Christian Langkammer

Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study

Quantitative susceptibility mapping (QSM) is a novel technique which allows determining the bulk magnetic susceptibility distribution of tissue in vivo from gradient echo magnetic resonance phase images. It is commonly assumed that paramagnetic iron is the predominant source of susceptibility variations in gray matter as many studies have reported a reasonable correlation of magnetic susceptibility with brain iron concentrations in vivo. Instead of performing direct comparisons, however, all these studies used the putative iron concentrations reported in the hallmark study by Hallgren and Sourander (1958) for their analysis. Consequently, the extent to which QSM can serve to reliably assess brain iron levels is not yet fully clear. To provide such information we investigated the relation between bulk tissue magnetic susceptibility and brain iron concentration in unfixed (in situ) post mortem brains of 13 subjects using MRI and inductively coupled plasma mass spectrometry. A strong linear correlation between chemically determined iron concentration and bulk magnetic susceptibility was found in gray matter structures (r = 0.84, p < 0.001), whereas the correlation coefficient was much lower in white matter (r = 0.27, p < 0.001). The slope of the overall linear correlation was consistent with theoretical considerations of the magnetism of ferritin supporting that most of the iron in the brain is bound to ferritin proteins. In conclusion, iron is the dominant source of magnetic susceptibility in deep gray matter and can be assessed with QSM. In white matter regions the estimation of iron concentrations by QSM is less accurate and more complex because the counteracting contribution from diamagnetic myelinated neuronal fibers confounds the interpretation.

Quantitative MR Imaging of Brain Iron: A Postmortem Validation Study

PURPOSE To investigate the relationship between transverse relaxation rates R2 and R2*, the most frequently used surrogate markers for iron in brain tissue, and chemically determined iron concentrations. MATERIALS AND METHODS This study was approved by the local ethics committee, and informed consent was obtained from each individuals next of kin. Quantitative magnetic resonance (MR) imaging was performed at 3.0 T in seven human postmortem brains in situ (age range at death, 38-81 years). Following brain extraction, iron concentrations were determined with inductively coupled plasma mass spectrometry in prespecified gray and white matter regions and correlated with R2 and R2* by using linear regression analysis. Hemispheric differences were tested with paired t tests. RESULTS The highest iron concentrations were found in the globus pallidus (mean ± standard deviation, 205 mg/kg wet mass ± 32), followed by the putamen (mean, 153 mg/kg wet mass ± 29), caudate nucleus (mean, 92 mg/kg wet mass ± 15), thalamus (mean, 49 mg/kg wet mass ± 11), and white matter regions. When all tissue samples were considered, transverse relaxation rates showed a strong linear correlation with iron concentration throughout the brain (r² = 0.67 for R2, r² = 0.90 for R2*; P < .001). In white matter structures, only R2* showed a linear correlation with iron concentration. Chemical analysis revealed significantly higher iron concentrations in the left hemisphere than in the right hemisphere, a finding that was not reflected in the relaxation rates. CONCLUSION Because of their strong linear correlation with iron concentration, both R2 and R2* can be used to measure iron deposition in the brain. Because R2* is more sensitive than R2 to variations in brain iron concentration and can detect differences in white matter, it is the preferred parameter for the assessment of iron concentration in vivo.

Quantitative Susceptibility Mapping in Multiple Sclerosis

PURPOSE To apply quantitative susceptibility mapping (QSM) in the basal ganglia of patients with multiple sclerosis (MS) and relate the findings to R2* mapping with regard to the sensitivity for clinical and morphologic measures of disease severity. MATERIALS AND METHODS The local ethics committee approved this study, and all subjects gave written informed consent. Sixty-eight patients (26 with clinically isolated syndrome, 42 with relapsing-remitting MS) and 23 control subjects underwent 3-T magnetic resonance (MR) imaging. Susceptibility and R2* maps were reconstructed from the same three-dimensional multiecho spoiled gradient-echo sequence. Mean susceptibilities and R2* rates were measured in the basal ganglia and were compared between different phenotypes of the disease (clinically isolated syndrome, MS) and the control subjects by using analysis of variance, and regressing analysis was used to identify independent predictors. RESULTS Compared with control subjects, patients with MS and clinically isolated syndrome had increased (more paramagnetic) magnetic susceptibilities in the basal ganglia. R2* mapping proved less sensitive than QSM regarding group differences. The strongest predictor of magnetic susceptibility was age. Susceptibilities were higher with increasing neurologic deficits (r = 0.34, P < .01) and lower with normalized volumes of gray matter (r = -0.35, P < .005) and the cortex (r = -0.35, P < .005). CONCLUSION QSM provides superior sensitivity over R2* mapping in the detection of MS-related tissue changes in the basal ganglia. With QSM but not with R2* mapping, changes were already observed in patients with clinically isolated syndrome, which suggests that QSM can serve as a sensitive measure at the earliest stage of the disease.

Quantitative assessment of brain iron by R2* relaxometry in patients with clinically isolated syndrome and relapsing–remitting multiple sclerosis

Background Increased iron deposition has been implicated in the pathophysiology of multiple sclerosis (MS), based on visual analysis of signal reduction on T2-weighted images. R2* relaxometry allows to assess brain iron accumulation quantitatively. Objective To investigate regional brain iron deposition in patients with a clinically isolated syndrome (CIS) or relapsing–remitting MS (RRMS) and its associations with demographical, clinical, and conventional magnetic resonance imaging (MRI) parameters. Methods We studied 69 patients (CIS, n = 32; RRMS, n = 37) with 3T MRI and analyzed regional R2* relaxation rates and their correlations with age, disease duration, disability, T2 lesion load, and normalized brain volumes. Results Basal ganglia R2* relaxation rates increased in parallel with age (r = 0.3–0.6; P < 0.01) and were significantly higher in RRMS than in CIS (P < 0.05). Using multivariate linear regression analysis, the rate of putaminal iron deposition was independently predicted by the patients’ age, disease duration, and gray matter atrophy. Conclusions Quantitative assessment by R2* relaxometry suggests increased iron deposition in the basal ganglia of MS patients, which is associated with disease duration and brain atrophy. This technique together with long-term follow-up thus appears suited to clarify whether regional iron accumulation contributes to MS morbidity or merely reflects an epiphenomenon.

Differential developmental trajectories of magnetic susceptibility in human brain gray and white matter over the lifespan.

As indicated by several recent studies, magnetic susceptibility of the brain is influenced mainly by myelin in the white matter and by iron deposits in the deep nuclei. Myelination and iron deposition in the brain evolve both spatially and temporally. This evolution reflects an important characteristic of normal brain development and ageing. In this study, we assessed the changes of regional susceptibility in the human brain in vivo by examining the developmental and ageing process from 1 to 83 years of age. The evolution of magnetic susceptibility over this lifespan was found to display differential trajectories between the gray and the white matter. In both cortical and subcortical white matter, an initial decrease followed by a subsequent increase in magnetic susceptibility was observed, which could be fitted by a Poisson curve. In the gray matter, including the cortical gray matter and the iron‐rich deep nuclei, magnetic susceptibility displayed a monotonic increase that can be described by an exponential growth. The rate of change varied according to functional and anatomical regions of the brain. For the brain nuclei, the age‐related changes of susceptibility were in good agreement with the findings from R2* measurement. Our results suggest that magnetic susceptibility may provide valuable information regarding the spatial and temporal patterns of brain myelination and iron deposition during brain maturation and ageing. Hum Brain Mapp 35:2698–2713, 2014.

Determinants of brain iron in multiple sclerosis A quantitative 3T MRI study

Objectives: Abnormal high cerebral iron deposition may be implicated in chronic neurologic disorders, including multiple sclerosis (MS). R2* relaxometry has been recently validated in a postmortem study to indicate brain iron accumulation in a quantitative manner. We used this technique to assess brain iron levels in different stages of MS and healthy controls (HC) and determined their relation with demographic, clinical, neuropsychological, and other imaging variables. Methods: We studied 113 consecutive patients (35 clinically isolated syndrome [CIS], 78 MS) and 35 HC with 3 T MRI and clinical and neuropsychological examination. Iron deposition in subcortical gray matter structures was assessed by automated, regional calculation of R2* rates. Results: Basal ganglia (BG) R2* levels were significantly increased in MS compared to CIS (p < 0.001) and HC (p < 0.005). They were correlated with age (r = 0.5, p < 0.001), disease duration (r = 0.5, p < 0.001), Expanded Disability Status Scale (r = 0.3, p < 0.005), and the z values of mental processing speed (r = −0.3, p < 0.01). Stepwise linear regression analysis revealed gray matter atrophy as the strongest independent predictor of BG R2* levels (p < 0.001), followed by age (p < 0.001) and T2 lesion load (p < 0.005). Conclusion: BG iron accumulation in MS occurs with advancing disease and is related to the extent of morphologic brain damage, which argues for iron deposition as an epiphenomenon. The absence of increased iron levels in patients with CIS indicates that iron accumulation does not precede the development of MS.

Susceptibility induced gray–white matter MRI contrast in the human brain

MR phase images have shown significantly improved contrast between cortical gray and white matter regions compared to magnitude images obtained with gradient echo sequences. A variety of underlying biophysical mechanisms (including iron, blood, myelin content, macromolecular chemical exchange, and fiber orientation) have been suggested to account for this observation but assessing the individual contribution of these factors is limited in vivo. For a closer investigation of iron and myelin induced susceptibility changes, postmortem MRI of six human corpses (age range at death: 56–80 years) was acquired in situ. Following autopsy, the iron concentrations in the frontal and occipital cortex as well as in white matter regions were chemically determined. The magnetization transfer ratio (MTR) was used as an indirect measure for myelin content. Susceptibility effects were assessed separately by determining R2* relaxation rates and quantitative phase shifts. Contributions of myelin and iron to local variations of the susceptibility were assessed by univariate and multivariate linear regression analysis. Mean iron concentration was lower in the frontal cortex than in frontal white matter (26 ± 6 vs. 45 ± 6 mg/kg wet tissue) while an inverse relation was found in the occipital lobe (cortical gray matter: 41 ± 10 vs. white matter: 34 ± 10 mg/kg wet tissue). Multiple regression analysis revealed iron and MTR as independent predictors of the effective transverse relaxation rate R2* but solely MTR was identified as source of MR phase contrast. R2* was correlated with iron concentrations in cortical gray matter only (r = 0.42, p < 0.05). In conclusion, MR phase contrast between cortical gray and white matter can be mainly attributed to variations in myelin content, but not to iron concentration. Both, myelin and iron impact the effective transverse relaxation rate R2* significantly. Magnitude contrast is limited because it only reflects the extent but not the direction of the susceptibility shift.

MRI assessment of iron deposition in multiple sclerosis.

Iron deposition in the human brain tissue occurs in the process of normal aging and in many neurodegenerative diseases. Elevated iron levels in certain brain regions are also an increasingly recognized finding in multiple sclerosis (MS). The exact mechanism(s) for this phenomenon and its implication in terms of pathophysiology and clinical significance are still largely unknown and debated. Reliable methods to exactly quantify brain iron are a first step to clarify these issues. Therefore, the aim of this review is to present currently available magnetic resonance imaging (MRI) techniques for the assessment of brain iron. These include relaxation time mapping, phase imaging, susceptibility‐weighted imaging, susceptibility mapping, magnetic field correlation imaging, and direct saturation imaging. After discussing their advantages and disadvantages, existing MRI clinical correlations with brain iron concentration in MS are summarized and future research directions are shown. J. Magn. Reson. Imaging 2011;.

Fast quantitative susceptibility mapping using 3D EPI and total generalized variation

Quantitative susceptibility mapping (QSM) allows new insights into tissue composition and organization by assessing its magnetic property. Previous QSM studies have already demonstrated that magnetic susceptibility is highly sensitive to myelin density and fiber orientation as well as to para- and diamagnetic trace elements. Image resolution in QSM with current approaches is limited by the long acquisition time of 3D scans and the need for high signal to noise ratio (SNR) to solve the dipole inversion problem. We here propose a new total-generalized-variation (TGV) based method for QSM reconstruction, which incorporates individual steps of phase unwrapping, background field removal and dipole inversion in a single iteration, thus yielding a robust solution to the reconstruction problem. This approach has beneficial characteristics for low SNR data, allowing for phase data to be rapidly acquired with a 3D echo planar imaging (EPI) sequence. The proposed method was evaluated with a numerical phantom and in vivo at 3 and 7 T. Compared to total variation (TV), TGV-QSM enforced higher order smoothness which yielded solutions closer to the ground truth and prevented stair-casing artifacts. The acquisition time for images with 1mm isotropic resolution and whole brain coverage was 10s on a clinical 3 Tesla scanner. In conclusion, 3D EPI acquisition combined with single-step TGV reconstruction yields reliable QSM images of the entire brain with 1mm isotropic resolution in seconds. The short acquisition time combined with the robust reconstruction may enable new QSM applications in less compliant populations, clinical susceptibility tensor imaging, and functional resting state examinations.

Cognitive impairment in relation to MRI metrics in patients with clinically isolated syndrome

Background: Cognitive deficits are frequent in multiple sclerosis (MS) and have been associated with morphologic brain changes. Less information exists on their extent and relation to MRI findings in clinically isolated syndrome (CIS). It is also unclear if structural changes as detected by magnetization transfer (MT) imaging may provide an additional explanation for cognitive dysfunction. Objective: To analyse the extent of cognitive deficits and their relation to MRI metrics including MT imaging in CIS compared to relapsing-remitting MS (RRMS). Methods: Forty-four CIS and 80 RRMS patients underwent the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) and a 3 T MRI scan. Results: BRB-N subtests revealed similar results in CIS and RRMS. Impaired mental processing speed was most prevalent in both groups (CIS 13.6%; RRMS 16.3%) and thus served for correlation with MRI metrics. Using stepwise linear regression analyses, the strongest predictor for decreased mental processing speed was normalized cortex volume (p < 0.001) followed by T2-lesion load (p < 0.05) in RRMS, whereas cortical MT ratio was the only MRI parameter associated with decreased mental processing speed in CIS (p < 0.005). Conclusion: Cognitive dysfunction occurs in CIS in a pattern similar to RRMS, with impaired mental processing speed being most prevalent. Cortical MT-ratio changes may be an early sign for tissue changes related to impaired mental processing speed in CIS while this association shifts to increased signs of cortical atrophy and lesion load in RRMS.