NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2018
Integrated imaging of [11C]-PBR28 PET, MR diffusion and magnetic resonance spectroscopy 1H-MRS in amyotrophic lateral sclerosis.
To determine the relationship between brain tissue metabolites measured by in vivo magnetic resonance spectroscopy (1H-MRS), and glial activation assessed with [11C]-PBR28 uptake in people with amyotrophic lateral sclerosis (ALS). ⋯ Integrated PET-MR and 1H-MRS imaging demonstrates associations between markers for neuronal integrity and neuroinflammation and may provide valuable insights into disease mechanisms in ALS.
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NeuroImage. Clinical · Jan 2018
Corpus callosum volumes in the 5 years following the first-episode of schizophrenia: Effects of antipsychotics, chronicity and maturation.
White matter (WM) structural changes, particularly affecting the corpus callosum (CC), seem to be critically implicated in psychosis. Whether such abnormalities are progressive or static is still a matter of debate in schizophrenia research. Aberrant maturation processes might also influence the longitudinal trajectory of age-related CC changes in schizophrenia patients. We investigated whether patients with first-episode schizophrenia-related psychoses (FESZ) would present longitudinal CC and whole WM volume changes over the 5 years after disease onset. ⋯ Continuous AP exposure can influence CC morphology during the first years after schizophrenia onset. Schizophrenia is associated with an abnormal pattern of total WM and anterior CC aging during non-elderly adulthood, and this adds complexity to the discussion on the static or progressive nature of structural abnormalities in psychosis.
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NeuroImage. Clinical · Jan 2018
A dual modeling approach to automatic segmentation of cerebral T2 hyperintensities and T1 black holes in multiple sclerosis.
Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WML) in multiple sclerosis (MS). The most widely established MRI outcome measure is the volume of hyperintense lesions on T2-weighted images (T2L). Unfortunately, T2L are non-specific for the level of tissue destruction and show a weak relationship to clinical status. Interest in lesions that appear hypointense on T1-weighted images (T1L) ("black holes") has grown because T1L provide more specificity for axonal loss and a closer link to neurologic disability. The technical difficulty of T1L segmentation has led investigators to rely on time-consuming manual assessments prone to inter- and intra-rater variability. This study aims to develop an automatic T1L segmentation approach, adapted from a T2L segmentation algorithm. ⋯ Though originally designed to segment T2L, MIMoSA performs well for segmenting T1 black holes in patients with MS.
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NeuroImage. Clinical · Jan 2018
Multi-component relaxation in clinically isolated syndrome: Lesion myelination may predict multiple sclerosis conversion.
We performed a longitudinal case-control study on patients with clinically isolated syndrome (CIS) with the aid of quantitative whole-brain myelin imaging. The aim was (1) to parse early myelin decay and to break down its distribution pattern, and (2) to identify an imaging biomarker of the conversion into clinically definite Multiple Sclerosis (MS) based on in vivo measurable changes of myelination. Imaging and clinical data were collected immediately after the onset of first neurological symptoms and follow-up explorations were performed after 3, 6, and, 12 months. ⋯ We initially hypothesized that normal appearing WM myelin loss may determine the severity of early disease and the subsequent risk of clinically definite MS development. However, in contrast we found that WM lesion myelin loss was pivotal for MS conversion. Regional myelination measures may thus play an important role in future clinical risk stratification.
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NeuroImage. Clinical · Jan 2018
FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort.
In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. ⋯ Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.