Biology subjects

Schifitto, G.

Publications and source records attributed to Schifitto, G..

7 recordsLinked to original sources

bioRxiv2026

Anatomically Guided Deep Learning Reconstruction of Accelerated Snapshot CEST MRI

Abstract Purpose: To determine whether structural MRI information can improve reconstruction of highly accelerated 3D snapshot chemical exchange saturation transfer (CEST) MRI. Methods: Fully sampled brain CEST data were retrospectively undersampled at acceleration factors (AFs) of 4, 6, 8, 10, and 12. We compared reconstruction without structural information with population-level pretraining using T1-weighted (T1w), T2-weighted (T2w), or combined T1w-T2w images, as well as direct conditioning using a co-registered subject-specific T1w image. Performance was evaluated in two held-out healthy subjects using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean absolute error (MAE) across frequency offsets. Z-spectrum fidelity and derived magnetization transfer ratio asymmetry (MTRasym) maps were additionally evaluated within three-dimensional gray- and white-matter masks. Results: Subject-specific T1w conditioning consistently achieved the highest PSNR and SSIM and the lowest MAE across AFs, with greater improvements at higher acceleration. It also improved Z-spectrum agreement, particularly in white matter and combined gray- and white-matter regions across most AFs. Improvements in MTRasym were more modest and varied across tissue types and acceleration factors. Conclusion: Incorporating subject-specific structural information can improve reconstruction of highly accelerated snapshot CEST MRI, particularly at higher acceleration factors. However, improvements in reconstructed source images did not consistently translate into better preservation of derived CEST contrast, highlighting the need for reconstruction strategies that more directly incorporate CEST spectral information.

bioengineering↗

bioRxiv2024

Brain white matter pathways of resilience to chronic back pain: a multisite validation

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have pointed to brain characteristics as predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over six- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve [~] 0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.

neuroscience↗

bioRxiv2023

Monocyte-derived Dll4 is a novel contributor to persistent systemic inflammation in HIV patients

BackgroundIn people living with HIV (PLWH) on combination antiretroviral therapy (cART), persistent systemic inflammation is a driving force for the progression of comorbidities, such as cardiovascular and cerebrovascular diseases. In this context, monocyte- and macrophage-related inflammation rather than T cell activation is a major cause of chronic inflammation. However, the underlying mechanism of how monocytes cause persistent systemic inflammation in PLWH is elusive. Methods and ResultsIn vitro, we demonstrated that lipopolysaccharides (LPS) or tumor necrosis factor alpha (TNF), induced a robust increase of Delta-like ligand 4 (Dll4) mRNA and protein expression in human monocytes and Dll4 secretion (extracellular Dll4, exDll4) from monocytes. Enhanced membrane-bound Dll4 (mDll4) expression in monocytes triggered Notch1 activation to promote pro-inflammatory factors expression. Dll4 silencing and inhibition of Nocth1 activation diminished the LPS or TNF -induced inflammation. exDll4 releases in response to cytokines occurred in monocytes but not endothelial cells or T cells. In clinical specimens, we found that PLWH, both male and female, on cART, showed a significant increase in mDll4 expression, activation of Dll4-Notch1 signaling, and inflammatory markers in monocytes. Although there was no sex effect on mDII4 in PLWH, plasma exDll4 was significantly elevated in males but not females compared to HIV uninfected individuals. Furthermore, exDll4 plasma levels paralleled with monocytes mDll4 in male PLWH. Circulating exDll4 was also positively associated with pro-inflammatory monocytes phenotype and negatively associated with classic monocytes phenotype in male PLWH. ConclusionPro-inflammatory stimuli increase Dll4 expression and Dll4-Notch1 signaling activation in monocytes and enhance monocyte proinflammatory phenotype, contributing to persistent systemic inflammation in male and female PLWH. Therefore, monocyte mDll4 could be a potential biomarker and therapeutic target of systemic inflammation. Plasma exDll4 may also play an additional role in systemic inflammation but primarily in men.

molecular biology↗

bioRxiv2021

Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV Associated Neurocognitive Disorders

White matter damage is a consistent finding in HIV infected (HIV+) individuals. Previous studies have evaluated WM fiber tract specific brain regions in HIV-associated neurocognitive disorders using diffusion tensor imaging (DTI). However, DTI might lack an accurate biological interpretation, and the technique suffers from several limitations. Here, we sought to evaluate Fixel-based analysis (FBA) and free water corrected DTI (fwcDTI) metrics between HIV+ and HIV uninfected (HIV-) individuals, and their relationships with blood markers and cognitive scores. We also compared the specificity of both MRI metrics in their ability to distinguish between individuals with and without cognitive impairment using machine learning classifiers. Using 94 age-matched participants, we found that whole brain FBA was significantly reduced (up to 15%) in various fiber bundles. Tract based special statistics (TBSS) of fwcDTI metrics revealed decreased fractional anisotropy FAT (by 1-2%) in HIV+ compared to HIV- individuals in areas consistent with those observed in FBA, but these were not significant. An adaptive boosting classifier reliably distinguished between cognitively normal patients and those with cognitive impairment with 80% precision and 78% recall. Therefore, FBA may serve as a potential in-vivo biomarker for evaluating and monitoring axonal degeneration in HIV+ patients at risk for neurocognitive impairment.

neuroscience↗

bioRxiv2021

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↗

bioRxiv2021

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↗

bioRxiv2020

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↗