Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

A recent randomized controlled trial in young patients with long‐term post‐concussion symptoms showed that a novel behavioral intervention “Get going After concussIoN” is superior to enhanced usual care in terms of symptom reduction. It is unknown whether these interventional effects are associated with microstructural brain changes. The aim of this study was to examine whether diffusion‐weighted MRI indices, which are sensitive to the interactions between cellular structures and water molecules' Brownian motion, respond differently to the interventions of the above‐mentioned trial and whether such differences correlate with the improvement of post‐concussion symptoms. Twenty‐three patients from the intervention group (mean age 22.8, 18 females) and 19 patients from the control group (enhanced usual care) (mean age 23.9, 14 females) were enrolled. The primary outcome measure was the mean kurtosis tensor, which is sensitive to the microscopic complexity of brain tissue. The mean kurtosis tensor was significantly increased in the intervention group ( p = 0.003) in the corpus callosum but not in the thalamus ( p = 0.78) and the hippocampus ( p = 0.34). An increase in mean kurtosis tensor in the corpus callosum tended to be associated with a reduction in symptoms, but this association did not reach significance ( p = 0.059). Changes in diffusion tensor imaging metrics did not differ between intervention groups and were not associated with symptoms. The current study found different diffusion‐weighted MRI responses from the microscopic cellular structures of the corpus callosum between patients receiving a novel behavioral intervention and patients receiving enhanced usual care. Correlations with improvement of post‐concussion symptoms were not evident.

Purpose: Some advanced RF pulses, like multi-dimensional RF pulses, are often long and require substantial computation time due to a number of constraints and requirements, sometimes hampering clinical use. However, the pulses offer opportunities of reduced-FOV imaging, regional flip-angle homogenization, and localized spectroscopy, e.g., of hyperpolarized metabolites. We propose a novel deep learning approach to ultra-fast design multi-dimensional RF pulses with intention of real-time pulse updates. Methods: The proposed neural network considers input maps of the desired excitation region of interest, and outputs a multi-dimensional RF pulse. The training library is retrieved from a large image database, and the target RF pulses trained upon are calculated with a method of choice. Results: A relatively simple neural network is enough to produce reliable 2D spatial-selective RF pulses of comparable performance to the teaching method. For binary regions of interest, the training library does not need to be vast, hence, re-establishment of the training library is not necessarily cumbersome. The predicted, single-channel pulses were tested numerically and experimentally at 3 T. Conclusion: We demonstrate a relatively effortless training of multi-dimensional RF pulses, based on non-MRI related inputs, but working in an MRI setting still. The prediction time of few milliseconds renders real-time updates of advanced RF pulses possible.

Background: Pigs and minipigs are increasingly used as non-primate large animal models for preclinical research on nervous system disorders resulting in motor dysfunction. Knowledge of the minipig pyramidal tract is therefore essential to support such models. Aim and methods: This study used 5 female Gottingen minipigs aging 11-15 months. The Gottingen minipig corticospinal tract was investigated, in the same animals, with in vivo neuronal tracing and with postmortem diffusion weighted MRI tractography to provide a thorough insight in the encephalic distribution of this primary motor pathway and its decussation at the craniocervical junction. Results: The two methods similarly outlined the course of the pyramidal tract from its origin in the motor cortex down through the internal capsule to the craniocervical junction, where both methods displayed an axonal crossover at the pyramid decussation. The degree of crossover was quantified with unbiased stereology, where 81-93% of the traced corticospinal fibers crossed to the contralateral spinal cord. Accordingly, in the upper cervical spinal cord the corticospinal tract is primarily distributed in the contralateral lateral funiculus and in close relation to the gray matter, wherein some direct terminations on large ventral column gray matter neurons could be identified. Discussion: The combination of neuronal tracing and tractography exploited the strengths of the respective methods to gain a better understanding of the encephalic distribution and craniocervical decussation of the Gottingen minipig corticospinal tract. Moreover, a quantification of the crossing fibers was obtained from the tracing data, which was not possible with tractography. Our data indicate that the porcine corticospinal system is quite lateralized down to the investigated upper cervical levels. However, further elucidation of this point will require a full examination of the corticospinal tracing pattern into the caudal spinal cord combined with an analysis of the direct versus indirect termination pattern on the lower motor neurons.

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases, and has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared with typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI, which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI with those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (one sample) and in vivo human (three subjects) and rat brain (four animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 μm isotropic resolution with whole brain coverage in a 1 h acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice, which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders.

Background: Stereotaxic neurosurgery in large animals is used widely in different sophisticated models, where precision is becoming more crucial as desired anatomical target regions are becoming smaller. Individually calculated coordinates are necessary in large animal models with cortical and subcortical anatomical differences.New method: We present a convenient method to make an MRI-visible skull fiducial for 3D MRI-based stereotaxic procedures in larger experimental animals. Plastic screws were filled with either copper sulfate solution or MRI-visible paste from a commercially available cranial head marker. The screw fiducials were inserted in the animal skulls and T1 weighted MRI was performed allowing identification of the inserted skull marker.Results: Both types of fiducial markers were clearly visible on the MRIis. This allows high precision in the stereotaxic space.Comparison with existing method: The use of skull bone based fiducial markers gives high precision for both targeting and evaluation of stereotaxic systems. There are no metal artifacts and the fiducial is easily removed after surgery.Conclusion: The fiducial marker can be used as a very precise reference point, either for direct targeting or in evaluation of other stereotaxic systems. (C) 2017 Elsevier B.V. All rights reserved.

OBJECTIVEMutations in the isocitrate dehydrogenase (IDH) genes are of proven diagnostic and prognostic significance for cerebral gliomas. The objective of this study was to evaluate the clinical feasibility of using a recently described method for determining IDH mutation status by using magnetic resonance spectroscopy (MRS) to detect the presence of 2-hydroxyglutarate (2HG), the metabolic product of the mutant IDH enzyme.METHODSBy extending imaging time by 6 minutes, the authors were able to include a point-resolved spectroscopy (PRESS) MRS sequence in their routine glioma imaging protocol. In 30 of 35 patients for whom this revised protocol was used the lesions were subsequently diagnosed histologically as gliomas. Of the remaining 5 patients, 1 had a gangliocytoma, 1 had a primary CNS lymphoma, and 3 had nonneoplastic lesions. Immunohistochemistry and/or polymerase chain reaction were used to detect the presence of IDH mutations in the glioma tissue resected.RESULTSIn vivo MRS for 2HG correctly identified the IDH mutational status in 88.6% of patients. The sensitivity and specificity was 89.5% and 81.3%, respectively, when using 2 mM 2HG as threshold to discriminate IDH-mutated from wildtype tumors. Two glioblastomas that had elevated 2HG levels did not have detectable IDH mutations, and in 2 IDH-mutated gliomas 2HG was not reliably detectable.CONCLUSIONSThe noninvasive determination of the IDH mutation status of a presumed glioma by means of MRS may be incorporated into a routine diagnostic imaging protocol and can be used to obtain additional information for patient care.

Diffusion kurtosis imaging (DKI) is sensitive to tissue microstructure and may therefore be useful in the diagnosis and monitoring of disease in brain and body organs. Generally, diffusion magnetic resonance imaging (dMRI) in the body is challenging because of the heterogeneous body composition, which can cause image artefacts as a result of chemical shifts and susceptibility differences. In addition, the abdomen possesses physiological factors (e.g. breathing, heartbeat, blood flow) which may severely reduce image quality, especially when echo planar imaging is employed, as is typical in dMRI. Collectively, these challenging measurement conditions impede the use and exploration of DKI in the body. This impediment is further exacerbated by the traditionally large amount of data required for DKI and the low signal‐to‐noise ratio at the b‐values needed to effectively probe the kurtosis regime. Recently introduced fast DKI techniques reduce the challenge of DKI in the body by decreasing the data requirement substantially, so that, for example, triggering and breath‐hold techniques may be applied for the entire DKI acquisition without causing unfeasible scan times. One common pathological condition for which body DKI may be of immediate clinical value is kidney fibrosis, which causes progressive changes in organ microstructure. With its sensitivity to microstructure, DKI is an obvious candidate for a non‐invasive evaluation method. We present preclinical evidence indicating that the rapidly obtainable tensor‐derived mean kurtosis ( ) distinguishes moderately fibrotic kidneys from healthy controls. The presence and degree of fibrosis are confirmed by histology, which also indicates fibrosis as the main driver behind the DKI differences observed between groups. We therefore conclude that fast kurtosis is a likely candidate for an MRI‐based method for the detection and monitoring of renal fibrosis. We provide protocol recommendations for fast renal DKI in humans based on a b‐value optimisation performed using data acquired at 3 T in normal human kidney.

Purpose The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor and mean diffusivity ( ) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1‐3‐9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1‐9‐9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA). Theory and Methods 1‐3‐9/1‐9‐9 data are acquired in rat and human brains, and estimates of , FA, from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b‐values are determined from simulations and data. Results Accuracy and precision in and are comparable to nonlinear least squares estimation, and is improved with the 1‐9‐9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data. Conclusion The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455–1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

This erratum corrects a misprint in the original article. The correct equation was used in all the analysis, and, therefore, the misprint has no influence on the results or conclusions. In the Supplementary Information, which is available online, the reference to Eq. [12] immediately below Eq. [A14], should instead be a reference to Eq. [13].

PURPOSE:Results from several recent studies suggest the magnetic resonance diffusion-derived metric mean kurtosis (MK) to be a sensitive marker for tissue pathology; however, lengthy acquisition and postprocessing time hamper further exploration. The purpose of this study is to introduce and evaluate a new MK metric and a rapid protocol for its estimation. METHODS:The protocol requires acquisition of 13 standard diffusion-weighted images, followed by linear combination of log diffusion signals, thus avoiding nonlinear optimization. The method was evaluated on an ex vivo rat brain and an in vivo human brain. Parameter maps were compared with MK estimated from a standard diffusion kurtosis imaging (DKI) data set comprising 160 diffusion-weighted images. RESULTS:The new MK displays remarkably similar contrast to MK, and the proposed protocol acquires the necessary data in less than 1 min for full human brain coverage, with a postprocessing time of a few seconds. Scan-rescan reproducibility was comparable with MK. CONCLUSION:The framework offers a robust and rapid method for estimating MK, with a protocol easily adapted on commercial scanners, as it requires only minimal modification of standard diffusion-weighting protocols. These properties make the method feasible in practically any clinical setting.

Introduction: Diffusion kurtosis imaging (DKI) is a popular extension of diffusion tensor imaging (DTI) accounting for nongaussian aspects of diffusion in biological tissue. Recently, several studies have indicated enhanced sensitivity of mean kurtosis (MK) to tissue pathology, including stroke. However, the relatively lengthy acquisition time and postprocessing required to estimate kurtosis metrics remains a barrier for further investigations, and hence current research efforts are directed at speeding up DKI . Here we propose a very fast acquisition and postprocessing scheme for estimation of a new mean kurtosis, which is demonstrated on a large diffusion MR data set from fixed rat brain and a large data set from in-vivo human brain to be very similar to MK. We then introduce and evaluate a fast experimental protocol for estimation of this new mean kurtosis. This protocol requires only 13 diffusion weighted images, which can be acquired in less than one minute, followed by a postprocessing time of seconds. Thus, our new measure is shown to be a clinically feasible alternative to MK, even in an acute setting. Theory: The mean kurtosis is tedious to estimate because it is the orientational average of the apparent kurtosis ˆ ( ) K n in the direction n̂ , which is multiplied by the apparent diffusivity ( ) ˆ D n in the cumulant expansion of the signal log S(b, n̂) = −bD(n̂) + b 2 6 D(n̂) K (n̂) + O(b ) = −bD(n̂) + b 2 6 DW (n̂) + O(b ) (1)

Advanced and exclusive software solutions are offered to reduce susceptibility artefacts on MRI echo-planar sequences. We present a straightforward surgical technique to reduce the cortical distortion and signal loss that normally occur using diffusion tensor imaging (DTI) of the Göttingen minipig brain. Pronounced pneumatisation of the minipig cranium causes considerable susceptibility artefacts at the air/tissue interface around the frontal sinuses. Five Göttingen minipigs had burr holes drilled through the outer lamina of the skull bilaterally at the level of bregma. The underlying frontal sinuses were filled with a suspension of an MRI-compatible alginate. DTI was obtained before and after placing the medium in the sinus, quantifying the change using mutual information and Wilcoxon's rank-sum test. Fibertracking algorithms were applied to visualize the effect of treatment. We showed that the susceptibility artefacts were reduced at the air, bone and brain interfaces and that major cortical fiberbundles could be reliably visualized. This study demonstrated that DTI fibertracking of cortical bundles in experimental animals with extensive skull pneumatisation is feasible even when advanced software is unavailable.

Background: The Gottingen minipig is increasingly used as an animal model in experimental neuroscience as a much needed alternative to non-human primates. Accurate spatial targeting in this species in vivo is challenging, and most clinically available magnetic resonance imaging (MRI) protocols do not provide sufficient spatial resolution for this purpose. Thus, the aim of this study was to develop an in vivo pre-operative MRI protocol allowing direct visualization of individual nuclei of major interest in the minipig brain.Materials and methods: Three Gottingen minipigs underwent MRI using an inversion-recovery fast spin-echo sequence that was optimized with regards to the following parameters: inversion time, relaxation time, echo time and spatial and temporal resolution, giving a scan duration acceptable for the tight schedule usually employed in a neurosurgical procedure. The most optimal pulse sequence was applied in 8 Gottingen minipigs and the anatomical structures were identified.Results and conclusion: High-resolution images with excellent contrast were acquired, presenting negligible geometric distortions. Minor flow artifacts from the large neck vessels generated the most prominent artifact. Determination of coordinates necessary in experimental neurosurgery in the Gottingen minipig was considerably improved with this MRI protocol. (C) 2009 Elsevier Inc. All rights reserved.

High sensitivity to magnetic susceptibility changes and accurate localization of functional activations are key requisites for pulse sequences used for BOLD fMRI. This paper seeks to develop a framework for analysing the performance of various k-space sampling techniques in this respect, with special emphasis on spiral EPI (spiral) and cartesian EPI (EPI) and their performance under influence of induced field gradients (SFGs) and stochastic noise. A numerical method for calculating synthetic MR images is developed and used to simulate BOLD fMRI experiments using EPI and spirals. The data is then examined for activation using a pixel-wise t test. Nine subjects are scanned with both techniques while performing a motor task. SPM99 is used for analysing the experimental data. The simulated spirals provide generally higher t scores at low SFGs but lose more strength than EPI at higher SFGs, where EPI activation is offset from the true position. In the primary motor area spirals provide significantly higher t scores (P < 0.0002). In-plane variation of EPI is higher in phase-encoding direction than in frequency-encoding direction (P < 0.003). In the low SFG areas spirals provide stronger activation than EPI and less spatial variability. Thus, spirals are recommended for fMRI in motor area and language areas.

Purpose: To demonstrate the feasibility of sequential diffusion-weighted (DW) and perfusion-weighted (PW) magnetic resonance imaging (MM) of a recently developed porcine stroke model and to evaluate the evolution of cerebral perfusion and the apparent diffusion coefficient (ADC) over time.Materials and Methods: In five pigs, DW imaging (DWI) and PW imaging (PWI) was carried out for 7 hours after stroke onset, starting I hour after middle cerebral artery occlusion (MCAO).Results: The DWI lesion volume increased significantly with time, and final DWI lesion volume correlated well with lesion area on histological sections (r = 0.910). T2 changes could be recognized 3 hours after stroke onset. At I hour the ADC ratio (ischemic lesion/contralateral side) was reduced to 0.81 in the caudate-putamen and to 0.87 in the cortex, and the cerebral blood flow ratio was reduced to 0.40 in the caudate-putamen and 0.51 in the cortex.Conclusion: The level of flow reduction in the caudateputamen and the cortex after 1 hour is in good correlation with human thresholds of irreversible and reversible ischemic damage, and accordingly, this model might be a model for mechanisms of infarct evolution and therapeutic intervention.