3D Digital Modeling of Dental Casts from Their 3D CT Images with Scatter and Beam-Hardening Correction.

Dental 3D modeling plays a pivotal role in digital dentistry, offering precise tools for treatment planning, implant placement, and prosthesis customization. Traditional methods rely on physical plaster casts, which pose challenges in storage, accessibility, and accuracy, fueling interest in digitization using 3D computed tomography (CT) imaging. We introduce a method that can reduce both artifacts simultaneously. To validate the proposed method, we carried out CT scan experiments using plaster dental casts created from dental impressions. After the artifact correction, the CT image quality was greatly improved in terms of image uniformity, contrast-to-noise ratio (CNR), and edge sharpness. We examined the correction effects on the accuracy of the 3D models generated from the CT images. As referenced to the 3D models derived from the optical scan data, the root mean square (RMS) errors were reduced by 8.8~71.7% for three dental casts of different sizes and shapes. Our method offers a solution to challenges posed by artifacts in CT scanning of plaster dental casts, leading to enhanced 3D model accuracy. This advancement holds promise for dental professionals seeking precise digital modeling for diverse applications in dentistry.

Metal Artifact Reduction in Dental CBCT Images Using Direct Sinogram Correction Combined with Metal Path-Length Weighting.

Metal artifacts in dental computed tomography (CT) images, caused by highly X-ray absorbing objects, such as dental implants or crowns, often more severely compromise image readability than in medical CT images. Since lower tube voltages are used for dental CTs in spite of the more frequent presence of metallic objects in the patient, metal artifacts appear more severely in dental CT images, and the artifacts often persist even after metal artifact correction. The direct sinogram correction (DSC) method, which directly corrects the sinogram using the mapping function derived by minimizing the sinogram inconsistency, works well in the case of mild metal artifacts, but it often fails to correct severe metal artifacts. We propose a modified DSC method to reduce severe metal artifacts, and we have tested it on human dental images. We first segment the metallic objects in the CT image, and then we forward-project the segmented metal mask to identify the metal traces in the projection data with computing the metal path length for the rays penetrating the metal mask. In the sinogram correction with the DSC mapping function, we apply the weighting proportional to the metal path length. We have applied the proposed method to the phantom and patient images taken at the X-ray tube voltage of 90 kVp. We observed that the proposed method outperforms the original DSC method when metal artifacts were severe. However, we need further extensive studies to verify the proposed method for various CT scan conditions with many more patient images.

Cone-Beam Angle Dependency of 3D Models Computed from Cone-Beam CT Images.

Cone-beam dental CT can provide high-precision 3D images of the teeth and surrounding bones. From the 3D CT images, 3D models, also called digital impressions, can be computed for CAD/CAM-based fabrication of dental restorations or orthodontic devices. However, the cone-beam angle-dependent artifacts, mostly caused by the incompleteness of the projection data acquired in the circular cone-beam scan geometry, can induce significant errors in the 3D models. Using a micro-CT, we acquired CT projection data of plaster cast models at several different cone-beam angles, and we investigated the dependency of the model errors on the cone-beam angle in comparison with the reference models obtained from the optical scanning of the plaster models. For the 3D CT image reconstruction, we used the conventional Feldkamp algorithm and the combined half-scan image reconstruction algorithm to investigate the dependency of the model errors on the image reconstruction algorithm. We analyzed the mean of positive deviations and the mean of negative deviations of the surface points on the CT-image-derived 3D models from the reference model, and we compared them between the two image reconstruction algorithms. It has been found that the model error increases as the cone-beam angle increases in both algorithms. However, the model errors are smaller in the combined half-scan image reconstruction when the cone-beam angle is as large as 10 degrees.

U-net based metal segmentation on projection domain for metal artifact reduction in dental CT.

Unlike medical computed tomography (CT), dental CT often suffers from severe metal artifacts stemming from high-density materials employed for dental prostheses. Despite the many metal artifact reduction (MAR) methods available for medical CT, those methods do not sufficiently reduce metal artifacts in dental CT images because MAR performance is often compromised by the enamel layer of teeth, whose X-ray attenuation coefficient is not so different from that of prosthetic materials. We propose a deep learning-based metal segmentation method on the projection domain to improve MAR performance in dental CT. We adopted a simplified U-net for metal segmentation on the projection domain without using any information from the metal-artifacts-corrupted CT images. After training the network with the projection data of five patients, we segmented the metal objects on the projection data of other patients using the trained network parameters. With the segmentation results, we corrected the projection data by applying region filling inside the segmented region. We fused two CT images, one from the corrected projection data and the other from the original raw projection data, and then we forward-projected the fused CT image to get the fused projection data. To get the final corrected projection data, we replaced the metal regions in the original projection data with the ones in the fused projection data. To evaluate the efficacy of the proposed segmentation method on MAR, we compared the MAR performance of the proposed segmentation method with a conventional MAR method based on metal segmentation on the CT image domain. For the MAR performance evaluation, we considered the three primary MAR performance metrics: the relative error (REL), the sum of square difference (SSD), and the normalized absolute difference (NAD). The proposed segmentation method improved MAR performances by around 5.7% for REL, 6.8% for SSD, and 8.2% for NAD. The proposed metal segmentation method on the projection domain showed better MAR performance than the conventional segmentation on the CT image domain. We expect that the proposed segmentation method can improve the performance of the existing MAR methods that are based on metal segmentation on the CT image domain.

A motion artifact reduction method for dental CT based on subpixel-resolution image registration of projection data.

High-resolution imaging is essential in three-dimensional (3D) CT image-based digital dentistry. A small amount of head motion during a CT scan can degrade the spatial resolution of the images to the extent where the efficacy of 3D image-based digital dentistry is greatly compromised. We introduce a retrospective motion artifact reduction (MAR) method for dental CTs that eliminates the necessity for any external motion tracking devices. Assuming that rigid-body motions are dominant in a dental scan of a human head, we extracted motion information from the projection data. By taking the cross-correlation between two successive projection data for every projection view, we determined the displacement of the projection data at each view. We experimentally found that any motion of the imaging object during the scan resulted in displacement of the projection data proportional to the motion amplitude. We decomposed the displacement into two components, one caused by translational motion and the other caused by rotational motion. The displacement components were used to correct the projection data before CT image reconstruction. We experimentally verified the MAR method using the projection data of a few phantoms acquired through a clinical dental CT machine. When the MAR performance was evaluated by the structural similarity index (SSIM) and the normalized absolute error (NAE) in reference to the motion-less images, the SSIM improved to 99% while the NAE was reduced by 80-90%.

A head motion estimation algorithm for motion artifact correction in dental CT imaging.

A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.

Dual-energy-based metal segmentation for metal artifact reduction in dental computed tomography.

PURPOSE: In a dental CT scan, the presence of dental fillings or dental implants generates severe metal artifacts that often compromise readability of the CT images. Many metal artifact reduction (MAR) techniques have been introduced, but dental CT scans still suffer from severe metal artifacts particularly when multiple dental fillings or implants exist around the region of interest. The high attenuation coefficient of teeth often causes erroneous metal segmentation, compromising the MAR performance. We propose a metal segmentation method for a dental CT that is based on dual-energy imaging with a narrow energy gap. METHODS: Unlike a conventional dual-energy CT, we acquire two projection data sets at two close tube voltages (80 and 90 kVp ), and then, we compute the difference image between the two projection images with an optimized weighting factor so as to maximize the contrast of the metal regions. We reconstruct CT images from the weighted difference image to identify the metal region with global thresholding. We forward project the identified metal region to designate metal trace on the projection image. We substitute the pixel values on the metal trace with the ones computed by the region filling method. The region filling in the metal trace removes high-intensity data made by the metallic objects from the projection image. We reconstruct final CT images from the region-filled projection image with the fusion-based approach. We have done imaging experiments on a dental phantom and a human skull phantom using a lab-built micro-CT and a commercial dental CT system. RESULTS: We have corrected the projection images of a dental phantom and a human skull phantom using the single-energy and dual-energy-based metal segmentation methods. The single-energy-based method often failed in correcting the metal artifacts on the slices on which tooth enamel exists. The dual-energy-based method showed better MAR performances in all cases regardless of the presence of tooth enamel on the slice of interest. We have compared the MAR performances between both methods in terms of the relative error (REL), the sum of squared difference (SSD) and the normalized absolute difference (NAD). For the dental phantom images corrected by the single-energy-based method, the metric values were 95.3%, 94.5%, and 90.6%, respectively, while they were 90.1%, 90.05%, and 86.4%, respectively, for the images corrected by the dual-energy-based method. For the human skull phantom images, the metric values were improved from 95.6%, 91.5%, and 89.6%, respectively, to 88.2%, 82.5%, and 81.3%, respectively. CONCLUSIONS: The proposed dual-energy-based method has shown better performance in metal segmentation leading to better MAR performance in dental imaging. We expect the proposed metal segmentation method can be used to improve the MAR performance of existing MAR techniques that have metal segmentation steps in their correction procedures.

A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector.

We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean value at each detector element along the view angle in the sinogram to obtain the one-dimensional (1D) mean vector, and we then compute the 1D correction vector by taking inverse of the mean vector. We multiply the correction vector with the sinogram row by row over all view angles. In the third step, we apply a Gaussian filter on the difference image between the original CT image and the corrected CT image obtained in the previous step. The filtered difference image is added to the corrected CT image to compensate the possible contrast anomaly that may appear due to the contrast change in the sinogram after removing stripe artifacts. We applied the proposed method to the projection data acquired by two flat-panel detectors (FPDs) and a silicon-based photon-counting X-ray detector (PCXD). Micro-CT imaging experiments of phantoms and a small animal have shown that the proposed method can greatly reduce ring artifacts regardless of detector types. Despite the great reduction of ring artifacts, the proposed method does not compromise the original spatial resolution and contrast.

A bench-top micro-CT capable of simulating head motions.

Computational three-dimensional (3D) models of a dental structure generated from 3D dental computed tomography (CT) images are now widely used in digital dentistry. To generate precise 3D models, high-resolution imaging of the dental structure with a dental CT is required. However, a small head motion of the patient during the dental CT scan could degrade the spatial resolution of CT images to the extent that digital dentistry is no longer possible. A bench-top micro-CT has been built to evaluate the head motion effects on the dental CT images. A micro-CT has been built on an optic table with a micro-focus x-ray source and a flat-panel detector. A rotation stage, placed in between the x-ray source and the detector, is mounted on two-directional goniometers that can rotate the rotation stage in two orthogonal directions while the rotation stage is performing the CT scan. The goniometers can make object motions of an arbitrary waveform to simulate head tilting or head nodding. CT images of a phantom have been taken with and without introducing the motions, and the motion effects on the CT images have been evaluated. Object motions parallel to the detector plane have greater effects on the CT images than those against the detector plane. With the bench-top micro-CT, the motion effects have been visually seen at a tiny rotational motion as small as 0.3°. The bench-top micro-CT can be used to evaluate head motion effects on the dental CT images. The projection data, taken with the motion effects, would be used to develop motion artifact correction methods for a high-resolution dental-CT.

A metal artifact reduction method for a dental CT based on adaptive local thresholding and prior image generation.

BACKGROUND: Metal artifacts appearing as streaks and shadows often compromise readability of computed tomography (CT) images. Particularly in a dental CT in which high resolution imaging is crucial for precise preparation of dental implants or orthodontic devices, reduction of metal artifacts is very important. However, metal artifact reduction algorithms developed for a general medical CT may not work well in a dental CT since teeth themselves also have high attenuation coefficients. METHODS: To reduce metal artifacts in dental CT images, we made prior images by weighted summation of two images: one, a streak-reduced image reconstructed from the metal-region-modified projection data, and the other a metal-free image reconstructed from the original projection data followed by metal region deletion. To make the streak-reduced image, we precisely segmented the metal region based on adaptive local thresholding, and then, we modified the metal region on the projection data using linear interpolation. We made forward projection of the prior image to make the prior projection data. We replaced the pixel values at the metal region in the original projection data with the ones taken from the prior projection data, and then, we finally reconstructed images from the replaced projection data. To validate the proposed method, we made computational simulations and also we made experiments on teeth phantoms using a micro-CT. We compared the results with the ones obtained by the fusion prior-based metal artifact reduction (FP-MAR) method. RESULTS: In the simulation studies using a bilateral prostheses phantom and a dental phantom, the proposed method showed a performance similar to the FP-MAR method in terms of the edge profile and the structural similarity index when an optimal global threshold was chosen for the FP-MAR method. In the imaging studies of teeth phantoms, the proposed method showed a better performance than the FP-MAR method in reducing the streak artifacts without introducing any contrast anomaly. CONCLUSIONS: The simulation and experimental imaging studies suggest that the proposed method can be used for reducing metal artifacts in dental CT images.

Iterative multi-channel radio frequency pulse calibration with improving B1 field uniformity in high field MRI.

BACKGROUND: In high field MRI capable of multi-channel radio frequency (RF) transmission, B 1 shimming is a time-consuming job because conventional B 1 shimming techniques require B 1 mapping for each channel. After acquiring the complex-numbered B 1 field maps, the optimal amplitude and phase of the driving RF pulse are determined for each channel to maximize the B 1 field uniformity in conventional B 1 shimming. However, time-consuming B 1 shimming procedures at the pre-scan may not be tolerated in the clinical imaging in which patient throughput is one of the important factors. METHODS: To avoid the time-consuming B 1 mapping, the first spin echo and the stimulated echo were repeatedly acquired in the slice-selective stimulated echo sequence without imaging gradients. A cost function of the amplitudes and phases of the driving RF pulse for every channel was defined in a way that the ratio between the spin echo and stimulated echo amplitudes rapidly converged to √ 2. The amplitude and phase of the driving RF pulse were iteratively modified over the repeating RF pulse sequence so that the cost function was minimized. RESULTS: From the finite-difference-time-domain (FDTD) electromagnetic field simulations with a human body model placed in a birdcage coil operating at 3 T, it was observed that the RF pulse calibration with iterative cost function minimization can give improvement of B1 field uniformity as well as flip-angle calibration. The experiments at 3 T also showed improvement of RF field uniformity in the phantom imaging studies. CONCLUSIONS: Since the proposed RF pulse calibration is not based on B 1 mapping, the RF pulse calibration time could be much shorter than the B 1-mapping based methods. The proposed method is expected to be a practical substitute for the B 1-mapping-based B 1 shimming methods when long pre-scan time is not tolerable.

Denoising of B1⁺ field maps for noise-robust image reconstruction in electrical properties tomography.

PURPOSE: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B1(+) maps in electrical properties tomography (EPT). METHODS: In EPT, electrical property images are computed by taking Laplacian of the B1(+) maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B1(+) maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. RESULTS: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. CONCLUSIONS: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T.

Magnetic Resonance Imaging Compatibility of the Polymer-based Cochlear Implant.

OBJECTIVES: In this study, we compared the magnetic resonance (MR) image artifacts caused by a conventional metal-based cochlear implant and a newly developed liquid crystal polymer (LCP)-based device. METHODS: The metal-based cochlear implant system (Nurobiosys Co.) was attached to side of the head of a subject and the LCP-based device was attached to opposite side. In both devices, alignment magnets were removed for safety. Magnetic resonance imaging (MRI) was performed on a widely used 3.0 T and an ultra-high 7.0 T MRI machine. 3.0 and 7.0 T MR images were acquired using T1- and T2(*)-weighted gradient echo sequences, respectively. RESULTS: In the 3.0 T images, the metal-based device on the left side generated the significant amount of artifacts. The MR images in the proximity of the metal package were obscured by the artifacts in both axial and sagittal views. On the other hand, the MR images near the LCP-based device were relatively free from the artifacts and clearly showed the brain structures. 7.0 T MR images showed the more severe distortion in the both sides but the metal-based cochlear implant system caused a much larger obscure area than the LCP-based system. CONCLUSION: The novel LCP-based cochlear implant provides a good MRI compatibility beyond present-day cochlear implants. Thus, MR images can be obtained from the subjects even with the implanted LCP-based neural prosthetic systems providing useful diagnostic information. Furthermore, it will be also useful for functional MRI studies of the auditory perception mechanism after cochlear implantations as well as for positron emission tomography-MRI hybrid imaging.

Royal jelly increases collagen production in rat skin after ovariectomy.

Royal jelly (RJ) is a honeybee product that contains proteins, carbohydrates, fats, free amino acids, vitamins, and minerals. RJ has been reported to have antitumor, antibacterial, and wound-healing activities. We previously reported that RJ enhanced the migration of human dermal fibroblasts and altered the levels of cholesterol and sphinganine in an in vitro wound-healing model in addition to regulating skin photoaging following exposure to ultraviolet-B radiation. We established an animal model of skin aging in the context of estrogen deficiency and assessed the antiaging effects of RJ on skin. To establish an in vivo model of skin aging, bilateral ovariectomies were performed in 12-week-old virgin female Sprague-Dawley rats. Induction of osteoporosis was confirmed through two-dimensional images of the trabecular bone in the left femoral necks using microcomputed tomography. The protective effects of RJ ovariectomy-induced skin aging were examined by determining the protein expression of type I procollagen and matrix metalloproteinase (MMP)-1. The collagen content and epidermal thickness of skin tissue were measured by staining techniques. There was a significant difference in weight between sham-operated and ovariectomized groups. Food efficiency ratio did not differ significantly among the groups. The level of procollagen type I protein was increased in the dorsal skin of ovariectomized rats fed with a dietary supplement containing 1% RJ extract, but the level of MMP-1 was not altered. In particular, the amount of collagen recovered was close to the normal level. RJ may protect against skin aging by enhancing collagen production in rats with ovariectomy-induced estrogen deficiency.

Geometric nonlinear diffusion filter and its application to X-ray imaging.

BACKGROUND: Denoising with edge preservation is very important in digital x-ray imaging since it may allow us to reduce x-ray dose in human subjects without noticeable degradation of the image quality. In denoising filter design for x-ray imaging, edge preservation as well as noise reduction is of great concern not to lose detailed spatial information for accurate diagnosis. In addition to this, fast computation is also important since digital x-ray images are mostly comprised of large sized matrices. METHODS: We have developed a new denoising filter based on the nonlinear diffusion filter model. Rather than employing four directional gradients around the pixel of interest, we use geometric parameters derived from the local pixel intensity distribution in calculating the diffusion coefficients in the horizontal and vertical directions. We have tested the filter performance, including edge preservation and noise reduction, using low dose digital radiography and micro-CT images. RESULTS: The proposed denoising filter shows performance similar to those of nonlinear anisotropic diffusion filters (ADFs), one Perona-Malik ADF and the other Weickert's ADF in terms of edge preservation and noise reduction. However, the computation time has been greatly reduced. CONCLUSIONS: We expect the proposed denoising filter can be greatly used for fast noise reduction particularly in low-dose x-ray imaging.

Strain measurement from 3D micro-CT images of a breast-mimicking phantom.

Strain distribution in compressed tissues gives information about elasticity of the tissues. We have measured strain from two sets of 3D micro-CT images of a breast-mimicking phantom; one obtained without compressing the phantom and the other with compressing it. To measure strain, we first calculated compression-induced displacements of high-intensity feature patterns in the image. In measuring displacement of a pixel of interest, we searched the pixel in the compressed-phantom image, whose surrounding resembles the uncompressed-phantom image most closely, using the image correlation technique. From the displacement data, we calculated average strain at a region of interest. With the calculated average strains, we could distinguish the hard inclusion in the phantom which was not distinguishable from the background body of the phantom in the ordinary micro-CT images. The calculated strains account for stiffness of the tissue of interest, one of the important parameters for diagnosing malignant tissues. We present experimental results of the displacement and strain measurement along with FEM analysis results.

Finite element simulation of ultrasound propagation in bone for quantitative ultrasound toward the diagnosis of osteoporosis.

Osteoporosis is a serious bone disease which leads to the increased risk of bone fractures. For prevention and therapy, early detection of osteoporosis is critical. In general, for diagnosis of osteoporosis, dual-energy X-ray absoptiometry (DXA) or densitometry is most commonly used. However DXA exhibits some disadvantages such as ionizing radiation, relatively expensive cost, and limited information on mineralization and geometry of the bone. As an alternative method of DXA, quantitative ultrasound (QUS) is being investigated. In contrast to DXA, QUS is non-ionizing and relatively inexpensive. It can also provide some bone-related parameters (e.g., quantitative measurements including speed of sound and frequency-dependent attenuation). However the estimation of these parameters is difficult and few analytical solutions exist due to the complex behavior of ultrasound propagation in bone. As an alternative to the analytical methods, in most attempts, finite difference time domain (FDTD) method is used for simulation of ultrasound propagation in bone with a limited capability of modeling complex geometries of the bone. Finite element method (FEM) is a better solution since it can handle the complex geometry, but has been rarely applied due to its computational complexity. In this work, we propose an approach of FEM-based simulation of ultrasound propagation in bone. To validate our approach, we have tested simulated and real bone models from micro-CT using the index of speed-of-sound. Our results achieve an average of 97.54% in the computational accuracy.

Protective effect of apigenin on ovariectomy-induced bone loss in rats.

Recent studies have shown that apigenin not only inhibits bone resorption by osteoclasts but also induces osteoclast apoptosis. However, the influence of apigenin on osteoporosis in animals is relatively unknown. The purpose of this study was to examine the bone-protective effects of apigenin in estrogen-deficient ovariectomized rats. Three-month-old female Sprague-Dawley rats were either sham-operated or ovariectomized and fed AIN-93G diet for 7 weeks to induce bone loss. To confirm bone loss, we used a newly developed non-invasive technique involving zoom-in micro-computed tomography. Apigenin was administered at a dose of 10 mg/kg three times a week for 15 weeks. Our results indicate that apigenin not only increased the mineral content and density of the trabecular bone at the neck of the left femur, but also decreased body weight and dietary consumption. Moreover, our biochemical results indicate that apigenin has a positive effect on bone turnover. The present data suggest that apigenin should be considered for use in the treatment of osteoporosis.

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.

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.