Diffusion Magnetic Resonance Imaging Research Articles

Assessment of spinal cord injury using ultrasound elastography in a rabbit model in vivo

The effect of the mechanical micro-environment on spinal cord injury (SCI) and treatment effectiveness remains unclear. Currently, there are limited imaging methods that can directly assess the localized mechanical behavior of spinal cords in vivo. In this study, we apply new ultrasound elastography (USE) techniques to assess SCI in vivo at the site of the injury and at the time of one week post injury, in a rabbit animal model. Eleven rabbits underwent laminectomy procedures. Among them, spinal cords of five rabbits were injured during the procedure. The other six rabbits were used as control. Two neurological statuses were achieved: non-paralysis and paralysis. Ultrasound data were collected one week post-surgery and processed to compute strain ratios. Histologic analysis, mechanical testing, magnetic resonance imaging (MRI), computerized tomography and MRI diffusion tensor imaging (DTI) were performed to validate USE results. Strain ratios computed via USE were found to be significantly different in paralyzed versus non-paralyzed rabbits. The myelomalacia histologic score and spinal cord Young’s modulus evaluated in selected animals were in good qualitative agreement with USE assessment. It is feasible to use USE to assess changes in the spinal cord of the presented animal model. In the future, with more experimental data available, USE may provide new quantitative tools for improving SCI diagnosis and prognosis.

Advancements in Diffusion MRI Tractography for Neurosurgery.

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

Glymphatic system dysfunction in restless legs syndrome: evidenced by diffusion tensor imaging along the perivascular space.

There is growing evidence pointing at glymphatic system dysfunction in diseases with circadian disruption, such as sleep disorders. Lower diffusivity in the direction of perivascular space has been shown in several neurological and sleep-related disorders; however, its role in restless legs syndrome (RLS) is unclear. We hypothesized that similarly, in RLS the diffusivity in glymphatic system is decreased. Here, we aimed to evaluate glymphatic system functionality in patients with RLS, compare it to healthy controls, and analyze the correlation between its function and clinical characteristics. Sixty-nine patients with primary RLS and 51 healthy controls were recruited at a tertiary hospital. All participants underwent diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI) using a 3T MRI scanner, and the DTI along the perivascular space (DTI-ALPS) index was calculated using DTI data. We compared the DTI-ALPS index between the patients with RLS and healthy controls. We also conducted the correlation analysis between the DTI-ALPS index and clinical characteristics, including age, age of onset, symptom duration, and RLS severity. DTI-ALPS index differed significantly between the patients with RLS and healthy controls; the DTI-ALPS index in the patients with RLS was lower than that in the healthy controls (1.48 vs. 0.60, p = 0.008). There was no significant correlation between the DTI-ALPS index and clinical characteristics. A significantly lower DTI-ALPS index in patients with RLS suggests that the glymphatic system function is impaired in patients with RLS.

A numerical method for solving snapping out Brownian motion in 2D bounded domains

Diffusion in heterogeneous media partitioned by semi-permeable interfaces has a wide range of applications in the physical and life sciences, including gas permeation in soils, diffusion magnetic resonance imaging (dMRI), drug delivery, thermal conduction in composite media, synaptic receptor trafficking, and intercellular gap junctions. At the single particle level, diffusion across a semi-permeable interface can be formulated in terms of so-called snapping out Brownian motion (SNOBM). The latter sews together successive rounds of reflected BM, each of which is restricted to one side of the interface. Each round of reflected BM is killed when the local time at the interface exceeds an independent, exponentially distributed random variable. (The local time specifies the amount of time a reflected Brownian particle spends in a neighborhood of the interface.) The particle then immediately resumes reflected BM on the same side or the other side of the interface according to a stochastic switch, and the process is iterated. In this paper, we develop a Monte Carlo algorithm for simulating a two-dimensional version of SNOBM, which is used to solve a first passage time (FPT) problem for diffusion in a domain with semi-permeable partially absorbing traps. Our method combines a walk-on-spheres (WOS) method with an efficient algorithm for computing the boundary local time that uses a Skorokhod integral representation of the latter. We validate our algorithm by comparing the Monte Carlo estimates of the mean first passage time (MFPT) to the exact solution for a single circular trap, and show that our simulations are consistent with asymptotic results obtained for the 2D narrow capture problem involving multiple small circular targets. We also discuss extensions to higher dimensions.

Discrimination between human epidermal growth factor receptor 2 (HER2)-low-expressing and HER2-overexpressing breast cancers: a comparative study of four MRI diffusion models.

To determine the value of conventional DWI, continuous-time random walk (CTRW), fractional order calculus (FROC), and stretched exponential model (SEM) in discriminating human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC). This prospective study included 158 women who underwent DWI, CTRW, FROC, and SEM and were pathologically categorized into the HER2-zero-expressing group (n = 10), HER2-low-expressing group (n = 86), and HER2-overexpressing group (n = 62). Nine diffusion parameters, namely ADC, αCTRW, βCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM of the primary tumor, were derived from four diffusion models. These diffusion metrics and clinicopathologic features were compared between groups. Logistic regression was used to determine the optimal diffusion metrics and clinicopathologic variables for classifying the HER2-expressing statuses. Receiver operating characteristic(ROC) curves were used to evaluate their discriminative ability. The estrogen receptor (ER) status, progesterone receptor (PR) status, and tumor size differed between HER2-low-expressing and HER2-overexpressing groups (p < 0.001 to p = 0.009). The αCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM were significantly lower in HER2-low-expressing BCs than those in HER2-overexpressing BCs (p < 0.001 to p = 0.01). Further multivariable logistic regression analysis showed that the αCTRW was the single best discriminative metric, with an area under the curve (AUC) being higher than that of ADC (0.802 vs. 0.610, p < 0.05); the addition of ER status, PR status, and tumor size to the αCTRW improved the AUC to 0.877. The αCTRW could help discriminate the HER2-low-expressing and HER2-overexpressing BCs. Human epidermal growth factorreceptor 2 (HER2)-low-expressing breast cancer (BC) might also benefit from the HER2-targeted therapy. Prediction of HER2-low-expressing BC or HER2-overexpressing BC is crucial for appropriate management. Advanced continuous-time random walk diffusion MRI offers a solution to this clinical issue. • Human epidermal receptor 2 (HER2)-low-expressing BC had lower αCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM values compared with HER2-overexpressing breast cancer. • The αCTRW was the single best diffusion metric (AUC = 0.802) for discrimination between the HER2-low-expressing and HER2-overexpressing breast cancers. • The addition of αCTRW to the clinicopathologic features (estrogen receptor status, progesterone receptor status, and tumor size) further improved the discriminative ability.

Placental differences between uncomplicated and complicated monochorionic diamniotic pregnancies on diffusion and multicompartment Magnetic Resonance Imaging

IntroductionTwin-twin transfusion syndrome (TTTS) and selective fetal growth restriction (sFGR) are common complications in monochorionic diamniotic (MCDA) pregnancies. The Diffusion-rElaxation Combined Imaging for Detailed Placental Evaluation (DECIDE) model, a placental-specific model, separates the T2 values of the fetal and maternal blood from the background tissue and estimates the fetal blood oxygen saturation. This study investigates diffusion and relaxation differences in uncomplicated MCDA pregnancies and MCDA pregnancies complicated by TTTS and sFGR in mid-pregnancy. MethodsThis prospective monocentric cohort study included uncomplicated MCDA pregnancies and pregnancies complicated by TTTS and sFGR. We performed MRI with conventional diffusion-weighted imaging (DWI) and combined relaxometry – DWI-intravoxel incoherent motion. DECIDE analysis was used to quantify different parameters within the placenta related to the fetal, placental, and maternal compartments. ResultsWe included 99 pregnancies, of which 46 were uncomplicated, 12 were complicated by sFGR and 41 by TTTS. Conventional DWI did not find differences between or within cohorts. On DECIDE imaging, fetoplacental oxygen saturation was significantly lower in the smaller member of sFGR (p = 0.07) and in both members of TTTS (p = 0.01 and p = 0.004) compared to the uncomplicated pairs. Additionally, average T2 relaxation time was significantly lower in the smaller twin of the sFGR (p = 0.004) compared to the uncomplicated twins (p = 0.03). ConclusionMulticompartment functional MRI showed significant differences in several MRI parameters between the placenta of uncomplicated MCDA pregnancies and those complicated by sFGR and TTTS in mid-pregnancy.

Evaluation of the Real-time Teleradiology Consultation System in the Emergency Department

ABSTRACT Background and Objectives: Teleradiology involves the transmission of all radiological images to a radiologist in a remote location to ensure an accurate diagnosis. Although various teleradiology systems exist, there is not a fully accepted real-time interactive teleradiology system yet. In this study, we analyzed “the teleradiology consultation system which includes a real-time and instant messaging program (Skype®)” established in an emergency department. Methods: The consultations requested from the teleradiology system implemented in the emergency department (ED) of a Medical Faculty Training and Research Hospital were evaluated between January 2018 and June 2018 retrospectively. Results: A total of 18,284 teleconsultations were included in the study. The mean age of the patients who required teleconsultation was 40.6 ± 24.8 years (range: 0–109 years) and 10,069 (55.1%) were male. And 17,079 (93.4%) computed tomography (CT) was consulted. The majority of CT scans were cranial CT (n = 7113, 41.6%) and upper-lower abdominal CT (n = 5436, 31.8%). And 1205 magnetic resonance imaging (MRIs) (6.6%) were consulted. The majority of MRIs were diffusion MRIs (n = 975, 80.9%). The mean evaluation time of radiological imaging was 66.3 minutes. In 7238 (39.6%) of all consultations, a problem or a demand was reported via interactive communication by radiologists or emergency physicians. They are as follows; the desire to speed up delayed reports (33.0%, n = 2388), problems related to radiological images (32.0%, n = 2316); demand for correction of delay problems from health system technicians (11.6%, n = 839), incomplete reporting (6.6%, n = 477), demand for the acceleration of reports of critical patients (6.4%, n = 463), request for re-evaluation of radiological images (5.2%, n = 376), the demand for additional clinical information of the radiology doctor (2.0%, n = 144), asking radiology doctor the statements in the report or to request for disclosure of findings (1.1%, n = 78), the other reasons (2.0%, n = 144). All of these problems were answered with real-time interviews and solved. Conclusion: The teleradiology system is important in health institutions where there is no 7/24 radiologist. Conclusions: This study showed that the establishment of a teleradiology consultation system integrated with a messaging service in the ED might provide real-time and immediate resolution of the occurring problems.

An interactive triangle-based ODF glyph rendering for high angular resolution diffusion imaging

Diffusion magnetic resonance imaging quantifies the diffusion of water molecules. It is unique in showing white matter fiber structures and connectivity in-vivo, relying on the fact that the water molecules’ displacements are more significant along with the fiber orientation than in other directions due to biological barriers. High angular resolution diffusion imaging (HARDI) acquisition enables the differentiation of multiple fiber signals passing through a voxel. Advanced methods for processing diffusion data were developed to synthesize the HARDI data of each voxel into an orientation distribution function (ODF) that relates each direction sample to its probability of water diffusion. Visualizing ODFs through glyphs helps gain insight into the local structure of the brain white matter. Because of the high dimensionality of the data, interactive glyph exploration remains a challenge for a volume containing millions of voxels. This work presents a 3D triangle-based multi-resolution rendering scheme for the ODF glyph. We explored data properties and GPU features to make the triangle-based rendering interactive. Linear performance relative to some fixed-resolution rendered glyphs was assessed using NVIDIA® Nsight Visual StudioTM. A control volume, available in the Retest dataset of the WU-Minn Human Connectome Project, was used to assess the effectiveness of interactive 3D visualization over a multiplanar and curvilinear reformatted volume of ODF glyphs in voxels with multiple fibers, namely the triple crossing at the centrum semiovale, the fanning at the corona radiata, and the crossing of the cingulum and corpus callosum fiber bundles.

Incorporating interface permeability into the diffusion MRI signal representation while using impermeable Laplace eigenfunctions

Objective. The complex-valued transverse magnetization due to diffusion-encoding magnetic field gradients acting on a permeable medium can be modeled by the Bloch–Torrey partial differential equation. The diffusion magnetic resonance imaging (MRI) signal has a representation in the basis of the Laplace eigenfunctions of the medium. However, in order to estimate the permeability coefficient from diffusion MRI data, it is desirable that the forward solution can be calculated efficiently for many values of permeability. Approach. In this paper we propose a new formulation of the permeable diffusion MRI signal representation in the basis of the Laplace eigenfunctions of the same medium where the interfaces are made impermeable. Main results. We proved the theoretical equivalence between our new formulation and the original formulation in the case that the full eigendecomposition is used. We validated our method numerically and showed promising numerical results when a partial eigendecomposition is used. Two diffusion MRI sequences were used to illustrate the numerical validity of our new method. Significance. Our approach means that the same basis (the impermeable set) can be used for all permeability values, which reduces the computational time significantly, enabling the study of the effects of the permeability coefficient on the diffusion MRI signal in the future.

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning.

The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones. Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature. Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines. Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Diffusion magnetic resonance imaging-based surrogate marker in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is the most prevalent type of motor neuron disease (MND) and is diagnosed with a delay from the first appearance of symptoms. Surrogate markers that may be used to detect pathological changes before a significant neuronal loss occurs and allow for early intervention with disease-modifying therapy techniques are desperately needed. Using water molecules that diffuse within the tissue and experience displacement on the micron scale, diffusion magnetic resonance imaging (MRI) is a promising technique that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, axonal density, order, and myelination. Diffusion tensor imaging (DTI) is the primary diffusion MRI technique used to evaluate the pathogenesis of ALS. Neurite orientation dispersion and density imaging (NODDI), diffusion kurtosis imaging (DKI), and free water elimination DTI (FWE-DTI) are only a few of the approaches that have been developed to overcome the shortcomings of the diffusion tensor technique. This article provides a summary of these methods and their potential as surrogate markers for detecting the onset of ALS at an early stage.

Structural impairment in superficial and deep white matter in schizophrenia.

Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects. We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonizing the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fiber clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman's rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing. Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial-occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing. We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.

Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI.

The hippocampus is classically divided into mesoscopic subfields which contain varying microstructure that contribute to their unique functional roles. It has been challenging to characterize this microstructure with current magnetic resonance based neuroimaging techniques. In this work, we used diffusion magnetic resonance imaging (dMRI) and a novel surface-based approach in the hippocampus which revealed distinct microstructural distributions of neurite density and dispersion, T1w/T2w ratio as a proxy for myelin content, fractional anisotropy, and mean diffusivity. We used the neurite orientation dispersion and density imaging (NODDI) model optimized for grey matter diffusivity to characterize neurite density and dispersion. We found that neurite dispersion was highest in the cornu ammonis (CA) 1 and subiculum subfields which likely captures the large heterogeneity of tangential and radial fibres, such as the Schaffer collaterals, perforant path, and pyramidal neurons. Neurite density and T1w/T2w were highest in the subiculum and CA3 and lowest in CA1, which may reflect known myeloarchitectonic differences between these subfields. Using a simple logistic regression model, we showed that neurite density, dispersion, and T1w/T2w measures were separable across the subfields, suggesting that they may be sensitive to the known variability in subfield cyto- and myeloarchitecture. We report macrostructural measures of gyrification, thickness, and curvature that were in line with ex vivo descriptions of hippocampal anatomy. We employed a multivariate orthogonal projective non-negative matrix factorization (OPNNMF) approach to capture co-varying regions of macro- and microstructure across the hippocampus. The clusters were highly variable along the medial-lateral (proximal-distal) direction, likely reflecting known differences in morphology, cytoarchitectonic profiles, and connectivity. Finally, we show that by examining the main direction of diffusion relative to canonical hippocampal axes, we could identify regions with stereotyped microstructural orientations that may map onto specific fibre pathways, such as the Schaffer collaterals, perforant path, fimbria, and alveus. These results highlight the value of combining in vivo dMRI with computational approaches for capturing hippocampal microstructure, which may provide useful features for understanding cognition and for diagnosis of disease states.

Diagnostic Approach and Differences between Spinal Infections and Tumors.

A systematic review of the literature about differential diagnosis between spine infection and bone tumors of the spine. The differential diagnosis between spine infection and bone tumors of the spine can be misled by the prevalence of one of the conditions over the other in different areas of the world. A review of the existing literature on suggestive or even pathognomonic imaging aspects of both can be very useful for correctly orientating the diagnosis and deciding the most appropriate area for biopsy. The purpose of our study is to identify which imaging technique is the most reliable to suggest the diagnosis between spine infection and spine bone tumor. A primary search on Medline through PubMed distribution was made. We identified five main groups: tuberculous, atypical spinal tuberculosis, pyogenic spondylitis, and neoplastic (primitive and metastatic). For each group, we evaluated the commonest localization, characteristics at CT, CT perfusion, MRI, MRI with Gadolinium, MRI diffusion (DWI) and, in the end, the main features for each group. A total of 602 studies were identified through the database search and a screening by titles and abstracts was performed. After applying inclusion and exclusion criteria, 34 articles were excluded and a total of 22 full-text articles were assessed for eligibility. For each article, the role of CT-scan, CT-perfusion, MRI, MRI with Gadolinium and MRI diffusion (DWI) in distinguishing the most reliable features to suggest the diagnosis of spine infection versus bone tumor/metastasis was collected. Definitive differential diagnosis between infection and tumor requires biopsy and culture. The sensitivity and specificity of percutaneous biopsy are 72% and 94%, respectively. Imaging studies can be added to address the diagnosis, but a multidisciplinary discussion with radiologists and nuclear medicine specialists is mandatory.

Usefulness of Diffusion Weighted MRI in Differentiating Benign from Malignant Bone Lesions

Background Bone tumors represent a wide spectrum of disease in children &amp; adult ranging from benign lesions to an aggressive malignancy, so finding a noninvasive diagnostic tool was needed. Objective We aimed to differentiate between benign and malignant bone lesions and to limits the number of patient with benign lesion who undergo biopsy. Patients and Methods Our study was carried out on 32 patients were diagnosed with bone tumors (21 benign &amp; 11 malignant), at the MRI unit of the Radiology Department Ain Shams University, outpatient clinics and private centers after getting approval from each ethical committee. They were assessed with conventional &amp; diffusion MR images, DW EPI carried out using different b values including 0 s/ mm², 500 s/ mm², and 800 s/ mm². ADC map were automatically calculated. Results The mean ADC value for benign tumors was 1.6±0.4 x 10 -3 mm2/s. while malignant tumors were 1.2±0.3 x 10 -3 mm2/s. ROC analysis was used to define the best cut off mean ADC value for detecting malignancy which was &amp;lt;1.3, with sensitivity of 81.8% specificity of 81%. Conclusion The present study showed high specificity and sensitivity of DWI as a complementary sequence with conventional MRI and ADC value measurements in discrimination between benign and malignant bone tumors with significant cut-off value, making it a noninvasive tool for increasing the accuracy in identifying bone lesions.

Role of MRI Diffusion Tensor Imaging in Early Diagnosis of Cervical Spondylotic Myelopathy (CSM)

Abstract Background and Purpose Cervical spondylotic myelopathy (CSM) is a common degenerative disorder of the cervical spine and is considered as the most common cause of spinal cord dysfunction in older individuals worldwide. Assessing the severity of the disease objectively remains a challenge and there is still remaining controversy in terms of the optimal timing and indications for surgical intervention. The conventional MRI is the gold standard for radiographic evaluation of the spinal cord; however, it cannot assess the underlying microstructural deficits of the spinal cord and it has a limited application in determining prognosis and recovery of the disease [1]. We sought to assess the utility of MR diffusion tensor imaging as an imaging technique in clinically suggested CSM patients by obtaining the microstructural parameters (Fractional anisotropy; FA and apparent diffusion coefficient; ADC) in the cervical spinal cord segments. Patient &amp; methods our study was a prospective cross-sectional study including 40 patients with clinical manifestations of cervical spondylotic myelopathy. The patients were sorted according to the European myelopathy score into three categories as follows: grade 1 (with mild symptoms), grade 2 (with moderate symptoms) and grade 3 (with severe symptoms). All the patients were investigated with a 1.5 T MRI unit acquiring conventional MRI and DTI sequences. FA and ADC values at each spinal segment from C2/C3 to C6/C7 were generated and measured using manual drawing of multiple ROIs within the cervical cord in the sagittal and axial combined anatomical and color-coded images. For each of these cases, the patient’s age, gender, DTI parameters at each spinal segment level, maximum compression level, conventional T2WI characteristics and EMS score were recorded, analyzed and compared. Results The study included 23 females (57.5%) and 17 males (42.5%). Their age ranged from 30 to 72 years with a mean age of 47.3 ± 9.79 years. The study revealed a significant difference in the mean FA and ADC values between stenotic and non-stenotic segments of the cervical spinal cord. There was a significant correlation between the European myelopathy score and DTI parameters (FA and ADC). FA and ADC values performed better in recognizing myelopathic changes in patients who were classified as grade 1 according to EMS compared to conventional MRI T2WI which performed very poorly in recognizing myelopathy changes in the same patients, therefore DTI indices were more sensitive in the detection of CSM patients compared to conventional MRI especially in early myelopathic stages. T2 weighted images were highly significant in recognizing myelopathy changes in patients who were classified as grade 3 according to EMS. The CSM patients had significant FA decrease and ADC increase at the most compressed part of the cervical spinal cord and there was a significant correlation between the number of patients who had myelopathic changes by DTI parameters and the severity of disease. The FA sensitivity and specificity in recognition of myelopathic changes were 73.5% and 83.3% respectively and the ADC sensitivity and specificity were 100% and 70.6% respectively. Conclusion In conclusion, diffusion tensor imaging enhances the efficacy and accuracy of MRI in the diagnosis of cervical spondylotic myelopathy. Therefore, it can be used as a non-invasive modality for detection of the spondylotic myelopathy changes in the early stages helping to decide the appropriate timing of decompression surgery before attaining the irreversible chronic changes. Abbreviations ADC: Apparent diffusion coefficient; CSM: Cervical spondylotic myelopathy; DTI: Diffusion tensor imaging; FA: Fractional Anisotropy; EMS: European myelopathy score

Evidence for adaptive myelination of subcortical shortcuts for visual motion perception in healthy adults.

Conscious visual motion information follows a cortical pathway from the retina to the lateral geniculate nucleus (LGN) and on to the primary visual cortex (V1) before arriving at the middle temporal visual area (MT/V5). Alternative subcortical pathways that bypass V1 are thought to convey unconscious visual information. One flows from the retina to the pulvinar (PUL) and on to medial temporal visual area (MT); while the other directly connects the LGN to MT. Evidence for these pathways comes from non-human primates and modest-sized studies in humans with brain lesions. Thus, the aim of the current study was to reconstruct these pathways in a large sample of neurotypical individuals and to determine the degree to which these pathways are myelinated, suggesting information flow is rapid. We used the publicly available 7T (N = 98; 'discovery') and 3T (N = 381; 'validation') diffusion magnetic resonance imaging datasets from the Human Connectome Project to reconstruct the PUL-MT (including all subcompartments of the PUL) and LGN-MT pathways. We found more fibre tracts with greater density in the left hemisphere. Although the left PUL-MT path was denser, the bilateral LGN-MT tracts were more heavily myelinated, suggesting faster signal transduction. We suggest that this apparent discrepancy may be due to 'adaptive myelination' caused by more frequent use of the LGN-MT pathway that leads to greater myelination and faster overall signal transmission.

VersaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database.

The lack of "gold standards" in Diffusion Weighted Imaging (DWI) makes validation cumbersome. To tackle this task, studies use translational analysis where results in humans are benchmarked against findings in other species. Non-Human Primates (NHP) are particularly interesting for this, as their cytoarchitecture is closely related to humans. However, tools used for processing and analysis must be adapted and finely tuned to work well on NHP images. Here, we propose versaFlow, a modular pipeline implemented in Nextflow, designed for robustness and scalability. The pipeline is tailored to in vivo NHP DWI at any spatial resolution; it allows for maintainability and customization. Processes and workflows are implemented using cutting-edge and state-of-the-art Magnetic Resonance Imaging (MRI) processing technologies and diffusion modeling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD), and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND). Using versaFlow, we provide an in-depth study of the variability of diffusion metrics computed on 32 subjects from 3 sites of the Primate Data Exchange (PRIME-DE), which contains anatomical T1-weighted (T1w) and T2-weighted (T2w) images, functional MRI (fMRI), and DWI of NHP brains. This dataset includes images acquired over a range of resolutions, using single and multi-shell gradient samplings, on multiple scanner vendors. We perform a reproducibility study of the processing of versaFlow using the Aix-Marseilles site's data, to ensure that our implementation has minimal impact on the variability observed in subsequent analyses. We report very high reproducibility for the majority of metrics; only gamma distribution parameters of DIAMOND display less reproducible behaviors, due to the absence of a mechanism to enforce a random number seed in the software we used. This should be taken into consideration when future applications are performed. We show that the PRIME-DE diffusion data exhibits a great level of variability, similar or greater than results obtained in human studies. Its usage should be done carefully to prevent instilling uncertainty in statistical analyses. This hints at a need for sufficient harmonization in acquisition protocols and for the development of robust algorithms capable of managing the variability induced in imaging due to differences in scanner models and/or vendors.

White Matter Microstructural Differences between Essential Tremor and Parkinson Disease, Evaluated Using Advanced Diffusion MRI Biomarkers.

Essential tremor (ET) is a common slowly-progressive neurologic disorder. It is predominantly characterized by kinetic tremors involving bilateral upper limbs. Although ET shares motor similarities with Parkinson disease (PD), there is no known relationship between ET and PD. We studied white matter differences between 17 ET and 68 PD patients using standard diffusion tensor imaging and fixel-based analysis (FBA). Diffusion magnetic resonance imaging data were acquired from two scanners (General Electric (GE) and Philips) with different numbers of diffusion directions. Fractional anisotropy maps were generated by the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL), and FBA was performed using MRtrix3 to obtain fiber density, fiber bundle, and fiber density bundle cross-section. Compared with PD, significantly lower values of fiber density, fiber bundle, and fiber density bundle cross-section were found in the corpus callosum and left tapetum of the ET group. Additionally, significantly lower functional anisotropy values were found in the ET compared to the PD group, principally in the corpus callosum, corona radiata, and cingulum. In conclusion, differences in white matter integrity between ET and PD were observed by both FBA-based metrics and diffusion tensor imaging. Advanced diffusion-based metrics may provide a better understanding of the white matter microstructural characteristics in disparate motor-associated diseases with different underlying phenotypes, such as ET and PD.

Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI

BackgroundThis study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases.MethodsA retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz − ADC0Hz and the relative ADC change (rcADC): (ADC50Hz − ADC0Hz)/ ADC0Hz × 100 (%).ResultsThe mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10−3mm2/s vs. 0.14 ± 0.03 × 10−3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001).ConclusionsThe time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.