Brain energy metabolism measured by (13) C magnetic resonance spectroscopy in vivo upon infusion of [3-(13) C]lactate.

The brain uses lactate produced by glycolysis as an energy source. How lactate originated from the blood stream is used to fuel brain metabolism is not clear. The current study measures brain metabolic fluxes and estimates the amount of pyruvate that becomes labeled in glial and neuronal compartments upon infusion of [3-(13) C]lactate. For that, labeling incorporation into carbons of glutamate and glutamine was measured by (13) C magnetic resonance spectroscopy at 14.1 T and analyzed with a two-compartment model of brain metabolism to estimate rates of mitochondrial oxidation, glial pyruvate carboxylation, and the glutamate-glutamine cycle as well as pyruvate fractional enrichments. Extracerebral lactate at supraphysiological levels contributes at least two-fold more to replenish the neuronal than the glial pyruvate pools. The rates of mitochondrial oxidation in neurons and glia, pyruvate carboxylase, and glutamate-glutamine cycles were similar to those estimated by administration of (13) C-enriched glucose, the main fuel of brain energy metabolism. These results are in agreement with primary utilization of exogenous lactate in neurons rather than astrocytes. © 2014 Wiley Periodicals, Inc.

Resistance Switching in Transparent Magnetic MgO Films

We have studied the abrupt and hysteretic changes of resistance in MgO-based capacitor devices. The switching behavior is discussed in terms of the formation and rupture of conduction filaments due to the migration of structural defects in the electric field, together with the redox events which affects the mobile carriers. The results presented in this paper suggest that MgO transparent films combining ferromagnetism and multilevel switching characteristics might pave the way for a new method for spintronic multibit data storage.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Comparison of electrical nerve stimulation, electrical muscle stimulation and magnetic nerve stimulation to assess the neuromuscular function of the plantar flexor muscles.

INTRODUCTION: As it might lead to less discomfort, magnetic nerve stimulation (MNS) is increasingly used as an alternative to electrical stimulation methods. Yet, MNS and electrical nerve stimulation (ENS) and electrical muscle stimulation (EMS) have not been formally compared for the evaluation of plantar flexor neuromuscular function. METHODS: We quantified plantar flexor neuromuscular function with ENS, EMS and MNS in 10 volunteers in fresh and fatigued muscles. Central alterations were assessed through changes in voluntary activation level (VAL) and peripheral function through changes in M-wave, twitch and doublet (PS100) amplitudes. Discomfort associated with 100-Hz paired stimuli delivered with each method was evaluated on a 10-cm visual analog scale. RESULTS: VAL, agonist and antagonist M-wave amplitudes and PS100 were similar between the different methods in both fresh and fatigued states. Potentiated peak twitch was lower in EMS compared to ENS, whereas no difference was found between ENS and MNS for any parameter. Discomfort associated with MNS (1.5 ± 1.4 cm) was significantly less compared to ENS (5.5 ± 1.9 cm) and EMS (4.2 ± 2.6 cm) (p < 0.05). CONCLUSION: When PS100 is used to evaluate neuromuscular properties, MNS, EMS and ENS can be used interchangeably for plantar flexor neuromuscular function assessment as they provide similar evaluation of central and peripheral factors in unfatigued and fatigued states. Importantly, electrical current spread to antagonist muscles was similar between the three methods while discomfort from MNS was much less compared to ENS and EMS. MNS may be potentially employed to assess neuromuscular function of plantar flexor muscles in fragile populations.

The potential of 3T high-resolution magnetic resonance imaging for diagnosis, staging, and follow-up of retinoblastoma.

We demonstrate the value of high-resolution magnetic resonance imaging (MRI) in diagnosing, staging, and follow-up of retinoblastoma during eye-saving treatment. We have included informative retinoblastoma cases scanned on a 3T MRI system from a retrospective retinoblastoma cohort from 2009 through 2013. We show that high-resolution MRI has the potential to detect small intraocular seeds, hemorrhage, and metastatic risk factors not visible with fundoscopy (e.g., optic nerve invasion and choroidal invasion), and treatment response. Unfortunately, however, the diagnostic accuracy of high-resolution MRI is not perfect, especially for subtle intraocular seeds or minimal postlaminar optic nerve invasion. The most important application of MRI is the detection of metastatic risk factors, as these cannot be found by fundoscopy and ultrasound.

Detection of Clinically Significant Prostate Cancer Using Magnetic Resonance Imaging-Ultrasound Fusion Targeted Biopsy: A Systematic Review.

CONTEXT: The current standard for diagnosing prostate cancer in men at risk relies on a transrectal ultrasound-guided biopsy test that is blind to the location of the cancer. To increase the accuracy of this diagnostic pathway, a software-based magnetic resonance imaging-ultrasound (MRI-US) fusion targeted biopsy approach has been proposed. OBJECTIVE: Our main objective was to compare the detection rate of clinically significant prostate cancer with software-based MRI-US fusion targeted biopsy against standard biopsy. The two strategies were also compared in terms of detection of all cancers, sampling utility and efficiency, and rate of serious adverse events. The outcomes of different targeted approaches were also compared. EVIDENCE ACQUISITION: We performed a systematic review of PubMed/Medline, Embase (via Ovid), and Cochrane Review databases in December 2013 following the Preferred Reported Items for Systematic reviews and Meta-analysis statement. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. EVIDENCE SYNTHESIS: Fourteen papers reporting the outcomes of 15 studies (n=2293; range: 13-582) were included. We found that MRI-US fusion targeted biopsies detect more clinically significant cancers (median: 33.3% vs 23.6%; range: 13.2-50% vs 4.8-52%) using fewer cores (median: 9.2 vs 37.1) compared with standard biopsy techniques, respectively. Some studies showed a lower detection rate of all cancer (median: 50.5% vs 43.4%; range: 23.7-82.1% vs 14.3-59%). MRI-US fusion targeted biopsy was able to detect some clinically significant cancers that would have been missed by using only standard biopsy (median: 9.1%; range: 5-16.2%). It was not possible to determine which of the two biopsy approaches led most to serious adverse events because standard and targeted biopsies were performed in the same session. Software-based MRI-US fusion targeted biopsy detected more clinically significant disease than visual targeted biopsy in the only study reporting on this outcome (20.3% vs 15.1%). CONCLUSIONS: Software-based MRI-US fusion targeted biopsy seems to detect more clinically significant cancers deploying fewer cores than standard biopsy. Because there was significant study heterogeneity in patient inclusion, definition of significant cancer, and the protocol used to conduct the standard biopsy, these findings need to be confirmed by further large multicentre validating studies. PATIENT SUMMARY: We compared the ability of standard biopsy to diagnose prostate cancer against a novel approach using software to overlay the images from magnetic resonance imaging and ultrasound to guide biopsies towards the suspicious areas of the prostate. We found consistent findings showing the superiority of this novel targeted approach, although further high-quality evidence is needed to change current practice.

Transcranial Magnetic Stimulation Combined with EEG Reveals Covert States of Elevated Excitability in the Human Epileptic Brain.

BACKGROUND: Transcranial magnetic stimulation combined with electroencephalogram (TMS-EEG) can be used to explore the dynamical state of neuronal networks. In patients with epilepsy, TMS can induce epileptiform discharges (EDs) with a stochastic occurrence despite constant stimulation parameters. This observation raises the possibility that the pre-stimulation period contains multiple covert states of brain excitability some of which are associated with the generation of EDs. OBJECTIVE: To investigate whether the interictal period contains "high excitability" states that upon brain stimulation produce EDs and can be differentiated from "low excitability" states producing normal appearing TMS-EEG responses. METHODS: In a cohort of 25 patients with Genetic Generalized Epilepsies (GGE) we identified two subjects characterized by the intermittent development of TMS-induced EDs. The high-excitability in the pre-stimulation period was assessed using multiple measures of univariate time series analysis. Measures providing optimal discrimination were identified by feature selection techniques. The "high excitability" states emerged in multiple loci (indicating diffuse cortical hyperexcitability) and were clearly differentiated on the basis of 14 measures from "low excitability" states (accuracy = 0.7). CONCLUSION: In GGE, the interictal period contains multiple, quasi-stable covert states of excitability a class of which is associated with the generation of TMS-induced EDs. The relevance of these findings to theoretical models of ictogenesis is discussed.

Modelling the curing process in magneto-sensitive polymers: Rate-dependence and shrinkage

This paper deals with a phenomenologically motivated magneto-viscoelastic coupled finite strain framework for simulating the curing process of polymers under the application of a coupled magneto-mechanical road. Magneto-sensitive polymers are prepared by mixing micron-sized ferromagnetic particles in uncured polymers. Application of a magnetic field during the curing process causes the particles to align and form chain-like structures lending an overall anisotropy to the material. The polymer curing is a viscoelastic complex process where a transformation from fluid. to solid occurs in the course of time. During curing, volume shrinkage also occurs due to the packing of polymer chains by chemical reactions. Such reactions impart a continuous change of magneto-mechanical properties that can be modelled by an appropriate constitutive relation where the temporal evolution of material parameters is considered. To model the shrinkage during curing, a magnetic-induction-dependent approach is proposed which is based on a multiplicative decomposition of the deformation gradient into a mechanical and a magnetic-induction-dependent volume shrinkage part. The proposed model obeys the relevant laws of thermodynamics. Numerical examples, based on a generalised Mooney-Rivlin energy function, are presented to demonstrate the model capacity in the case of a magneto-viscoelastically coupled load.

Interplay between surface anisotropy and dipolar interactions in an assembly of nanomagnets

We study the interplay between the effects of surface anisotropy and dipolar interactions in monodisperse assemblies of nanomagnets with oriented anisotropy. We derive asymptotic formulas for the assembly magnetization, taking into account temperature, applied field, core and surface anisotropy, and dipolar interparticle interactions. We find that the interplay between surface anisotropy and dipolar interactions is well described by the analytical expression of the assembly magnetization derived here: the overall sign of the product of the two parameters governing the surface and the dipolar contributions determines whether intrinsic and collective terms compete or have synergistic effects on the magnetization. This is illustrated by the magnetization curves of γ-Fe2O3 nanoparticle assemblies in the low concentration limit.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.