High-resolution diffusion tensor imaging of the fornix predicts memory function in multiple sclerosis.

Background: Cognitive dysfunction is a known symptom of multiple sclerosis (MS), with memory recognized as a frequently impacted domain. Here, we used high-resolution MRI at 7 tesla to build on cross-sectional work by evaluating the longitudinal relationship of diffusion tensor imaging (DTI) measures of the fornix to episodic memory performance. Methods: A sample of 80 people with multiple sclerosis (mean age 51.9 ± 8.1 years; 24% male) underwent baseline clinical evaluation, neuropsychological assessment, and MRI. Sixty-four participants had follow-up neuropsychological testing after 1-2 years. Linear regression was used to assess the relationship of baseline imaging measures to follow-up episodic memory performance, measured using the Selective Reminding Test and Brief Visuospatial Memory Test. A reduced prediction model included cognitive function at baseline, age, sex, and disease course. Results: Radial (ß = -0.222, p < 0.026; likelihood ratio test (LRT) p < 0.018), axial (ß = -0.270, p < 0.005; LRT p < 0.003), and mean (ß = -0.242, p < 0.0139; LRT p < 0.009) diffusivity of the fornix significantly added to the model, with follow-up analysis indicating that a longer prediction interval may increase accuracy. Conclusion: These results suggest that fornix DTI has predictive value specific to memory function in MS and warrants additional investigation in the drive to develop predictors of disease progression.

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

BACKGROUND AND PURPOSE: Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7 Tesla (T) MRI. METHODS: The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n = 15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12 months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. RESULTS: A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38 vs. 1.53, p < .001) and qMT (2.47 vs. 2.97, p < .001) but not in NODDI measures (p > .27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p = .03). CONCLUSIONS: SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection.

OBJECTIVE: We aim to improve focal cortical dysplasia (FCD) detection by combining high-resolution, three-dimensional (3D) magnetic resonance fingerprinting (MRF) with voxel-based morphometric magnetic resonance imaging (MRI) analysis. METHODS: We included 37 patients with pharmacoresistant focal epilepsy and FCD (10 IIa, 15 IIb, 10 mild Malformation of Cortical Development [mMCD], and 2 mMCD with oligodendroglial hyperplasia and epilepsy [MOGHE]). Fifty-nine healthy controls (HCs) were also included. 3D lesion labels were manually created. Whole-brain MRF scans were obtained with 1 mm3 isotropic resolution, from which quantitative T1 and T2 maps were reconstructed. Voxel-based MRI postprocessing, implemented with the morphometric analysis program (MAP18), was performed for FCD detection using clinical T1w images, outputting clusters with voxel-wise lesion probabilities. Average MRF T1 and T2 were calculated in each cluster from MAP18 output for gray matter (GM) and white matter (WM) separately. Normalized MRF T1 and T2 were calculated by z-scores using HCs. Clusters that overlapped with the lesion labels were considered true positives (TPs); clusters with no overlap were considered false positives (FPs). Two-sample t-tests were performed to compare MRF measures between TP/FP clusters. A neural network model was trained using MRF values and cluster volume to distinguish TP/FP clusters. Ten-fold cross-validation was used to evaluate model performance at the cluster level. Leave-one-patient-out cross-validation was used to evaluate performance at the patient level. RESULTS: MRF metrics were significantly higher in TP than FP clusters, including GM T1, normalized WM T1, and normalized WM T2. The neural network model with normalized MRF measures and cluster volume as input achieved mean area under the curve (AUC) of .83, sensitivity of 82.1%, and specificity of 71.7%. This model showed superior performance over direct thresholding of MAP18 FCD probability map at both the cluster and patient levels, eliminating ≥75% FP clusters in 30% of patients and ≥50% of FP clusters in 91% of patients. SIGNIFICANCE: This pilot study suggests the efficacy of MRF for reducing FPs in FCD detection, due to its quantitative values reflecting in vivo pathological changes. © 2024 International League Against Epilepsy.

Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease.

BACKGROUND AND PURPOSE: A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD. METHODS: Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5). RESULTS: Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language. CONCLUSION: This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.

Facilitating diffusion tensor imaging of the brain during continuous gross head motion with first and second order motion compensating diffusion gradients.

PURPOSE: To demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion. METHODS: Five healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion-weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections. RESULTS: In the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion-M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion-M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion-M2 data were consistent with reference data. CONCLUSION: This proof-of-principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion.

Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification.

PURPOSE: To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating. METHODS: The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments. RESULTS: The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved. CONCLUSION: The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency.

Magnetic resonance fingerprinting in multiple sclerosis.

BACKGROUND: In this cross sectional study, we used MRF to investigate tissue properties of normal-appearing white matter, gray matter, and lesions in relapsing remitting MS (n = 21), secondary progressive MS (n = 16) and healthy controls (n = 9). A FISP-based MRF sequence was used for acquisition, imaging time 5 min 15 s. MRF T1 and T2 relaxation times were measured from lesional tissue, normal-appearing frontal white matter, corpus callous, thalamus, and caudate. Differences between healthy controls and MS were examined using ANCOVA adjusted for age and sex. Spearman rank correlations were assessed between T1 and T2 relaxation times and clinical measures. OBJECTIVES: To examine brain T1 and T2 values using magnetic resonance fingerprinting (MRF) in healthy controls and MS. METHODS: The subjects included 21 relapsing-remitting (RR) MS, 16 secondary progressive (SP) MS, and 9 age- and sex-matched HC without manifest neurological disease participating in a longitudinal MRI study. A 3T/ FISP-based MRF sequence was acquired. Regions of interest were drawn for lesions and normal appearing white matter. ANCOVA adjusted for age and sex were used to compare the groups with significance set at 0.05. RESULTS: A step-wise increase in T1 and T2 relaxation times was found between healthy controls, relapsing remitting MS, and secondary progressive MS. Significant differences were found in T1 and T2 between MS and healthy controls in the frontal normal-appearing white matter, corpus callosum, and thalamus (p < 0.04 for all). Significant differences in T1 and T2 between RR and SPMS were found in the frontal normal-appearing white matter and T2 lesions (p < 0.02 for all). T1 relaxation from the frontal normal-appearing white matter correlated with the Expanded Disability Status Scale [ρ = 0.62, p < 0.001], timed 25 foot walk (ρ = 0.45, p = 0.01), 9 hole peg test (ρ = 0.62, p < 0.001), and paced auditory serial addition test (ρ = -0.4, p = 0.01). CONCLUSION: These results suggest that MRF may be a clinically feasible quantitative approach for characterizing tissue damage in MS.

Evaluating whole-brain tissue-property changes in MRI-negative pharmacoresistant focal epilepsies using MR fingerprinting.

OBJECTIVE: We aim to quantify whole-brain tissue-property changes in patients with magnetic resonance imaging (MRI)-negative pharmacoresistant focal epilepsy by three-dimensional (3D) magnetic resonance fingerprinting (MRF). METHODS: We included 30 patients with pharmacoresistant focal epilepsy and negative MRI by official radiology report, as well as 40 age- and gender-matched healthy controls (HCs). MRF scans were obtained with 1 mm3 isotropic resolution. Quantitative T1 and T2 relaxometry maps were reconstructed from MRF and registered to the Montreal Neurological Institute (MNI) space. A two-sample t test was performed in Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) to evaluate significant abnormalities in patients comparing to HCs, with correction by the threshold-free cluster enhancement (TFCE) method. Subgroups analyses were performed for extra-temporal epilepsy/temporal epilepsy (ETLE/TLE), and for those with/without subtle abnormalities detected by morphometric analysis program (MAP), to investigate each subgroup's pattern of MRF changes. Correlation analyses were performed between the mean MRF values in each significant cluster and seizure-related clinical variables. RESULTS: Compared to HCs, patients exhibited significant group-level T1 increase ipsilateral to the epileptic origin, in the mesial temporal gray matter (GM) and white matter (WM), temporal pole GM, orbitofrontal GM, hippocampus, and amygdala, with scattered clusters in the neocortical temporal and insular GM. No significant T2 changes were detected. The ETLE subgroup showed a T1-increase pattern similar to the overall cohort, with additional involvement of the ipsilateral anterior cingulate GM. The subgroup of MAP+ patients also showed a T1-increase pattern similar to the overall cohort, with additional cluster in the ipsilateral lateral orbitofrontal GM. Higher T1 was associated with younger seizure-onset age, longer epilepsy duration, and higher seizure frequency. SIGNIFICANCE: MRF revealed group-level T1 increase in limbic/paralimbic structures ipsilateral to the epileptic origin, in patients with pharmacoresistant focal epilepsy and no apparent lesions on MRI, suggesting that these regions may be commonly affected by seizures in the epileptic brain. The significant association between T1 increase and higher seizure burden may reflect progressive tissue damage.

Normative quantitative relaxation atlases for characterization of cortical regions using magnetic resonance fingerprinting.

Quantitative magnetic resonance (MR) has been used to study cyto- and myelo-architecture of the human brain non-invasively. However, analyzing brain cortex using high-resolution quantitative MR acquisition can be challenging to perform using 3T clinical scanners. MR fingerprinting (MRF) is a highly efficient and clinically feasible quantitative MR technique that simultaneously provides T1 and T2 relaxation maps. Using 3D MRF from 40 healthy subjects (mean age = 25.6 ± 4.3 years) scanned on 3T magnetic resonance imaging, we generated whole-brain gyral-based normative MR relaxation atlases and investigated cortical-region-based T1 and T2 variations. Gender and age dependency of T1 and T2 variations were additionally analyzed. The coefficient of variation of T1 and T2 for each cortical-region was 3.5% and 7.3%, respectively, supporting low variability of MRF measurements across subjects. Significant differences in T1 and T2 were identified among 34 brain regions (P < 0.001), lower in the precentral, postcentral, paracentral lobule, transverse temporal, lateral occipital, and cingulate areas, which contain sensorimotor, auditory, visual, and limbic functions. Significant correlations were identified between age and T1 and T2 values. This study established whole-brain MRF T1 and T2 atlases of healthy subjects using a clinical 3T scanner, which can provide a quantitative and region-specific baseline for future brain studies and pathology detection.

Characterizing thalamic and basal ganglia nuclei in medically intractable focal epilepsy by MR fingerprinting.

OBJECTIVES: Magnetic resonance fingerprinting (MRF) is a novel, quantitative, and noninvasive technique to measure brain tissue properties. We aim to use MRF for characterizing normal-appearing thalamic and basal ganglia nuclei in the epileptic brain. METHODS: A three-dimensional (3D) MRF protocol (1 mm3 isotropic resolution) was acquired from 48 patients with unilateral medically intractable focal epilepsy and 39 healthy controls (HCs). Whole-brain T1 and T2 maps (containing T1 and T2 relaxation times) were reconstructed for each subject. Ten subcortical nuclei in the thalamus and basal ganglia were segmented as regions of interest (ROIs), within which the mean T1 and T2 values, as well as their coefficient of variation (CV) were compared between the patients and HCs at the group level. Subgroup and correlation analyses were performed to examine the relationship between significant MRF measures and various clinical characteristics. Using significantly abnormal MRF measures from the group-level analyses, support vector machine (SVM) and logistic regression machine learning models were built and tested with 5-fold and 10-fold cross-validations, to separate patients from HCs, and to separate patients with left-sided and right-sided epilepsy, at the individual level. RESULTS: MRF revealed increased T1 mean value in the ipsilateral thalamus and nucleus accumbens; increased T1 CV in the bilateral thalamus, bilateral pallidum, and ipsilateral caudate; and increased T2 CV in the ipsilateral thalamus in patients compared to HCs (p < .05, false discovery rate [FDR] corrected). The SVM classifier produced 78.2% average accuracy to separate individual patients from HCs, with an area under the curve (AUC) of 0.83. The logistic regression classifier produced 67.4% average accuracy to separate patients with left-sided and right-sided epilepsy, with an AUC of 0.72. SIGNIFICANCE: MRF revealed bilateral tissue-property changes in the normal-appearing thalamus and basal ganglia, with ipsilateral predominance and thalamic preference, suggesting subcortical involvement/impairment in patients with medically intractable focal epilepsy. The individual-level performance of the MRF-based machine-learning models suggests potential opportunities for predicting lateralization.

MR Fingerprinting with b-Tensor Encoding for Simultaneous Quantification of Relaxation and Diffusion in a Single Scan.

PURPOSE: Although both relaxation and diffusion imaging are sensitive to tissue microstructure, studies have reported limited sensitivity and robustness of using relaxation or conventional diffusion alone to characterize tissue microstructure. Recently, it has been shown that tensor-valued diffusion encoding and joint relaxation-diffusion quantification enable more reliable quantification of compartment-specific microstructural properties. However, scan times to acquire such data can be prohibitive. Here, we aim to simultaneously quantify relaxation and diffusion using MR fingerprinting (MRF) and b-tensor encoding in a clinically feasible time. METHODS: We developed multidimensional MRF scans (mdMRF) with linear and spherical b-tensor encoding (LTE and STE) to simultaneously quantify T1, T2, and ADC maps from a single scan. The image quality, accuracy, and scan efficiency were compared between the mdMRF using LTE and STE. Moreover, we investigated the robustness of different sequence designs to signal errors and their impact on the maps. RESULTS: T1 and T2 maps derived from the mdMRF scans have consistently high image quality, while ADC maps are sensitive to different sequence designs. Notably, the fast imaging steady state precession (FISP)-based mdMRF scan with peripheral pulse gating provides the best ADC maps that are free of image distortion and shading artifacts. CONCLUSION: We demonstrated the feasibility of quantifying T1, T2, and ADC maps simultaneously from a single mdMRF scan in around 24 s/slice. The map quality and quantitative values are consistent with the reference scans.

Contralaterally Controlled Functional Electrical Stimulation Combined With Brain Stimulation for Severe Upper Limb Hemiplegia-Study Protocol for a Randomized Controlled Trial.

Background: Approximately two-thirds of stroke survivors experience chronic upper limb paresis, and of them, 50% experience severe paresis. Treatment options for severely impaired survivors are often limited. Rehabilitation involves intensively engaging the paretic upper limb, and disincentivizing use of the non-paretic upper limb, with the goal to increase excitability of the ipsilesional primary motor cortex (iM1) and suppress excitability of the undamaged (contralesional) motor cortices, presumed to have an inhibitory effect on iM1. Accordingly, brain stimulation approaches, such as repetitive transcranial magnetic stimulation (rTMS), are also given to excite iM1 and/or suppress contralesional motor cortices. But such approaches aimed at ultimately increasing iM1 excitability yield limited functional benefit in severely impaired survivors who lack sufficient ipsilesional substrate. Aim: Here, we test the premise that combining Contralaterally Controlled Functional Electrical Stimulation (CCFES), a rehabilitation technique that engages the non-paretic upper limb in delivery of neuromuscular electrical stimulation to the paretic upper limb, and a new rTMS approach that excites intact, contralesional higher motor cortices (cHMC), may have more favorable effect on paretic upper limb function in severely impaired survivors based on recruitment of spared, transcallosal and (alternate) ipsilateral substrate. Methods: In a prospective, double-blind, placebo-controlled RCT, 72 chronic stroke survivors with severe distal hand impairment receive CCFES plus cHMC rTMS, iM1 rTMS, or sham rTMS, 2X/wk for 12wks. Measures of upper limb motor impairment (Upper Extremity Fugl Meyer, UEFM), functional ability (Wolf Motor-Function Test, WMFT) and perceived disability are collected at 0, 6, 12 (end-of-treatment), 24, and 36 wks (follow-up). TMS is performed at 0, 12 (end-of-treatment), and 36 wks (follow-up) to evaluate inter-hemispheric and ipsilateral mechanisms. Influence of baseline severity is also characterized with imaging. Conclusions: Targeting of spared neural substrates and rehabilitation which engages the unimpaired limb in movement of the impaired limb may serve as a suitable combinatorial treatment option for severely impaired stroke survivors. ClinicalTrials No: NCT03870672.

Using magnetic resonance fingerprinting to characterize periventricular nodular heterotopias in pharmacoresistant epilepsy.

OBJECTIVE: We aimed to use a novel magnetic resonance fingerprinting (MRF) technique to examine in vivo tissue property characteristics of periventricular nodular heterotopia (PVNH). These characteristics were further correlated with stereotactic-electroencephalographic (SEEG) ictal onset findings. METHODS: We included five patients with PVNH who had SEEG-guided surgery and at least 1 year of seizure freedom or substantial seizure reduction. High-resolution MRF scans were acquired at 3 T, generating three-dimensional quantitative T1 and T2  maps. We assessed the differences between T1 and T2  values from the voxels in the nodules located in the SEEG-defined seizure onset zone (SOZ) and non-SOZ, on -individual and group levels. Receiver operating characteristic analyses were performed to obtain the optimal classification performance. Quantification of SEEG ictal onset signals from the nodules was performed by calculating power spectrum density (PSD). The association between PSD and T1 /T2  values was further assessed at different frequency bands. RESULTS: Individual-level analysis showed T1 was significantly higher in SOZ voxels than non-SOZ voxels (p < .05), with an average 73% classification accuracy. Group-level analysis also showed higher T1 was significantly associated with SOZ voxels (p < .001). At the optimal cutoff (normalized T1 of 1.1), a 76% accuracy for classifying SOZ nodules from non-SOZ nodules was achieved. T1  values were significantly associated with ictal onset PSD at the ultraslow, θ, ß, γ, and ripple bands (p < .05). T2  values were significantly associated with PSD only at the ultraslow band (p < .05). SIGNIFICANCE: Quantitative MRF measures, especially T1 , can provide additional noninvasive information to separate nodules in SOZ and non-SOZ. The T1 and T2 tissue property changes carry electrophysiological underpinnings relevant to the epilepsy, as shown by their significant positive associations with power changes during the SEEG seizure onset. The use of MRF as a supplementary noninvasive tool may improve presurgical evaluation for patients with PVNH and pharmacoresistant epilepsy.

Repetitive Transcranial Magnetic Stimulation of the Contralesional Dorsal Premotor Cortex for Upper Extremity Motor Improvement in Severe Stroke: Study Protocol for a Pilot Randomized Clinical Trial.

Up to 50% of stroke survivors have persistent, severe upper extremity paresis even after receiving rehabilitation. Repetitive transcranial magnetic stimulation (rTMS) can augment the effects of rehabilitation by modulating corticomotor excitability, but the conventional approach of facilitating excitability of the ipsilesional primary motor cortex (iM1) fails to produce motor improvement in stroke survivors with severe loss of ipsilesional substrate. Instead, the undamaged, contralesional dorsal premotor cortex (cPMd) may be a more suitable target. CPMd can offer alternate, bi-hemispheric and ipsilateral connections in support of paretic limb movement. This pilot, randomized clinical trial seeks to investigate whether rTMS delivered to facilitate cPMd in conjunction with rehabilitation produces greater gains in motor function than conventional rTMS delivered to facilitate iM1 in conjunction with rehabilitation in severely impaired stroke survivors. Twenty-four chronic (≥6 months) stroke survivors with severe loss of ipsilesional substrate (defined by the absence of physiologic evidence of excitable residual pathways tested using TMS) will be included. Participants will be randomized to receive rTMS to facilitate cPMd or iM1 in conjunction with task-oriented upper limb rehabilitation given for 2 sessions/week for 6 weeks. Assessments of primary outcome related to motor impairment (upper extremity Fugl-Meyer [UEFM]), motor function, neurophysiology, and functional neuroimaging will be made at baseline and at 6-week end-of-treatment. An additional assessment of motor outcomes will be repeated at 3-month follow-up to evaluate retention. The primary endpoint is 6-week change in UEFM. This pilot trial will provide preliminary evidence on the effects and mechanisms associated with facilitating intact cPMd in chronic severe stroke survivors. The trial is registered on clinicaltrials.gov, NCT03868410.

Leveraging redundancy in simultaneous multislice acquisitions to improve spike detection.

PURPOSE: To improve the performance of low-level spike noise artifact detection for daily quality assurance protocols by taking advantage of redundancy in simultaneous multislice (SMS) acquisitions. METHODS: Magnitude images were transformed into pseudo k-space images. Time series at each pseudo k-space point were detrended. A slice was determined to contain spiking artifact if it exceeded an intensity threshold and if all simultaneously acquired slices contained outliers. RESULTS: A total of 401 112 slices were inspected. Of these, 42 showed a spike artifact, based on visual inspection of image data and k-space data. With an intensity threshold of 4.6 SDs over time for each pseudo k-space point, all slices containing artifact were correctly flagged, and only 30 slices were incorrectly flagged when using the SMS criterion. Without the SMS criterion, 12 908 slices were incorrectly flagged as containing artifact. Without the SMS criterion, sensitivity to artifact would have to be sacrificed to substantially reduce the number of incorrectly flagged slices. CONCLUSION: This study demonstrates that the SMS criterion reduced the number of outliers reported to a manageable level while accurately identifying low-level spike artifacts. Successfully identifying low-level spikes allows early detection of hardware problems that can be fixed before the problem becomes debilitating and corrupts data. As part of a daily quality assurance protocol, the method prevents the need to retrospectively carry out time-intensive despiking and reanalysis of data.

Functional connectivity abnormalities in Type I Chiari: associations with cognition and pain.

There is initial evidence of microstructural abnormalities in the fibre-tract pathways of the cerebellum and cerebrum of individuals diagnosed with Type I Chiari malformation. However, it is unclear whether abnormal white matter architecture and macro-level morphological deviations that have been observed in Chiari translate to differences in functional connectivity. Furthermore, common symptoms of Chiari include pain and cognitive deficits, but the relationship between these symptoms and functional connectivity has not been explored in this population. Eighteen Type I Chiari patients and 18 age-, sex- and education-matched controls underwent resting-state functional MRI to measure functional connectivity. Participants also completed a neuropsychological battery and completed self-report measures of chronic pain. Group differences in functional connectivity were identified. Subsequently, pathways of significant difference were re-analyzed after controlling for the effects of attention performance and self-reported chronic pain. Chiari patients exhibited functional hypoconnectivity between areas of the cerebellum and cerebrum. Controlling for attention eliminated all deficits with the exception of that from the posterior cerebellar pathway. Similarly, controlling for pain also eliminated deficits except for those from the posterior cerebellar pathway and vermis VII. Patterns of Chiari hyperconnectivity were also found between regions of the cerebellum and cerebrum in Chiari patients. Hyperconnectivity in all regions was eliminated after controlling for attention except between left lobule VIII and the left postcentral gyrus and between vermis IX and the precuneus. Similarly, hyperconnectivity was eliminated after controlling for pain except between the default mode network and globus pallidus, left lobule VIII and the left postcentral gyrus, and Vermis IX and the precuneus. Evidence of both hyper- and hypoconnectivity were identified in Chiari, which is posited to support the hypothesis that the effect of increased pain in Chiari draws on neural resources, requiring an upregulation in inhibitory control mechanisms and resulting in cognitive dysfunction. Areas of hypoconnectivity in Chiari patients also suggest disruption in functional pathways, and potential mechanisms are discussed.

Evaluation of a connectivity-based imaging metric that reflects functional decline in Multiple Sclerosis.

Cognitive impairment is a common symptom in individuals with Multiple Sclerosis (MS), but meaningful, reliable biomarkers relating to cognitive decline have been elusive, making evaluation of the impact of therapeutics on cognitive function difficult. Here, we combine pathway-based MRI measures of structural and functional connectivity to construct a metric of functional decline in MS. The Structural and Functional Connectivity Index (SFCI) is proposed as a simple, z-scored metric of structural and functional connectivity, where changes in the metric have a simple statistical interpretation and may be suitable for use in clinical trials. Using data collected at six time points from a 2-year longitudinal study of 20 participants with MS and 9 age- and sex-matched healthy controls, we probe two common symptomatic domains, motor and cognitive function, by measuring structural and functional connectivity in the transcallosal motor pathway and posterior cingulum bundle. The SFCI is significantly lower in participants with MS compared to controls (p = 0.009) and shows a significant decrease over time in MS (p = 0.012). The change in SFCI over two years performed favorably compared to measures of brain parenchymal fraction and lesion volume, relating to follow-up measures of processing speed (r = 0.60, p = 0.005), verbal fluency (r = 0.57, p = 0.009), and score on the Multiple Sclerosis Functional Composite (r = 0.67, p = 0.003). These initial results show that the SFCI is a suitable metric for longitudinal evaluation of functional decline in MS.

Influence of equipment changes on MRI measures of brain atrophy and brain microstructure in a placebo-controlled trial of ibudilast in progressive multiple sclerosis.

BACKGROUND: Hardware changes can be an unavoidable confound in imaging trials. Understanding the impact of such changes may play an important role in the analysis of imaging data. OBJECTIVE: To characterize the effect of equipment changes in a longitudinal, multi-site multiple sclerosis trial. METHODS: Using data from a clinical trial in progressive multiple sclerosis, we explored how major changes in imaging hardware affected data. We analyzed the extent to which these changes affected imaging biomarkers and the estimated treatment effects by including such changes as a time-dependent covariate. RESULTS: Significant differences whole brain atrophy (brain parenchymal fraction, BPF) and microstructure (transverse diffusivity, TD) between scans with and without changes were found and depended on the type of hardware change. A switch from GE HDxt to Siemens Skyra led to significant shifts in BPF (p < 0.04) and TD (p < 0.0001). However, we could not detect the influence of hardware changes on overall trial outcomes- differences between placebo and treatment arms in change over time of BPF and TD (p > 0.5). CONCLUSIONS: The results suggest that differences among hardware types should be considered when planning and analyzing brain atrophy and diffusivity in a longitudinal clinical trial.

Importance of incorporating quantitative imaging biomarker technical performance characteristics when estimating treatment effects.

BACKGROUND/AIMS: Quantitative imaging biomarkers have the potential to detect change in disease early and noninvasively, providing information about the diagnosis and prognosis of a patient, aiding in monitoring disease, and informing when therapy is effective. In clinical trials testing new therapies, there has been a tendency to ignore the variability and bias in quantitative imaging biomarker measurements. Unfortunately, this can lead to underpowered studies and incorrect estimates of the treatment effect. We illustrate the problem when non-constant measurement bias is ignored and show how treatment effect estimates can be corrected. METHODS: Monte Carlo simulation was used to assess the coverage of 95% confidence intervals for the treatment effect when non-constant bias is ignored versus when the bias is corrected for. Three examples are presented to illustrate the methods: doubling times of lung nodules, rates of change in brain atrophy in progressive multiple sclerosis clinical trials, and changes in proton-density fat fraction in trials for patients with nonalcoholic fatty liver disease. RESULTS: Incorrectly assuming that the measurement bias is constant leads to 95% confidence intervals for the treatment effect with reduced coverage (<95%); the coverage is especially reduced when the quantitative imaging biomarker measurements have good precision and/or there is a large treatment effect. Estimates of the measurement bias from technical performance validation studies can be used to correct the confidence intervals for the treatment effect. CONCLUSION: Technical performance validation studies of quantitative imaging biomarkers are needed to supplement clinical trial data to provide unbiased estimates of the treatment effect.