Biomedical subjects

Soo Yeol Lee

Publications and source records attributed to Soo Yeol Lee.

16 recordsLinked to original sources

PubMed2006

A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study.

fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging.

Biophysical Phenomena↗

PubMed2006

In vivo trabecular thickness measurement in cancellous bones: longitudinal rat imaging studies.

Using cross-sectional x-ray images taken with zoom-in micro computed tomography (micro-CT), we have measured trabecular thickness in the femoral bones of live rats. Since zoom-in micro-CT is capable of high-resolution imaging of a small local region inside a large subject, we were able to measure trabecular thickness in femoral bones without sacrificing the rats. To longitudinally observe the trabecular thickness change caused by ovariectomy-induced osteoporosis, we have taken zoom-in micro-CT images of 15 live Sprague-Dawley rats (group A: 5 ovariectomized rats fed with regular food; group B: 5 ovariectomized rats fed with calcium-deficient food; group C: 5 controls) every other week for 10 weeks. We have observed that the mean trabecular thickness in the femoral bones of groups A and B decreased monotonically down to about 10.7% and 15.5%, respectively, as compared to that of group C, within 12 weeks after the ovariectomy, while the mean trabecular thickness of group C increased about 12.7%. We expect that zoom-in micro-CT can be successfully used in osteoporosis studies in which longitudinal imaging studies are required.

Animals↗

PubMed2006

Observation of the fast response of a magnetic resonance signal to neuronal activity: a snail ganglia study.

We observed the response of a magnetic resonance signal to neuronal activity in dissected snail ganglia to investigate faster responding components than the blood oxygenation level dependent (BOLD) component. To eliminate the BOLD component completely from the magnetic resonance signal, we used dissected snail ganglia which have non-magnetic hemocyanin, other than hemoglobin, as an oxygen carrying protein. To activate the snail ganglia in synchronization with the magnetic resonance signal measurement, we applied 30 Hz electrical stimulation with a pulse width of 2 s to the ganglia just before the 90 degrees RF pulse. The increase of neuronal activity in the snail ganglia after the electrical stimulation was confirmed with extracellular potential recording. The magnetic resonance signal intensity, measured with the volume selection pulse sequence in a 3.0 T MRI, decreased by about 2.97 +/- 1.10% when the ganglia were activated by the electrical stimulation. We think that the MRI signal decrease is partly due to the magnetic field produced by the neuronal current and partly due to the Lorentz force exerted on the neurons when they were firing.

Animals↗

PubMed2006

Basic setup for breast conductivity imaging using magnetic resonance electrical impedance tomography.

We present a new medical imaging technique for breast imaging, breast MREIT, in which magnetic resonance electrical impedance tomography (MREIT) is utilized to get high-resolution conductivity and current density images of the breast. In this work, we introduce the basic imaging setup of the breast MREIT technique with an investigation of four different imaging configurations of current-injection electrode positions and pathways through computer simulation studies. Utilizing the preliminary findings of a best breast MREIT configuration, additional numerical simulation studies have been carried out to validate breast MREIT at different levels of SNR. Finally, we have performed an experimental validation with a breast phantom on a 3.0 T MREIT system. The presented results strongly suggest that breast MREIT with careful imaging setups could be a potential imaging technique for human breast which may lead to early detection of breast cancer via improved differentiation of cancerous tissues in high-resolution conductivity images.

Algorithms↗

PubMed2006

Conductivity image reconstruction from defective data in MREIT: numerical simulation and animal experiment.

Magnetic resonance electrical impedance tomography (MREIT) is designed to produce high resolution conductivity images of an electrically conducting subject by injecting current and measuring the longitudinal component, Bz, of the induced magnetic flux density B = (Bx, By, Bz). In MREIT, accurate measurements of Bz are essential in producing correct conductivity images. However, the measured Bz data may contain fundamental defects in local regions where MR magnitude image data are small. These defective Bz data result in completely wrong conductivity values there and also affect the overall accuracy of reconstructed conductivity images. Hence, these defects should be appropriately recovered in order to carry out any MREIT image reconstruction algorithm. This paper proposes a new method of recovering Bz data in defective regions based on its physical properties and neighboring information of Bz. The technique will be indispensable for conductivity imaging in MREIT from animal or human subjects including defective regions such as lungs, bones, and any gas-filled internal organs.

Algorithms↗

PubMed2005

Noise analysis in magnetic resonance electrical impedance tomography at 3 and 11 T field strengths.

In magnetic resonance electrical impedance tomography (MREIT), we measure the induced magnetic flux density inside an object subject to an externally injected current. This magnetic flux density is contaminated with noise, which ultimately limits the quality of reconstructed conductivity and current density images. By analysing and experimentally verifying the amount of noise in images gathered from two MREIT systems, we found that a carefully designed MREIT study will be able to reduce noise levels below 0.25 and 0.05 nT at main magnetic field strengths of 3 and 11 T, respectively, at a voxel size of 3 x 3 x 3 mm(3). Further noise level reductions can be achieved by optimizing MREIT pulse sequences and using signal averaging. We suggest two different methods to estimate magnetic flux noise levels, and the results are compared to validate the experimental setup of an MREIT system.

Electric Impedance↗

PubMed2005

Trabecular thickness measurement in cancellous bones: postmortem rat studies with the zoom-in micro-tomography technique.

Using the cross-sectional images taken with the zoom-in micro-tomography technique, we measured trabecular thicknesses of femur bones in postmortem rats. Since the zoom-in micro-tomography technique is capable of high resolution imaging of a small local region inside a large subject, we were able to measure the trabecular thickness without extracting bone samples from the rats. For the zoom-in micro-tomography, we used a micro-tomography system consisting of a micro-focus x-ray source, a 1248 x 1248 flat-panel x-ray detector and a precision scan mechanism. To compensate for the limited spatial resolution in the zoom-in micro-tomography images, we used the fuzzy distance transform for the calculation of the trabecular thickness. To validate the trabecular thickness measurement with the zoom-in micro-tomography images, we compared the measurement results with those obtained from the conventional micro-tomography images of the extracted bone samples. The difference between the two types of measurement results was less than 2.5%.

Animals↗

PubMed2005

Electrical conductivity images of biological tissue phantoms in MREIT.

We present cross-sectional conductivity images of two biological tissue phantoms. Each of the cylindrical phantoms with both diameter and height of 140 mm contained chunks of biological tissues such as bovine tongue and liver, porcine muscle and chicken breast within a conductive agar gelatin as the background medium. We attached four recessed electrodes on the sides of the phantom with equal spacing among them. Injecting current pulses of 480 or 120 mA ms into the phantom along two different directions, we measured the z-component Bz of the induced magnetic flux density B=(Bx, By, Bz) with a magnetic resonance electrical impedance tomography (MREIT) system based on a 3.0 T MRI scanner. Using the harmonic Bz algorithm, we reconstructed cross-sectional conductivity images from the measured Bz data. Reconstructed images clearly distinguish different tissues in terms of both their shapes and conductivity values. In this paper, we experimentally demonstrate the feasibility of the MREIT technique in producing conductivity images of different biological soft tissues with a high spatial resolution and accuracy when we use a sufficient amount of the injection current.

Algorithms↗

PubMed2004

X-ray micro-tomography system for small-animal imaging with zoom-in imaging capability.

Since a micro-tomography system capable of microm-resolution imaging cannot be used for whole-body imaging of a small laboratory animal without sacrificing its spatial resolution, it is desirable for a micro-tomography system to have local imaging capability. In this paper, we introduce an x-ray micro-tomography system capable of high-resolution imaging of a local region inside a small animal. By combining two kinds of projection data, one from a full field-of-view (FOV) scan of the whole body and the other from a limited FOV scan of the region of interest (ROI), we have obtained zoomed-in images of the ROI without any contrast anomalies commonly appearing in conventional local tomography. For experimental verification of the zoom-in imaging capability, we have integrated a micro-tomography system using a microfocus x-ray source, a 1248 x 1248 flat-panel x-ray detector, and a precision scan mechanism. The mismatches between the two projection data caused by misalignments of the scan mechanism have been estimated with a calibration phantom, and the mismatch effects have been compensated in the image reconstruction procedure. Zoom-in imaging results of bony tissues with a spatial resolution of 10 lp mm(-1) suggest that zoom-in micro-tomography can be greatly used for high-resolution imaging of a local region in small-animal studies.

Algorithms↗

PubMed2004

Ex vivo proton MR spectroscopy (1H-MRS) for evaluation of human gastric carcinoma.

The present study was performed to determine the characteristics of the biochemical metabolites related to gastric cancer using ex vivo (1)H magnetic resonance spectroscopy (MRS), and to assess the clinical usefulness. A total of 35 gastric specimens resected during surgery for gastric cancer were used to compare MR spectra. A 1.5-T (64-MHz) clinical MR imager equipped with facilities for spectroscopy was used to obtain MR spectra from 33 gastric specimens. High-resolution (1)H nuclear magnetic resonance (NMR) spectra of the remains of two specimens were also examined with a 9.4-T (400-MHz) NMR spectrometer. Localized spectroscopic measurements were performed in two layers of gastric tissue, the proper muscle layer and the composite mucosa/submucosa layer. T(2) FSE and 3D SPGR images were used to determine the voxel size and the location for MRS data collection. MR spectra were obtained using the single-voxel PRESS technique with parameters of TR/TE = 2000/30 ms, NA = 256, and voxel size = 3 x 3 x 3 mm(3) (27 microL). Cancerous and noncancerous gastric tissues in the voxel were determined by histopathological analysis. On 9.4-T ex vivo NMR spectroscopy, the following metabolite peaks were found: lipids at 0.9 ppm (CH(3)) and 1.3 ppm (CH(2)); alanine (beta-CH(3)) at 1.58 ppm; N-Acetyl neuraminic acid (NANA: sialic acid) at 2.03 ppm; and glutathione at 2.25 ppm in normal gastric tissue layers. In the 1.5-T MR system, broad and featureless spectral peaks of the various metabolites in normal human gastric tissue were observed at 0.9 ppm, 1.3 ppm, 2.0 ppm, and 2.2 ppm regardless of gastric tissue layer. In specimens (Borrmann type III) with tubular adenocarcinoma, resonance peaks were observed at 1.26 ppm, 1.36 ppm (doublet of lactate), and 3.22 ppm (choline). Cancer lesions showed decreased levels of lipid peaks, showing the significant lactate doublet peaks, and increased intensity of the choline peak as compared with noncancerous gastric tissue. We found that decreased levels of lipids and increases in lactate and choline peaks in gastric tissue were markers for malignancy in gastric lesions. Information provided by ex vivo (1)H MRS, together with the development of in vivo (1)H MRS with high field strength and high resolution, may be very useful for the diagnosis of gastric cancer in clinical situation.

Adenocarcinoma↗

PubMed2003

A flat-panel detector based micro-CT system: performance evaluation for small-animal imaging.

A dedicated small-animal x-ray micro computed tomography (micro-CT) system has been developed to screen laboratory small animals such as mice and rats. The micro-CT system consists of an indirect-detection flat-panel x-ray detector with a field-of-view of 120 x 120 mm2, a microfocus x-ray source, a rotational subject holder and a parallel data processing system. The flat-panel detector is based on a matrix-addressed photodiode array fabricated by a CMOS (complementary metal-oxide semiconductor) process coupled to a CsI:T1 (thallium-doped caesium iodide) scintillator as an x-ray-to-light converter. Principal imaging performances of the micro-CT system have been evaluated in terms of image uniformity, voxel noise and spatial resolution. It has been found that the image non-uniformity mainly comes from the structural non-uniform sensitivity pattern of the flat-panel detector and the voxel noise is about 48 CT numbers at the voxel size of 100 x 100 x 200 microm3 and the air kerma of 286 mGy. When the magnification ratio is 2, the spatial resolution of the micro-CT system is about 14 1p/mm (line pairs per millimetre) that is almost determined by the flat-panel detector showing about 7 1p/mm resolving power. Through low-contrast phantom imaging studies, the minimum resolvable contrast has been found to be less than 36 CT numbers at the air kerma of 95 mGy. Some laboratory rat imaging results are presented.

Animals↗

PubMed2003

Conductivity and current density image reconstruction using harmonic Bz algorithm in magnetic resonance electrical impedance tomography.

Magnetic resonance electrical impedance tomography (MREIT) is to provide cross-sectional images of the conductivity distribution sigma of a subject. While injecting current into the subject, we measure one component Bz of the induced magnetic flux density B = (Bx, By, Bz) using an MRI scanner. Based on the relation between (inverted delta)2 Bz and inverted delta sigma, the harmonic Bz algorithm reconstructs an image of sigma using the measured Bz data from multiple imaging slices. After we obtain sigma, we can reconstruct images of current density distributions for any given current injection method. Following the description of the harmonic Bz algorithm, this paper presents reconstructed conductivity and current density images from computer simulations and phantom experiments using four recessed electrodes injecting six different currents of 26 mA. For experimental results, we used a three-dimensional saline phantom with two polyacrylamide objects inside. We used our 0.3 T (tesla) experimental MRI scanner to measure the induced Bz. Using the harmonic Bz algorithm, we could reconstruct conductivity and current density images with 82 x 82 pixels. The pixel size was 0.6 x 0.6 mm2. The relative L2 errors of the reconstructed images were between 13.8 and 21.5% when the signal-to-noise ratio (SNR) of the corresponding MR magnitude images was about 30. The results suggest that in vitro and in vivo experimental studies with animal subjects are feasible. Further studies are requested to reduce the amount of injection current down to less than 1 mA for human subjects.

Algorithms↗

PubMed2003

Three-dimensional forward solver and its performance analysis for magnetic resonance electrical impedance tomography (MREIT) using recessed electrodes.

In magnetic resonance electrical impedance tomography (MREIT), we try to reconstruct a cross-sectional resistivity (or conductivity) image of a subject. When we inject a current through surface electrodes, it generates a magnetic field. Using a magnetic resonance imaging (MRI) scanner, we can obtain the induced magnetic flux density from MR phase images of the subject. We use recessed electrodes to avoid undesirable artefacts near electrodes in measuring magnetic flux densities. An MREIT image reconstruction algorithm produces cross-sectional resistivity images utilizing the measured internal magnetic flux density in addition to boundary voltage data. In order to develop such an image reconstruction algorithm, we need a three-dimensional forward solver. Given injection currents as boundary conditions, the forward solver described in this paper computes voltage and current density distributions using the finite element method (FEM). Then, it calculates the magnetic flux density within the subject using the Biot-Savart law and FEM. The performance of the forward solver is analysed and found to be enough for use in MREIT for resistivity image reconstructions and also experimental designs and validations. The forward solver may find other applications where one needs to compute voltage, current density and magnetic flux density distributions all within a volume conductor.

Algorithms↗

PubMed2003

A single current density component imaging by MRCDI without subject rotations.

Magnetic resonance current density imaging (MRCDI) is a useful method for measuring electrical current density distribution inside a subject. Due to the requirement of subject rotations in MRCDI, MRCDI has not been widely applied to in vivo studies. In this paper, we propose a new current density image (CDI) reconstruction method by which a single component of the current density can be imaged by MRCDI without subject rotations. After measuring one of the two magnetic field components, produced by the current density component passing through the measurement plane, we have reconstructed the current density component images in the spatial frequency domain. Even though the proposed method has a limitation that the area of magnetic field measurement should be much larger than that of the current density, the proposed method is expected to expedite MRCDI applications to in vivo studies.

Computer Simulation↗

PubMed2003

Static resistivity image of a cubic saline phantom in magnetic resonance electrical impedance tomography (MREIT).

In magnetic resonance electrical impedance tomography (MREIT) we inject currents through electrodes placed on the surface of a subject and try to reconstruct cross-sectional resistivity (or conductivity) images using internal magnetic flux density as well as boundary voltage measurements. In this paper we present a static resistivity image of a cubic saline phantom (50 x 50 x 50 mm3) containing a cylindrical sausage object with an average resistivity value of 123.7 ohms cm. Our current MREIT system is based on an experimental 0.3 T MRI scanner and a current injection apparatus. We captured MR phase images of the phantom while injecting currents of 28 mA through two pairs of surface electrodes. We computed current density images from magnetic flux density images that are proportional to the MR phase images. From the current density images and boundary voltage data we reconstructed a cross-sectional resistivity image within a central region of 38.5 x 38.5 mm2 at the middle of the phantom using the J-substitution algorithm. The spatial resolution of the reconstructed image was 64 x 64 and the reconstructed average resistivity of the sausage was 117.7 ohms cm. Even though the error in the reconstructed average resistivity value was small, the relative L2-error of the reconstructed image was 25.5% due to the noise in measured MR phase images. We expect improvements in the accuracy by utilizing an MRI scanner with higher SNR and increasing the size of voxels scarifying the spatial resolution.

Artifacts↗

PubMed2002

J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): phantom experiments for static resistivity images.

Recently, a new static resistivity image reconstruction algorithm is proposed utilizing internal current density data obtained by magnetic resonance current density imaging technique. This new imaging method is called magnetic resonance electrical impedance tomography (MREIT). The derivation and performance of J-substitution algorithm in MREIT have been reported as a new accurate and high-resolution static impedance imaging technique via computer simulation methods. In this paper, we present experimental procedures, denoising techniques, and image reconstructions using a 0.3-tesla (T) experimental MREIT system and saline phantoms. MREIT using J-substitution algorithm effectively utilizes the internal current density information resolving the problem inherent in a conventional EIT, that is, the low sensitivity of boundary measurements to any changes of internal tissue resistivity values. Resistivity images of saline phantoms show an accuracy of 6.8%-47.2% and spatial resolution of 64 x 64. Both of them can be significantly improved by using an MRI system with a better signal-to-noise ratio.

Algorithms↗