Full magnetic gradient tensor from triaxial aeromagnetic gradient measurements:Calculation and application

The full magnetic gradient tensor （MGT） refers to the spatial change rate of the three field components of the geomagnetic field vector along three mutually orthogonal axes. The tensor is of use to geological mapping, resources exploration, magnetic navigation, and others. However, it is very difficult to measure the full magnetic tensor gradient using existing engineering technology. We present a method to use triaxial aeromagnetic gradient measurements for deriving the full MGT. The method uses the triaxial gradient data and makes full use of the variation of the magnetic anomaly modulus in three dimensions to obtain a self-consistent magnetic tensor gradient. Numerical simulations show that the full MGT data obtained with the proposed method are of high precision and satisfy the requirements of data processing. We selected triaxial aeromagnetic gradient data from the Hebei Province for calculating the full MGT. Data processing shows that using triaxial tensor gradient data allows to take advantage of the spatial rate of change of the total field in three dimensions and suppresses part of the independent noise in the aeromagnetic gradient. The calculated tensor components have improved resolution, and the transformed full tensor gradient satisfies the requirement of geological mapping and interpretation.

EFFECT OF POSITIVE-INDEFINITE MATRIX ON MAGNETIC RESONANCE DIFFUSION TENSOR-DERIVED PARAMETERS

To evaluate the effect of the positive-indefinite matrix on the diffusion tensor-derived parameters, a modified algorithm is proposed for calculating these parameters. Magnetic resonance （MR） diffusion tensor images of five healthy volunteers are collected. The diffusion sensitive gradient magnetic fields are applied along 25 directions and the diffusion weighting value is 1 000 s/mm^2. Many positive-indefinite diffusion tensors can be found in the white matter area, such as the genu and the splenium of corpus callosum. Due to the positive-indefinite matrix, the mean diffusivity （MD） and the fractional anisotropy （FA） are under-estimated and over-estimated by using the conventional algorithm. Thus, the conventional algorithm is modified by using the absolute values of all eigenvalues. Results show that both the robustness and the reliability for deriving these parameters are improved by the modified algorithm.

Calculation and correction of magnetic object positioning error caused by magnetic field gradient tensor measurement

Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tensor, field differentiation is generally approximated by field difference. As a result, magnetic objects positioning by magnetic field gradient tensor measurement always involves an inherent error caused by sensor sizes, leading to a reduction in detectable distance and detectable angle. In this paper, the inherent positioning error caused by magnetic field gradient tensor measurement is calculated and corrected by iterations based on the systematic position error distribution patterns. The results show that, the detectable distance range and the angle range of an ac magnetic object（2.44 Am^2@1 kHz） can be increased from（0.45 m, 0.75 m）,（0？, 25？） to（0.30 m, 0.80 m）,（0？,80？）, respectively.

Three direction analytical signal analysis method of magnetic gradient tensor and application in the interpretation

Compared to conventional magnetic data,magnetic gradient tensor data contain more high-frequency signal components,which can better describe the features of geological bodies.The directional analytic signal of the magnetic gradient tensor is not easily interfered from the tilting magnetization,but it can infer the range of the fi eld source more accurately.However,the analytic signal strength decays faster with depth,making it diffi cult to identify deep fi eld sources.Balanced-boundary recognition can eff ectively overcome this disadvantage.We present here a balanced-boundary identifi cation technique based on the normalization of three-directional analytic signals from aeromagnetic gradient tensor data.This method can eff ectively prevent the fast attenuation of analytic signals.We also derive an Euler inversion algorithm of three-directional analytic signal derivative.By combining magnetic-anomaly model testing with the traditional magnetic anomaly interpretation method,we show that the boundary-recognition technology based on a magnetic gradient tensor analytic signal has a greater advantage in identifying the boundaries of the geological body and can better refl ect shallow anomalies.The characteristics of the Euler equation based on the magnetic anomaly direction to resolve the signal derivative have better convergence,and the obtained solution is more concentrated,which can obtain the depth and horizontal range information of the geological body more accurately.Applying the above method to the measured magneticanomaly gradient data from Baoding area,more accurate fi eld source information is obtained,which shows the feasibility of applying this method to geological interpretations.

Magnetic susceptibility inversion method with full tensor gradient data using low-temperature SQUIDs

Full tensor magnetic gradient measurements are available nowadays. These are essential for determining magnetization parameters in deep layers. Using full or partial tensor magnetic gradient measurements to determine the subsurface properties, e.g., magnetic susceptibility, is an inverse problem. Inversion using total magnetic intensity data is a traditional way.Because of di culty in obtaining the practical full tensor magnetic gradient data, the corresponding inversion results are not so widely reported. With the development of superconducting quantum interference devices(SQUIDs), we can acquire the full tensor magnetic gradient data through field measurements. In this paper, we study the inverse problem of retrieving magnetic susceptibility with the field data using our designed low-temperature SQUIDs. The solving methodology based on sparse regularization and an alternating directions method of multipliers is established. Numerical and field data experiments are performed to show the feasibility of our algorithm.

Effect of the Waveguide Walls on Magnetic Polarizability Tensor of the End Opening

The paper discusses the effect of the waveguidc walls on magnetic polarizability tensor of the end opening. The solution is given on the basis of application of a new Greed's function which is constructed by taking into account the mirror image retlection of the waveguide walls.

COMPARISON OF OPTICAL POLARIMETRY AND DIFFUSION TENSOR MR IMAGING FOR ASSESSING MYOCARDIAL ANISOTROPY

We have recently proposed an optical method for assessing heart structure that uses polarized light measurement of birefringence as an indicator of tissue anisotropy.The highly aligned nature of healthy cardiac muscle tissue has a detectable effect on the polarization of light,resulting in a measurable phase shift(“retardance”).When this organized tissue structure is perturbed,for example after cardiac infarction(heart attack),scar tissue containing disorganized collagen is formed,causing a decrease in the measured retardance values.However,these are dependent not only on tissue anisotropy,but also on the angle between the tissue’s optical anisotropy direction and the beam interrogating the sample.To remove this experimental ambiguity,we present a method that interrogates the sample at two different incident beam angles,thus yielding enough information to uniquely determine the true magnitude and orientation of the tissue optical anisotropy.We use an infarcted porcine heart model to compare these polarimetryderived anisotropy metrics with those obtained with diffusion tensor magnetic resonance imaging(DT-MRI).The latter yields the anisotropy and the direction of tissue water diffusivity,providing an independent measure of tissue anisotropy.The optical and MR results are thus directly compared in a common ex vivo biological model of interest,yielding reasonable agreement but also highlighting some technique-specific differences.

The ralationship between fractional anisotropy value and tumor microarchitecture in late-stage rat glioma

Objective: To explore the magnetic resonance diffusion tensor imaging(MR-DTI) features of in the late stage of Wistar rat C6 brain glioma, and the relationship between fractional anisotropy value and tumor microarchitecture. Methods: The concentration of more than 1.0×伊 106/10 μL glioma cells and complete medium were injected stereotactically into the right caudate nucleus of the experimental group(n=35) and control group(n=10), respectively. Conventional MRI, DTI, and enhanced T1 WI scans were Performed using the GE Signa HD× 3.0T MRI scanner about 3-4 weeks after implantation for the rats. Postproeessing was done using the DTI specific software Function Tool to gain FA image. Many ROIs were drawn avoiding hemorrhage, necrosis areas in tumor parenchyma, the value of FA was recorded. Each surviving rat brain was examined histologically using HE and immunohistochemical staining for VEGF and CD34. Pearson correlation analysis was used to determine the relationships between FA values and VEGF, MVD, cell density, respectively. Results: A total of 35 tumor-bearing rats were confirmed the tumor formation by the subsequent MRI and pathological examination. The mean FA values of the tumor and the contralateral brain tissue were 0.17 ± 0.03 and 0.31 ± 0.05 respectively, and the difference was statistically significant(t = 12.80, P <0.05). The mean FA value of grade III glioma(n=12) was 0.16 ± 0.03, and the average FA value of grade IV glioma(n=23) was about 0.18 ± 0.04. There was no significant difference between the two groups(t= 1.92, P> 0.05). FA value in the late stage of Wistar rat C6 brain glioma has significant positive correlation to VEGF, MVD, cell density. The correlation coefficients between FA and VEGF, MVD, and cell density were 0.67, 0.65 and 0.71(P<0.05), respectively. Conclusions: The FA value of rat glioma tumor in the late stage can preoperatively provide an accurate, reliable and noninvasive imaging monitoring method to evaluate the microstructure of glioma( cell density, the extent of angiogenesis, fiber bundle integrity and tumor cell infiltration and so on), predict the biological behavior of the tumor and make out surgical plan.

Magnetic resonance diffusion tensor imaging with fluorescein sodium dyeing for surgery of gliomas in brain motor functional areas

Background Tumor surgery in brain motor functional areas remains challenging. Novel techniques are being developed to gain maximal and safe resection for brain tumor surgery. Herein, we assessed the magnetic resonance diffusion tensor imaging （MR-DTI） and fluorescein sodium dyeing （FLS） guiding technique for surgery of glioma located in brain motor functional areas. Methods Totally 83 patients were enrolled according to our inclusion and exclusion criteria （56 patients in experimental group, 27 patients in control group）. In the experimental group, the surgical approach was designed by DTI imaging, which showed the relationship between the tumor and motor tract. The range of resection in the operation was determined using the FLS-stained area, which recognized the tumor and its infiltrated tissue. The traditional routine method was used in the control group. Postoperatively, all patients underwent enhanced brain MRI within 72 hours to ascertain the extent of resection. Patients were followed in our outpatient clinic over 6-24 months. Neurological deficits and Karnofsky scoring （KPS） were evaluated. Results There were no significant differences in balance test indexes of preoperative data （sex, age, lesion location and volume, and neurological deficits before operation） and diagnosis of histopathology between the two groups. There was a trend in the experimental group for greater rates of gross total resection （80.4% vs. 40.7%）, and the paralysis rate caused by surgery was lower in experimental （25.0%） vs. control （66.7%） groups （P 〈0.05）. The 6-month KPS in the low-grade and high-grade gliomas was 91＋11 and 73＋26, respectively, in the experimental group vs. 82＋9 and 43＋27, respectively, in the control group （P 〈0.05 for both）. Conclusions MR-DTI and FLS dye guiding for surgery of glioma located in brain motor functional areas can increase the gross total resection rate, decrease the paralysis rate caused by surgery, and improve patient quality of life compared with traditional glioma surgery.

Differences in brain pathological changes between rotenone and 6-hydroxydopamine Parkinson＇s disease models

Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal models.They not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the requirements for iron deposition.However,few studies have compared the characteristics of these two models by magnetic resonance imaging.In this study,rat models of Parkinson＇s disease were generated by injection of 3 μg rotenone or 10 μg 6-hydroxydopamine into the right substantia nigra.At 1,2,4,and 6 weeks after injection,coronal whole-brain T2-weighted imaging,transverse whole-brain T2-weighted imaging,and coronal diffusion tensor weighted imaging were conducted to measure fractional anisotropy and T2＊ values at the injury site.The fractional anisotropy value on the right side of the substantia nigra was remarkably lower at 6 weeks than at other time points in the rotenone group.In the 6-hydroxydopamine group,the fractional anisotropy value was decreased,but T2＊ values were increased on the right side of the substantia nigra at 1 week.Our findings confirm that the 6-hydroxydopamine-induced model is suitable for studying dopaminergic neurons over short periods,while the rotenone-induced model may be appropriate for studying the pathological and physiological processes of Parkinson＇s disease over long periods.

A brief report on MRI investigation of experimental traumatic brain injury

Traumatic brain injury is a major cause of death and disability. This is a brief report based on a symposium presentation to the 2014 Chinese Neurotrauma Association Meeting in San Francisco, USA. It covers the work from our laboratory in applying multimodal MRI to study experimental traumatic brain injury in rats with comparisons made to behavioral tests and histology. MRI protocols include structural, perfusion, manganese-enhanced, diffusion-tensor MRI, and MRI of blood-brain barrier integrity and cerebrovascular reactivity.

Why do stroke patients with negative motor evoked potential show poor limb motor function recovery?

Negative motor evoked potentials after cerebral infarction, indicative of poor recovery of limb motor function, tend to be accompanied by changes in fractional anisotropy values and the cerebral pe-duncle area on the affected side, but the characteristics of these changes have not been reported. This study included 57 cases of cerebral infarction whose motor evoked potentials were tested in the 24 hours after the first inspection for diffusion tensor imaging, in which 29 cases were in the negative group and 28 cases in the positive group. Twenty-nine patients with negative motor evoked potentials were divided into two groups according to fractional anisotropy on the affected side of the cerebral peduncle： a fractional anisotropy 〈 0.36 group and a fractional anisotropy 〉 0.36 group. All patients underwent a regular magnetic resonance imaging and a diffusion tensor imaging examina- tion at 1 week, 1, 3, 6 and 12 months after cerebral infarction. The FugI-Meyer scores of their hemiplegic limbs were tested before the magnetic resonance and diffusion tensor imaging exami-nations. In the negative motor evoked potential group, fractional anisotropy in the affected cerebral peduncle declined progressively, which was most obvious in the first 1-3 months after the onset of cerebral infarction. The areas and area asymmetries of the cerebral peduncle on the affected side were significantly decreased at 6 and 12 months after onset. At 12 months after onset, the area asymmetries of the cerebral peduncle on the affected side were lower than the normal lower limit value of 0.83. FugI-Meyer scores in the fractional anisotropy ≥0.36 group were significantly higher than in the fractional anisotropy 〈 0.36 group at 3-12 months after onset. The fractional anisotropy of the cerebral peduncle in the positive motor evoked potential group decreased in the first 1 month after onset, and stayed unchanged from 3-12 months; there was no change in the area of the cerebral peduncle in the first 1-12 months after cerebral infarction. These findings confirmed that if the fractional anisotropy of the cerebral peduncle on the affected side is 〈 0.36 and the area asym-metries 〈 0.83 in patients with negative motor evoked potential after cerebral infarction, then poor hemiplegic limb motor function recovery may occur.

Should we consider a new approach? Detecting grain deviation caused by knots within stems

This article describes the importance of detecting grain deviation caused by knots and reviews the main methods used in measuring grain orientation surrounding knots. It discusses the potential of using Diffusion Tensor Magnetic Resonance Imaging to track and map the grain deviation caused by knots.

DESIGN OF SPARSE ARRAY FOR MAD IMAGING BASED ON MAXIMIZING INFORMATION CAPACITY

In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.

Planning for selective amygdalohippocampectomy involving less neuronal fiber damage based on brain connectivity using tractography

Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（www.ppmi-info.org）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.

Relationship Between Perisylvian Essential Language Sites and Arcuate Fasciculus in the Left Hemisphere of Healthy Adults

Essential language sites and the arcuate fasciculus（AF） have been extensively researched. However, the relationship between them remains insufficiently studied,especially in healthy people. Navigated transcranial magnetic stimulation（n TMS） is increasingly used in language mapping. While enjoying the advantage of non-invasiveness, it is also capable of inducing a virtual lesion in the brain. Thus, it offers the possibility of using the virtuallesion method to study the healthy brain. This study combined n TMS and diffusion tensor imaging（DTI）tractography to investigate the relationship between essential language sites and the AF in 30 healthy right-handedvolunteers. A total of 143 essential language sites were identified using n TMS, and a total of 175 AF terminations were identified using DTI tractography. Sixty-six sites had a direct correlation with the AF, accounting for 46% of the total essential language sites. Forty-seven AF terminations harbored essential language sites, accounting for 27% of the total AF terminations. Upon data rendering to the cortical parcellation system, a region-related heterogeneity of the correlation rate was found. This study provides the first data on the relationship between essential language sites and the AF in healthy adults.

Can multi-modal neuroimaging evidence from hippocampus provide biomarkers for the progression of amnestic mild cognitive impairment?

Impaired structure and function of the hippocampus is a valuable predictor of progression from amnestic mild cognitive impairment（a MCI） to Alzheimer＇s disease（AD）. As a part of the medial temporal lobe memory system,the hippocampus is one of the brain regions affected earliest by AD neuropathology,and shows progressive degeneration as a MCI progresses to AD. Currently,no validated biomarkers can precisely predict the conversion from a MCI to AD. Therefore,there is a great need of sensitive tools for the early detection of AD progression. In this review,we summarize the specifi c structural and functional changes in the hippocampus from recent a MCI studies using neurophysiological and neuroimaging data. We suggest that a combination of advanced multi-modal neuroimaging measures in discovering biomarkers will provide more precise and sensitive measures of hippocampal changes than using only one of them. These will potentially affect early diagnosis and disease-modifying treatments. We propose a new sequential and progressive framework in which the impairment spreads from the integrity of fibers to volume and then to function in hippocampal subregions. Meanwhile,this is likely to be accompanied by progressive impairment of behavioral and neuropsychological performance in the progression of a MCI to AD.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research ？eld of Autism Spectrum Disorder（ASD）. Magnetic resonance imaging（MRI） provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation,connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and largescale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.