Introduction

Diffusion MRI tractography has been increasingly used to delineate white matter pathways in vivo for which the leading clinical application is presurgical mapping of eloquent regions. However, there is rare opportunity to quantify the accuracy or sensitivity of these approaches to delineate white matter fiber pathways in vivo due to the lack of a gold standard. Intraoperative electrical stimulation (IES) provides a gold standard for the location and existence of functional motor pathways that can be used to determine the accuracy and sensitivity of fiber tracking algorithms. In this study we used intraoperative stimulation from brain tumor patients as a gold standard to estimate the sensitivity and accuracy of diffusion tensor MRI (DTI) and q-ball models of diffusion with deterministic and probabilistic fiber tracking algorithms for delineation of motor pathways.

Methods

We used preoperative high angular resolution diffusion MRI (HARDI) data (55 directions, b = 2000 s/mm(2)) acquired in a clinically feasible time frame from 12 patients who underwent a craniotomy for resection of a cerebral glioma. The corticospinal fiber tracts were delineated with DTI and q-ball models using deterministic and probabilistic algorithms. We used cortical and white matter IES sites as a gold standard for the presence and location of functional motor pathways. Sensitivity was defined as the true positive rate of delineating fiber pathways based on cortical IES stimulation sites. For accuracy and precision of the course of the fiber tracts, we measured the distance between the subcortical stimulation sites and the tractography result. Positive predictive rate of the delineated tracts was assessed by comparison of subcortical IES motor function (upper extremity, lower extremity, face) with the connection of the tractography pathway in the motor cortex.

Results

We obtained 21 cortical and 8 subcortical IES sites from intraoperative mapping of motor pathways. Probabilistic q-ball had the best sensitivity (79%) as determined from cortical IES compared to deterministic q-ball (50%), probabilistic DTI (36%), and deterministic DTI (10%). The sensitivity using the q-ball algorithm (65%) was significantly higher than using DTI (23%) (p < 0.001) and the probabilistic algorithms (58%) were more sensitive than deterministic approaches (30%) (p = 0.003). Probabilistic q-ball fiber tracks had the smallest offset to the subcortical stimulation sites. The offsets between diffusion fiber tracks and subcortical IES sites were increased significantly for those cases where the diffusion fiber tracks were visibly thinner than expected. There was perfect concordance between the subcortical IES function (e.g. hand stimulation) and the cortical connection of the nearest diffusion fiber track (e.g. upper extremity cortex).

Discussion

This study highlights the tremendous utility of intraoperative stimulation sites to provide a gold standard from which to evaluate diffusion MRI fiber tracking methods and has provided an object standard for evaluation of different diffusion models and approaches to fiber tracking. The probabilistic q-ball fiber tractography was significantly better than DTI methods in terms of sensitivity and accuracy of the course through the white matter. The commonly used DTI fiber tracking approach was shown to have very poor sensitivity (as low as 10% for deterministic DTI fiber tracking) for delineation of the lateral aspects of the corticospinal tract in our study. Effects of the tumor/edema resulted in significantly larger offsets between the subcortical IES and the preoperative fiber tracks. The provided data show that probabilistic HARDI tractography is the most objective and reproducible analysis but given the small sample and number of stimulation points a generalization about our results should be given with caution. Indeed our results inform the capabilities of preoperative diffusion fiber tracking and indicate that such data should be used carefully when making pre-surgical and intra-operative management decisions.

Structural magnetic resonance (MR) connectomics holds promise for the diagnosis, outcome prediction, and treatment monitoring of many common neurodevelopmental, psychiatric, and neurodegenerative disorders for which there is currently no clinical utility for MR imaging (MRI). Before computational network metrics from the human connectome can be applied in a clinical setting, their precision and their normative intersubject variation must be understood to guide the study design and the interpretation of longitudinal data. In this work, the reproducibility of commonly used graph theoretic measures is investigated, as applied to the structural connectome of healthy adult volunteers. Two datasets are examined, one consisting of 10 subjects scanned twice at one MRI facility and one consisting of five subjects scanned once each at two different facilities using the same imaging platform. Global graph metrics are calculated for unweighed and weighed connectomes, and two levels of granularity of the connectome are evaluated: one based on the 82-node cortical and subcortical parcellation from FreeSurfer and one based on an atlas-free parcellation of the gray-white matter boundary consisting of 1000 cortical nodes. The consistency of the unweighed and weighed edges and the module assignments are also computed for the 82-node connectomes. Overall, the results demonstrate good-to-excellent test-retest reliability for the entire connectome-processing pipeline, including the graph analytics, in both the intrasite and intersite datasets. These findings indicate that measurements of computational network metrics derived from the structural connectome have sufficient precision to be tested as potential biomarkers for diagnosis, prognosis, and monitoring of interventions in neurological and psychiatric diseases.

Copy number variants (CNVs) of the chromosomal locus 16p11.2, consisting of either deletions or duplications, have been implicated in autism, schizophrenia, epilepsy, and other neuropsychiatric disorders. Since abnormal white matter microstructure can be seen in these more broadly defined clinical disorders, we used diffusion magnetic resonance imaging and tract-based spatial statistics to investigate white matter microstructural integrity in human children with 16p11.2 deletions. We show that deletion carriers, compared with typically developing matched controls, have increased axial diffusivity (AD) in many major central white matter tracts, including the anterior corpus callosum as well as bilateral internal and external capsules. Higher AD correlated with lower nonverbal IQ in the deletion carriers, but not controls. Increases in fractional anisotropy and mean diffusivity were also found in some of the same tracts with elevated AD. Closer examination with neurite orientation dispersion and density imaging revealed that fiber orientation dispersion was decreased in some central white matter tracts. Notably, these alterations of white matter are unlike microstructural differences reported for any other neurodevelopmental disorders, including autism spectrum disorders that have phenotypic overlap with the deletion carriers. These findings suggest that deletion of the 16p11.2 locus is associated with a unique widespread pattern of aberrant white matter microstructure that may underlie the impaired cognition characteristic of this CNV.

Deletions and duplications of the recurrent ~600 kb chromosomal BP4-BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N = 25) and duplication (N = 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N = 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion > control > duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development.

Individuals with the 16p11.2 BP4-BP5 copy number variant (CNV) exhibit a range of behavioral phenotypes that may include mild impairment in cognition and clinical diagnoses of autism spectrum disorder (ASD). To better understand auditory processing impairments in populations with this chromosomal variation, auditory evoked responses were examined in children with the 16p11.2 deletion, 16p11.2 duplication, and age-matched controls. Stimuli consisted of sinusoidal binaural tones presented passively while children underwent recording with magnetoencephalography (MEG). The primary indicator of auditory processing impairment was the latency of the ∼100-ms "M100" auditory response detected by MEG, with the 16p11.2 deletion population exhibiting profoundly delayed M100 latencies relative to controls. This delay remained even after controlling for potential confounds such as age and cognitive ability. No significant difference in M100 latency was observed between 16p11.2 duplication carriers and controls. Additionally, children meeting diagnostic criteria for ASD (16p11.2 deletion carriers) exhibited nonsignificant latency delays when compared with the corresponding CNV carriers not meeting criteria for ASD. Present results indicate that 16p11.2 deletion is associated with auditory processing delays analogous to (but substantially more pronounced than) those previously reported in "idiopathic" ASD.

Copy number variants at the 16p11.2 chromosomal locus are associated with several neuropsychiatric disorders, including autism, schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and speech and language disorders. A gene dosage dependence has been suggested, with 16p11.2 deletion carriers demonstrating higher body mass index and head circumference, and 16p11.2 duplication carriers demonstrating lower body mass index and head circumference. Here, we use diffusion tensor imaging to elucidate this reciprocal relationship in white matter organization, showing widespread increases of fractional anisotropy throughout the supratentorial white matter in pediatric deletion carriers and, in contrast, extensive decreases of white matter fractional anisotropy in pediatric and adult duplication carriers. We find associations of these white matter alterations with cognitive and behavioral impairments. We further demonstrate the value of imaging metrics for characterizing the copy number variant phenotype by employing linear discriminant analysis to predict the gene dosage status of the study subjects. These results show an effect of 16p11.2 gene dosage on white matter microstructure, and further suggest that opposite changes in diffusion tensor imaging metrics can lead to similar cognitive and behavioral deficits. Given the large effect sizes found in this study, our results support the view that specific genetic variations are more strongly associated with specific brain alterations than are shared neuropsychiatric diagnoses. Hum Brain Mapp 37:2833-2848, 2016. © 2016 Wiley Periodicals, Inc.

Purpose

Heating of gradient coils and passive shim components is a common cause of instability in the B₀ field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.

Method

A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).

Results

Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.

Discussion

This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.