NeuroImage. Clinical
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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
Longitudinal structural cerebral changes related to core CSF biomarkers in preclinical Alzheimer's disease: A study of two independent datasets.
Alzheimer's disease (AD) is characterized by an accumulation of β-amyloid (Aβ42) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that Aβ42 accumulation is associated with gray matter (GM) changes prior to the development of cognitive impairment, in the so-called preclinical stage of the AD (pre-AD). It also has been proved that the GM atrophy profile is not linear, both in normal ageing but, especially, on AD. ⋯ Such discrepancies may lead to significant differences in the sample size needed to detect a particular reduction on cerebral atrophy rates in prevention trials. Higher cognitive reserve and more advanced pathological progression in the ADNI sample could partially account for the observed discrepancies. Taken together, our findings in these two samples highlight the importance of comparing and merging independent datasets to draw more robust and generalizable conclusions on the structural changes in the preclinical stages of AD.
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NeuroImage. Clinical · Jan 2018
Neural responses to emotional involuntary memories in posttraumatic stress disorder: Differences in timing and activity.
Involuntary memories are a hallmark symptom of posttraumatic stress disorder (PTSD), but studies of the neural basis of involuntary memory retrieval in posttraumatic stress disorder (PTSD) are sparse. The study of the neural correlates of involuntary memories of stressful events in PTSD focuses on the voluntary retrieval of memories that are sometimes recalled as intrusive involuntary memories, not on involuntary retrieval while being scanned. Involuntary memory retrieval in controls has been shown to elicit activity in the parahippocampal gyrus, precuneus, inferior parietal cortex, and posterior midline regions. However, it is unknown whether involuntary memories are supported by the same mechanisms in PTSD. Because previous work has shown that both behavioral and neural responsivity is slowed in PTSD, we examined the spatiotemporal dynamics of the neural activity underlying negative and neutral involuntary memory retrieval. ⋯ The similarity between PTSD and controls in neural substrates underlying involuntary memories suggests that, unlike voluntary memories, involuntary memories elicit similar activity in regions critical for memory retrieval. Further, the delayed neural responsivity for involuntary memories in PTSD suggests that factors affecting cognition in PTSD, like increased fatigue, or avoidance behaviors could do so by delaying activity in regions necessary for cognitive processing. Finally, compared to neutral memories, negative involuntary memories elicit hyperactivity in the vmPFC, whereas the vmPFC is typically shown to be hypoactive in PTSD during voluntary memory retrieval. These patterns suggest that considering both the temporal dynamics of cognitive processes as well as involuntary cognitive processes would improve existing neurobiological models of PTSD.
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NeuroImage. Clinical · Jan 2018
Parkinson's disease related signal change in the nigrosomes 1-5 and the substantia nigra using T2* weighted 7T MRI.
Improved markers for the progression of Parkinson's disease (PD) are required. Previous work has proven that iron dependent MRI scans can detect the largest Nigrosome (N1) within the substantia nigra (SN) pars compacta and changes in PD. Histopathological studies have shown that N1 is particularly affected in early PD whereas the other nigrosomes (N2-N5) and the surrounding iron-rich SN are affected later. ⋯ All nigrosomes can be detected using 7T MRI, and PD induced T2*weighted signal reduction was greatest in the nigrosomes (especially N1). The graded T2*weighted signal alterations in the nigrosomes match previously described differential histopathological effects of PD. N1 was identified with the highest confidence and T2*weighted signal in N1 correlated with UPDRS confirming N1 as the most promising SN marker of PD pathology.
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NeuroImage. Clinical · Jan 2018
Anatomic & metabolic brain markers of the m.3243A>G mutation: A multi-parametric 7T MRI study.
One of the most common mitochondrial DNA (mtDNA) mutations, the A to G transition at base pair 3243, has been linked to changes in the brain, in addition to commonly observed hearing problems, diabetes and myopathy. However, a detailed quantitative description of m.3243A>G patients' brains has not been provided so far. In this study, ultra-high field MRI at 7T and volume- and surface-based data analyses approaches were used to highlight morphology (i.e. atrophy)-, microstructure (i.e. myelin and iron concentration)- and metabolism (i.e. cerebral blood flow)-related differences between patients (N = 22) and healthy controls (N = 15). ⋯ In addition, several regions linked to attentional control (e.g. middle frontal gyrus), the sensorimotor network (e.g. banks of central sulcus) and the default mode network (e.g. precuneus) were characterized by alterations in cortical thickness, T1, T2* and/or cerebral blood flow, which has not been described in previous MRI studies. Finally, several hypotheses, based either on vascular, metabolic or astroglial implications of the m.3243A>G mutation, are discussed that potentially explain the underlying pathobiology. To conclude, this is the first 7T and also the largest MRI study on this patient population that provides macroscopic brain correlates of the m.3243A>G mutation indicating potential MRI biomarkers of mitochondrial diseases and might guide future (longitudinal) studies to extensively track neuropathological and clinical changes.