Development and stability analysis of carpal kinematic metrics from 4D magnetic resonance imaging.

OBJECTIVE: To develop MRI-derived carpal kinematic metrics and investigating their stability. METHODS: The study used a 4D MRI method to track scaphoid, lunate, and capitate movements in the wrist. A panel of 120 metrics for radial-ulnar deviation and flexion-extension was created using polynomial models of scaphoid and lunate movements relative to the capitate. Intraclass correlation coefficients (ICCs) analyzed intra- and inter-subject stability in 49 subjects, 20 with and 29 without wrist injury history. RESULTS: Comparable degrees of stability were observed across the two different wrist movements. Among the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. For asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. The differential analysis of ICC values for each metric between asymptomatic and symptomatic cohorts revealed specific metrics (although relatively unstable) exhibiting greater variability in the symptomatic cohort, thereby highlighting the impact of wrist conditions on the variability of kinematic metrics. CONCLUSION: The findings demonstrate the developing potential of dynamic MRI for assessing and characterizing complex carpal bone dynamics. Stability analyses of the derived kinematic metrics revealed encouraging differences between cohorts with and without wrist injury histories. Although these broad metric stability variations highlight the potential utility of this approach for analyzing carpal instability, further studies are necessary to better characterize these observations.

Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy.

OBJECTIVE: Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality. METHODS: Participants including 74 TLE patients (47 male, mean age = 39.2 years) and 45 healthy controls (27 male, mean age = 31.9 years) from the Epilepsy Connectome Project were classified into ADI-defined low and high disadvantage groups. Graph theoretic metrics were applied to multishell connectome diffusion-weighted imaging (DWI) measurements to derive 162 × 162 structural connectivity matrices (SCMs). The SCMs were harmonized using neuroCombat to account for interscanner differences. Threshold-free network-based statistics were used for analysis, and findings were correlated with ADI quintile metrics. A decrease in cross-sectional area (CSA) indicates reduced white matter integrity. RESULTS: Sex- and age-adjusted CSA in TLE groups was significantly reduced compared to controls regardless of disadvantage status, revealing discrete aberrant white matter tract connectivity abnormalities in addition to apparent differences in graph measures of connectivity and network-based statistics. When comparing broadly defined disadvantaged TLE groups, differences were at trend level. Sensitivity analyses of ADI quintile extremes revealed significantly lower CSA in the most compared to least disadvantaged TLE group. SIGNIFICANCE: Our findings demonstrate (1) the general impact of TLE on DWI connectome status is larger than the association with neighborhood disadvantage; however, (2) neighborhood disadvantage, indexed by ADI, revealed modest relationships with white matter structure and integrity on sensitivity analysis in TLE. Further studies are needed to explore this relationship and determine whether the white matter relationship with ADI is driven by social drift or environmental influences on brain development. Understanding the etiology and course of the disadvantage-brain integrity relationship may serve to inform care, management, and policy for patients.

Functional Connectivity Magnetic Resonance Imaging Sequences in Patients With Postsurgical Persistent Spinal Pain Syndrome Type 2 With Implanted Spinal Cord Stimulation Systems: A Safety, Feasibility, and Validity Study.

BACKGROUND: Chronic pain has been associated with alterations in brain connectivity, both within networks (regional) and between networks (cross-network connectivity). Functional connectivity (FC) data on chronic back pain are limited and based on heterogeneous pain populations. Patients with postsurgical persistent spinal pain syndrome (PSPS) type 2 are good candidates for spinal cord stimulation (SCS) therapy. We hypothesize that 1) FC magnetic resonance imaging (fcMRI) scans can be safely obtained in patients with PSPS type 2 with implanted therapeutic SCS devices and that 2) their cross-network connectivity patterns are altered and involve emotion and reward/aversion functions. MATERIALS AND METHODS: Resting-state (RS) fcMRI (rsfcMRI) scans were obtained from nine patients with PSPS type 2 implanted with therapeutic SCS systems and 13 age-matched controls. Seven RS networks were analyzed, including the striatum. RESULTS: Cross-network FC sequences were safely obtained on a 3T MRI scanner in all nine patients with PSPS type 2 with implanted SCS systems. FC patterns involving emotion/reward brain circuitry were altered as compared with controls. Patients with a history of constant neuropathic pain, experiencing longer therapeutic effects of SCS, had fewer alterations in their connectivity patterns. CONCLUSIONS: To our knowledge, this is the first report of altered cross-network FC involving emotion/reward brain circuitry in a homogeneous population of patients with chronic pain with fully implanted SCS systems, on a 3T MRI scanner. All rsfcMRI studies were safe and well tolerated by all nine patients, with no detectable effects on the implanted devices.

Split-slice training and hyperparameter tuning of RAKI networks for simultaneous multi-slice reconstruction.

PURPOSE: Simultaneous multi-slice acquisitions are essential for modern neuroimaging research, enabling high temporal resolution functional and high-resolution q-space sampling diffusion acquisitions. Recently, deep learning reconstruction techniques have been introduced for unaliasing these accelerated acquisitions, and robust artificial-neural-networks for k-space interpolation (RAKI) have shown promising capabilities. This study systematically examines the impacts of hyperparameter selections for RAKI networks, and introduces a novel technique for training data generation which is analogous to the split-slice formalism used in slice-GRAPPA. METHODS: RAKI networks were developed with variable hyperparameters and with and without split-slice training data generation. Each network was trained and applied to five different datasets including acquisitions harmonized with Human Connectome Project lifespan protocol. Unaliasing performance was assessed through L1 errors computed between unaliased and calibration frequency-space data. RESULTS: Split-slice training significantly improved network performance in nearly all hyperparameter configurations. Best unaliasing results were achieved with three layer RAKI networks using at least 64 convolutional filters with receptive fields of 7 voxels, 128 single-voxel filters in the penultimate RAKI layer, batch normalization, and no training dropout with the split-slice augmented training dataset. Networks trained without the split-slice technique showed symptoms of network over-fitting. CONCLUSIONS: Split-slice training for simultaneous multi-slice RAKI networks positively impacts network performance. Hyperparameter tuning of such reconstruction networks can lead to further improvements in unaliasing performance.

Generalized simultaneous multi-orientation 2D imaging.

PURPOSE: Flexibility in slice prescription is critical for precise motion monitoring during MR-guided therapies. Adding more slices to improve spatial coverage during rapid 2D cine imaging often hampers temporal resolution. This work describes a framework to simultaneously acquire multiple arbitrarily oriented slices which share a common frequency encoding axis. This framework allows for higher frame rates for a given number of slices compared to conventional interleaved-slice multi-orientation cine imaging. THEORY AND METHODS: A framework to calculate zeroth gradient moments to be played out between sequentially excited slices with multiple orientations is described here. Experiments were performed in phantom, and in vivo in the head/neck and abdomen of patients. RESULTS: Images arbitrarily rotated relative to one another were successfully obtained in phantom and in vivo. Simultaneous multi-orientation (SMO) images were also acquired with additional in-plane acceleration to demonstrate the capability of this method to rapidly image objects moving with physiological motion. CONCLUSIONS: The technical feasibility of the generalized SMO imaging framework was tested in this study. It shows promise for continued development for motion monitoring during MR-guided therapies.

Longitudinal Reproducibility of MR Perfusion Using 3D Pseudocontinuous Arterial Spin Labeling With Hadamard-Encoded Multiple Postlabeling Delays.

BACKGROUND: Arterial spin labeling (ASL) can be confounded by varying arterial transit times (ATT) across the brain and with disease. Hadamard encoding schemes can be applied to 3D pseudocontinuous ASL (pCASL) to acquire ASL data with multiple postlabeling delays (PLDs) to estimate ATT and then correct cerebral blood flow (CBF). PURPOSE: To assess the longitudinal reproducibility of 3D pCASL with Hadamard-encoded multiple PLDs. STUDY TYPE: Prospective, longitudinal. POPULATION: Fifty-two healthy, right-handed male subjects who underwent imaging at four timepoints over 45 days. FIELD STRENGTH/SEQUENCE: A Hadamard-encoded 3D pCASL sequence was acquired at 3.0T with seven PLDs from 1.0-3.7 sec. ASSESSMENT: ATT and corrected CBF (cCBF) were computed. Conventional uncorrected CBF (unCBF) was also estimated. Within- and between-subject coefficient of variation (wCV and bCV, respectively) and intraclass correlation coefficient (ICC) were evaluated across four time intervals: 7, 14, 30, and 45 days, in gray matter and 17 independent regions of interest (ROIs). A power analysis was also conducted. STATISTICAL TESTS: A repeated-measures analysis of variance (ANOVA) was used to compare ATT, cCBF, and unCBF across the four scan sessions. A paired two-sample t-test was used to compare cCBF and unCBF. Pearson's correlation was used to examine the relationship between the cCBF and unCBF difference and ATT. Power calculations were completed using both the cCBF and unCBF variances. RESULTS: ATT showed the lowest wCV and bCV (3.3-4.4% and 6.0-6.3%, respectively) compared to both cCBF (10.5-11.7% and 20.6-22.2%, respectively) and unCBF (12.0-13.6% and 22.7-23.7%, respectively). wCV and bCV were lower for cCBF vs. unCBF. A significant difference between cCBF and unCBF was found in most regions (P = 5.5 × 10-5 -3.8 × 10-4 in gray matter) that was highly correlated with ATT (R2 = 0.79-0.86). A power analysis yielded acceptable power at feasible sample sizes using cCBF. DATA CONCLUSION: ATT and ATT-corrected CBF were longitudinally stable, indicating that ATT and CBF changes can be reliably evaluated with Hadamard-encoded 3D pCASL with multiple PLDs. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1846-1853.

Multispectral diffusion-weighted MRI of the instrumented cervical spinal cord: a preliminary study of 5 cases.

PURPOSE: Diffusion-weighted imaging has undergone substantial investigation as a potential tool for advanced assessment of spinal cord health. Unfortunately, commonly encountered surgically implanted spinal hardware has historically disrupted these studies. This preliminary investigation applies the recently developed multispectral diffusion-weighted PROPELLER technique to quantitative assessment of the spinal cord immediately adjacent to metallic spinal fusion instrumentation. METHODS: Morphological and diffusion-weighted MRI of the spinal cord was collected from 5 subjects with implanted cervical spinal fusion hardware. Conventional and multispectral diffusion-weighted images were also collected on a normative non-instrumented control cohort and utilized for methodological stability analysis. Variance of the ADC values derived from the normative control group was then analyzed on a subject-by-subject basis and qualitatively correlated with clinical morphological interpretations. RESULTS: Normative control ADC values within the spinal cord were stable across DWI methods for a b value of 600 s/mm2, though this stability degraded at lower b value levels. Susceptibility artifacts precluded conventional DWI analysis of the cord in subjects with spinal fusion hardware in 4 of the 5 test cases. On the contrary, multispectral PROPELLER DWI produced viable ADC measurements within the cord of all 5 instrumented subjects. Instrumented cord regions without obvious pathology (N = 4) showed ADC values that were lower than expected, whereas one subject with diagnosed myelomalacia showed abnormally elevated ADC. CONCLUSIONS: In the absence of instrumentation, multispectral DWI provides quantitative capabilities that match with those of conventional DWI approaches. In a preliminary instrumented subject analysis, cord ADC values showed both expected and unexpected variations from the normative cohort. These slides can be retrieved under Electronic Supplementary Material.

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Resting-state functional connectivity after concussion is associated with clinical recovery.

There has been a recent call for longitudinal imaging studies to better characterize the time course of physiological recovery following sport-related concussion (SRC) and its relationship with clinical recovery. To address this, we evaluated changes to resting-state functional connectivity (rs-FC) of the whole-brain network following SRC and explored associations between rs-FC and measures of clinical outcome. High school and collegiate football athletes were enrolled during preseason. Athletes that suffered SRC (N = 62) were assessed across the acute (within 48 hr) and sub-acute (days 8, 15, and 45) phases. Matched football athletes without concussion served as controls (N = 60) and participated in similar visits. Multi-band resting-state fMRI was used to assess whole-brain rs-FC at each visit using network-based statistic and average nodal strength from regions of interest defined using a common whole-brain parcellation. Concussed athletes had elevated symptoms, psychological distress, and oculomotor, balance, and memory deficits at 48 hr postconcussion relative to controls, with diminished yet significant elevations in symptoms and psychological distress at 8 days. Both rs-FC analyses showed that concussed athletes had a global increase in connectivity at 8 days postconcussion relative to controls, with no differences at the 48-hr, 15-day, or 45-day visits. Further analysis revealed the group effect at the 8-day visit was driven by the large minority of concussed athletes still symptomatic at their visit; asymptomatic concussed athletes did not differ from controls. Findings from this large-scale, prospective study suggest whole-brain rs-FC alterations following SRC are delayed in onset but associated with the presence of self-reported symptoms.

Analysis of errors in diffusion kurtosis imaging caused by slice crosstalk in simultaneous multi-slice imaging.

Simultaneous multi-slice (SMS) imaging techniques accelerate diffusion MRI data acquisition. However, slice separation is imperfect and results in residual signal leakage between the simultaneously excited slices. The resulting consistent bias may adversely affect diffusion model parameter estimation. Although this bias is usually small and might not affect the simplified diffusion tensor model significantly, higher order diffusion models such as kurtosis are likely to be more susceptible to such effects. In this work, two SMS reconstruction techniques and an alternative acquisition approach were tested to quantify the effects of slice crosstalk on diffusion kurtosis parameters. In reconstruction, two popular slice separation algorithms, slice GRAPPA and split-slice GRAPPA, are evaluated to determine the effect of slice leakage on diffusion kurtosis metrics. For the alternative acquisition, the slice pairings were varied across diffusion weighted images such that the signal leakage does not come from the same overlapped slice for all diffusion encodings. Simulation results demonstrated the potential benefits of randomizing the slice pairings. However, various experimental factors confounded the advantages of slice pair randomization. In volunteer experiments, region-of-interest analyses found high metric errors with each of the SMS acquisitions and reconstructions in the brain white matter.

Off-resonance based assessment of metallic wear debris near total hip arthroplasty.

PURPOSE: The presence of metallic debris near total hip arthroplasty can have a significant impact on longitudinal patient management. Methods for magnetic resonance imaging-based quantification of metallic debris near painful total hip replacements are described and applied to cohorts of symptomatic and control subject cases. METHODS: A combination of metal artifact reduction, off-resonance mapping, off-resonance background removal, and spatial clustering methods are utilized to quantify off-resonance signatures in cases of suspected metallosis. These methods are applied to a cohort of symptomatic hip arthroplasties composed of cobalt-chromium alloys. Magnetostatic simulations and theoretical principles are used to illuminate the potential sources of the measured off-resonance effects. Reported metrics from histological tissue assays extracted during surgical revision procedures are also correlated with the proposed magnetic resonance imaging-based quantification results. RESULTS: The presented methods identified quantifiable metallosis signatures in more than 70% of the symptomatic and none of the control cases. Preliminary correlations of the MR data with direct histological evaluation of retrieved tissue samples indicate that the observed off-resonance effect may be related to tissue necrosis. CONCLUSIONS: Magnetostatic simulations, theoretical principles, and preliminary histological trends suggest that disassociated cobalt is the source of the observed off-resonance signature. Magn Reson Med 79:1628-1637, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Diffusion Weighted Magnetic Resonance Imaging of Spinal Cord Injuries After Instrumented Fusion Stabilization.

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising technique for assessing spinal cord injury (SCI) that has historically been challenged by the presence of metallic stabilization hardware. This study leverages recent advances in metal-artifact resistant multi-spectral DW-MRI to enable diffusion quantification throughout the spinal cord even after fusion stabilization. Twelve participants with cervical spinal cord injuries treated with fusion stabilization and 49 asymptomatic able-bodied control participants underwent multi-spectral DW-MRI evaluation. Apparent diffusion coefficient (ADC) values were calculated in axial cord sections. Statistical modeling assessed ADC differences across cohorts and within distinct cord regions of the SCI participants (at, above, or below injured level). Computed models accounted for subject demographics and injury characteristics. ADC was found to be elevated at injured levels compared with non-injured levels (z = 3.2, p = 0.001), with ADC at injured levels decreasing over time since injury (z = -9.2, p < 0.001). Below the injury level, ADC was reduced relative to controls (z = -4.4, p < 0.001), with greater reductions after more severe injuries that correlated with lower extremity motor scores (z = 2.56, p = 0.012). No statistically significant differences in ADC above the level of injury were identified. By enabling diffusion analysis near fusion hardware, the multi-spectral DW-MRI technique allowed intuitive quantification of cord diffusion changes after SCI both at and away from injured levels. This demonstrates the approach's potential for assessing post-surgical spinal cord integrity throughout stabilized regions.

Asymmetric spin echo multi-echo echo planar imaging (ASEME-EPI) sequence for pre-clinical high-field fMRI.

In functional magnetic resonance imaging (fMRI) of the blood oxygen level-dependent (BOLD) contrast, gradient-recalled echo (GRE) acquisitions offer high sensitivity but suffer from susceptibility-induced signal loss and lack specificity to microvasculature. In contrast, spin echo (SE) acquisitions provide improved specificity at the cost of reduced sensitivity. This study introduces Asymmetric Spin Echo Multi-Echo Echo Planar Imaging (ASEME-EPI), a technique designed to combine the benefits of both GRE and SE for high-field preclinical fMRI. ASEME-EPI employs a spin echo readout followed by two asymmetric spin echo (ASE) GRE readouts, providing an initial T2-weighted SE image and subsequent T2*-weighted ASE images. A feasibility study for the technique was implemented on a 9.4 T pre-clinical MRI system and tested using a visual stimulation in northern tree shrews. Comparing ASEME-EPI with conventional GRE echo planar imaging (GRE-EPI) and SE echo planar imaging (SE-EPI) acquisitions, results showed that ASEME-EPI achieved BOLD contrast-to-noise ratio (CNR) comparable to GRE-EPI while offering improved specificity in activation maps. ASEME-EPI activation was more confined to the primary visual cortex (V1), unlike GRE-EPI which showed activation extending beyond anatomical boundaries. Additionally, ASEME-EPI demonstrated the ability to recover signal in areas of severe field inhomogeneity where GRE-EPI suffered from signal loss. The performance of ASEME-EPI is attributed to its multi-echo nature, allowing for SNR-optimized combination of echoes, effectively denoising the data. The inclusion of the initial SE also contributes to signal recovery in areas prone to susceptibility artifacts. This feasibility study demonstrates the potential of ASEME-EPI for high-field pre-clinical fMRI, offering a promising compromise between GRE sensitivity and SE specificity while addressing challenges of T2* decay at high field strengths.

Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics.

INTRODUCTION: Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study. Furthermore, we assessed whether aberrant white matter connections are differentially related to cognitive impairment and a history of focal-to-bilateral tonic-clonic (FBTC) seizures. METHODS: Multi-shell connectome MRI data were preprocessed using the DESIGNER guidelines. The IIT Destrieux gray matter atlas was used to derive the 162 × 162 structural connectivity matrices (SCMs) using MRTrix3. ComBat data harmonization was applied to harmonize the SCMs from pre- and post-scanner upgrade acquisitions. Threshold-free network-based statistics were used for statistical analysis of the harmonized SCMs. Cognitive impairment status and FBTC seizure status were then correlated with these findings. RESULTS: We employed connectome measurements from 142 subjects, including 92 patients with TLE (36 males, mean age = 40.1 ± 11.7 years) and 50 HCs (25 males, mean age = 32.6 ± 10.2 years). Our analysis revealed overall significant decreases in cross-sectional area (CSA) of the white matter tract in TLE group compared to controls, indicating decreased white matter tract integrity and connectivity abnormalities in addition to apparent differences in graph theoretic measures of connectivity and network-based statistics. Focal and generalized cognitive impaired TLE patients showcased higher trend-level abnormalities in the white matter connectome via decreased CSA than those with no cognitive impairment. Patients with a positive FBTC seizure history also showed trend-level findings of association via decreased CSA. CONCLUSIONS: Widespread global aberrant white matter connectome changes were observed in TLE patients and characterized by seizure history and cognitive impairment, laying a foundation for future studies to expand on and validate the novel biomarkers and further elucidate TLE's impact on brain plasticity.

Development and Stability Analysis of Carpal Kinematic Metrics from 4D Magnetic Resonance Imaging.

INTRODUCTION: Wrist instability remains a common health concern. The potential of dynamic Magnetic Resonance Imaging (MRI) in assessing carpal dynamics associated with this condition is a field of ongoing research. This study contributes to this line of inquiry by developing MRI-derived carpal kinematic metrics and investigating their stability. METHODS: A previously described 4D MRI approach for tracking the movements of carpal bones in the wrist was deployed in this study. A panel of 120 metrics characterizing radial/ulnar deviation and flexion extension movements was constructed by fitting low order polynomial models of scaphoid and lunate degrees of freedom against that of the capitate. Intraclass Correlation Coefficients were utilized to analyze intra- and inter-subject stability within a mixed cohort of 49 subjects, including 20 with and 29 without a history of wrist injury. RESULTS: A comparable degree of stability across the two different wrist movements. Out of the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. Among asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. Interestingly, some quadratic term metrics, although relatively unstable within asymptomatic subjects, showed increased stability within this group, hinting at potential differentiation in their behavior across different cohorts. CONCLUSION: This study showed the developing potential of dynamic MRI to characterize complex carpal bone dynamics. Stability analyses of the derived kinematic metrics showed encouraging differences between cohorts with and without a history of wrist injury. Although these broad metric stability variations highlight the potential utility of this approach for analysis of carpal instability, further studies are necessary to better characterize these observations.

Diffusion-weighted MRI of the spinal cord in cervical spondylotic myelopathy after instrumented fusion.

Introduction: This study investigated tissue diffusion properties within the spinal cord of individuals treated for cervical spondylotic myelopathy (CSM) using post-decompression stabilization hardware. While previous research has indicated the potential of diffusion-weighted MRI (DW-MRI) markers of CSM, the metallic implants often used to stabilize the decompressed spine hamper conventional DW-MRI. Methods: Utilizing recent developments in DW-MRI metal-artifact suppression technologies, imaging data was acquired from 38 CSM study participants who had undergone instrumented fusion, as well as asymptomatic (non-instrumented) control participants. Apparent diffusion coefficients were determined in axial slice sections and split into four categories: a) instrumented levels, b) non-instrumented CSM levels, c) adjacent-segment (to instrumentation) CSM levels, and d) non-instrumented control levels. Multi-linear regression models accounting for age, sex, and body mass index were used to investigate ADC measures within each category. Furthermore, the cord diffusivity within CSM subjects was correlated with symptom scores and the duration since fusion procedures. Results: ADC measures of the spinal cord in CSM subjects were globally reduced relative to control subjects (p = 0.005). In addition, instrumented levels within the CSM subjects showed reduced diffusivity relative to controls (p = 0.003), while ADC within non-instrumented CSM levels did not statistically deviate from control levels (p = 0.107). Discussion: Multi-spectral DW-MRI technology can be effectively employed to evaluate cord diffusivity near fusion hardware in subjects who have undergone surgery for CSM. Leveraging this advanced technology, this study had identified significant reductions in cord diffusivity, relative to control subjects, in CSM patients treated with conventional metallic fusion instrumentation.

Predicting Neoadjuvant Treatment Response in Rectal Cancer Using Machine Learning: Evaluation of MRI-Based Radiomic and Clinical Models.

BACKGROUND: Radiomics is an approach to medical imaging that quantifies the features normally translated into visual display. While both radiomic and clinical markers have shown promise in predicting response to neoadjuvant chemoradiation therapy (nCRT) for rectal cancer, the interrelationship is not yet clear. METHODS: A retrospective, single-institution study of patients treated with nCRT for locally advanced rectal cancer was performed. Clinical and radiomic features were extracted from electronic medical record and pre-treatment magnetic resonance imaging, respectively. Machine learning models were created and assessed for complete response and positive treatment effect using the area under the receiver operating curves. RESULTS: Of 131 rectal cancer patients evaluated, 68 (51.9%) were identified to have a positive treatment effect and 35 (26.7%) had a complete response. On univariate analysis, clinical T-stage (OR 0.46, p = 0.02), lymphovascular/perineural invasion (OR 0.11, p = 0.03), and statin use (OR 2.45, p = 0.049) were associated with a complete response. Clinical T-stage (OR 0.37, p = 0.01), lymphovascular/perineural invasion (OR 0.16, p = 0.001), and abnormal carcinoembryonic antigen level (OR 0.28, p = 0.002) were significantly associated with a positive treatment effect. The clinical model was the strongest individual predictor of both positive treatment effect (AUC = 0.64) and complete response (AUC = 0.69). The predictive ability of a positive treatment effect increased by adding tumor and mesorectal radiomic features to the clinical model (AUC = 0.73). CONCLUSIONS: The use of a combined model with both clinical and radiomic features resulted in the strongest predictive capability. With the eventual goal of tailoring treatment to the individual, both clinical and radiologic markers offer insight into identifying patients likely to respond favorably to nCRT.

Enhancing the utility of complex-valued functional magnetic resonance imaging detection of neurobiological processes through postacquisition estimation and correction of dynamic B(0) errors and motion.

Functional magnetic resonance imaging (fMRI) time series analysis is typically performed using only the magnitude portion of the data. The phase information remains unused largely due to its sensitivity to temporal variations in the magnetic field unrelated to the functional response of interest. These phase changes are commonly the result of physiologic processes such as breathing or motion either inside or outside the imaging field of view. As a result, although the functional phase response carries pertinent physiological information concerning the vasculature, one aspect of which is the location of large draining veins, the full hemodynamic phase response is understudied and is poorly understood, especially in comparison with the magnitude response. It is likely that the magnitude and phase contain disjoint information, which could be used in tandem to better characterize functional hemodynamics. In this work, simulated and human fMRI experimental data are used to demonstrate how statistical analysis of complex-valued fMRI time series can be problematic, and how robust analysis using these powerful and flexible complex-valued statistics is possible through postprocessing with correction for dynamic magnetic field fluctuations in conjunction with estimated motion parameters. These techniques require no special pulse sequence modifications and can be applied to any complex-valued echo planar imaging data set. This analysis shows that the phase component appears to contain information complementary to that in the magnitude and that processing and analysis techniques are available to investigate it in a robust and flexible manner.

Diffusion propagator metrics are biased when simultaneous multi-slice acceleration is used.

Advanced diffusion MRI models are being explored to study the complex microstructure of the brain with higher accuracy. However, these techniques require long acquisition times. Simultaneous Multi-Slice (SMS) accelerates data acquisition by exciting multiple image slices simultaneously and separating the overlapping slices using a mathematical model, which makes use of the distinct information coming from an array of receive coils. However, SMS acceleration introduces increased noise in reconstructed images and crosstalk between simultaneously excited slices. These compounded effects from SMS acceleration could affect quantitative MRI techniques such as diffusion imaging. In this study, the effects of SMS acceleration on the accuracy of propagator metrics obtained from a model-free advanced diffusion technique called Mean Apparent Propagator MRI (MAP-MRI) was investigated. Ten healthy volunteers were scanned with SMS accelerated multi-shell diffusion MRI acquisitions. Group analyses were performed to study brain regions affected by SMS acceleration. In addition, diffusion metrics from atlas-based fiber tracts of interest were analyzed to investigate how propagator metrics in major fiber tracts were biased by 2- and 3-band SMS acceleration. Both zero-displacement metrics and non-Gaussianity metrics were significantly altered when SMS acceleration was used. MAP-MRI metrics calculated from SMS-3 showed significant differences with respect to SMS-2. Furthermore, with the shorter TR afforded by SMS acceleration, the characteristics of this bias have changed. This has implications for studies using diffusion MRI with SMS acceleration to investigate the effects of a disease or injury on the brain tissues.