Multiparametric quantitative MRI reveals progressive cortical damage over time in clinically stable relapsing-remitting MS.

BACKGROUND: In relapsing-remitting multiple sclerosis (RRMS), cortical grey matter pathology relevantly contributes to long-term disability. Still, diffuse cortical inflammation cannot be detected with conventional MRI. OBJECTIVE: We aimed to assess microstructural damage of cortical grey matter over time and the relation to clinical disability as well as relapse activity in patients with RRMS using multiparametric quantitative (q)MRI techniques. METHODS: On 40 patients with RRMS and 33 age-matched and sex-matched healthy controls, quantitative T1, T2, T2* and proton density (PD) mapping was performed at baseline and follow-up after 2 years. Cortical qMRI parameter values were extracted with the FreeSurfer software using a surface-based approach. QMRI parameters, cortical thickness and white matter lesion (WML) load, as well as Expanded Disability Status Scale (EDSS) and relapse rate, were compared between time points. RESULTS: Over 2 years, significant increases of T1 (p≤0.001), PD (p≤0.001) and T2 (p=0.005) values were found in the patient, but not in the control group. At decreased relapse rate over time (p=0.001), cortical thickness, WML volume and EDSS remained unchanged. CONCLUSION: Despite clinical stability, cortical T1, T2 and PD values increased over time, indicating progressive demyelination and increasing water content. These parameters represent promising surrogate parameters of diffuse cortical inflammation in RRMS.

How stable is quantitative MRI? - Assessment of intra- and inter-scanner-model reproducibility using identical acquisition sequences and data analysis programs.

BACKGROUND: Quantitative MRI (qMRI) techniques allow assessing cerebral tissue properties. However, previous studies on the accuracy of quantitative T1 and T2 mapping reported a scanner model bias of up to 10% for T1 and up to 23% for T2. Such differences would render multi-centre qMRI studies difficult and raise fundamental questions about the general precision of qMRI. A problem in previous studies was that different methods were used for qMRI parameter mapping or for measuring the transmitted radio frequency field B1 which is critical for qMRI techniques requiring corrections for B1 non-uniformities. AIMS: The goal was to assess the intra- and inter-scanner reproducibility of qMRI data at 3 â€‹T, using two different scanner models from the same vendor with exactly the same multiparametric acquisition protocol. METHODS: Proton density (PD), T1, T2* and T2 mapping was performed on healthy subjects and on a phantom, performing each measurement twice for each of two scanner models. Although the scanners had different hardware and software versions, identical imaging sequences were used for PD, T1 and T2* mapping, adapting the codes of an existing protocol on the older system line by line to match the software version of the newer scanner. For T2-mapping, the respective manufacturer's sequence was used which depended on the software version. However, system-dependent corrections were carried out in this case. Reproducibility was assessed by average values in regions of interest. RESULTS: Mean scan-rescan variations were not exceeding 2.14%, with average values of 1.23% and 1.56% for the new and old system, respectively. Inter-scanner model deviations were not exceeding 5.21% with average values of about 2.2-3.8% for PD, 2.5-3.0% for T2*, 1.6-3.1% for T1 and 3.3-5.2% for T2. CONCLUSIONS: Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low. The level of systematic differences reported in this work may help to interpret multi-centre data.

Detection of cortical malformations using enhanced synthetic contrast images derived from quantitative T1 maps.

The detection of cortical malformations in conventional MR images can be challenging. Prominent examples are focal cortical dysplasias (FCD), the most common cause of drug-resistant focal epilepsy. The two main MRI hallmarks of cortical malformations are increased cortical thickness and blurring of the gray (GM) and white matter (WM) junction. The purpose of this study was to derive synthetic anatomies from quantitative T1 maps for the improved display of the above imaging characteristics in individual patients. On the basis of a T1 map, a mask comprising pixels with T1 values characteristic for GM is created from which the local cortical extent (CE) is determined. The local smoothness (SM) of the GM-WM junctions is derived from the T1 gradient. For display of cortical malformations, the resulting CE and SM maps serve to enhance local intensities in synthetic double inversion recovery (DIR) images calculated from the T1 map. The resulting CE- and/or SM-enhanced DIR images appear hyperintense at the site of cortical malformations, thus facilitating FCD detection in epilepsy patients. However, false positives may arise in areas with naturally elevated CE and/or SM, such as large GM structures and perivascular spaces. In summary, the proposed method facilitates the detection of cortical abnormalities such as cortical thickening and blurring of the GM-WM junction which are typical FCD markers. Still, subject motion artifacts, perivascular spaces, and large normal GM structures may also yield signal hyperintensity in the enhanced synthetic DIR images, requiring careful comparison with clinical MR images by an experienced neuroradiologist to exclude false positives.

Cortical Changes in Epilepsy Patients With Focal Cortical Dysplasia: New Insights With T2 Mapping.

BACKGROUND: In epilepsy patients with focal cortical dysplasia (FCD) as the epileptogenic focus, global cortical signal changes are generally not visible on conventional MRI. However, epileptic seizures or antiepileptic medication might affect normal-appearing cerebral cortex and lead to subtle damage. PURPOSE: To investigate cortical properties outside FCD regions with T2 -relaxometry. STUDY TYPE: Prospective study. SUBJECTS: Sixteen patients with epilepsy and FCD and 16 age-/sex-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3T, fast spin-echo T2 -mapping, fluid-attenuated inversion recovery (FLAIR), and synthetic T1 -weighted magnetization-prepared rapid acquisition of gradient-echoes (MP-RAGE) datasets derived from T1 -maps. ASSESSMENT: Reconstruction of the white matter and cortical surfaces based on MP-RAGE structural images was performed to extract cortical T2 values, excluding lesion areas. Three independent raters confirmed that morphological cortical/juxtacortical changes in the conventional FLAIR datasets outside the FCD areas were definitely absent for all patients. Averaged global cortical T2 values were compared between groups. Furthermore, group comparisons of regional cortical T2 values were performed using a surface-based approach. Tests for correlations with clinical parameters were carried out. STATISTICAL TESTS: General linear model analysis, permutation simulations, paired and unpaired t-tests, and Pearson correlations. RESULTS: Cortical T2 values were increased outside FCD regions in patients (83.4 ± 2.1 msec, control group 81.4 ± 2.1 msec, P = 0.01). T2 increases were widespread, affecting mainly frontal, but also parietal and temporal regions of both hemispheres. Significant correlations were not observed (P ≥ 0.55) between cortical T2 values in the patient group and the number of seizures in the last 3 months or the number of anticonvulsive drugs in the medical history. DATA CONCLUSION: Widespread increases in cortical T2 in FCD-associated epilepsy patients were found, suggesting that structural epilepsy in patients with FCD is not only a symptom of a focal cerebral lesion, but also leads to global cortical damage not visible on conventional MRI. EVIDENCE LEVEL: 21 TECHNICAL EFFICACY STAGE: 3 J. MAGN. RESON. IMAGING 2020;52:1783-1789.

Cortical quantitative MRI parameters are related to the cognitive status in patients with relapsing-remitting multiple sclerosis.

OBJECTIVES: We aimed to assess cortical damage in patients with relapsing-remitting multiple sclerosis (RRMS)/clinically isolated syndrome (CIS) with a multiparametric, surface-based quantitative MRI (qMRI) approach and to evaluate the correlation of imaging-derived parameters with cognitive scores, hypothesizing that qMRI parameters are correlated with cognitive abilities. METHODS: Multiparametric qMRI-data (T1, T2 and T2* relaxation times and proton density (PD)) were obtained from 34 patients/24 matched healthy control subjects. Cortical qMRI values were analyzed on the reconstructed cortical surface with Freesurfer. We tested for group differences of cortical microstructural parameters between the healthy and patient collectives and for partial Pearson correlations of qMRI parameters with cognitive scores, correcting for age. RESULTS: Cortical T2-/T2*-/PD values and four cognitive parameters differed between groups (p ≤ 0.046). These cognitive scores, reflecting information processing speed, verbal memory, visuospatial abilities, and attention, were correlated with cortical T2 (p ≤ 0.02) and T2* (p ≤ 0.03). Cortical changes appeared heterogeneous across the cortex and their distribution differed between the parameters. Vertex-wise correlation of T2 with neuropsychological parameters revealed specific patterns of cortical damage being related to distinct cognitive deficits. CONCLUSIONS: Microstructural changes are distributed heterogeneously across the cortex in RRMS/CIS. QMRI has the potential to provide surrogate parameters for the assessment of cognitive impairment in these patients for clinical studies. The characteristics of cognitive impairment in RRMS might depend on the distribution of cortical changes. KEY POINTS: • The goal of the presented study was to investigate cortical changes in RRMS/CIS and their relation to the cognitive status, using multiparametric quantitative MRI. • Cortical T2, T2*, and PD increases observed in patients appeared heterogeneous across the cortex and their distribution differed between the parameters. • Vertex-wise correlation of T2 with neuropsychological scores revealed specific patterns of cortical changes being related to distinct cognitive deficits.

Evaluating the utility of serum NfL, GFAP, UCHL1 and tTAU as estimates of CSF levels and diagnostic instrument in neuroinflammation and multiple sclerosis.

BACKGROUND: This study aimed to evaluate the utility of neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCHL1) and total tau (tTAU) serum concentrations as approximation for cerebrospinal fluid (CSF) concentrations of the respective biomarkers in the context of neuroinflammation and multiple sclerosis (MS). METHODS: NfL, GFAP, UCHL1 and tTAU concentrations in serum and CSF were measured in 183 patients (122 with neuroinflammatory disease and 61 neurological or somatoform disease controls) using the single molecule array HD-1 analyzer (Quanterix, Boston, MA). Spearman's rank correlations were computed between serum and CSF concentrations. In a second step, the effects of age, BMI, gadolinium-enhancing lesions in MRI, integrity of the blood-brain barrier (BBB) and presence of acute relapse were accounted for by computing partial correlations. The analyses were repeated for a subsample consisting of MS phenotype patients only (n = 118). EDSS, MS disease activity and acute relapse were considered as additional covariates. Receiver operating characteristic (ROC) analysis was performed for each serum/CSF biomarker concentration to assess how well the particular biomarker concentration differentiates MS patients from somatoform disease controls. Correlations between serum and CSF levels as well as area under the curve (AUC) values were compared for the different biomarkers using z-test statistics. RESULTS: Serum concentrations correlated positively with CSF levels for NfL (r = 0.705, p < 0.01) as well as for GFAP (r = 0.259, p < 0.01). Correlation coefficients were significantly higher for NfL than for GFAP (z = 5.492, p < 0.01). We found no significant serum-CSF correlations for UCHL1 or tTAU. After adjusting for covariates, the results remained unchanged. In the analysis focusing only on MS patients, the results were replicated. ROC analysis demonstrated similarly acceptable performance of serum and CSF NfL values in differentiating MS phenotype patients from somatoform disease controls. AUC values were significantly higher for serum and CSF NfL compared to other biomarkers. CONCLUSION: NfL and GFAP but not UCHL1 or tTAU serum concentrations are associated with CSF levels of the respective biomarker. NfL exhibits more robust correlations between its serum and CSF concentrations as compared to GFAP independently from BBB integrity, clinical and radiological covariates. Both serum and CSF NfL values differentiate between MS and controls.

Matching proposed clinical and MRI criteria of aggressive multiple sclerosis to serum and cerebrospinal fluid markers of neuroaxonal and glial injury.

BACKGROUND: Definitions of aggressive MS employ clinical and MR imaging criteria to identify highly active, rapidly progressing disease courses. However, the degree of overlap between clinical and radiological parameters and biochemical markers of CNS injury is not fully understood. Aim of this cross-sectional study was to match clinical and MR imaging hallmarks of aggressive MS to serum/CSF markers of neuroaxonal and astroglial injury (neurofilament light chain (sNfL, cNfL), and glial fibrillary acidic protein (sGFAP, cGFAP)). METHODS: We recruited 77 patients with relapsing-remitting MS (RRMS) and 22 patients with clinically isolated syndrome. NfL and GFAP levels in serum and CSF were assessed using a single-molecule-array HD-1-analyzer. A general linear model with each biomarker as a dependent variable was computed. Clinical and imaging criteria of aggressive MS, as recently proposed by the ECTRIMS Consensus Group, were modeled as independent variables. Other demographic, clinical or laboratory parameters, were modeled as covariates. Analyses were repeated in a homogenous subgroup, consisting only of newly diagnosed, treatment-naïve RRMS patients presenting with an acute relapse. RESULTS: After adjusting for covariates and multiplicity of testing, sNfL and cNfL concentrations were strongly associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.00008; pcNfL = 0.004) as well as the presence of infratentorial lesions on MRI (psNfL = 0.0003; pcNfL < 0.004). No other clinical and imaging criteria of aggressive MS correlated significantly with NfL or GFAP in serum and CSF. In the more homogeneous subgroup, sNfL still was associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.001), presence of more than 20 T2-lesions (psNfL = 0.049) as well as the presence of infratentorial lesions on MRI (psNfL = 0.034), while cNfL was associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.011) and presence of more than 20 T2-lesions (psNfL = 0.029). CONCLUSIONS: Among proposed risk factors for an aggressive disease course, MRI findings but not clinical characteristics correlated with sNfL and cNfL as a marker of neuroaxonal injury and should be given appropriate weight considering MS prognosis and therapy. No significant correlation was detected for GFAP alone.

Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI.

Background and purpose: In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. Methods: 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. Results: There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Conclusions: Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.

Serum and cerebrospinal fluid BDNF concentrations are associated with neurological and cognitive improvement in multiple sclerosis: A pilot study.

BACKGROUND: Biomarkers of disease activity have been intensively studied in multiple sclerosis (MS) but knowledge on predictors of disability improvement is limited. The aim of this pilot study was to explore whether increased brain-derived neurotrophic factor concentrations in serum and CSF (sBDNF/cBDNF) precede neurological and cognitive improvement in MS. METHODS: In this pilot, monocentric prospective cohort study we collected serum/CSF samples at baseline together with EDSS (n = 36) and cognitive testing (n = 34) in patients with relapsing-remitting/primary progressive MS or clinically isolated syndrome. BDNF was assessed in serum and CSF with a single molecule array (SIMOA) HD-1 analyser (Quanterix). Twelve months later EDSS and cognitive testing were repeated. BDNF concentrations of patients with vs. without disability or cognitive improvement (disability improvement: decrease in EDSS ≥ 0.5; cognitive improvement: average z-score increase in neuropsychological performance ≥ 0.5) were compared using univariate ANOVAs adjusting for covariates. RESULTS: Compared to subjects without, patients with disability improvement had higher sBDNF at baseline (q = 0.04). Subjects with cognitive improvement had higher cBDNF at baseline than those without cognitive improvement (q = 0.004). Secondary analysis demonstrated significant correlations between sBDNF and EDSS change (q = 0.036), cBDNF and average z-score change (q = 0.04) and cBDNF and number of cognitive tests with improvement (q = 0.04), while controlling for covariates. CONCLUSIONS: Our findings suggest a possible role for BDNF in neurological and cognitive improvement in MS. These findings have to be confirmed in a larger sample but they already highlight the potential of BDNF as a biomarker for disability improvement and neuroplasticity in MS.

Multiparametric Quantitative MRI in Neurological Diseases.

Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.

Improved Visualization of Focal Cortical Dysplasia With Surface-Based Multiparametric Quantitative MRI.

PURPOSE: In the clinical routine, detection of focal cortical dysplasia (FCD) by visual inspection is challenging. Still, information about the presence and location of FCD is highly relevant for prognostication and treatment decisions. Therefore, this study aimed to develop, describe and test a method for the calculation of synthetic anatomies using multiparametric quantitative MRI (qMRI) data and surface-based analysis, which allows for an improved visualization of FCD. MATERIALS AND METHODS: Quantitative T1-, T2- and PD-maps and conventional clinical datasets of patients with FCD and epilepsy were acquired. Tissue segmentation and delineation of the border between white matter and cortex was performed. In order to detect blurring at this border, a surface-based calculation of the standard deviation of each quantitative parameter (T1, T2, and PD) was performed across the cortex and the neighboring white matter for each cortical vertex. The resulting standard deviations combined with measures of the cortical thickness were used to enhance the signal of conventional FLAIR-datasets. The resulting synthetically enhanced FLAIR-anatomies were compared with conventional MRI-data utilizing regions of interest based analysis techniques. RESULTS: The synthetically enhanced FLAIR-anatomies showed higher signal levels than conventional FLAIR-data at the FCD sites (p = 0.005). In addition, the enhanced FLAIR-anatomies exhibited higher signal levels at the FCD sites than in the corresponding contralateral regions (p = 0.005). However, false positive findings occurred, so careful comparison with conventional datasets is mandatory. CONCLUSION: Synthetically enhanced FLAIR-anatomies resulting from surface-based multiparametric qMRI-analyses have the potential to improve the visualization of FCD and, accordingly, the treatment of the respective patients.

Multimodal Quantitative MRI Reveals No Evidence for Tissue Pathology in Idiopathic Cervical Dystonia.

Background: While in symptomatic forms of dystonia cerebral pathology is by definition present, it is unclear so far whether disease is associated with microstructural cerebral changes in idiopathic dystonia. Previous quantitative MRI (qMRI) studies assessing cerebral tissue composition in idiopathic dystonia revealed conflicting results. Objective: Using multimodal qMRI, the presented study aimed to investigate alterations in different cerebral microstructural compartments associated with idiopathic cervical dystonia in vivo. Methods: Mapping of T1, T2, T 2 * , and proton density (PD) was performed in 17 patients with idiopathic cervical dystonia and 29 matched healthy control subjects. Statistical comparisons of the parametric maps between groups were conducted for various regions of interest (ROI), including major basal ganglia nuclei, the thalamus, white matter, and the cerebellum, and voxel-wise for the whole brain. Results: Neither whole brain voxel-wise statistics nor ROI-based analyses revealed significant group differences for any qMRI parameter under investigation. Conclusions: The negative findings of this qMRI study argue against the presence of overt microstructural tissue change in patients with idiopathic cervical dystonia. The results seem to support a common view that idiopathic cervical dystonia might primarily resemble a functional network disease.

Improved synthetic T1-weighted images for cerebral tissue segmentation in neurological diseases.

Structural cerebral MRI analysis in patients with neurological diseases usually requires T1-weighted datasets for tissue segmentation. For this purpose, synthetic T1-weighted images which are constructed from quantitative maps of the underlying tissue parameters such as the T1 relaxation time and the proton density (PD) may provide advantages over conventional datasets. However, in some cases synthetic images may suffer from specific artifacts, hampering accurate tissue segmentation. The goal was to improve a previously described method for the calculation of synthetic magnetization-prepared rapid gradient-echo (MP-RAGE) datasets from quantitative T1 and PD maps. Improvements comprise a B0-correction for the water-selective excitation pulses employed in T1-mapping and the use of T1-based pseudo-PD maps. Synthetic T1-weighted MP-RAGE datasets were calculated, using the standard and the improved algorithm, for 10 patients with focal epilepsy (caused by focal cortical dysplasia in 9), 10 patients with multiple sclerosis and 10 healthy control subjects and segmented with the Freesurfer toolbox. Visual inspection disclosed that segmentation of the standard synthetic datasets was inaccurate in 6 out of 10 patients with epilepsy, 7 out of 10 patients with multiple sclerosis and 7 out of 10 healthy control subjects, while the improved synthetic datasets resulted in adequate segmentation outcomes in the majority of cases. Only for one patient with multiple sclerosis and one with epilepsy, segmentation in basal temporal regions was not sufficient. Furthermore, data based on the standard algorithm showed strong signal non-uniformities in basal regions. This effect was not present in the improved synthetic datasets.