dataset to study CSVD to derive and evaluate QSM, R2*, the iron microenvironment coefficient (IMC), and EIC in the presence of WMHs. ResultsThe simulations show that QSM signals increase in the presence of increased tissue iron, confirming that the EIC increases with pathology. Clinical results demonstrate that while QSM, R2*, and the IMC do not show differences in brain iron, the EIC does in the context of CSVD. ConclusionThe EIC is more sensitive to subtle changes in brain iron deposition caused by pathology, even when QSM, R2*, and the IMC do not.

pathology

Increased Risk for Cerebral Small Vessel Disease is Associated with Quantitative Susceptibility Mapping in HIV Infected and Uninfected Individuals

The aim of this study was to assess in the context of cerebral small vessel disease (CSVD), cardiovascular risk factors and white matter hyperintensities (WMHs) were associated with brain tissue susceptibility as measured by quantitative susceptibility mapping (QSM). Given that CSVD is diagnosed by the presence of lacunar strokes, periventricular and deep WMHs, increased perivascular spaces, and microbleeds, we expected that QSM could capture changes in brain tissue due to underlying CSVD pathology. We compared a cohort of 101 HIV-infected individuals (mean age (SD) = 53.2 (10.9) years) with mild to moderate cardiovascular risk scores, as measured by the Reynolds risk score, to 102 age-matched controls (mean age (SD) = 50.3 (15.7) years) with similar Reynold scores. We performed brain MRI to assess CSVD burden by acquiring 3D T1-MPRAGE, 3D FLAIR, 2D T2-TSE, and mGRE for QSM. We found that signs of CSVD are significantly higher in individuals with HIV-infection compared to controls and that WMH volumes are significantly correlated with age and cardiovascular risk scores. Regional QSM was associated with cardiovascular risk factors, age, sex, and WMH volumes but not HIV status. These results suggest that QSM may be an early imaging marker reflective of alterations in brain microcirculation.

pathology

Surface-Based Connectivity Integration

There has been increasing interest in jointly studying structural connectivity (SC) and functional connectivity (FC) derived from diffusion and functional MRI. However, several fundamental problems are still not well considered when conducting such connectome integration analyses, e.g., "Which structure (e.g., gray matter, white matter, white surface or pial surface) should be used for defining SC and FC and exploring their relationships", "Which brain parcellation should be used", and "How do the SC and FC correlate with each other and how do such correlations vary in different locations of the brain?". In this work, we develop a new framework called surface-based connectivity integration (SBCI) to facilitate the integrative analysis of SC and FC with a re-thinking of these problems. We propose to use the white surface (the interface of white matter and gray matter) to build both SC and FC since diffusion signals are in the white matter while functional signals are more present in the gray matter. SBCI also represents both SC and FC in a continuous manner at very high spatial resolution on the white surface, avoiding the need of pre-specified atlases which may bias the comparison of SC and FC. Using data from the Human Connectome Project, we show that SBCI can create reproducible, high quality SC and FC, in addition to three novel imaging biomarkers reflective of the similarity between SC and FC throughout the brain, called global, local, and discrete SC-FC coupling. Further, we demonstrate the usefulness of these biomarkers in finding group effects due to biological sex throughout the brain.

neuroscience