Cognitive Implications of Deep Gray Matter Iron in Multiple Sclerosis

Fujiwara, Esther; Kmech, J.A.; Cobzaş, Dana; Sun, Hongfu; Seres, Peter; Blevins, Gregg; Wilman, Alan H.

doi:10.3174/ajnr.a5109

Cited by 28 publications

(32 citation statements)

References 36 publications

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“…In addition, portions of the thalamic WM skeleton remained significantly associated with BVMTR and CVLT2, even after controlling for thalamic volume, which are for the most part in line with previous work except for the lack of association with SDMT . The lack of a relationship with magnetic susceptibility is supported by two previous studies that showed iron levels did not explain additional variance in cognitive outcomes after controlling for thalamic volume (Fujiwara et al, 2017;Modica et al, 2015). Overall, our findings point towards thalamic WM iron as having a weaker role in explaining cognitive status compared to that of diffusivity changes, especially when also considering structural atrophy.…”

Section: Discussionsupporting

confidence: 79%

“…It has been recently suggested that thalamic iron homeostasis may be altered in MS patients (Bagnato, et al, 2011; Quinn, et al, 2014; Zivadinov, et al, 2012), with some studies reporting increased thalamic iron content (Rudko, et al, 2014; Walsh, et al, 2014) while others have found decreased iron levels (Schweser, et al, 2018) compared to healthy individuals. Associations between thalamic iron content and cognitive impairment in MS patients have also been investigated (Fujiwara, et al, 2017; Modica, et al, 2015). Nevertheless, such associations specifically within the thalamic WM have yet to be investigated in MS.…”

Section: Introductionmentioning

confidence: 99%

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Thalamic white matter in multiple sclerosis: A combined diffusion‐tensor imaging and quantitative susceptibility mapping study

Bergsland

Schweser

Dwyer

et al. 2018

Human Brain Mapping

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Thalamic white matter (WM) injury in multiple sclerosis (MS) remains relatively poorly understood. Combining multiple imaging modalities, sensitive to different tissue properties, may aid in further characterizing thalamic damage. Forty-five MS patients and 17 demographically-matched healthy controls (HC) were scanned with 3T MRI to obtain quantitative measures of diffusivity and magnetic susceptibility. Participants underwent cognitive evaluation with the Brief International Cognitive Assessment for Multiple Sclerosis battery. Tract-based spatial statistics identified thalamic WM. Non-parametric combination (NPC) analysis was used to perform joint inference on fractional anisotropy (FA), mean diffusivity (MD) and magnetic susceptibility measures. The association of surrounding WM lesions and thalamic WM pathology was investigated with lesion probability mapping. Compared to HCs, the greatest extent of thalamic WM damage was reflected by the combination of increased MD and decreased magnetic susceptibility (63.0% of thalamic WM, peak p = .001). Controlling for thalamic volume resulted in decreased FA and magnetic susceptibility (34.1%, peak p = .004) as showing the greatest extent. In MS patients, the most widespread association with information processing speed was found with the combination of MD and magnetic susceptibility (67.6%, peak p = .0005), although this was not evident after controlling for thalamic volume. For memory measures, MD alone yielded the most widespread associations (45.9%, peak p = .012 or 76.7%, peak p = .001), even after considering thalamic volume, albeit with smaller percentages. White matter lesions were related to decreased FA (peak p = .0063) and increased MD (peak p = .007), but not magnetic susceptibility, of thalamic WM. Our study highlights the complex nature of thalamic pathology in MS.

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Section: Discussionsupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Thalamic white matter in multiple sclerosis: A combined diffusion‐tensor imaging and quantitative susceptibility mapping study

Bergsland

Schweser

Dwyer

et al. 2018

Human Brain Mapping

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“…Susceptibility estimates from QSM in vivo have been validated with X‐ray fluorescence and ICPMS measurements of ferritin levels . Cognitive performance has also been negatively linked to QSM values in the PUT, GP, and the thalamus . Schmalbrock et al used 7T imaging to confirm the hypothesis that decreased performance of basal ganglia‐reliant tasks involving inhibitory control is associated with increased iron content.…”

Section: Applications Of Iron Quantification In Neurodegenerative Dismentioning

confidence: 99%

Iron deposition quantification: Applications in the brain and liver

Yan

Lin

et al. 2018

Magnetic Resonance Imaging

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“…QSM shows 90% sensitivity and specificity with GdE [302], starts to increase following a GdE lesion, and falls to baseline after 4 years [303]. Iron accumulation in the deep GM by QSM correlates with cognitive impairment [304] and impaired ability to suppress task-irrelevant information (inhibitory control) [305].…”

Section: Iron Imagingmentioning

confidence: 99%

The Role of Advanced Magnetic Resonance Imaging Techniques in Multiple Sclerosis Clinical Trials

Mahajan

Ontaneda

2017

Neurotherapeutics

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Magnetic resonance imaging has been crucial in the development of anti-inflammatory disease-modifying treatments. The current landscape of multiple sclerosis clinical trials is currently expanding to include testing not only of anti-inflammatory agents, but also neuroprotective, remyelinating, neuromodulating, and restorative therapies. This is especially true of therapies targeting progressive forms of the disease where neurodegeneration is a prominent feature. Imaging techniques of the brain and spinal cord have rapidly evolved in the last decade to permit in vivo characterization of tissue microstructural changes, connectivity, metabolic changes, neuronal loss, glial activity, and demyelination. Advanced magnetic resonance imaging techniques hold significant promise for accelerating the development of different treatment modalities targeting a variety of pathways in MS.

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Cognitive Implications of Deep Gray Matter Iron in Multiple Sclerosis

Cited by 28 publications

References 36 publications

Thalamic white matter in multiple sclerosis: A combined diffusion‐tensor imaging and quantitative susceptibility mapping study

Thalamic white matter in multiple sclerosis: A combined diffusion‐tensor imaging and quantitative susceptibility mapping study

Iron deposition quantification: Applications in the brain and liver

The Role of Advanced Magnetic Resonance Imaging Techniques in Multiple Sclerosis Clinical Trials

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