Test-retest variability of brain morphometry analysis: an investigation of sequence and coil effects

Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

BACKGROUND

Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and brain SVD by using quantitative 82Rb cardiac PET/CT and brain MRI.

RESULTS

In our population of 370 patients, 176 had normal myocardial perfusion, 38 had pure cardiac SVD and 156 had obstructive coronary artery disease. All underwent both a cardiac 82Rb PET/CT and a brain 1.5T or 3T MRI. Left-ventricle myocardial blood flow (LV-MBF) and flow reserve (LV-MFR) were recorded from 82Rb PET/CT, while Fazekas score, white matter lesion (WMab) volume, deep gray matter lesion (GMab) volume, and brain morphometry (for z-score calculation) using the MorphoBox research application were derived from MRI. Groups were compared with Kruskal-Wallis test, and the potential interrelation between heart and brain SVD markers was assessed using Pearson's correlation coefficient. Patients with cardiac SVD had lower stress LV-MBF and MFR (P < 0.001) than patients with normal myocardial perfusion; Fazekas scores and WMab volumes were similar in those two groups (P > 0.45). In patients with cardiac SVD only, higher rest LV-MBF was associated with a lower left-putamen (rho = - 0.62, P = 0.033), right-thalamus (rho = 0.64, P = 0.026), and right-pallidum (rho = 0.60, P = 0.039) z-scores and with a higher GMab volume. Lower stress LV-MBF was associated with lower left-caudate z-score (rho = 0.69, P = 0.014), while lower LV-MFR was associated with lower left (rho = 0.75, P = 0.005)- and right (rho = 0.59, P = 0.045)-putamen z-scores, as well as higher right-thalamus GMab volume (rho = - 0.72, P = 0.009).

CONCLUSION

Significant interrelations between cardiac and cerebral SVD markers were found, especially regarding deep gray matter alterations, which supports the hypothesis of SVD as a systemic disease.

Longitudinal Imaging of Regional Brain Volumes, SV2A, and Glucose Metabolism In Huntington's Disease

BACKGROUND

Development of disease-modifying treatments for Huntington's disease (HD) could be aided by the use of imaging biomarkers of disease progression. Positron emission tomography (PET) with 11 C-UCB-J, a radioligand for the brain-wide presynaptic marker synaptic vesicle protein 2A (SV2A), detects more widespread brain changes in early HD than volumetric magnetic resonance imaging (MRI) and 18 F-fludeoxyglucose (18 F-FDG) PET, but longitudinal 11 C-UCB-J PET data have not been reported. The aim of this study was to compare the sensitivity of 11 C-UCB-J PET, 18 F-FDG PET, and volumetric MRI for detection of longitudinal changes in early HD.

METHODS

Seventeen HD mutation carriers (six premanifest and 11 early manifest) and 13 healthy controls underwent 11 C-UCB-J PET, 18 F-FDG PET, and volumetric MRI at baseline (BL) and after 21.4 ± 2.7 months (Y2). Within-group and between-group longitudinal clinical and imaging changes were assessed.

RESULTS

The HD group showed significant 2-year worsening of Unified Huntington's Disease Rating Scale motor scores. There was significant longitudinal volume loss within the HD group in caudate (-4.5% ± 3.8%), putamen (-3.6% ± 3.5%), pallidum (-3.0% ± 2.7%), and frontal cortex (-2.0% ± 2.1%) (all P < 0.001). Within the HD group there was longitudinal loss of putaminal SV2A binding (6.4% ± 8.8%, P = 0.01) and putaminal glucose metabolism (-2.8% ± 4.4%, P = 0.008), but these changes were not significant after correction for multiple comparisons. Premanifest subjects at BL only had significantly lower SV2A binding than controls in basal ganglia structures, but at Y2 additionally had significant SV2A loss in frontal and parietal cortex, indicating spread of SV2A loss from subcortical to cortical regions.

CONCLUSIONS

Volumetric MRI may be more sensitive than 11 C-UCB-J PET and 18 F-FDG PET for detection of 2-year brain changes in early HD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3

Automatic neuroimaging processing tools provide convenient and systematic methods for extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer, provides an easy-to-use pipeline to extract cortical and subcortical morphometric measures. There have been over 25 stable releases of FreeSurfer, with different versions used across published works. The reliability and compatibility of regional morphometric metrics derived from the most recent version releases have yet to be empirically assessed. Here, we used test-retest data from three public data sets to determine within-version reliability and between-version compatibility across 42 regional outputs from FreeSurfer versions 7.1, 6.0, and 5.3. Cortical thickness from v7.1 was less compatible with that of older versions, particularly along the cingulate gyrus, where the lowest version compatibility was observed (intraclass correlation coefficient 0.37-0.61). Surface area of the temporal pole, frontal pole, and medial orbitofrontal cortex, also showed low to moderate version compatibility. We confirm low compatibility between v6.0 and v5.3 of pallidum and putamen volumes, while those from v7.1 were compatible with v6.0. Replication in an independent sample showed largely similar results for measures of surface area and subcortical volumes, but had lower overall regional thickness reliability and compatibility. Batch effect correction may adjust for some inter-version effects when most sites are run with one version, but results vary when more sites are run with different versions. Age associations in a quality controlled independent sample (N = 106) revealed version differences in results of downstream statistical analysis. We provide a reference to highlight the regional metrics that may yield recent version-related inconsistencies in published findings. An interactive viewer is provided at http://data.brainescience.org/Freesurfer_Reliability/.

The Unresolved Methodological Challenge of Detecting Neuroplastic Changes in Astronauts

After completing a spaceflight, astronauts display a salient upward shift in the position of the brain within the skull, accompanied by a redistribution of cerebrospinal fluid. Magnetic resonance imaging studies have also reported local changes in brain volume following a spaceflight, which have been cautiously interpreted as a neuroplastic response to spaceflight. Here, we provide evidence that the grey matter volume changes seen in astronauts following spaceflight are contaminated by preprocessing errors exacerbated by the upwards shift of the brain within the skull. While it is expected that an astronaut's brain undergoes some neuroplastic adaptations during spaceflight, our findings suggest that the brain volume changes detected using standard processing pipelines for neuroimaging analyses could be contaminated by errors in identifying different tissue types (i.e., tissue segmentation). These errors may undermine the interpretation of such analyses as direct evidence of neuroplastic adaptation, and novel or alternate preprocessing or experimental paradigms are needed in order to resolve this important issue in space health research.

Association of Long-Term Speech Therapy and Neuromodulation in Primary Progressive Aphasia: Lessons from a Case Report

Primary progressive aphasia (PPA) is a neurodegenerative disorder with a progressive loss of language. Long-term support requires speech therapy but also individually set training programs. Here we propose an 8-month individualized speech-training program which alternates 3-week periods of transcranial direct current stimulation (tDCS) treatment with intensive daily language exercises and a 3-week period without tDCS treatment and a less intensive language exercise from home in a patient with non-fluent variant PPA (nfvPPA). The endpoints were the following: adherence to this program, language data after 8 months, questionnaires related to emotional valence, and brain volume changes. The results showed a persistent adherence after 8 months and a positive compliance reported by both the patient and the partner. The language evaluation showed a clinical stabilization. Moreover, a significant and positive influence of tDCS on mood was observed. This is, to our knowledge, the first ever published report of a combined neuromodulation and language training during the course of 8 months. Our finding suggests the feasibility of programs integrating hospital speech therapy, home training, and tDCS modulation in PPA. Further studies should be conducted in order to disentangle the contextual influences on language performance from the tDCS intervention effects and to address the observation of an initial improvement and a subsequent stabilization effect of language performances.

DBB - A Distorted Brain Benchmark for Automatic Tissue Segmentation in Paediatric Patients

T1-weighted magnetic resonance images provide a comprehensive view of the morphology of the human brain at the macro scale. These images are usually the input of a segmentation process that aims detecting the anatomical structures labeling them according to a predefined set of target tissues. Automated methods for brain tissue segmentation rely on anatomical priors of the human brain structures. This is the reason why their performance is quite accurate on healthy individuals. Nevertheless model-based tools become less accurate in clinical practice, specifically in the cases of severe lesions or highly distorted cerebral anatomy. More recently there are empirical evidences that a data-driven approach can be more robust in presence of alterations of brain structures, even though the learning model is trained on healthy brains. Our contribution is a benchmark to support an open investigation on how the tissue segmentation of distorted brains can be improved by adopting a supervised learning approach. We formulate a precise definition of the task and propose an evaluation metric for a fair and quantitative comparison. The training sample is composed of almost one thousand healthy individuals. Data include both T1-weighted MR images and their labeling of brain tissues. The test sample is a collection of several tens of individuals with severe brain distortions. Data and code are openly published on BrainLife, an open science platform for reproducible neuroscience data analysis.

Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images

Background and purpose:

Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements.

Materials and methods:

Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures.

Results:

ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles.

Conclusion:

Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.

Gray Matter Volume Variability in Young Healthy Adults: Influence of Gender Difference and Brain-Derived Neurotrophic Factor Genotype

Although brain gray matter (GM) plastically changes during short-term training, it is still unclear whether brain structures are stable for short periods (several months). Therefore, this study aimed to re-test the short-term variability of GM volumes and to clarify the effect of factors (gender and BDNF-genotype) expected to contribute to such variability. The subjects comprised 41 young healthy adults. T1-weighted images were acquired twice with an interval of approximately 4 months using a 3 T-MRI scanner. Voxel-based morphometry (VBM) was used to calculate GM volumes in 47 regions. The intraclass correlation coefficient (ICC) and Test–retest variability (%TRV) were used as indices of variability. As a result, the ICCs in 43 regions were excellent (ICC > 0.90) and those in 3 regions were good (ICC > 0.80), whereas the ICC in the thalamus was moderate (ICC = 0.694). Women had a higher %TRV than men in 5 regions, and %TRV of the Val66Val group was higher than that of the Met carrier group in 2 regions. Moreover, the Female-Val66Val group had a higher %TRV than the Male-Met carrier group in 3 regions. These results indicate that although the short-term variability of GM volumes is small, it is affected by within-subject factors.

Estimating the effect of a scanner upgrade on measures of grey matter structure for longitudinal designs

Longitudinal imaging studies are crucial for advancing the understanding of brain development over the lifespan. Thus, more and more studies acquire imaging data at multiple time points or with long follow-up intervals. In these studies changes to magnetic resonance imaging (MRI) scanners often become inevitable which may decrease the reliability of the MRI assessments and introduce biases. We therefore investigated the difference between MRI scanners with subsequent versions (3 Tesla Siemens Verio vs. Skyra) on the cortical and subcortical measures of grey matter in 116 healthy, young adults using the well-established longitudinal FreeSurfer stream for T1-weighted brain images. We found excellent between-scanner reliability for cortical and subcortical measures of grey matter structure (intra-class correlation coefficient > 0.8). Yet, paired t-tests revealed statistically significant differences in at least 67% of the regions, with percent differences around 2 to 4%, depending on the outcome measure. Offline correction for gradient distortions only slightly reduced these biases. Further, T1-imaging based quality measures reflecting gray-white matter contrast systematically differed between scanners. We conclude that scanner upgrades during a longitudinal study introduce bias in measures of cortical and subcortical grey matter structure. Therefore, before upgrading a MRI scanner during an ongoing study, researchers should prepare to implement an appropriate correction method for these effects.

Can 7T MPRAGE match MP2RAGE for gray-white matter contrast?

Ultra-High Field (UHF) MRI provides a significant increase in Signal-to-Noise Ratio (SNR) and gains in contrast weighting in several functional and structural acquisitions. Unfortunately, an increase in field strength also induces non-uniformities in the transmit field (B1+) that can compromise image contrast non-uniformly. The MPRAGE is one of the most common T1 weighted (T1w) image acquisitions for structural imaging. It provides excellent contrast between gray and white matter and is widely used for brain segmentation. At 7T, the signal non-uniformities tend to complicate this and therefore, the self-bias-field corrected MP2RAGE is often used there. In both MPRAGE and MP2RAGE, more homogeneous image contrast can be achieved with adiabatic pulses, like the TR-FOCI inversion pulse, or special pulse design on parallel transmission systems, like Universal Pulses (UP). In the present study, we investigate different strategies to improve the bias-field for MPRAGE at 7T, comparing the contrast and GM/WM segmentability against MP2RAGE. The higher temporal efficiency of MPRAGE combined with the potential of the user-friendly UPs was the primary motivation for this MPRAGE-MP2RAGE comparison. We acquired MPRAGE data in six volunteers, adding a k-space shutter to reduce scan time, a kt-point UP approach for homogeneous signal excitation, and a TR-FOCI pulse for homogeneous inversion. Our results show remarkable signal contrast improvement throughout the brain, including regions of low B1⁺ such as the cerebellum. The improvements in the MPRAGE were largest following the introduction of the UPs. In addition to the CNR, both SNR and GM/WM segmentability were also assessed. Among the MPRAGEs, the combined strategy (UP + TR-FOCI) yielded highest SNR and showed highest spatial similarity between GM segments to the MP2RAGE. Interestingly, the distance between gray and white matter peaks in the intensity histograms did not increase, as better pulses and higher SNR especially benefitted the (cerebellar) gray matter. Overall, the gray-white matter contrast from MP2RAGE is higher, with higher CNR and higher intensity peak distances, even when scaled to scan time. Hence, the extra acquisition time for MP2RAGE is justified by the improved segmentability.

Quantitative comparison of subcortical and ventricular volumetry derived from MPRAGE and MP2RAGE images using different brain morphometry software

OBJECTIVE

In brain volume assessment with MR imaging, it is of interest to know the effects of the pulse sequence and software used, to determine whether they provide equivalent data. The aim of this study was to compare cross-sectional volumes of subcortical and ventricular structures and their repeatability derived from MP2RAGE and MPRAGE images using MorphoBox, and FIRST or ALVIN.

MATERIALS AND METHODS

MPRAGE and MP2RAGE T1-weighted images were obtained from 24 healthy volunteers. Back-to-back scans were performed in 12 of them. Volumes, coefficients of variation, concordance, and correlations were determined.

RESULTS

Significant differences were found for volumes derived from MorphoBox and FIRST. Ventricular volumes determined by MorphoBox and ALVIN were similar. Differences between volumes obtained using MPRAGE and MP2RAGE were significant for a few regions. Coefficients of variation, ranged from 0.2 to 9.1%, showed a significant inverse correlation with the mean volume. There was a correlation between volume measures, but agreement was rated as poor for most regions.

CONCLUSION

MP2RAGE sequences and MorphoBox are valid options for assessing subcortical and ventricular volumes, in the same way as MPRAGE and FIRST or ALVIN, accepted tools for clinical research. However, caution is needed when comparing volumes obtained with different tools.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Cortical Thickness in Migraine: A Coordinate-Based Meta-Analysis

Cortical thickness (CTh) via surface-based morphometry analysis is a popular method to characterize brain morphometry. Many studies have been performed to investigate CTh abnormalities in migraine. However, the results from these studies were not consistent and even conflicting. These divergent results hinder us to obtain a clear picture of brain morphometry regarding CTh alterations in migraine. Coordinate-based meta-analysis (CBMA) is a promising technique to quantitatively pool individual neuroimaging studies to identify consistent brain areas involved. Electronic databases (PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure, WanFang, and SinoMed) and other sources (bioRxiv and reference lists of relevant articles and reviews) were systematically searched for studies that compared regional CTh differences between patients with migraine and healthy controls (HCs) up to May 15, 2020. A CBMA was performed using the Seed-based d Mapping with Permutation of Subject Images approach. In total, we identified 16 studies with 17 datasets reported that were eligible for the CBMA. The 17 datasets included 872 patients with migraine (average sample size 51.3, mean age 39.6 years, 721 females) and 949 HCs (average sample size 59.3, mean age 44.2 years, 680 females). The CBMA detected no statistically significant consistency of CTh alterations in patients with migraine relative to HCs. Sensitivity analysis and subgroup analysis verified this result to be robust. Metaregression analyses revealed that this CBMA result was not confounded by age, gender, aura, attack frequency per month, and illness duration. Our CBMA adds to the evidence of the replication crisis in neuroimaging research that is increasingly recognized. Many potential confounders, such as underpowered sample size, heterogeneous patient selection criteria, and differences in imaging collection and methodology, may contribute to the inconsistencies of CTh alterations in migraine, which merit attention before planning future research on this topic.

Normal volumetric and T1 relaxation time values at 1.5 T in segmented pediatric brain MRI using a MP2RAGE acquisition

OBJECTIVES

This study introduced a tailored MP2RAGE-based brain acquisition for a comprehensive assessment of the normal maturing brain.

METHODS

Seventy normal patients (35 girls and 35 boys) from 1 to 16 years of age were recruited within a prospective monocentric study conducted from a single University Hospital. Brain MRI examinations were performed at 1.5 T using a 20-channel head coil and an optimized 3D MP2RAGE sequence with a total acquisition time of 6:36 min. Automated 38 region segmentation was performed using the MorphoBox (template registration, bias field correction, brain extraction, and tissue classification) which underwent a major adaptation of three age-group T1-weighted templates. Volumetry and T1 relaxometry reference ranges were established using a logarithmic model and a modified Gompertz growth respectively.

RESULTS

Detailed automated brain segmentation and T1 mapping were successful in all patients. Using these data, an age-dependent model of normal brain maturation with respect to changes in volume and T1 relaxometry was established. After an initial rapid increase until 24 months of life, the total intracranial volume was found to converge towards 1400 mL during adolescence. The expected volumes of white matter (WM) and cortical gray matter (GM) showed a similar trend with age. After an initial major decrease, T1 relaxation times were observed to decrease progressively in all brain structures. The T1 drop in the first year of life was more pronounced in WM (from 1000-1100 to 650-700 ms) than in GM structures.

CONCLUSION

The 3D MP2RAGE sequence allowed to establish brain volume and T1 relaxation time normative ranges in pediatrics.

KEY POINTS

• The 3D MP2RAGE sequence provided a reliable quantitative assessment of brain volumes and T1 relaxation times during childhood. • An age-dependent model of normal brain maturation was established. • The normative ranges enable an objective comparison to a normal cohort, which can be useful to further understand, describe, and identify neurodevelopmental disorders in children.