Cerebral T2-Weighted Signal Decrease During Aging in the Mouse Lemur Primate Reflects Iron Accumulation

Dhénain, Marc; Duyckaerts, C; Michot, Jean–Luc; Volk, Andreas; Picq, Jean‐Luc; Boller, François

doi:10.1016/s0197-4580(98)00005-0

Cited by 36 publications

(23 citation statements)

References 26 publications

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“…Paramagnetic materials have a high magnetic susceptibility and therefore, a relatively long transverse relaxation rate (R2) or short relaxation time constant, T2 (= 1/R2). Thus, iron-rich regions appear hypointense on T2-weighted images, and R2 prolongation corresponds to greater iron content in several structures, including the basal ganglia (Dhenain et al, 1998; Siemonsen et al, 2008). Longer R2, however, can also be related to lower water content of the parenchyma (Haacke et al, 2005), a fact that diminishes the validity of R2 as an index of iron content, especially in injured tissue.…”

Section: Estimating Brain Iron Content In Vivomentioning

confidence: 99%

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

2015

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Age-related increase in frailty is accompanied by a fundamental shift in cellular iron homeostasis. By promoting oxidative stress, the intracellular accumulation of non-heme iron outside of binding complexes contributes to chronic inflammation and interferes with normal brain metabolism. In the absence of direct non-invasive biomarkers of brain oxidative stress, iron accumulation estimated in vivo may serve as its proxy indicator. Hence, developing reliable in vivo measurements of brain iron content via magnetic resonance imaging (MRI) is of significant interest in human neuroscience. To date, by estimating brain iron content through various MRI methods, significant age differences and age-related increases in iron content of the basal ganglia have been revealed across multiple samples. Less consistent are the findings that pertain to the relationship between elevated brain iron content and systemic indices of vascular and metabolic dysfunction. Only a handful of cross-sectional investigations have linked high iron content in various brain regions and poor performance on assorted cognitive tests. The even fewer longitudinal studies indicate that iron accumulation may precede shrinkage of the basal ganglia and thus predict poor maintenance of cognitive functions. This rapidly developing field will benefit from introduction of higher-field MRI scanners, improvement in iron-sensitive and -specific acquisition sequences and post-processing analytic and computational methods, as well as accumulation of data from long-term longitudinal investigations. This review describes the potential advantages and promises of MRI-based assessment of brain iron, summarizes recent findings and highlights the limitations of the current methodology.

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Section: Estimating Brain Iron Content In Vivomentioning

confidence: 99%

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

2015

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“…This validation is justified as it is commonly accepted that the loss in the T2-weighted signal within the most T2-hypointense GM areas is due to an increased iron content, which is not only related to neurodegeneration but also to normal aging [15], [28], [29]. We compared the results derived from our approach to those derived from SPM8.…”

Section: Methodsmentioning

confidence: 99%

Fully Bayesian Inference for Structural MRI: Application to Segmentation and Statistical Analysis of T2-Hypointensities

et al. 2013

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Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: ; range, ). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data.

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“…Lithium treatment induced a decrease in hippocampal T 2 relaxation time 19 that could not only indicate an improvement in various neuropathologies (for example, edema), but also reflect an increase in tissue iron. 61,62,63,64,65 As iron elevation in the SN could contribute to Parkinson-like side effects such as the commonly observed hand tremor, we revisited this study and measured T 2 relaxation in this region, as well as other comparison regions in the same coronal planes (as marked in Supplementary Figure 1a, with reference to a standard neuroanatomical atlas). We found that the average T 2 relaxation time in the SN of the lithium group at 3 months (scan two) was significantly reduced from baseline (scan one) (−5%, P=0.007), and significantly lower than the Figure 1b).…”

Section: Low-dose Lithium Treatment Induces Reversible T 2 * Changes mentioning

confidence: 99%

Lithium suppression of tau induces brain iron accumulation and neurodegeneration

et al. 2016

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Lithium is a first-line therapy for bipolar affective disorder. However, various adverse effects, including a Parkinson-like hand tremor, often limit its use. The understanding of the neurobiological basis of these side effects is still very limited. Nigral iron elevation is also a feature of Parkinsonian degeneration that may be related to soluble tau reduction. We found that magnetic resonance imaging T 2 relaxation time changes in subjects commenced on lithium therapy were consistent with iron elevation. In mice, lithium treatment lowers brain tau levels and increases nigral and cortical iron elevation that is closely associated with neurodegeneration, cognitive loss and parkinsonian features. In neuronal cultures lithium attenuates iron efflux by lowering tau protein that traffics amyloid precursor protein to facilitate iron efflux. Thus, tauand amyloid protein precursor-knockout mice were protected against lithium-induced iron elevation and neurotoxicity. These findings challenge the appropriateness of lithium as a potential treatment for disorders where brain iron is elevated (for example, Alzheimer's disease), and may explain lithium-associated motor symptoms in susceptible patients.

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Cerebral T2-Weighted Signal Decrease During Aging in the Mouse Lemur Primate Reflects Iron Accumulation

Cited by 36 publications

References 26 publications

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

Fully Bayesian Inference for Structural MRI: Application to Segmentation and Statistical Analysis of T2-Hypointensities

Lithium suppression of tau induces brain iron accumulation and neurodegeneration

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