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Background: The extent and clinical significance of brain volume changes in different phases of multiple sclerosis (MS) is still under discussion. Objective: To determine the rate of global and compartmental brain volume changes in patients with a clinically-isolated syndrome (CIS) compared to patients with definite MS, by long-term follow-up and as a predictor of conversion to MS in a routine clinical setting. Methods: We investigated 120 patients (63 CIS and 57 MS) at baseline and after a mean follow-up period of 43 months, including detailed clinical examination and 3-Tesla magnetic resonance imaging (MRI). Our imaging analyses comprised the normalized brain volume (NBV), cortical grey matter (cGMV) and white matter (WMV) volumes using SIENA/X, the percentage of brain volume change (PBVC) using SIENA and the change in the volume of the thalami (TV) and basal ganglia (BGV). We also determined the amount and change of T2-lesion load (T2-LL). Results: At baseline, all the brain volume metrics, except cGMV, were significantly lower; and the T2-LL was significantly higher, in patients with MS rather than CIS. During the follow-up, only the PBVC was higher in MS (p = 0.008) and this difference was driven by converters from CIS to MS. Quartiles of PBVC did not allow us to predict conversion to MS, but were associated with the degree of disability. Conclusions: PBVC is the most sensitive marker of progressing atrophy and a higher PBVC was generally associated with more active disease; however, it did not serve to predict the course of MS on an individual basis, in this study. [ABSTRACT FROM AUTHOR]

The article presents a study which assessed the reflection and prediction for cerebrospinal spinal fluid (CSF) biomarkers for axonal damage. The study performed baseline magnetic resonance imaging (MRI) to patients with clinically isolated syndrome (CIS). The result of the study shows that there was an increase neurofilament levels in CIS.

The article presents a study which compares the evolution of morphologic brain abnormalities between paediatric (p)and adult-onset multiple sclerosis (aMS). The study the examined the differences and similarities in the evolution of the T2- and T1-lesion load (LL), annualised brain volume change (aBVC), and the black hole ratio (BHR), between 21 pMS and aMS patients. Results showed higher compensatory capacity in pMS than aMS based on the observation of the disease evolution.

Background: Lesion dissemination in time and space represents a key feature and diagnostic marker of multiple sclerosis (MS). The correlation between magnetic resonance imaging (MRI) lesion load and disability is only modest, however. Strategic lesion location might at least partially account for this ‘clinico-radiologic paradox’.Objectives: Here we used a non-parametric permutation-based approach to map lesion location probability based on MS lesions identified on T2-weighted MRI. We studied 121 patients with clinically isolated syndrome, relapsing–remitting or secondary progressive MS and correlated these maps to assessments of neurologic and cognitive functions.Results: The Expanded Disability Status Scale correlated with bilateral periventricular lesion location (LL), and sensory and coordination functional system deficits correlated with lesion accumulation in distinct anatomically plausible regions, i.e. thalamus and middle cerebellar peduncule. Regarding cognitive performance, decreased verbal fluency correlated with left parietal LL comprising the putative superior longitudinal fascicle. Delayed spatial recall correlated with _amygdalar, _left frontal and parietal LL. Delayed selective reminding correlated with bilateral frontal and temporal LL. However, only part of the spectrum of cognitive and neurological problems encountered in our cohort could be explained by specific lesion location.Conclusions: Lesion probability mapping supports the association of specific lesion locations with symptom development in MS, but only to limited extent. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Iron is the most abundant trace metal in the human brain and consistently shown elevated in prevalent neurological disorders. Because of its paramagnetism, brain iron can be assessed in vivo by quantitative MRI techniques such as R 2 * mapping and Quantitative Susceptibility Mapping (QSM). While Inductively Coupled Plasma Mass Spectrometry (ICP-MS) has demonstrated good correlations of the total iron content to MRI parameters in gray matter, the relationship to ferritin levels as assessed by Electron Paramagnetic Resonance (EPR) has not been systematically analyzed. Therefore, we included 15 postmortem subjects (age: 26-91 years) which underwent quantitative in-situ MRI at 7 Tesla within a post-mortem interval of 24 h after death. ICP-MS and EPR were used to measure the total iron and ferritin content in 8 selected gray matter (GM) structures and the correlations to R 2 * and QSM were calculated. We found that R 2 * and QSM in the iron rich basal ganglia and the red nucleus were highly correlated with iron (R² > 0.7) and ferritin (R² > 0.6), whereas those correlations were lost in cortical regions and the hippocampus. The neuromelanin-rich substantia nigra showed a different behavior with a correlation with total iron only (R² > 0.5) but not with ferritin. Although qualitative results were similar for both qMRI techniques the observed correlation was always stronger for QSM than R 2 *. This study demonstrated the quantitative correlations between R 2 *, QSM, total iron and ferritin levels in an in-situ MRI setup and therefore aids to understand how molecular forms of iron are responsible for MRI contrast generation., Competing Interests: Declaration of competing interest None, (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Multiparametric quantitative MRI (mp-qMRI) provides noninvasive, quantitative measurements sensitive to a variety of tissue properties. In brain tumors (BTs), longitudinal relaxation time (T1), effective transverse relaxation time (T2*), transverse relaxation time (T2), water content (H 2 O), and quantitative susceptibility (χ) give valuable insights into the microenvironment. To generate large multicenter datasets, protocols need to be short and implementable on any scanner. The goal of this work was to develop and validate an 8-min, 3T mp-qMRI protocol for BT patients solely using generalized pulse sequences (mGRE and EPI)., Methods: A protocol was developed and tested on a multicompartment phantom, 5 healthy subjects (mean age: 31.64 years), and 4 BT patients (mean age:39.5 years) . Phantom and healthy subject longitudinal relaxation time (T1) maps were compared to those obtained using 2 reference methods. The 5 healthy subjects were scanned on 3T MRI scanners at 2 different sites and the reproducibility between scanners was assessed by computing Coefficients of Variance (COV) maps, performing Bland-Altman analysis and t -tests. Clinical feasibility was tested on 4 BT patients., Results: T1 values obtained using the proposed mp-qMRI protocol agree with those obtained using the reference methods in volunteers (mean error = 8.94 ms) . The qMRI maps (T1, T2*, H 2 O, and χ ) of the volunteers showed good reproducibility between scanners with no significant differences for mean WM and GM qMRI values. WM and GM mean qMRI values agreed well with literature values. H 2 O gave the lowest COV and χ maps the highest., Conclusion: The proposed vendor sequence-based 3T mp-qMRI protocol gives interpolated, high resolution (1 mm isotropic) T1, T2*, H 2 O, and χ maps in 8 min of acquisition., Competing Interests: The authors have no conflicts of interest to report., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting., (© 2024 International Society for Magnetic Resonance in Medicine.)

Multiple sclerosis (MS) is a prevalent immune-mediated inflammatory disease of the central nervous system inducing a widespread degradation of myelin and resulting in neurological deficits. Recent advances in molecular and atomic imaging provide the means to probe the microenvironment in affected brain tissues at an unprecedented level of detail and may provide new insights. This study showcases state-of-the-art spectroscopic and mass spectrometric techniques to compare distributions of molecular and atomic entities in MS lesions and surrounding brain tissues. MS brains underwent post-mortem magnetic resonance imaging (MRI) to locate and subsequently dissect MS lesions and surrounding white matter. Digests of lesions and unaffected white matter were analysed via ICP-MS/MS revealing significant differences in concentrations of Li, Mg, P, K, Mn, V, Rb, Ag, Gd and Bi. Micro x-ray fluorescence spectroscopy (μXRF) and laser ablation - inductively coupled plasma - time of flight - mass spectrometry (LA-ICP-ToF-MS) were used as micro-analytical imaging techniques to study distributions of both endogenous and xenobiotic elements. The essential trace elements Fe, Cu and Zn were subsequently calibrated using in-house manufactured gelatine standards. Lipid distributions were studied using IR-micro spectroscopy and matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI). MALDI-MSI was complemented with high-resolution tandem mass spectrometry and trapped ion mobility spectroscopy for the annotation of specified phospho- and sphingolipids, revealing specific lipid species decreased in MS lesions compared to surrounding white matter. This explorative study demonstrated that modern molecular and atomic mapping techniques provide high-resolution imaging for relevant bio-indicative entities which may complement our current understanding of the underlying pathophysiological processes., Competing Interests: Declaration of competing interest Marten Seeba works for Bruker Corporation., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Deep neural networks are increasingly used for neurological disease classification by MRI, but the networks' decisions are not easily interpretable by humans. Heat mapping by deep Taylor decomposition revealed that (potentially misleading) image features even outside of the brain tissue are crucial for the classifier's decision. We propose a regularization technique to train convolutional neural network (CNN) classifiers utilizing relevance-guided heat maps calculated online during training. The method was applied using T1-weighted MR images from 128 subjects with Alzheimer's disease (mean age = 71.9 ± 8.5 years) and 290 control subjects (mean age = 71.3 ± 6.4 years). The developed relevance-guided framework achieves higher classification accuracies than conventional CNNs but more importantly, it relies on less but more relevant and physiological plausible voxels within brain tissue. Additionally, preprocessing effects from skull stripping and registration are mitigated. With the interpretability of the decision mechanisms underlying CNNs, these results challenge the notion that unprocessed T1-weighted brain MR images in standard CNNs yield higher classification accuracy in Alzheimer's disease than solely atrophy., (© 2022. The Author(s).)

Background: While iron is essential for normal brain functioning, elevated concentrations are commonly found in neurodegenerative diseases and are associated with impaired cognition and neurological deficits. Currently, only little is known about genetic and environmental factors that influence brain iron concentrations., Methods: Heritability and bivariate heritability of regional brain iron concentrations, assessed by R2* relaxometry at 3 Tesla MRI, were estimated with variance components models in 130 middle-aged to elderly participants of the Austrian Stroke Prevention Family Study., Results: Heritability of R2* iron ranged from 0.46 to 0.82 in basal ganglia and from 0.65 to 0.76 in cortical lobes. Age and BMI explained up to 12% and 9% of the variance of R2* iron, while APOE ε4 carrier status, hypertension, diabetes, hypercholesterolemia, sex and smoking explained 5% or less. The genetic correlation of R2* iron among basal ganglionic nuclei and among cortical lobes ranged from 0.78 to 0.87 and from 0.65 to 0.97, respectively. R2* rates in basal ganglia and cortex were not genetically correlated., Conclusions: Regional brain iron concentrations are mainly driven by genetic factors while environmental factors contribute to a certain extent. Brain iron levels in the basal ganglia and cortex are controlled by distinct sets of genes.

Purpose: Susceptibility maps are usually derived from local magnetic field estimations by minimizing a functional composed of a data consistency term and a regularization term. The data-consistency term measures the difference between the desired solution and the measured data using typically the L2-norm. It has been proposed to replace this L2-norm with the L1-norm, due to its robustness to outliers and reduction of streaking artifacts arising from highly noisy or strongly perturbed regions. However, in regions with high SNR, the L1-norm yields a suboptimal denoising performance. In this work, we present a hybrid data fidelity approach that uses the L1-norm and subsequently the L2-norm to exploit the strengths of both norms., Methods: We developed a hybrid data fidelity term approach for QSM (HD-QSM) based on linear susceptibility inversion methods, with total variation regularization. Each functional is solved with ADMM. The HD-QSM approach is a two-stage method that first finds a fast solution of the L1-norm functional and then uses this solution to initialize the L2-norm functional. In both norms we included spatially variable weights that improve the quality of the reconstructions., Results: The HD-QSM approach produced good quantitative reconstructions in terms of structural definition, noise reduction, and avoiding streaking artifacts comparable with nonlinear methods, but with higher computational efficiency. Reconstructions performed with this method achieved first place at the lowest RMS error category in stage 1 of the 2019 QSM Reconstruction Challenge., Conclusions: The proposed method allows robust and accurate QSM reconstructions, obtaining superior performance to state-of-the-art methods., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts., Methods: QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages., Results: The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups., Conclusion: The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers., (© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)