Human brain iron mapping using atlas‐based T₂ relaxometry

Abstract

Several in vivo quantitative magnetic resonance imaging (qMRI) techniques have been proposed as surrogate measures to map iron content in the human brain. The majority of in vivo qMRI iron mapping methods utilized the age-dependent iron content data based on postmortem data. In this work we fused atlas-based human brain volumetry obtained on a large cohort of healthy adults using FreeSurfer with T2 relaxation time measurements. We provide a brain atlas-based T2 relaxation time map which was subsequently used along with published postmortem iron content data to obtain a map of iron content in subcortical and cortical gray matter. We have also investigated the sensitivity of the linear model relating transverse relaxation rate with published iron content to the number of regions used. Our work highlights the challenges encountered upon using the simple model along with postmortem data to infer iron content in several brain regions where postmortem iron data are scant (e.g. corpus callosum, amygdale).

High-resolution characterisation of the aging brain using simultaneous quantitative susceptibility mapping (QSM) and R2* measurements at 7 T

“…This is an important result because seminal work from Hallgren and Sourander (1958) but also in vivo evidence using T2* (Hasan et al, 2012), has suggested that there might be a graded behaviour across cerebral lobes, i.e. greatest iron deposition as a function of age in motor cortex, followed by occipital, parietal, temporal and finally, prefrontal regions.…”

“…Previous studies using either post mortem (Hallgren and Sourander, 1958) or in vivo iron-sensitive MRI techniques (Acosta-Cabronero et al, 2016;Bartzokis et al, 2007;Haacke et al, 2007;Hasan et al, 2012;Pfefferbaum et al, 2009;Raz et al, 2007) have revealed that iron levels and its rate of accumulation are heterogeneous in the human brain. Furthermore, iron deposition may correlate with cognitive impairment (Daugherty et al, 2015;Ghadery et al, 2015;Penke et al, 2012) and slowing of motor performance (Cass et al, 2007;Li et al, 2015;Sullivan et al, 2009), though it is unclear whether this is cause or consequence.…”

Value of transverse relaxometry difference methods for iron in human brain

“…For example, tissue neurodegeneration may have contributions from both iron-independent and iron-related processes (25,26). A correlation between R 2 and post-mortem iron concentration in deep grey matter at 1.5 T was first reported by Drayer et al (10) and has since been investigated extensively by other groups (12,14,20,(27)(28)(29)(30)(31) at different field strengths ranging from 0.5 T to 7.0 T.…”

“…Note several previous studies (2,14,20,24,25,(28)(29)(30)(31)(39)(40)(41)(42)(43)(59)(60)(61) have used the age versus regional iron content best fits of post-mortem data reported by Hallgren and Sourander (5) to estimate iron content using relaxometry such as R 1 (14,60), R 2 (28,32), R 2 * (32,59) and R 2 ' (28,32) .…”

Volumetric T1 and T2 magnetic resonance brain toolkit for relaxometry mapping simulation

“…One classical MRI technique is the relaxometry, which measures the characteristic energy decay after a radio-frequency pulse, also known as the relaxometry constants (T2 or T1, depending the weighted imaging technique used) (Carneiro et al, 2006;Deoni, 2010;Haacke et al, 1999). This process is widely used for different studies, especially for brain research in clinical applications (Cheng et al, 2012;Ellingson et al, 2012;Hasan et al, 2012;Kosior et al, 2011), which plays an important role in the diagnosis of several brain diseases, e.g. in Parkinson (Barbosa et al, 2015), Alzheimer (House et al, 2006) and Multiple Sclerosis (Burgetova et al, 2010;Ellingson et al, 2012).…”