A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging

A phantom that can be used for mapping geometric distortion in magnetic resonance imaging (MRI) is described. This phantom provides an array of densely distributed control points in three-dimensional (3D) space. These points form the basis of a comprehensive measurement method to correct for geometric distortion in MR images arising principally from gradient field non-linearity and magnet field inhomogeneity. The phantom was designed based on the concept that a point in space can be defined using three orthogonal planes. This novel design approach allows for as many control points as desired. Employing this novel design, a highly accurate method has been developed that enables the positions of the control points to be measured to sub-voxel accuracy. The phantom described in this paper was constructed to fit into a body coil of a MRI scanner, (external dimensions of the phantom were: 310 mm x 310 mm x 310 mm), and it contained 10,830 control points. With this phantom, the mean errors in the measured coordinates of the control points were on the order of 0.1 mm or less, which were less than one tenth of the voxel's dimensions of the phantom image. The calculated three-dimensional distortion map, i.e., the differences between the image positions and true positions of the control points, can then be used to compensate for geometric distortion for a full image restoration. It is anticipated that this novel method will have an impact on the applicability of MRI in both clinical and research settings. especially in areas where geometric accuracy is highly required, such as in MR neuro-imaging. (C) 2004 Elsevier Inc. All rights reserved.

Method for a detailed measurement of image intensity nonuniformity in magnetic resonance imaging

In magnetic resonance imaging (MRI), the MR signal intensity can vary spatially and this spatial variation is usually referred to as MR intensity nonuniformity. Although the main source of intensity nonuniformity arises from B, inhomogeneity of the coil acting as a receiver and/or transmitter, geometric distortion also alters the MR signal intensity. It is useful on some occasions to have these two different sources be separately measured and analyzed. In this paper, we present a practical method for a detailed measurement of the MR intensity nonuniformity. This method is based on the same three-dimensional geometric phantom that was recently developed for a complete measurement of the geometric distortion in MR systems. In this paper, the contribution to the intensity nonuniformity from the geometric distortion can be estimated and thus, it provides a mechanism for estimation of the intensity nonuniformity that reflects solely the spatial characteristics arising from B-1. Additionally, a comprehensive scheme for characterization of the intensity nonuniformity based on the new measurement method is proposed. To demonstrate the method, the intensity nonuniformity in a 1.5 T Sonata MR system was measured and is used to illustrate the main features of the method. (c) 2005 American Association of Physicists in Medicine.

Modeling diffraction and imaging of laser beams by the mode-expansion method

We present a new method of modeling imaging of laser beams in the presence of diffraction. Our method is based on the concept of first orthogonally expanding the resultant diffraction field (that would have otherwise been obtained by the laborious application of the Huygens diffraction principle) and then representing it by an effective multimodal laser beam with different beam parameters. We show not only that the process of obtaining the new beam parameters is straightforward but also that it permits a different interpretation of the diffraction-caused focal shift in laser beams. All of the criteria that we have used to determine the minimum number of higher-order modes needed to accurately represent the diffraction field show that the mode-expansion method is numerically efficient. Finally, the characteristics of the mode-expansion method are such that it allows modeling of a vast array of diffraction problems, regardless of the characteristics of the incident laser beam, the diffracting element, or the observation plane. (C) 2005 Optical Society of America.

A new decoupling method for quadrature coils in magnetic resonance imaging

A powerful decoupling method is introduced to obtain decoupled signal voltages from quadrature coils in magnetic resonance imaging (MRI). The new method uses the knowledge of the position of the signal source in MRI, the active slice, to define a new mutual impedance which accurately quantifies the coupling voltages and enables them to be removed almost completely. Results show that by using the new decoupling method, the percentage errors in the decoupled voltages are of the order of 10(-7)% and isolations between two coils are more than 170 dB.

A solvent-free matrix application method for matrix-assisted laser desorption/ionization imaging of small molecules

Matrix application continues to be a critical step in sample preparation for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Imaging of small molecules such as drugs and metabolites is particularly problematic because the commonly used washing steps to remove salts are usually omitted as they may also remove the analyte, and analyte spreading is more likely with conventional wet matrix application methods. We have developed a method which uses the application of matrix as a dry, finely divided powder, here referred to as dry matrix application, for the imaging of drug compounds. This appears to offer a complementary method to wet matrix application for the MALDI-MSI of small molecules, with the alternative matrix application techniques producing different ion profiles, and allows the visualization of compounds not observed using wet matrix application methods. We demonstrate its value in imaging clozapine from rat kidney and 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylic acid from rat brain. In addition, exposure of the dry matrix coated sample to a saturated moist atmosphere appears to enhance the visualization of a different set of molecules.

Comparison of techniques for measuring anterior chamber depth:Orbscan imaging, Smith's technique, and van Herick's method

Background Evaluation of anterior chamber depth (ACD) can potentially identify those patients at risk of angle-closure glaucoma. We aimed to: compare van Herick’s limbal chamber depth (LCDvh) grades with LCDorb grades calculated from the Orbscan anterior chamber angle values; determine Smith’s technique ACD and compare to Orbscan ACD; and calculate a constant for Smith’s technique using Orbscan ACD. Methods Eighty participants free from eye disease underwent LCDvh grading, Smith’s technique ACD, and Orbscan anterior chamber angle and ACD measurement. Results LCDvh overestimated grades by a mean of 0.25 (coefficient of repeatability [CR] 1.59) compared to LCDorb. Smith’s technique (constant 1.40 and 1.31) overestimated ACD by a mean of 0.33 mm (CR 0.82) and 0.12 mm (CR 0.79) respectively, compared to Orbscan. Using linear regression, we determined a constant of 1.22 for Smith’s slit-length method. Conclusions Smith’s technique (constant 1.31) provided an ACD that is closer to that found with Orbscan compared to a constant of 1.40 or LCDvh. Our findings also suggest that Smith’s technique would produce values closer to that obtained with Orbscan by using a constant of 1.22.

Imaging of activated complement using ultrasmall superparamagnetic iron oxide particles (USPIO) - conjugated vectors: an in vivo in utero non-invasive method to predict placental insufficiency and abnormal fetal brain development.

In the current study, we have developed a magnetic resonance imaging-based method for non-invasive detection of complement activation in placenta and foetal brain in vivo in utero. Using this method, we found that anti-complement C3-targeted ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles bind within the inflamed placenta and foetal brain cortical tissue, causing a shortening of the T2* relaxation time. We used two mouse models of pregnancy complications: a mouse model of obstetrics antiphospholipid syndrome (APS) and a mouse model of preterm birth (PTB). We found that detection of C3 deposition in the placenta in the APS model was associated with placental insufficiency characterised by increased oxidative stress, decreased vascular endothelial growth factor and placental growth factor levels and intrauterine growth restriction. We also found that foetal brain C3 deposition was associated with cortical axonal cytoarchitecture disruption and increased neurodegeneration in the mouse model of APS and in the PTB model. In the APS model, foetuses that showed increased C3 in their brains additionally expressed anxiety-related behaviour after birth. Importantly, USPIO did not affect pregnancy outcomes and liver function in the mother and the offspring, suggesting that this method may be useful for detecting complement activation in vivo in utero and predicting placental insufficiency and abnormal foetal neurodevelopment that leads to neuropsychiatric disorders.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

Magnetic resonance imaging in the evaluation of patients with aseptic meningoencephalitis and connective tissue disorders

OBJECTIVE: To describe the role of magnetic resonance imaging (MRI) in the evaluation of patients with chronic and recurrent aseptic meningitis.METHOD: A retrospective study of five patients with aseptic meningoencefalitis diagnosed by clinical and CSF findings. CT scans showed without no relevant findings. RESULTS: MRI showed small multifocal lesions hyperintense on T2 weighted images and FLAIR, with mild or no gadolinium enhancement, mainly in periventricular and subcortical regions. Meningoencephalitis preceded the diagnosis of the underlying disease in four patients (Behçet´s disease or systemic lupus erythematosus). After the introduction of adequate treatment for the rheumatic disease, they did not present further symptoms of aseptic meningoencephalitis. CONCLUSION: Aseptic meningoencephalitis can be an early presentation of an autoimmune disease. It is important to emphasize the role of MRI in the diagnosis and follow-up of these patients.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Random numbers from astronomical imaging

This article describes a method to turn astronomical imaging into a random number generator by using the positions of incident cosmic rays and hot pixels to generate bit streams. We subject the resultant bit streams to a battery of standard benchmark statistical tests for randomness and show that these bit streams are statistically the same as a perfect random bit stream. Strategies for improving and building upon this method are outlined.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required, The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.