Fast and high-resolution quantitative mapping of tissue water content with full brain coverage for clinically-driven studies ☆ , ☆☆

a b s t r a c t a r t i c l e i n f o An efficient method for obtaining longitudinal relaxation time (T1) maps is based on acquiring two spoiled gradient recalled echo (SPGR) images in steady states with different flip angles, which has also been extended, with additional acquisitions, to obtain a tissue water content (M0) map. Several factors, including inhomogeneities of the radio-frequency (RF) fields and low signal-to-noise ratios may negatively affect the accuracy of this method and produce systematic errors in T1 and M0 estimations. Thus far, these limitations have been addressed by using additional measurements and applying suitable corrections; however, the concomitant increase in scan time is undesirable for clinical studies. In this note, a modified dual-acquisition SPGR method based on an optimization of the sequence formulism is presented for good and reliable M0 mapping with an isotropic spatial resolution of 1 × 1 × 1 mm 3 that covers the entire human brain in 6:30 min. A combined RF transmit/receive map is estimated from one of the SPGR scans and the optimal flip angles for M0 map are found analytically. The method was successfully evaluated in eight healthy subjects producing mean M0 values of 69.8% (in white matter) and 80.1% (in gray matter) that are in good agreement with those found in the literature and with high reproducibility. The mean value of the resultant voxel-based coefficients-of-variation was 3.6%

K-Bayes Reconstruction for Perfusion MRI I: Concepts and Application

Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. In this study, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach (described in detail in Part II: Modeling and Technical Development) combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT

Comparison of inter subject variability and reproducibility of whole brain proton spectroscopy.

The aim of these studies was to provide reference data on intersubject variability and reproducibility of metabolite ratios for Choline/Creatine (Cho/Cr), N-acetyl aspartate/Choline (NAA/Cho) and N-acetyl aspartate/Creatine (NAA/Cr), and individual signal-intensity normalised metabolite concentrations of NAA, Cho and Cr. Healthy volunteers underwent imaging on two occasions using the same 3T Siemens Verio magnetic resonance scanner. At each session two identical Metabolic Imaging and Data Acquisition Software (MIDAS) sequences were obtained along with standard structural imaging. Metabolite maps were created and regions of interest applied in normalised space. The baseline data from all 32 volunteers were used to calculate the intersubject variability, while within session and between session reproducibility were calculated from all the available data. The reproducibility of measurements were used to calculate the overall and within session 95% prediction interval for zero change. The within and between session reproducibility data were lower than the values for intersubject variability, and were variable across the different brain regions. The within and between session reproducibility measurements were similar for Cho/Cr, NAA/Choline, Cho and Cr (11.8%, 11.4%, 14.3 and 10.6% vs. 11.9%, 11.4%, 13.5% and 10.5% respectively), but for NAA/Creatine and NAA between session reproducibility was lower (9.3% and 9.1% vs. 10.1% and 9.9%; p <0.05). This study provides additional reference data that can be utilised in interventional studies to quantify change within a single imaging session, or to assess the significance of change in longitudinal studies of brain injury and disease.TV Veenith was supported by clinical research training fellowship from the National Institute of Academic Anaesthesia and Raymond Beverly Sackler studentship. VFJN is supported by an NIHR academic clinical fellowship. JPC was supported by Wellcome trust project grant. DKM is supported by an NIHR Senior Investigator Award. This work was supported by a Medical Research Council (UK) Program Grant (Acute brain injury: heterogeneity of mechanisms, therapeutic targets and outcome effects (G9439390 ID 65883)), the UK National Institute of Health Research Biomedical Research Centre at Cambridge, and the Technology Platform funding provided by the UK Department of Health.This article was originally published in PLoS ONE (Veenith TV, Mada M, Carter E, Grossac J, Newcombe V, et al. (2014) Comparison of Inter Subject Variability and Reproducibility of Whole Brain Proton Spectroscopy. PLoS ONE 9(12): e115304. doi:10.1371/journal.pone.0115304

Metabolic counterparts of sodium accumulation in multiple sclerosis: A whole brain 23Na-MRI and fast 1H-MRSI study

Increase of brain total sodium concentrations (TSC) is present in multiple sclerosis (MS), but its pathological involvement has not been assessed yet. To determine in vivo the metabolic counterpart of brain sodium accumulation. Whole brain Na-MR imaging and 3D- H-EPSI data were collected in 21 relapsing-remitting multiple sclerosis (RRMS) patients and 20 volunteers. Metabolites and sodium levels were extracted from several regions of grey matter (GM), normal-appearing white matter (NAWM) and white matter (WM) T lesions. Metabolic and ionic levels expressed as Z-scores have been averaged over the different compartments and used to explain sodium accumulations through stepwise regression models. MS patients showed significant Na accumulations with lower choline and glutamate-glutamine (Glx) levels in GM; Na accumulations with lower N-acetyl aspartate (NAA), Glx levels and higher Myo-Inositol (m-Ins) in NAWM; and higher Na, m-Ins levels with lower NAA in WM T lesions. Regression models showed associations of TSC increase with reduced NAA in GM, NAWM and T lesions, as well as higher total-creatine, and smaller decrease of m-Ins in T lesions. GM Glx levels were associated with clinical scores. Increase of TSC in RRMS is mainly related to neuronal mitochondrial dysfunction while dysfunction of neuro-glial interactions within GM is linked to clinical scores

Comprehensive Evaluation of Corticospinal Tract Metabolites in Amyotrophic Lateral Sclerosis Using Whole-Brain 1H MR Spectroscopy

Changes in the distribution of the proton magnetic resonance spectroscopy (MRS) observed metabolites N-acetyl aspartate (NAA), total-choline (Cho), and total-creatine (Cre) in the entire intracranial corticospinal tract (CST) including the primary motor cortex were evaluated in patients with amyotrophic lateral sclerosis (ALS). The study included 38 sporadic definite-ALS subjects and 70 age-matched control subjects. All received whole-brain MR imaging and spectroscopic imaging scans at 3T and clinical neurological assessments including percentage maximum forced vital capacity (FVC) and upper motor neuron (UMN) function. Differences in each individual metabolite and its ratio distributions were evaluated in the entire intracranial CST and in five segments along the length of the CST (at the levels of precentral gyrus (PCG), centrum semiovale (CS), corona radiata (CR), posterior limb of internal capsule (PLIC) and cerebral peduncle (CP)). Major findings included significantly decreased NAA and increased Cho and Cho/NAA in the entire intracranial CST, with the largest differences for Cho/NAA in all the groups. Significant correlations between Cho/NAA in the entire intracranial CST and the right finger tap rate were noted. Of the ten bilateral CST segments, significantly decreased NAA in 4 segments, increased Cho in 5 segments and increased Cho/NAA in all the segments were found. Significant left versus right CST asymmetries were found only in ALS for Cho/NAA in the CS. Among the significant correlations found between Cho/NAA and the clinical assessments included the left-PCG versus FVC and right finger tap rate, left -CR versus FVC and right finger tap rate, and left PLIC versus FVC and right foot tap rate. These results demonstrate that a significant and bilaterally asymmetric alteration of metabolites occurs along the length of the entire intracranial CST in ALS, and the MRS metrics in the segments correlate with measures of disease severity and UMN function

A retrospective analysis of ezrin protein and mRNA expression in breast cancer: Ezrin expression is associated with patient survival and survival of patients with receptor‐positive disease

Introduction: The cytoskeletal protein ezrin is upregulated in many cancer types and is strongly associated with poor patient outcome. While the clinical and prognostic value of ezrin has been previously evaluated in breast cancer, most studies to date have been conducted in smaller cohorts (less than 500 cases) or have focused on specific disease characteristics. The current study is the largest of its kind to evaluate ezrin both at the protein and mRNA levels in early‐stage breast cancer patients using the Nottingham (n = 1094) and METABRIC (n = 1980) cohorts, respectively. Results: High expression of ezrin was significantly associated with larger tumour size (p = 0.027), higher tumour grade (p < 0.001), worse Nottingham Prognostic Index prognostic group (p = 0.011) and HER2‐positive status (p = 0.001). High ezrin expression was significantly associated with adverse survival of breast cancer patients (p < 0.001) and remained associated with survival in multivariate Cox‐regression analysis (p = 0.018, hazard ratio (HR) = 1.343, 95% confidence interval (CI) = 1.051–1.716) when potentially confounding factors were included. High ezrin expression was significantly associated with adverse survival of patients whose tumours were categorised as receptor (oestrogen receptor (ER), progesterone receptor (PgR) or HER2) positive (p < 0.001) in comparison to those categorised as triple‐negative breast cancer (p = 0.889). High expression of ezrin mRNA (VIL2) in the METABRIC cohort was also significantly associated with adverse survival of breast cancer patients (p < 0.001). Conclusion: Retrospective analyses show that ezrin is an independent prognostic marker, with higher expression associated with shortened survival in receptor‐positive (ER, PgR or HER2) patients. Ezrin expression is associated with more aggressive disease and may have clinical utility as a biomarker of patient prognosis in early‐stage breast cancer

A convolutional neural network to filter artifacts in spectroscopic MRI

Purpose Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. Methods A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency‐domain spectra to detect artifacts. Results When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single‐voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole‐brain spectroscopic MRI volumes in real time. Conclusion The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning

Exendin-4 Improves Glycemic Control, Ameliorates Brain and Pancreatic Pathologies, and Extends Survival in a Mouse Model of Huntington's Disease

OBJECTIVE—The aim of this study was to find an effective treatment for the genetic form of diabetes that is present in some Huntington's disease patients and in Huntington's disease mouse models. Huntington's disease is a neurodegenerative disorder caused by a polyglutamine expansion within the huntingtin protein. Huntington's disease patients exhibit neuronal dysfunction/degeneration, chorea, and progressive weight loss. Additionally, they suffer from abnormalities in energy metabolism affecting both the brain and periphery. Similarly to Huntington's disease patients, mice expressing the mutated human huntingtin protein also exhibit neurodegenerative changes, motor dysfunction, perturbed energy metabolism, and elevated blood glucose levels

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

© 2019 International Society for Magnetic Resonance in Medicine Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use