Sensitivity of voxel-based morphometry analysis to choice of imaging protocol at 3 T

Identifying Biases in a Multicenter MRI Database for Parkinson's Disease Classification: Is the Disease Classifier a Secret Site Classifier?

Sharing multicenter imaging datasets can be advantageous to increase data diversity and size but may lead to spurious correlations between site-related biological and non-biological image features and target labels, which machine learning (ML) models may exploit as shortcuts. To date, studies analyzing how and if deep learning models may use such effects as a shortcut are scarce. Thus, the aim of this work was to investigate if site-related effects are encoded in the feature space of an established deep learning model designed for Parkinson's disease (PD) classification based on T1-weighted MRI datasets. Therefore, all layers of the PD classifier were frozen, except for the last layer of the network, which was replaced by a linear layer that was exclusively re-trained to predict three potential bias types (biological sex, scanner type, and originating site). Our findings based on a large database consisting of 1880 MRI scans collected across 41 centers show that the feature space of the established PD model (74% accuracy) can be used to classify sex (75% accuracy), scanner type (79% accuracy), and site location (71% accuracy) with high accuracies despite this information never being explicitly provided to the PD model during original training. Overall, the results of this study suggest that trained image-based classifiers may use unwanted shortcuts that are not meaningful for the actual clinical task at hand. This finding may explain why many image-based deep learning models do not perform well when applied to data from centers not contributing to the training set.

Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data

OBJECTIVE

This work investigates if deep learning (DL) models can classify originating site locations directly from magnetic resonance imaging (MRI) scans with and without correction for intensity differences.

MATERIAL AND METHODS

A large database of 1880 T1-weighted MRI scans collected across 41 sites originally for Parkinson's disease (PD) classification was used to classify sites in this study. Forty-six percent of the datasets are from PD patients, while 54% are from healthy participants. After preprocessing the T1-weighted scans, 2 additional data types were generated: intensity-harmonized T1-weighted scans and log-Jacobian deformation maps resulting from nonlinear atlas registration. Corresponding DL models were trained to classify sites for each data type. Additionally, logistic regression models were used to investigate the contribution of biological (age, sex, disease status) and non-biological (scanner type) variables to the models' decision.

RESULTS

A comparison of the 3 different types of data revealed that DL models trained using T1-weighted and intensity-harmonized T1-weighted scans can classify sites with an accuracy of 85%, while the model using log-Jacobian deformation maps achieved a site classification accuracy of 54%. Disease status and scanner type were found to be significant confounders.

DISCUSSION

Our results demonstrate that MRI scans encode relevant site-specific information that models could use as shortcuts that cannot be removed using simple intensity harmonization methods.

CONCLUSION

The ability of DL models to exploit site-specific biases as shortcuts raises concerns about their reliability, generalization, and deployability in clinical settings.

Reliability of spinal cord measures based on synthetic T1-weighted MRI derived from multiparametric mapping (MPM)

Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T₁-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T₁-w MRI (synT₁-w) estimated from the MPM, in order to measure CSA. SynT₁-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R₁) and effective transverse (R₂*) relaxation rates. The reliability of CSA measurements from synT₁-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT₁-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT₁-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm² compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT₁-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT₁-w images, thereby reducing scan time significantly.

Grey matter volume abnormalities in the first depressive episode of medication-naïve adult individuals: a systematic review of voxel based morphometric studies

BACKGROUND

To identify the reliable and consistent grey matter volume (GMV) abnormalities associated with major depressive disorder (MDD), we excluded the influence of confounding clinical characteristics, comorbidities and brain degeneration on brain morphological abnormalities by inclusion of non-comorbid and non-geriatric drug-naïve MDD individuals experiencing first episode depressive.

METHODS

The PubMed, Scopus, Web of Science, Science Direct and Google scholar databases were searched for papers published in English up to April 2020.

RESULTS

A total of 21 voxel based morphometric (VBM) studies comparing 845 individuals in the first depressive episode and medication-naïve with 940 healthy control subjects were included. The results showed a grey matter volumes reductions in the orbitofrontal cortex (OFC), prefrontal cortex (PFC), frontal and temporal gyri, temporal pole, insular lobe, thalamus, basal ganglia, cerebellum, hippocampus, cingulate cortex, and amygdala. In addition, increased grey matter volumes in the postcentral gyrus, superior frontal gyrus, insula, basal ganglia, thalamus, amygdala, cuneus, and precuneus differentiated the first depressive episode in medication-naïve individuals from healthy subjects.

CONCLUSION

The present systematic review provided additional support for the involvement of grey matter structural abnormalities in limbic-cortical circuits as possibly specific structural abnormalities in the early stage of MDD.Key pointsDistinct brain regions in MDD patients might be associated with the early stages of illness, and thus it is critical to study the causal relationship between brain structures and the onset of the disease to improve the evaluation in clinic.Grey matter alterations in the fronto-limbic networks in the first episode, medication-naïve MDD might suggest that these abnormalities may play an important role in the neuropathophysiology of MDD at its onset.First episode, medically naïve depressive patients show grey matter volume alterations in brain regions mainly associated with emotion regulation including parietal-temporal regions, PFC, insular lobe, thalamus, basal ganglia, cerebellum and limbic structures that may be specific changes in early stage of MDD.Genotype-diagnosis interaction effects on brain morphology in the cortico-limbic-striatal circuits, including the PFC, amygdala, hippocampus and striatum that might be implicated in the dysfunctional regulation of emotion in first-episode MDD patients.Future longitudinal and prospective studies should be conducted to identify the core structural brain changes in people at-risk for MDD and explore the association of their brain volumes with symptom onset.

Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants

•

Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy.

•

Simulate spinal cord atrophy and scan-rescan variability.

•

Fully automated analysis method available on an open access database.

•

Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.

Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases. It is measured by segmenting the spinal cord on an MRI image and computing the average cross-sectional area (CSA) over a few slices. Introduced about 25 years ago, this procedure is highly sensitive to the quality of the segmentation and is prone to rater-bias. Recently, fully-automated spinal cord segmentation methods, which remove the rater-bias and enable the automated analysis of large populations, have been introduced. A lingering question related to these automated methods is: How reliable are they at detecting atrophy? In this study, we evaluated the precision and accuracy of automated atrophy measurements by simulating scan-rescan experiments.

Spinal cord MRI data from the open-access spine-generic project were used. The dataset aggregates 42 sites worldwide and consists of 260 healthy subjects and includes T1w and T2w contrasts. To simulate atrophy, each volume was globally rescaled at various scaling factors. Moreover, to simulate patient repositioning, random rigid transformations were applied. Using the DeepSeg algorithm from the Spinal Cord Toolbox, the spinal cord was segmented and vertebral levels were identified. Then, the average CSA between C3-C5 vertebral levels was computed for each Monte Carlo sample, allowing us to derive measures of atrophy, intra/inter-subject variability, and sample-size calculations.

The minimum sample size required to detect an atrophy of 2% between unpaired study arms, commonly seen in MS studies, was 467 +/− 13.9 using T1w and 467 +/− 3.2 using T2w images. The minimum sample size to detect a longitudinal atrophy (between paired study arms) of 0.8% was 60 +/− 25.1 using T1w and 10 +/− 1.2 using T2w images. At the intra-subject level, the estimated CSA, observed in this study, showed good precision compared to other studies with COVs (across Monte Carlo transformations) of 0.8% for T1w and 0.6% for T2w images.

While these sample sizes seem small, we would like to stress that these results correspond to a “best case” scenario, in that the dataset used here was of particularly good quality and the model for simulating atrophy does not encompass all the variability met in real-life datasets. The simulated atrophy and scan-rescan variability may over-simplify the biological reality. The proposed framework is open-source and available at https://csa-atrophy.readthedocs.io/.

Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners

•We present Neuroharmony, a harmonization tool for images from unseen scanners. •We developed Neuroharmony using a total of 15,026 sMRI images. •The tool was able to reduce scanner-related bias from unseen scans. •Neuroharmony represents a significant step towards imaging-based clinical tools. •Neuroharmony is available at https://github.com/garciadias/Neuroharmony .

Extrapyramidal plasticity predicts recovery after spinal cord injury

Spinal cord injury (SCI) leads to wide-spread neurodegeneration across the neuroaxis. We explored trajectories of surface morphology, demyelination and iron concentration within the basal ganglia-thalamic circuit over 2 years post-SCI. This allowed us to explore the predictive value of neuroimaging biomarkers and determine their suitability as surrogate markers for interventional trials. Changes in markers of surface morphology, myelin and iron concentration of the basal ganglia and thalamus were estimated from 182 MRI datasets acquired in 17 SCI patients and 21 healthy controls at baseline (1-month post injury for patients), after 3, 6, 12, and 24 months. Using regression models, we investigated group difference in linear and non-linear trajectories of these markers. Baseline quantitative MRI parameters were used to predict 24-month clinical outcome. Surface area contracted in the motor (i.e. lower extremity) and pulvinar thalamus, and striatum; and expanded in the motor thalamus and striatum in patients compared to controls over 2-years. In parallel, myelin-sensitive markers decreased in the thalamus, striatum, and globus pallidus, while iron-sensitive markers decreased within the left caudate. Baseline surface area expansions within the striatum (i.e. motor caudate) predicted better lower extremity motor score at 2-years. Extensive extrapyramidal neurodegenerative and reorganizational changes across the basal ganglia-thalamic circuitry occur early after SCI and progress over time; their magnitude being predictive of functional recovery. These results demonstrate a potential role of extrapyramidal plasticity during functional recovery after SCI.

Tracking the neurodegenerative gradient after spinal cord injury

OBJECTIVE

To quantify neurodegenerative changes along the cervical spinal cord rostral to a spinal cord injury (SCI) by means of quantitative MRI (qMRI) and to determine its relationship with clinical impairment.

METHODS

Thirty chronic SCI patients (15 tetraplegics and 15 paraplegics) and 23 healthy controls underwent a high-resolution T1-weighted and myelin-sensitive magnetization transfer (MT) MRI. We assessed macro- and microstructural changes along the cervical cord from levels C1 to C4, calculating cross-sectional spinal cord area, its anterior-posterior and left-right width and myelin content (i.e. MT). Regression analysis determined associations between qMRI parameters and clinical impairment.

RESULTS

In SCI patients, cord area decreased by 2.67 mm² (p = 0.004) and left-right width decreased by 0.35 mm (p = 0.002) per cervical cord level in the caudal direction when compared to the healthy controls. This gradient of neurodegeneration was greater in tetraplegic than paraplegics in the cross-sectional cervical cord area (by 3.28 mm², p = 0.011), left-right width (by 0.36 mm, p = 0.03), and mean cord MT (by 0.13%, p = 0.04), but independant of lesion severity (p > 0.05). Higher lesion level was associated with greater magnitudes of neurodegeneration. Greater loss in myelin content in the dorsal columns and spinothalamic tract was associated with worse light touch (p = 0.016) and pin prick score (p = 0.024), respectively.

CONCLUSIONS

A gradient of neurodegeneration is evident in the cervical cord remote from a SCI. Tract-specific associations with appropriate clinical outcomes highlight that remote neurodegenerative changes are clinically eloquent. Monitoring the neurodegenerative gradient could be used to track treatment effects of regenerative and neuroprotective agents, both in trials targeting cervical and thoracic SCI patients.

The effect of the MR pulse sequence on the regional corpus callosum morphometry

Background and purposes

Brain morphometry is an important assessment technique to assess certain morphological brain features of various brain regions, which can be quantified in vivo by using high-resolution structural magnetic resonance (MR) imaging. This study aims to investigate the effect of different types of pulse sequence on regional corpus callosum (CC) morphometry analysis.

Materials and methods

Twenty-one healthy volunteers were scanned twice on the same 3T MRI scanner (Magnetom Trio, Siemens, Erlangen, Germany) equipped with an 8-channel head coil. Two different MR pulse sequences were applied to acquire high-resolution 3D T1-weighted images: magnetization-prepared rapid gradient-echo (MP-RAGE) and modified driven equilibrium Fourier transform (MDEFT) pulse sequence. Image quality measurements such as SNR, contrast-to-noise ratio, and relative contrast were calculated for each pulse sequence images independently. The values of corpus callosum volume were calculated based on the vertex of reconstructed surfaces. The paired dependent t test was applied to compare the means of two matched groups.

Results

Three sub-regional CC, namely anterior, mid-anterior, and posterior, resulted in an estimated volume difference between MDEFT and MP-RAGE pulse sequences. Central and mid-posterior sub-regional CC volume resulted in not significant difference between the two named pulse sequences.

Conclusion

The findings of this study demonstrate that combining data from different pulse sequences in a multisite study could make some variations in the results.

Optimization of magnetization-prepared rapid gradient echo (MP-RAGE) sequence for neonatal brain MRI

BACKGROUND

Sequence optimization in neonates might improve detection sensitivity of abnormalities for a variety of conditions. However this has been historically challenging because tissue properties such as the longitudinal relaxation time and proton density differ significantly between neonates and adults.

OBJECTIVE

To optimize the magnetization-prepared rapid gradient echo (MP-RAGE) sequence to enhance both signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) efficiencies.

MATERIALS AND METHODS

We optimized neonatal MP-RAGE sequence through (1) reducing receive bandwidth to decrease noise, (2) shortening acquisition train length (acquisition number per repetition time or total number of read-out radiofrequency rephrasing pulses) using slice partial Fourier acquisition and (3) simulating the solution of Bloch's equation under optimal receive bandwidth and acquisition train length. Using the optimized sequence parameters, we scanned 12 healthy full-term infants within 2 weeks of birth and four preterm infants at 40 weeks' corrected age.

RESULTS

Compared with a previously published neonatal protocol, we were able to reduce the total scan time by reduce the total scan time by 60% and increase the average SNR efficiency by 160% (P<0.001) and the average CNR efficiency by 26% (P=0.029).

CONCLUSION

Our in vivo neonatal brain imaging experiments confirmed that both SNR and CNR efficiencies significantly increased with our proposed protocol. Our proposed optimization methodology could be readily extended to other populations (e.g., older children, adults), as well as different organ systems, field strengths and MR sequences.

Magnetic resonance imaging does not reveal structural alterations in the brain of grapheme-color synesthetes

Several publications have reported structural changes in the brain of synesthetes compared to controls, either local differences or differences in connectivity. In the present study, we pursued this quest for structural brain differences that might support the subjective experience of synesthesia. In particular, for the first time in this field, we investigated brain folding in comparing 45 sulcal shapes in each hemisphere of control and grapheme-color synesthete populations. To overcome flaws relative to data interpretation based only on p-values, common in the synesthesia literature, we report confidence intervals of effect sizes. Moreover, our statistical maps are displayed without introducing the classical, but misleading, p-value level threshold. We adopt such a methodological procedure to facilitate appropriate data interpretation and promote the "New Statistics" approach. Based on structural or diffusion magnetic resonance imaging data, we did not find any strong cerebral anomaly, in sulci, tissue volume, tissue density or fiber organization that could support synesthetic color experience. Finally, by sharing our complete datasets, we strongly support the multi-center construction of a sufficient large dataset repository for detecting, if any, subtle brain differences that may help understanding how a subjective experience, such as synesthesia, is mentally constructed.

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

Improving structural brain images acquired with the 3D FLASH sequence

The three-dimension Fast Low Angle SHot Magnetic Resonance Imaging (3D FLASH) sequence has been widely adopted in medical diagnostic imaging because of its availability, simplicity, and high spatial resolution. To improve the quality of structural brain images acquired with the 3D FLASH sequence, we developed a parameter optimization scheme and image inhomogeneity correction methods. The optimal imaging parameters were determined by maximizing gray-matter and white-matter CNR efficiency. Compared to protocols based on published parameters, applying the proposed optimal imaging parameters increased CNR efficiency by >10%. Image inhomogeneity, including signal and CNR inhomogeneity, was corrected by the choice of an optimal flip angle, estimated transmit function, and estimated receive sensitivity. As a result, our optimization and image inhomogeneity correction greatly improved the quality of images acquired with the 3D FLASH sequence.

Relationship between Clinical Parameters and Brain Structure in Sporadic Amyotrophic Lateral Sclerosis Patients According to Onset Type: A Voxel-Based Morphometric Study

Background and purpose

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing, phenotypically heterogeneous neurodegenerative disease affecting mainly the motor neuron system. The present voxel-based morphometry (VBM) study investigated whether patterns of brain atrophy differ among sporadic ALS subtypes.

Material and methods

Sporadic ALS patients (n = 62) with normal cognition and age-matched healthy controls (n = 57) were included in the study. ALS patients were divided into limb- and bulbar-onset groups according to clinical manifestations at symptom onset (n = 48 and 14, respectively). Clinical measures were ALS Functional Rating Scale-Revised (ALSFRS-R) score, disease duration, and forced vital capacity (FVC). Patterns of brain atrophy between ALS subgroups were compared by VBM.

Results

In limb-onset ALS patients, atrophy was largely confined to the motor cortex and adjacent pre- and postcentral regions. However, in the bulbar-onset group, affected regions were more widespread and included these same areas but also extended to the bilateral frontotemporal and left superior temporal and supramarginal gyri, and multiple regression analysis revealed that their ALSFRS-R scores were associated with extensive loss of gray matter while FVC was related to atrophy in subcortical regions of the left superior temporal gyrus. In limb-onset ALS patients, disease duration was related to the degree of atrophy in the motor and adjacent areas.

Conclusion

Sporadic ALS subtypes show different patterns of brain atrophy. Neural networks related to limb and bulbar motor functions in each ALS subtype may underlie their distinct patterns of cerebral atrophy. That is, more extensive cortical and subcortical atrophy is correlated with greater ALSFRS-R severity and shorter disease duration in the bulbar-onset subtype and may explain the poor prognosis of these patients.

Structural explanation of poor prognosis of amyotrophic lateral sclerosis in the non-demented state

BACKGROUND AND PURPOSE

Amyotrophic lateral sclerosis (ALS), a motor neuron disease, is associated with various cortical symptoms including mild cognitive decline with behavior changes, suggesting the involvement of extra-motor areas in ALS. Our aim was to investigate the specific patterns of brain atrophy in sporadic, impaired ALS patients without commonly known genetic mutations using voxel-based morphometry.

MATERIALS AND METHODS

Forty-seven patients with sporadic ALS and 28 age-matched healthy controls were recruited. ALS participants were divided into three groups according to comprehensive neuropsychological testing: pure (ALS-pure), cognitive impairment (ALSci) and behavioral impairment (ALSbi). Quantitative comparison of brain atrophy patterns was performed amongst these three groups using voxel-based analysis. All analyses were adjusted for total intracranial volume, age, sex, disease duration and functional disability score.

RESULTS

The ALSci group exhibited decreased volume in the left cerebellum, fusiform gyrus, optic radiations and corticospinal tracts compared to healthy controls. ALSci patient imaging showed decreased brain volume in the bilateral cerebellum, right putamen gray matter and bilateral superior longitudinal fasciculi white matter compared to pure ALS patients (P < 0.001 uncorrected, corrected for the entire volume). Compared to healthy controls, ALS-pure and ALSbi groups did not show any significant volume changes in gray and white matter.

CONCLUSIONS

These findings also support the hypothesis that ALS pathogenesis has a dual focality of onset (cortex and anterior horn) with contiguous spread outwards. Additionally, neuropsychological features may be an important predictor of progression and survival rates in ALS.

Power estimation for non-standardized multisite studies

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

The Heterogeneity in Retrieved Relations between the Personality Trait 'Harm Avoidance' and Gray Matter Volumes Due to Variations in the VBM and ROI Labeling Processing Settings

Concerns are raising about the large variability in reported correlations between gray matter morphology and affective personality traits as ‘Harm Avoidance’ (HA). A recent review study (Mincic 2015) stipulated that this variability could come from methodological differences between studies. In order to achieve more robust results by standardizing the data processing procedure, as a first step, we repeatedly analyzed data from healthy females while changing the processing settings (voxel-based morphology (VBM) or region-of-interest (ROI) labeling, smoothing filter width, nuisance parameters included in the regression model, brain atlas and multiple comparisons correction method). The heterogeneity in the obtained results clearly illustrate the dependency of the study outcome to the opted analysis settings. Based on our results and the existing literature, we recommended the use of VBM over ROI labeling for whole brain analyses with a small or intermediate smoothing filter (5-8mm) and a model variable selection step included in the processing procedure. Additionally, it is recommended that ROI labeling should only be used in combination with a clear hypothesis and that authors are encouraged to report their results uncorrected for multiple comparisons as supplementary material to aid review studies.

Neurobiological origin of spurious brain morphological changes: A quantitative MRI study

The high gray‐white matter contrast and spatial resolution provided by T1‐weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1‐weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1‐weighted images (R₁ (=1/T1), R₂*, and PD) in a large cohort of healthy subjects (n = 120, aged 18–87 years). Synthetic T1‐weighted images were calculated from these quantitative maps and used to extract morphometry features—gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue—myelination, iron, and water content—on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp 37:1801–1815, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Tracking sensory system atrophy and outcome prediction in spinal cord injury

Objective

In patients with subacute spinal cord injury (SCI), the motor system undergoes progressive structural changes rostral to the lesion, which are associated with motor outcome. The extent to which the sensory system is affected and how this relates to sensory outcome are uncertain.

Methods

Changes in the sensory system were prospectively followed by applying a comprehensive magnetic resonance imaging (MRI) protocol to 14 patients with subacute traumatic SCI at baseline, 2 months, 6 months, and 12 months after injury, combined with a full neurological examination and comprehensive pain assessment. Eighteen controls underwent the same MRI protocol. T1‐weighted volumes, myelin‐sensitive magnetization transfer saturation (MT), and longitudinal relaxation rate (R1) mapping provided data on spinal cord and brain morphometry and microstructure. Regression analysis assessed the relationship between MRI readouts and sensory outcomes.

Results

At 12 months from baseline, sensory scores were unchanged and below‐level neuropathic pain became prominent. Compared with controls, patients showed progressive degenerative changes in cervical cord and brain morphometry across the sensory system. At 12 months, MT and R1 were reduced in areas of structural decline. Sensory scores at 12 months correlated with rate of change in cord area and brain volume and decreased MT in the spinal cord at 12 months.

Interpretation

This study has demonstrated progressive atrophic and microstructural changes across the sensory system with a close relation to sensory outcome. Structural MRI protocols remote from the site of lesion provide new insights into neuronal degeneration underpinning sensory disturbance and have potential as responsive biomarkers of rehabilitation and treatment interventions. Ann Neurol 2015;78:Ann Neurol 2015;78:679–696

Effects of an opioid (proenkephalin) polymorphism on neural response to errors in health and cocaine use disorder

Chronic exposure to drugs of abuse perturbs the endogenous opioid system, which plays a critical role in the development and maintenance of addictive disorders. Opioid genetics may therefore play an important modulatory role in the expression of substance use disorders, but these genes have not been extensively characterized, especially in humans. In the current imaging genetics study, we investigated a single nucleotide polymorphism (SNP) of the protein-coding proenkephalin gene (PENK: rs2609997, recently shown to be associated with cannabis dependence) in 55 individuals with cocaine use disorder and 37 healthy controls. Analyses tested for PENK associations with fMRI response to error (during a classical color-word Stroop task) and gray matter volume (voxel-based morphometry) as a function of Diagnosis (cocaine, control). Results revealed whole-brain Diagnosis×PENK interactions on the neural response to errors (fMRI error>correct contrast) in the right putamen, left rostral anterior cingulate cortex/medial orbitofrontal cortex, and right inferior frontal gyrus; there was also a significant Diagnosis×PENK interaction on right inferior frontal gyrus gray matter volume. These interactions were driven by differences between individuals with cocaine use disorders and controls that were accentuated in individuals carrying the higher-risk PENK C-allele. Taken together, the PENK polymorphism-and potentially opioid neurotransmission more generally-modulates functioning and structural integrity of brain regions previously implicated in error-related processing. PENK could potentially render a subgroup of individuals with cocaine use disorder (i.e., C-allele carriers) more sensitive to mistakes or other related challenges; in future studies, these results could contribute to the development of individualized genetics-informed treatments.

Improved visibility of brain tumors in synthetic MP-RAGE anatomies with pure T1 weighting

Conventional MRI for brain tumor diagnosis employs T2 -weighted and contrast-enhanced T1 -weighted sequences. Non-enhanced T1 -weighted images provide improved anatomical details for precise tumor location, but reduced tumor-to-background contrast as elevated T1 and proton density (PD) values in tumor tissue affect the signal inversely. Radiofrequency (RF) coil inhomogeneities may further mask tumor and edema outlines. To overcome this problem, the aims of this work were to employ quantitative MRI techniques to create purely T1 -weighted synthetic anatomies which can be expected to yield improved tissue and tumor-to-background contrasts, to compare the quality of conventional and synthetic anatomies, and to investigate optical contrast and visibility of brain tumors and edema in synthetic anatomies. Conventional magnetization-prepared rapid acquisition of gradient echoes (MP-RAGE) anatomies and maps of T1 , PD and RF coil profiles were acquired in comparable and clinically feasible times. Three synthetic MP-RAGE anatomies (PD T1 weighting both with and without RF bias; pure T1 weighting) were calculated for healthy subjects and 32 patients with brain tumors. In healthy subjects, the PD T1 -weighted synthetic anatomies with RF bias precisely matched the conventional anatomies, yielding high signal-to-noise (SNR) and contrast-to-noise (CNR) ratios. Pure T1 weighting yielded lower SNR, but high CNR, because of increased optical contrasts. In patients with brain tumors, synthetic anatomies with pure T1 weighting yielded significant increases in optical contrast and improved visibility of tumor and edema in comparison with anatomies reflecting conventional T1 contrasts. In summary, the optimized purely T1 -weighted synthetic anatomy with an isotropic resolution of 1 mm, as proposed in this work, considerably enhances optical contrast and visibility of brain tumors and edema.

Whole Brain Volume Measured from 1.5T versus 3T MRI in Healthy Subjects and Patients with Multiple Sclerosis

BACKGROUND

Whole brain atrophy is a putative outcome measure in monitoring relapsing‐remitting multiple sclerosis (RRMS). With the ongoing MRI transformation from 1.5T to 3T, there is an unmet need to calibrate this change. We evaluated brain parenchymal volumes (BPVs) from 1.5T versus 3T in MS and normal controls (NC).

METHODS

We studied MS [n = 26, age (mean, range) 43 (21‐55), 22 (85%) RRMS, Expanded Disability Status Scale (EDSS) 1.98 (0‐6.5), timed 25 foot walk (T25FW) 5.95 (3.2‐33.0 seconds)] and NC [n = 9, age 45 (31‐53)]. Subjects underwent 1.5T (Phillips) and 3T (GE) 3‐dimensional T1‐weighted scans to derive normalized BPV from an automated SIENAX pipeline. Neuropsychological testing was according to consensus panel recommendations.

RESULTS

BPV‐1.5T was higher than BPV‐3T [mean (95% CI) + 45.7 mL (+35.3, +56.1), P < .00001], most likely due to improved tissue‐CSF contrast at 3T. BPV‐3T showed a larger volume decrease and larger effect size in detecting brain atrophy in MS versus NC [−74.5 mL (−126.5, −22.5), P = .006, d = .92] when compared to BPV‐1.5T [−51.3.1 mL (−99.8, −2.8), P = .04, d = .67]. Correlations between BPV‐1.5T and EDSS (r = −.43, P = .027) and BPV‐3T and EDSS (r = −.49, P = .011) and between BPV‐1.5T and T25FW (r = −.46, P = .018) and BPV‐3T and T25FW (r = −.56, P = .003) slightly favored 3T. BPV‐cognition correlations were significant (P < .05) for 6 of 11 subscales to a similar degree at 1.5T (r range = .44‐.58) and 3T (r range = .43‐.53).

CONCLUSIONS

Field strength may impact whole brain volume measurements in patients with MS though the differences are not too divergent between 1.5T and 3T.

Desperately seeking grey matter volume changes in sleep apnea: A methodological review of magnetic resonance brain voxel-based morphometry studies

Cognitive impairment related to obstructive sleep apnea might be explained by subtle changes in brain anatomy. This has been mainly investigated using magnetic resonance brain scans coupled with a voxel-based morphometry analysis. However, this approach is prone to several methodological pitfalls that may explain the large discrepancy in the results reported in the literature. We critically reviewed twelve papers addressing grey matter volume modifications in association with obstructive sleep apnea. Finally, based on strict methodological criteria, only three studies reported robust, but conflicting, results. No clear evidence has emerged and exploring brain alteration due to obstructive sleep apnea should thus be considered as an open field. We provide recommendations for designing additional robust voxel-based morphometry studies, notably the use of larger cohorts, which is the only way to solve the underpowered issue and the underestimated role of confounders in neuroimaging studies.

False positive rates in Voxel-based Morphometry studies of the human brain: should we be worried?

Voxel-based Morphometry (VBM) is a widely used automated technique for the analysis of neuroanatomical images. Despite its popularity within the neuroimaging community, there are outstanding concerns about its potential susceptibility to false positive findings. Here we review the main methodological factors that are known to influence the results of VBM studies comparing two groups of subjects. We then use two large, open-access data sets to empirically estimate false positive rates and how these depend on sample size, degree of smoothing and modulation. Our review and investigation provide three main results: (i) when groups of equal size are compared false positive rate is not higher than expected, i.e. about 5%; (ii) the sample size, degree of smoothing and modulation do not appear to influence false positive rate; (iii) when they exist, false positive findings are randomly distributed across the brain. These results provide reassurance that VBM studies comparing groups are not vulnerable to the higher than expected false positive rates that are evident in single case VBM.

Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors

Purpose

We tested the validity of a freely available segmentation pipeline to measure compartmental brain volumes from 3T MRI in patients with multiple sclerosis (MS). Our primary focus was methodological to explore the effect of segmentation corrections on the clinical relevance of the output metrics.

Methods

Three-dimensional T1-weighted images were acquired to compare 61 MS patients to 30 age- and gender-matched normal controls (NC). We also tested the within patient MRI relationship to disability (eg, expanded disability status scale [EDSS] score) and cognition. Statistical parametric mapping v. 8 (SPM8)-derived gray matter (GMF), white matter (WMF), and total brain parenchyma fractions (BPF) were derived before and after correcting errors from T1 hypointense MS lesions and/or ineffective deep GM contouring.

Results

MS patients had lower GMF and BPF as compared to NC (P<.05). Cognitively impaired patients had lower BPF than cognitively preserved patients (P<.05). BPF was related to EDSS; BPF and GMF were related to disease duration (all P<.05). Errors caused bias in GMFs and WMFs but had no discernable influence on BPFs or any MRI-clinical associations.

Conclusions

We report the validity of a segmentation pipeline for the detection of MS-related brain atrophy with 3T MRI. Longitudinal studies are warranted to extend these results.

Grey matter volumetric changes related to recovery from hand paresis after cortical sensorimotor stroke

Preclinical studies using animal models have shown that grey matter plasticity in both perilesional and distant neural networks contributes to behavioural recovery of sensorimotor functions after ischaemic cortical stroke. Whether such morphological changes can be detected after human cortical stroke is not yet known, but this would be essential to better understand post-stroke brain architecture and its impact on recovery. Using serial behavioural and high-resolution magnetic resonance imaging (MRI) measurements, we tracked recovery of dexterous hand function in 28 patients with ischaemic stroke involving the primary sensorimotor cortices. We were able to classify three recovery subgroups (fast, slow, and poor) using response feature analysis of individual recovery curves. To detect areas with significant longitudinal grey matter volume (GMV) change, we performed tensor-based morphometry of MRI data acquired in the subacute phase, i.e. after the stage compromised by acute oedema and inflammation. We found significant GMV expansion in the perilesional premotor cortex, ipsilesional mediodorsal thalamus, and caudate nucleus, and GMV contraction in the contralesional cerebellum. According to an interaction model, patients with fast recovery had more perilesional than subcortical expansion, whereas the contrary was true for patients with impaired recovery. Also, there were significant voxel-wise correlations between motor performance and ipsilesional GMV contraction in the posterior parietal lobes and expansion in dorsolateral prefrontal cortex. In sum, perilesional GMV expansion is associated with successful recovery after cortical stroke, possibly reflecting the restructuring of local cortical networks. Distant changes within the prefrontal-striato-thalamic network are related to impaired recovery, probably indicating higher demands on cognitive control of motor behaviour.

Multimodal evidence of regional midcingulate gray matter volume underlying conflict monitoring

Functional neuroimaging studies have long implicated the mid-cingulate cortex (MCC) in conflict monitoring, but it is not clear whether its structural integrity (i.e., the gray matter volume) influences its conflict monitoring function. In this multimodal study, we used T1-weighted MRI scans as well as event-related potentials (ERPs) to test whether the MCC gray matter volume is associated with the electrocortical marker (i.e., No-go N200 ERP component) of conflict monitoring in healthy individuals. The specificity of such a relationship in health was determined in two ways: by (A) acquiring the same data from individuals with cocaine use disorder (CUD), known to have deficits in executive function including behavioral monitoring; and (B) acquiring the P300 ERP component that is linked with attention allocation and not specifically with conflict monitoring. Twenty-five (39.1 ± 8.4 years; 8 females) healthy individuals and 25 (42.7 ± 5.9 years; 6 females) individuals with CUD underwent a rewarded Go/No-go task during which the ERP data was collected, and they also underwent a structural MRI scan. The whole brain regression analysis showed a significant correlation between MCC structural integrity and the well-known ERP measure of conflict monitoring (N200, but not the P300) in healthy individuals, which was absent in CUD who were characterized by reduced MCC gray matter volume, N200 abnormalities as well as reduced task accuracy. In individuals with CUD instead, the N200 amplitude was associated with drug addiction symptomatology. These results show that the integrity of MCC volume is directly associated with the electrocortical correlates of conflict monitoring in healthy individuals, and such an association breaks down in psychopathologies that impact these brain processes. Taken together, this MCC–N200 association may serve as a biomarker of improved behavioral monitoring processes in diseased populations.

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No-go N200 amplitude is correlated with gray matter volume of the midcingulate cortex in controls.

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Such N200-midcingulate association is absent in individuals with cocaine use disorder (CUD).

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In the CUD group, No-go N200 amplitude is correlated with withdrawal symptoms.

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N200-midcingulate association can serve as a biomarker of intact conflict monitoring.

Optimizing the magnetization-prepared rapid gradient-echo (MP-RAGE) sequence

The three-dimension (3D) magnetization-prepared rapid gradient-echo (MP-RAGE) sequence is one of the most popular sequences for structural brain imaging in clinical and research settings. The sequence captures high tissue contrast and provides high spatial resolution with whole brain coverage in a short scan time. In this paper, we first computed the optimal k-space sampling by optimizing the contrast of simulated images acquired with the MP-RAGE sequence at 3.0 Tesla using computer simulations. Because the software of our scanner has only limited settings for k-space sampling, we then determined the optimal k-space sampling for settings that can be realized on our scanner. Subsequently we optimized several major imaging parameters to maximize normal brain tissue contrasts under the optimal k-space sampling. The optimal parameters are flip angle of 12°, effective inversion time within 900 to 1100 ms, and delay time of 0 ms. In vivo experiments showed that the quality of images acquired with our optimal protocol was significantly higher than that of images obtained using recommended protocols in prior publications. The optimization of k-spacing sampling and imaging parameters significantly improved the quality and detection sensitivity of brain images acquired with MP-RAGE.

Functional, structural, and emotional correlates of impaired insight in cocaine addiction

IMPORTANCE

Individuals with cocaine use disorder (CUD) have difficulty monitoring ongoing behavior, possibly stemming from dysfunction of brain regions mediating insight and self-awareness.

OBJECTIVE

To investigate the neural correlates of impaired insight in addiction using a combined functional magnetic resonance imaging and voxel-based morphometry approach.

DESIGN, SETTING, AND PARTICIPANTS

This multimodal imaging study was performed at the Clinical Research Center at Brookhaven National Laboratory. The study included 33 CUD cases and 20 healthy controls.

MAIN OUTCOMES AND MEASURES

Functional magnetic resonance imaging, voxel-based morphometry, Levels of Emotional Awareness Scale, and drug use variables.

RESULTS

Compared with the other 2 study groups, the impaired insight CUD group had lower error-induced rostral anterior cingulate cortex (rACC) activity as associated with more frequent cocaine use, less gray matter within the rACC, and lower Levels of Emotional Awareness Scale scores.

CONCLUSIONS AND RELEVANCE

These results point to rACC functional and structural abnormalities and diminished emotional awareness in a subpopulation of CUD cases characterized by impaired insight. Because the rACC has been implicated in appraising the affective and motivational significance of errors and other types of self-referential processing, functional and structural abnormalities in this region could result in lessened concern (frequently ascribed to minimization and denial) about behavioral outcomes that could potentially culminate in increased drug use. Treatments that target this CUD subgroup could focus on enhancing the salience of errors (eg, lapses).

Impact of image acquisition on voxel-based-morphometry investigations of age-related structural brain changes

A growing number of magnetic resonance imaging studies employ voxel-based morphometry (VBM) to assess structural brain changes. Recent reports have shown that image acquisition parameters may influence VBM results. For systematic evaluation, gray-matter-density (GMD) changes associated with aging were investigated by VBM employing acquisitions with different radiofrequency head coils (12-channel matrix coil vs. 32-channel array), different pulse sequences (MP-RAGE vs. MP2RAGE), and different voxel dimensions (1mm vs. 0.8mm). Thirty-six healthy subjects, classified as young, middle-aged, or elderly, participated in the study. Two-sample and paired t-tests revealed significant effects of acquisition parameters (coil, pulse sequence, and resolution) on the estimated age-related GMD changes in cortical and subcortical regions. Potential advantages in tissue classification and segmentation were obtained for MP2RAGE. The 32-channel coil generally outperformed the 12-channel coil, with more benefit for MP2RAGE. Further improvement can be expected from higher resolution if the loss in SNR is accounted for. Use of inconsistent acquisition parameters in VBM analyses is likely to introduce systematic bias. Overall, acquisition and protocol changes require careful adaptations of the VBM analysis strategy before generalized conclusion can be drawn.

MRI investigation of the sensorimotor cortex and the corticospinal tract after acute spinal cord injury: a prospective longitudinal study

Background

In patients with chronic spinal cord injury, imaging of the spinal cord and brain above the level of the lesion provides evidence of neural degeneration; however, the spatial and temporal patterns of progression and their relation to clinical outcomes are uncertain. New interventions targeting acute spinal cord injury have entered clinical trials but neuroimaging outcomes as responsive markers of treatment have yet to be established. We aimed to use MRI to assess neuronal degeneration above the level of the lesion after acute spinal cord injury.

Methods

In our prospective longitudinal study, we enrolled patients with acute traumatic spinal cord injury and healthy controls. We assessed patients clinically and by MRI at baseline, 2 months, 6 months, and 12 months, and controls by MRI at the same timepoints. We assessed atrophy in white matter in the cranial corticospinal tracts and grey matter in sensorimotor cortices by tensor-based analyses of T1-weighted MRI data. We used cross-sectional spinal cord area measurements to assess atrophy at cervical level C2/C3. We used myelin-sensitive magnetisation transfer (MT) and longitudinal relaxation rate (R1) maps to assess microstructural changes associated with myelin. We also assessed associations between MRI parameters and clinical improvement. All analyses of brain scans done with statistical parametric mapping were corrected for family-wise error.

Findings

Between Sept 17, 2010, and Dec 31, 2012, we recruited 13 patients and 18 controls. In the 12 months from baseline, patients recovered by a mean of 5·27 points per log month (95% CI 1·91–8·63) on the international standards for the neurological classification of spinal cord injury (ISNCSCI) motor score (p=0·002) and by 10·93 points per log month (6·20–15·66) on the spinal cord independence measure (SCIM) score (p<0·0001). Compared with controls, patients showed a rapid decline in cross-sectional spinal cord area (patients declined by 0·46 mm per month compared with a stable cord area in controls; p<0·0001). Patients had faster rates than controls of volume decline of white matter in the cranial corticospinal tracts at the level of the internal capsule (right Z score 5·21, p=0·0081; left Z score 4·12, p=0·0004) and right cerebral peduncle (Z score 3·89, p=0·0302) and of grey matter in the left primary motor cortex (Z score 4·23, p=0·041). Volume changes were paralleled by significant reductions of MT and R1 in the same areas and beyond. Improvements in SCIM scores at 12 months were associated with a reduced loss in cross-sectional spinal cord area over 12 months (Pearson's correlation 0·77, p=0·004) and reduced white matter volume of the corticospinal tracts at the level of the right internal capsule (Z score 4·30, p=0·0021), the left internal capsule (Z score 4·27, p=0·0278), and left cerebral peduncle (Z score 4·05, p=0·0316). Improvements in ISNCSCI motor scores were associated with less white matter volume change encompassing the corticospinal tract at the level of the right internal capsule (Z score 4·01, p<0·0001).

Interpretation

Extensive upstream atrophic and microstructural changes of corticospinal axons and sensorimotor cortical areas occur in the first months after spinal cord injury, with faster degenerative changes relating to poorer recovery. Structural volumetric and microstructural MRI protocols remote from the site of spinal cord injury could serve as neuroimaging biomarkers in acute spinal cord injury.

Funding

SRH Holding, Swiss National Science Foundation, Clinical Research Priority Program “NeuroRehab” University of Zurich, Wellcome Trust.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Perfumers' expertise induces structural reorganization in olfactory brain regions

The human brain's ability to adapt to environmental changes is obvious in specific sensory domains of experts, and olfaction is one of the least investigated senses. As we have previously demonstrated that olfactory expertise is related to functional brain modifications, we investigated here whether olfactory expertise is also coupled with structural changes. We used voxel-based morphometry to compare the gray-matter volume in student and professional perfumers, as well as untrained control subjects, and accounted for all methodological improvements that have been recently developed to limit possible errors associated with image processing. In all perfumers, we detected an increase in gray-matter volume in the bilateral gyrus rectus/medial orbital gyrus (GR/MOG), an orbitofrontal area that surrounds the olfactory sulcus. In addition, gray-matter volume in the anterior PC and left GR/MOG was positively correlated with experience in professional perfumers. We concluded that the acute olfactory knowledge acquired through extensive olfactory training leads to the structural reorganization of olfactory brain areas.

Is DARTEL-based voxel-based morphometry affected by width of smoothing kernel and group size? A study using simulated atrophy

PURPOSE

To quantify to what extent the new registration method, DARTEL (Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra), may reduce the smoothing kernel width required and investigate the minimum group size necessary for voxel-based morphometry (VBM) studies.

MATERIALS AND METHODS

A simulated atrophy approach was employed to explore the role of smoothing kernel, group size, and their interactions on VBM detection accuracy. Group sizes of 10, 15, 25, and 50 were compared for kernels between 0-12 mm.

RESULTS

A smoothing kernel of 6 mm achieved the highest atrophy detection accuracy for groups with 50 participants and 8-10 mm for the groups of 25 at P < 0.05 with familywise correction. The results further demonstrated that a group size of 25 was the lower limit when two different groups of participants were compared, whereas a group size of 15 was the minimum for longitudinal comparisons but at P < 0.05 with false discovery rate correction.

CONCLUSION

Our data confirmed DARTEL-based VBM generally benefits from smaller kernels and different kernels perform best for different group sizes with a tendency of smaller kernels for larger groups. Importantly, the kernel selection was also affected by the threshold applied. This highlighted that the choice of kernel in relation to group size should be considered with care.

Chronic pelvic pain syndrome in men is associated with reduction of relative gray matter volume in the anterior cingulate cortex compared to healthy controls

PURPOSE

Although chronic pelvic pain syndrome impairs the life of millions of people worldwide, the exact pathomechanisms involved remain to be elucidated. As with other chronic pain syndromes, the central nervous system may have an important role in chronic pelvic pain syndrome. Thus, we assessed brain alterations associated with abnormal pain processing in patients with chronic pelvic pain syndrome.

MATERIALS AND METHODS

Using brain morphology assessment applying structural magnetic resonance imaging, we prospectively investigated a consecutive series of 20 men with refractory chronic pelvic pain syndrome, and compared these patients to 20 gender and age matched healthy controls. Between group differences in relative gray matter volume and the association with bother of chronic pelvic pain syndrome were assessed using whole brain covariate analysis.

RESULTS

Patients with chronic pelvic pain syndrome had a mean (± SD) age of 40 (± 14) years, a mean NIH-CPSI (National Institutes of Health Chronic Prostatitis Symptom Index) total score of 28 (± 6) and a mean pain subscale of 14 (± 3). In patients with chronic pelvic pain syndrome compared to healthy controls there was a significant reduction in relative gray matter volume in the anterior cingulate cortex of the dominant hemisphere. This finding correlated with the NIH-CPSI total score (r = 0.57) and pain subscale (r = 0.51).

CONCLUSIONS

Reduction in relative gray matter volume in the anterior cingulate cortex and correlation with bother of chronic pelvic pain syndrome suggest an essential role for the anterior cingulate cortex in chronic pelvic pain syndrome. Since this area is a core structure of emotional pain processing, central pathomechanisms of chronic pelvic pain syndrome may be considered a promising therapeutic target and may explain the often unsatisfactory results of treatments focusing on peripheral dysfunction.

The impact of lesion in-painting and registration methods on voxel-based morphometry in detecting regional cerebral gray matter atrophy in multiple sclerosis

BACKGROUND AND PURPOSE

VBM has been widely used to study GM atrophy in MS. MS lesions lead to segmentation and registration errors that may affect the reliability of VBM results. Improved segmentation and registration have been demonstrated by WM LI before segmentation. DARTEL appears to improve registration versus the USM. Our aim was to compare the performance of VBM-DARTEL versus VBM-USM and the effect of LI in the regional analysis of GM atrophy in MS.

MATERIALS AND METHODS

3T T1 MR imaging scans were acquired from 26 patients with RRMS and 28 age-matched NC. LI replaced WM lesions with normal-appearing WM intensities before image segmentation. VBM analysis was performed in SPM8 by using DARTEL and USM with and without LI, allowing the comparison of 4 VBM methods (DARTEL + LI, DARTEL - LI, USM + LI, and USM - LI). Accuracy of VBM was assessed by using NMI, CC, and a simulation analysis.

RESULTS

Overall, DARTEL + LI yielded the most accurate GM maps among the 4 methods (highest NMI and CC, P < .001). DARTEL + LI showed significant GM loss in the bilateral thalami and caudate nuclei in patients with RRMS versus NC. The other 3 methods overestimated the number of regions of GM loss in RRMS versus NC. LI improved the accuracy of both VBM methods. Simulated data suggested the accuracy of the results provided from patient MR imaging analysis.

CONCLUSIONS

We introduce a pipeline that shows promise in limiting segmentation and registration errors in VBM analysis in MS.

Quantitative and qualitative assessment of structural magnetic resonance imaging data in a two-center study

BACKGROUND

Multi-center magnetic resonance imaging (MRI) studies present an opportunity to advance research by pooling data. However, brain measurements derived from MR-images are susceptible to differences in MR-sequence parameters. It is therefore necessary to determine whether there is an interaction between the sequence parameters and the effect of interest, and to minimise any such interaction by careful choice of acquisition parameters. As an exemplar of the issues involved in multi-center studies, we present data from a study in which we aimed to optimize a set of volumetric MRI-protocols to define a protocol giving data that are consistent and reproducible across two centers and over time.

METHODS

Optimization was achieved based on data quality and quantitative measures, in our case using FreeSurfer and Voxel Based Morphometry approaches. Our approach consisted of a series of five comparisons. Firstly, a single-center dataset was collected, using a range of candidate pulse-sequences and parameters chosen on the basis of previous literature. Based on initial results, a number of minor changes were implemented to optimize the pulse-sequences, and a second single-center dataset was collected. FreeSurfer data quality measures were compared between datasets in order to determine the best performing sequence(s), which were taken forward to the next stage of testing. We subsequently acquired short-term and long-term two-center reproducibility data, and quantitative measures were again assessed to determine the protocol with the highest reproducibility across centers. Effects of a scanner software and hardware upgrade on the reproducibility of the protocols at one of the centers were also evaluated.

RESULTS

Assessing the quality measures from the first two datasets allowed us to define artefact-free protocols, all with high image quality as assessed by FreeSurfer. Comparing the quantitative test and retest measures, we found high within-center reproducibility for all protocols, but lower between-center reproducibility for some protocols than others. The upgrade showed no important effects.

CONCLUSIONS

We were able to determine (for the scanners used in this study) an optimised protocol, which gave the highest within- and between-center reproducibility of those assessed, and give details of this protocol here. More generally, we discuss some of the issues raised by multi-center studies and describe a methodical approach to take towards optimization and standardization, and recommend performing this kind of procedure to other investigators.

Structural and behavioral correlates of abnormal encoding of money value in the sensorimotor striatum in cocaine addiction

Abnormalities in frontostriatal systems are thought to be central to the pathophysiology of addiction, and may underlie the maladaptive processing of the highly generalizable reinforcer, money. Although abnormal frontostriatal structure and function have been observed in individuals addicted to cocaine, it is less clear how individual variability in brain structure is associated with brain function to influence behavior. Our objective was to examine frontostriatal structure and neural processing of money value in chronic cocaine users and closely matched healthy controls. A reward task that manipulated different levels of money was used to isolate neural activity associated with money value. Gray matter volume measures were used to assess frontostriatal structure. Our results indicated that cocaine users had an abnormal money value signal in the sensorimotor striatum (right putamen/globus pallidus) that was negatively associated with accuracy adjustments to money and was more pronounced in individuals with more severe use. In parallel, group differences were also observed in both the function and gray matter volume of the ventromedial prefrontal cortex; in the cocaine users, the former was directly associated with response to money in the striatum. These results provide strong evidence for abnormalities in the neural mechanisms of valuation in addiction and link these functional abnormalities with deficits in brain structure. In addition, as value signals represent acquired associations, their abnormal processing in the sensorimotor striatum, a region centrally implicated in habit formation, could signal disadvantageous associative learning in cocaine addiction.

Structural integrity of the prefrontal cortex modulates electrocortical sensitivity to reward

The P300 is a known ERP component assessing stimulus value, including the value of a monetary reward. In parallel, the incentive value of reinforcers relies on the PFC, a major cortical projection region of the mesocortical reward pathway. Here we show a significant positive correlation between P300 response to money (vs. no money) with PFC gray matter volume in the OFC, ACC, and dorsolateral and ventrolateral PFC in healthy control participants. In contrast, individuals with cocaine use disorders showed compromises in both P300 sensitivity to money and PFC gray matter volume in the ventrolateral PFC and OFC and their interdependence. These results document for the first time the importance of gray matter structural integrity of subregions of PFC to the reward-modulated P300 response.

Gene x disease interaction on orbitofrontal gray matter in cocaine addiction

CONTEXT

Long-term cocaine use has been associated with structural deficits in brain regions having dopamine-receptive neurons. However, the concomitant use of other drugs and common genetic variability in monoamine regulation present additional structural variability.

OBJECTIVE

To examine variations in gray matter volume (GMV) as a function of lifetime drug use and the genotype of the monoamine oxidase A gene, MAOA, in men with cocaine use disorders (CUD) and healthy male controls.

DESIGN

Cross-sectional comparison.

SETTING

Clinical Research Center at Brookhaven National Laboratory.

PATIENTS

Forty individuals with CUD and 42 controls who underwent magnetic resonance imaging to assess GMV and were genotyped for the MAOA polymorphism (categorized as high- and low-repeat alleles).

MAIN OUTCOME MEASURES

The impact of cocaine addiction on GMV, tested by (1) comparing the CUD group with controls, (2) testing diagnosis × MAOA interactions, and (3) correlating GMV with lifetime cocaine, alcohol, and cigarette smoking, and testing their unique contribution to GMV beyond other factors.

RESULTS

(1) Individuals with CUD had reductions in GMV in the orbitofrontal, dorsolateral prefrontal, and temporal cortex and the hippocampus compared with controls. (2) The orbitofrontal cortex reductions were uniquely driven by CUD with low- MAOA genotype and by lifetime cocaine use. (3) The GMV in the dorsolateral prefrontal cortex and hippocampus was driven by lifetime alcohol use beyond the genotype and other pertinent variables.

CONCLUSIONS

Long-term cocaine users with the low-repeat MAOA allele have enhanced sensitivity to gray matter loss, specifically in the orbitofrontal cortex, indicating that this genotype may exacerbate the deleterious effects of cocaine in the brain. In addition, long-term alcohol use is a major contributor to gray matter loss in the dorsolateral prefrontal cortex and hippocampus, and is likely to further impair executive function and learning in cocaine addiction.

A 3T MR imaging investigation of the topography of whole spinal cord atrophy in multiple sclerosis

BACKGROUND AND PURPOSE

Spinal cord atrophy is a common feature of MS. However, it is unknown which cord levels are most susceptible to atrophy. We performed whole cord imaging to identify the levels most susceptible to atrophy in patients with MS versus controls and also tested for differences among MS clinical phenotypes.

MATERIALS AND METHODS

Thirty-five patients with MS (2 with CIS, 27 with RRMS, 2 with SPMS, and 4 with PPMS phenotypes) and 27 healthy controls underwent whole cord 3T MR imaging. The spinal cord contour was segmented and assigned to bins representing each C1 to T12 vertebral level. Volumes were normalized, and group comparisons were age-adjusted.

RESULTS

There was a trend toward decreased spinal cord volume at the upper cervical levels in PPMS/SPMS versus controls. A trend toward increased spinal cord volume throughout the cervical and thoracic cord in RRMS/CIS versus controls reached statistical significance at the T10 vertebral level. A statistically significant decrease was found in spinal cord volume at the upper cervical levels in PPMS/SPMS versus RRMS/CIS.

CONCLUSIONS

Opposing pathologic factors impact spinal cord volume measures in MS. Patients with PPMS demonstrated a trend toward upper cervical cord atrophy. However patients with RRMS showed a trend toward increased volume at the cervical and thoracic levels, which most likely reflects inflammation or edema-related cord expansion. With the disease causing both expansion and contraction of the cord, the specificity of spinal cord volume measures for neuroprotective therapeutic effect may be limited.

The relationships among MRI-defined spinal cord involvement, brain involvement, and disability in multiple sclerosis

OBJECTIVE

To determine the interrelationships between MRI-defined lesion and atrophy measures of spinal cord involvement and brain involvement and their relationships to disability in a small cohort of patients with multiple sclerosis (MS).

BACKGROUND

Although it is known that cervical spinal cord atrophy correlates with disability in MS, it is unknown whether it is the most important determinant when compared to other regions of the central nervous system (CNS). Furthermore, it is not clear to what extent brain and cord lesions and atrophy are related.

DESIGN AND METHODS

3T MRI of the whole brain and whole spinal cord was obtained in 21 patients with MS, including 18 with relapsing-remitting, one with secondary progressive, one with primary progressive, and one with a clinically isolated syndrome. Brain global gray and white matter volumes were segmented with Statistical Parametric Mapping 8. Spinal cord contour volume was segmented in whole by a semi-automated method with bins assigned to either the cervical or thoracic regions. All CNS volumes were normalized by the intracranial volume. Brain and cord T2 hyperintense lesions were segmented using a semi-automated edge finding tool.

RESULTS

Among all MRI measures, only upper cervical spinal cord volume significantly correlated with Expanded Disability Status Scale score (r =-.515, P = .020). The brain cord relationships between whole or regional spinal cord volume or lesions and gray matter, white matter, or whole brain volume or whole brain lesions were generally weak and all nonsignificant.

CONCLUSIONS AND RELEVANCE

In this preliminary study of mildly disabled, treated MS patients, cervical spinal cord atrophy most strongly correlates with physical disability in MS when accounting for a wide range of other CNS measures of lesions and atrophy, including thoracic or whole spinal cord volume, and cerebral gray, white or whole brain volume. The weak relationship between spinal cord and brain lesions and atrophy may suggest that they progress rather independently in patients with MS.

Structural and functional bases for individual differences in motor learning

People vary in their ability to learn new motor skills. We hypothesize that between-subject variability in brain structure and function can explain differences in learning. We use brain functional and structural MRI methods to characterize such neural correlates of individual variations in motor learning. Healthy subjects applied isometric grip force of varying magnitudes with their right hands cued visually to generate smoothly-varying pressures following a regular pattern. We tested whether individual variations in motor learning were associated with anatomically colocalized variations in magnitude of functional MRI (fMRI) signal or in MRI differences related to white and grey matter microstructure. We found that individual motor learning was correlated with greater functional activation in the prefrontal, premotor, and parietal cortices, as well as in the basal ganglia and cerebellum. Structural MRI correlates were found in the premotor cortex [for fractional anisotropy (FA)] and in the cerebellum [for both grey matter density and FA]. The cerebellar microstructural differences were anatomically colocalized with fMRI correlates of learning. This study thus suggests that variations across the population in the function and structure of specific brain regions for motor control explain some of the individual differences in skill learning. This strengthens the notion that brain structure determines some limits to cognitive function even in a healthy population. Along with evidence from pathology suggesting a role for these regions in spontaneous motor recovery, our results also highlight potential targets for therapeutic interventions designed to maximize plasticity for recovery of similar visuomotor skills after brain injury.

Method for simultaneous voxel-based morphometry of the brain and cervical spinal cord area measurements using 3D-MDEFT

Purpose

To investigate whether a 3D-modified driven equilibrium Fourier transform (MDEFT)-based acquisition protocol established for brain morphometry also yields reliable information about the cross-sectional spinal cord area (SCA).

Materials and Methods

Images of brain and cervical cord of 10 controls and eight subjects with spinal cord injury (SCI) were acquired with the 3D-MDEFT-based imaging protocol and an 8-channel receive head coil. The new protocol was validated by two observers 1) comparing the SCA measured with the standard acquisition protocol (3D magnetization-prepared rapid acquisition gradient echo [MPRAGE] and dedicated spine coil) and the new protocol; and 2) determining the scan–rescan reproducibility of the new protocol.

Results

Scan–rescan reproducibility of SCA measurements with the MDEFT approach showed a similar precision for both observers with standard deviation (SD) <4.5 mm² and coefficient of variation (CV) ≤5.1%. Analysis of variance (ANOVA) revealed a main effect of observer and interaction between observer and scan protocol that could be primarily attributed to a small observer bias for MPRAGE (difference in SCA <2.1 mm²). No bias was observed for 3D-MDEFT vs. 3D-MPRAGE.

Conclusion

The 3D-MDEFT method allows for robust unbiased assessment of SCA in addition to brain morphology. J. Magn. Reson. Imaging 2010;32:1242–1247. © 2010 Wiley-Liss, Inc.