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BackgroundBehavioural Variant Frontotemporal Dementia (bvFTD) is a rapidly progressing neurodegenerative proteinopathy. Perivascular spaces (PVS) form a part of the brain’s glymphatic clearance system. When enlarged due to poor glymphatic clearance of toxic proteins, PVS become larger and more conspicuous on MRI. Therefore, enlarged PVS may be a useful biomarker of disease severity and progression in neurodegenerative proteinopathies such as bvFTD. This study aimed to determine the utility of PVS as a biomarker of disease progression in patients with bvFTD.Materials and methodsSerial baseline and week 52 MRIs acquired from ten patients with bvFTD prospectively recruited and followed in a Phase 1b open label trial of sodium selenate for bvFTD were used in this study. An automated algorithm quantified PVS on MRI, which was visually inspected and validated by a member of the study team. The number and volume of PVS were extracted and mixed models used to assess the relationship between PVS burden and other measures of disease (cognition, carer burden scale, protein biomarkers). Additional exploratory analysis investigated PVS burden in patients who appeared to not progress over the 12 months of selenate treatment (i.e., “non-progressors”).ResultsOverall, PVS cluster number (ß = −3.27, CI [−7.80 – 1.27], p = 0.267) and PVS volume (ß = −36.8, CI [−84.9 – 11.3], p = 0.171) did not change over the paired MRI scans 12 months apart. There was association between cognition total composite scores and the PVS burden (PVS cluster ß = −0.802e–3, CI [9.45e–3 – −6.60e–3, p ≤ 0.001; PVS volume ß = −1.30e–3, CI [−1.55e–3 – −1.05e–3], p ≤ 0.001), as well as between the change in the cognition total composite score and the change in PVS volume (ß = 4.36e–3, CI [1.33e–3 – 7.40e–3], p = 0.046) over the trial period. There was a significant association between CSF t-tau and the number of PVS clusters (ß = 2.845, CI [0.630 – 5.06], p = 0.036). Additionally, there was a significant relationship between the change in CSF t-tau and the change in the number of PVS (ß = 1.54, CI [0.918 – 2.16], p < 0.001) and PVS volume (ß = 13.8, CI [6.37 – 21.1], p = 0.003) over the trial period. An association was found between the change in NfL and the change in PVS volume (ß = 1.40, CI [0.272 – 2.52], p = 0.045) over time. Within the “non-progressor” group (n = 7), there was a significant relationship between the change in the CSF total-tau (t-tau) levels and the change in the PVS burden (PVS cluster (ß = 1.46, CI [0.577 – 2.34], p = 0.014; PVS volume ß = 14.6, CI [3.86 – 25.4], p = 0.032) over the trial period. Additionally, there was evidence of a significant relationship between the change in NfL levels and the change in the PVS burden over time (PVS cluster ß = 0.296, CI [0.229 – 0.361], p ≤ 0.001; PVS volume ß = 3.67, CI [2.42 – 4.92], p = 0.002).ConclusionAnalysis of serial MRI scans 12 months apart in patients with bvFTD demonstrated a relationship between PVS burden and disease severity as measured by the total cognitive composite score and CSF t-tau. Further studies are needed to confirm PVS as a robust marker of neurodegeneration in proteinopathies.

The current concept of brain aging proposes three gradient patterns of changes in white matter that occur during healthy brain aging: antero-posterior, supero-inferior, and the myelodegeneration-retrogenesis (or the “last-in-first-out”) concept. The aim of this study was to correlate white matter diffusivity measures (fractional anisotropy-FA, mean diffusivity-MD, radial diffusivity-RD, and axial diffusivity-AD) in healthy volunteers with chronological age and education level, in order to potentially incorporate the findings with proposed patterns of physiological brain aging. The study was performed on 75 healthy participants of both sexes, with an average age of 37.32 ± 11.91 years underwent brain magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). DTI was performed using tract-based spatial statistics (TBSS), with the analysis of four parameters: FA, MD, RD, and AD. Skeletonized measures were averaged in 29 regions of interest in white matter. Correlations between age and DTI measures and between education-level and DTI measures were performed using Pearson's correlation test. To correct for multiple comparisons, we applied a Bonferroni correction to the p-values. Significance was set at p ≤ 0.001. A significant negative correlation of FA with age was observed in posterior thalamic radiation (PTR) (p< 0.001). A significant positive correlation between age and MD was observed in sagittal stratum (SS) (p< 0.001), between age and RD in PTR, SS, and retrolenticular internal capsule (p< 0.001), and between age and AD in the body of the corpus callosum (p< 0.001). There were no significant correlations of DTI parameters with educational level. According to our study, RD showed the richest correlations with age, out of all DTI metrics. FA, MD, and RD showed significant changes in the diffusivity of projection fibers, while AD presented diffusivity changes in the commissural fibers. The observed heterogeneity in diffusivity changes across the brain cannot be explained by a single aging gradient pattern, since it seems that different patterns of degradation are true for different fiber tracts that no currently available theory can globally explain age-related changes in the brain. Additional factors, such as the effect of somatosensory decline, should be included as one of the important covariables to the existing patterns.

Axonal loss in the CNS is a key driver of progressive neurological impairments in people with multiple sclerosis. Currently, there are no established methods for tracking axonal loss clinically. This study aimed to determine the sensitivity of longitudinal diffusion MRI-derived fibre-specific measures of axonal loss in people with multiple sclerosis. Fibre measures were derived from diffusion MRI acquired as part of a standard radiological MRI protocol and were compared (i) to establish measures of neuro-axonal degeneration: brain parenchymal fraction and retinal nerve fibre layer thickness and (ii) between different disease stages: clinically isolated syndrome and early/late relapsing–remitting multiple sclerosis. Retrospectively identified data from 59 people with multiple sclerosis (18 clinically isolated syndrome, 22 early and 19 late relapsing–remitting) who underwent diffusion MRI as part of their routine clinical monitoring were collated and analysed. Twenty-six patients had 1-year and 14 patients had a 2-year follow-up. Brain parenchymal fraction was calculated from 3D MRI scans, and fibre-specific measures were calculated from diffusion MRI using multi-tissue constrained spherical deconvolution. At each study visit, patients underwent optical coherence tomography to determine retinal nerve fibre layer thickness, and standard neurological assessment expanded the disability status scale. We found a significant annual fibre-specific neuro-axonal degeneration (mean ± SD = −3.49 ± 3.32%, P < 0.001) that was ∼7 times larger than the annual change of brain parenchymal fraction (−0.53 ± 0.95%, P < 0.001), and more than four times larger than annual retinal nerve fibre layer thinning (−0.75 ± 2.50% P = 0.036). Only fibre-specific measures showed a significant difference in annual degeneration between the disease stages (P = 0.029). Reduced brain parenchymal fraction, retinal nerve fibre layer thickness and fibre-specific measures were moderately related to higher expanded disability status scale (rho = −0.368, rho = −0.408 and rho = −0.365, respectively). Fibre-specific measures can be measured from data collected within a standard radiological multiple sclerosis study and are substantially more sensitive to longitudinal change compared with brain atrophy and retinal nerve fibre layer thinning.

Supplemental material, sj-pdf-4-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-4-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-3-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-2-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Supplemental material, sj-pdf-3-jcb-10.1177_0271678X20972856 for Body mass index, time of day, and genetics affect perivascular spaces in the white matter by Giuseppe Barisano, Nasim Sheikh-Bahaei, Meng Law, Arthur W Toga and Farshid Sepehrband in Journal of Cerebral Blood Flow & Metabolism

Recent works show that Generative Adversarial Networks (GANs) can be successfully applied to chest X-ray data augmentation for lung disease recognition. However, the implausible and distorted pathology features generated from the less than perfect generator may lead to wrong clinical decisions. Why not keep the original pathology region? We proposed a novel approach that allows our generative model to generate high quality plausible images that contain undistorted pathology areas. The main idea is to design a training scheme based on an image-to-image translation network to introduce variations of new lung features around the pathology ground-truth area. Moreover, our model is able to leverage both annotated disease images and unannotated healthy lung images for the purpose of generation. We demonstrate the effectiveness of our model on two tasks: (i) we invite certified radiologists to assess the quality of the generated synthetic images against real and other state-of-the-art generative models, and (ii) data augmentation to improve the performance of disease localisation., Code: https://github.com/yunyanxing/pairwise_xray_augmentation - Accepted to the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2019

Purpose: To apply tracer kinetic models as temporal constraints during reconstruction of under-sampled dynamic contrast enhanced (DCE) MRI. Methods: A library of concentration v.s time profiles is simulated for a range of physiological kinetic parameters. The library is reduced to a dictionary of temporal bases, where each profile is approximated by a sparse linear combination of the bases. Image reconstruction is formulated as estimation of concentration profiles and sparse model coefficients with a fixed sparsity level. Simulations are performed to evaluate modeling error, and error statistics in kinetic parameter estimation in presence of noise. Retrospective under-sampling experiments are performed on a brain tumor DCE digital reference object (DRO) at different signal to noise levels (SNR=20-40) at (k-t) space under-sampling factor (R=20), and 12 brain tumor in- vivo 3T datasets at (R=20-40). The approach is compared against an existing compressed sensing based temporal finite-difference (tFD) reconstruction approach. Results: Simulations demonstrate that sparsity levels of 2 and 3 model the library profiles from the Patlak and extended Tofts-Kety (ETK) models, respectively. Noise sensitivity analysis showed equivalent kinetic parameter estimation error statistics from noisy concentration profiles, and model approximated profiles. DRO based experiments showed good fidelity in recovery of kinetic maps from 20-fold under- sampled data at SNRs between 10-30. In-vivo experiments demonstrated reduced bias and uncertainty in kinetic mapping with the proposed approach compared to tFD at R>=20. Conclusions: Tracer kinetic models can be applied as temporal constraints during DCE-MRI reconstruction, enabling more accurate reconstruction from under- sampled data. The approach is flexible, can use several kinetic models, and does not require tuning of regularization parameters., Submitted to Medical Physics. 9 figures; 1 table; 32 pages

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is used to track the first pass of an exogenous, paramagnetic, nondiffusible contrast agent through brain tissue, and has emerged as a powerful tool in the characterization of brain tumor hemodynamics. DSC-MRI parameters can be helpful in many aspects, including tumor grading, prediction of treatment response, likelihood of malignant transformation, discrimination between tumor recurrence and radiation necrosis, and differentiation between true early progression and pseudoprogression. This review aims to provide a conceptual overview of the underlying principles of DSC-MRI of the brain for clinical neuroradiologists, scientists, or students wishing to improve their understanding of the technical aspects, pitfalls, and controversies of DSC perfusion MRI of the brain. Future consensus on image acquisition parameters and postprocessing of DSC-MRI will most likely allow this technique to be evaluated and used in high-quality multicenter studies and ultimately help guide clinical care.

To determine optimal parameters for acquisition and processing of dynamic contrast-enhanced MRI (DCE-MRI) to detect small changes in near normal low blood-brain barrier (BBB) permeability.Using a contrast-to-noise ratio metric (K-CNR) for Ktrans precision and accuracy, the effects of kinetic model selection, scan duration, temporal resolution, signal drift, and length of baseline on the estimation of low permeability values was evaluated with simulations.The Patlak model was shown to give the highest K-CNR at low Ktrans . The Ktrans transition point, above which other models yielded superior results, was highly dependent on scan duration and tissue extravascular extracellular volume fraction (ve ). The highest K-CNR for low Ktrans was obtained when Patlak model analysis was combined with long scan times (10-30 min), modest temporal resolution (60 s/image), and long baseline scans (1-4 min). Signal drift as low as 3% was shown to affect the accuracy of Ktrans estimation with Patlak analysis.DCE acquisition and modeling parameters are interdependent and should be optimized together for the tissue being imaged. Appropriately optimized protocols can detect even the subtlest changes in BBB integrity and may be used to probe the earliest changes in neurodegenerative diseases such as Alzheimer's disease and multiple sclerosis.

A 15-year-old male high school football player presented with episodes of headache and complete body stiffness, especially in the arms, lower back, and thighs, immediately following a football game. This was accompanied by severe nausea and vomiting for several days. Viral meningitis was suspected by the primary clinician, and treatment with corticosteroids was initiated. Over the next several weeks, there was gradual symptom improvement and the patient returned to his baseline clinical status. The patient experienced a severe recurrence of the previous myriad of symptoms following a subsequent football game, without an obvious isolated traumatic episode. In addition, he experienced a new left sided headache, fatigue, and difficulty ambulating. He was admitted and an extensive workup was performed. CT and MRI of the head revealed concurrent intracranial and spinal subdural hematomas (SDH). Clinical workup did not reveal any evidence of coagulopathy or predisposing vascular lesions. Spinal SDH is an uncommon condition whose concurrence with intracranial SDH is an even greater clinical rarity. We suggest that our case represents an acute on chronic intracranial SDH with rebleeding, membrane rupture, and symptomatic redistribution of hematoma to the spinal subdural space.

International audience; PURPOSE: Dynamic contrast-enhanced imaging provides unique physiological information, notably the endothelial permeability (K(trans) ), and may improve the diagnosis and management of multiple pathologies. Current acquisition methods provide limited spatial-temporal resolution and field-of-view, often preventing characterization of the entire pathology and precluding measurement of the arterial input function. We present a method for highly accelerated dynamic imaging and demonstrate its utility for dynamic contrast-enhanced modeling. METHODS: We propose a novel Poisson ellipsoid sampling scheme and enforce multiple spatial and temporal l1 -norm constraints during image reconstruction. Retrospective and prospective analyses were performed to validate the approach. RESULTS: Retrospectively, no mean bias or diverging trend was observed as the acceleration rate was increased from 3× to 18×; less than 10% error was measured in K(trans) at any individual rates in this range. Prospectively accelerated images at a rate of 36× enabled full brain coverage with 0.94 × 0.94 × 1.9 mm(3) spatial and 4.1 s temporal resolutions. Images showed no visible degradation and provided accurate K(trans) values when compared to a clinical population. CONCLUSION: Highly accelerated dynamic MRI using compressed sensing and parallel imaging provides accurate permeability modeling and enables full brain, high resolution acquisitions. Magn Reson Med 000:000-000, 2013. © 2013 Wiley Periodicals, Inc.

In two children with near drowning hypoxic encephalopathy and normal-appearing structural MRI, acute proton magnetic resonance spectroscopy (¹H MRS) showed biochemical alterations that correctly indicated prognosis and helped to guide management decisions. Elevation of the lipid-lactate and glutamine-glutamate peaks, on the early (72 hour) ¹H MRS, predicts a poor prognosis. Absence of lipid-lactate and glutamine-glutamate peaks on the early ¹H MRS and reversibility of early mild metabolite abnormalities on follow up examination relates with good outcome. Em duas criancas vítimas de quase-afogamento com encefalopatia hipóxico-isquêmica, que apresentaram ressonância magnética por imagem normal, a espectroscopia de prótons por ressonância magnética (¹H MRS) na fase aguda mostrou alterações bioquímicas que corretamente indicaram o prognóstico e ajudaram a guiar o manejo terapêutico. Elevação dos picos de lipídeo-lactato e glutamina-glutamato na ¹H MRS precoce realizada com 72 horas previu um mau prognóstico. Relacionaram-se com bom prognóstico; a ausência dos picos de lipídeo-lactato e glutamina-glutamato na ¹H MRS precoce, e a reversibilidade no exame de controle (3 meses) das discretas anormalidades metabólicas encontradas no primeiro exame.

BACKGROUND AND PURPOSE: Preoperative differentiation of primitive neuroectodermal tumors (PNETs) from other tumors is important for presurgical staging, intraoperative management, and postoperative treatment. Dynamic, susceptibility-weighted, contrast-enhanced MR imaging can provide in vivo assessment of the microvasculature in intracranial mass lesions. The purpose of this study was to determine the perfusion characteristics of adult cerebral PNETs and to compare those values with low and high grade gliomas. METHODS: Conventional MR images of 12 adult patients with pathologically proved cerebral PNETs were analyzed and provided a preoperative diagnosis. Relative cerebral blood volume (rCBV) measurements and estimates of the vascular permeability transfer constant, K(trans), derived by a pharmacokinetic modeling algorithm, were also obtained. These results were compared with rCBV and K(trans) values obtained in a group of low grade gliomas (n = 30) and a group of high grade gliomas (n = 55) by using a Student t test. RESULTS: On conventional MR images, PNETs were generally well-defined contrast-enhancing masses with solid and cystic components, little or no surrounding edema, and occasional regions of susceptibility. The rCBV of cerebral PNETs was 4.76 ± 1.99 SD, and the K(trans) was 0.0033 ± 0.0035. A comparative group of patients with low grade gliomas (n = 30) had significantly lower rCBV (P < .0005) and lower K(trans) (P < .05). Comparison with a group of high grade gliomas showed no statistical significance in the rCBV and K(trans) (P = .53 and .19, respectively). CONCLUSION: Dynamic, susceptibility-weighted, contrast-enhanced MR imaging shows areas of increased cerebral blood volume and vascular permeability in PNETs. These results may be helpful in the diagnosis and preoperative differentiation between PNETs and other intracranial mass lesions (such as low grade gliomas), which have decreased perfusion but may sometimes have a similar conventional MR imaging appearance.

BACKGROUND AND PURPOSE: Sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of conventional MR imaging in predicting glioma grade are not high. Relative cerebral blood volume (rCBV) measurements derived from perfusion MR imaging and metabolite ratios from proton MR spectroscopy are useful in predicting glioma grade. We evaluated the sensitivity, specificity, PPV, and NPV of perfusion MR imaging and MR spectroscopy compared with conventional MR imaging in grading primary gliomas. METHODS: One hundred sixty patients with a primary cerebral glioma underwent conventional MR imaging, dynamic contrast-enhanced T2*-weighted perfusion MR imaging, and proton MR spectroscopy. Gliomas were graded as low or high based on conventional MR imaging findings. The rCBV measurements were obtained from regions of maximum perfusion. Metabolite ratios (choline [Cho]/creatine [Cr], Cho/N-acetylaspartate [NAA], and NAA/Cr) were measured at a TE of 144 ms. Tumor grade determined with the three methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic analyses were performed to determine optimum thresholds for tumor grading. Sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas were also calculated. RESULTS: Sensitivity, specificity, PPV, and NPV for determining a high-grade glioma with conventional MR imaging were 72.5%, 65.0%, 86.1%, and 44.1%, respectively. Statistical analysis demonstrated a threshold value of 1.75 for rCBV to provide sensitivity, specificity, PPV, and NPV of 95.0%, 57.5%, 87.0%, and 79.3%, respectively. Threshold values of 1.08 and 1.56 for Cho/Cr and 0.75 and 1.60 for Cho/NAA provided the minimum C2 and C1 errors, respectively, for determining a high-grade glioma. The combination of rCBV, Cho/Cr, and Cho/NAA resulted in sensitivity, specificity, PPV, and NPV of 93.3%, 60.0%, 87.5%, and 75.0%, respectively. Significant differences were noted in the rCBV and Cho/Cr, Cho/NAA, and NAA/Cr ratios between low- and high-grade gliomas (P < .0001, .0121, .001, and .0038, respectively). CONCLUSION: The rCBV measurements and metabolite ratios both individually and in combination can increase the sensitivity and PPV when compared with conventional MR imaging alone in determining glioma grade. The rCBV measurements had the most superior diagnostic performance (either with or without metabolite ratios) in predicting glioma grade. Threshold values can be used in a clinical setting to evaluate tumors preoperatively for histologic grade and provide a means for guiding treatment and predicting postoperative patient outcome.

BACKGROUND AND PURPOSE: The measurement of relative cerebral blood volume (rCBV) and the volume transfer constant (K(trans)) by means of dynamic contrast-enhanced (DCE) perfusion MR imaging (pMRI) can be useful in characterizing brain tumors. The purpose of our study was to evaluate the utility of these measurements in differentiating typical meningiomas and atypical meningiomas. METHODS: Fifteen patients with pathologically confirmed typical meningiomas and seven with atypical meningiomas underwent conventional imaging and DCE pMRI before resection. rCBV measurements were calculated by using standard intravascular indicator dilution algorithms. K(trans) was calculated from the same DCE pMRI data by using a new pharmacokinetic modeling (PM) algorithm. Results were compared with pathologic findings. RESULTS: Mean rCBV was 8.02 ± 4.74 in the 15 typical meningiomas and 10.50 ± 2.1 in the seven atypical meningiomas. K(trans) was 0.0016 seconds(−1) ± 0.0012 in the typical group and 0.0066 seconds(−1) ± 0.0026 in the atypical group. The difference in K(trans) was statistically significant (P < .01, Student t test). Other parameters generated with the PM algorithm (plasma volume, volume of the extravascular extracellular space, and flux rate constant) were not significantly different between the two tumor types. CONCLUSION: DCE pMRI may have a role in the prospective characterization of meningiomas. Specifically, the measurement of K(trans) is of use in distinguishing atypical meningiomas from typical meningiomas.

OBJECTIVE. This and its companion article address the 10 most frequently asked questions that radiologists face when planning, performing, processing, and interpreting different MR perfusion studies in CNS imaging. CONCLUSION. Perfusion MRI is a promising tool in assessing stroke, brain tumors, and patients with neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols. © American Roentgen Ray Society.

OBJECTIVE. This and its companion article address the 10 most frequently asked questions that radiologists face when planning, performing, processing, and interpreting different MR perfusion studies in CNS imaging. CONCLUSION. Perfusion MRI is a promising tool in assessing stroke, brain tumors, and patients with neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.