A diagnostic index based on quantitative susceptibility mapping and voxel-based morphometry may improve early diagnosis of Alzheimer's disease.

OBJECTIVES: Voxel-based morphometry (VBM) is widely used to quantify the progression of Alzheimer's disease (AD), but improvement is still needed for accurate early diagnosis. We evaluated the feasibility of a novel diagnosis index for early diagnosis of AD based on quantitative susceptibility mapping (QSM) and VBM. METHODS: Thirty-seven patients with AD, 24 patients with mild cognitive impairment (MCI) due to AD, and 36 cognitively normal (NC) subjects from four centers were included. A hybrid sequence was performed by using 3-T MRI with a 3D multi-echo GRE sequence to obtain both a T1-weighted image for VBM and phase images for QSM. The index was calculated from specific voxels in QSM and VBM images by using a linear support vector machine. The method of voxel extraction was optimized to maximize diagnostic accuracy, and the optimized index was compared with the conventional VBM-based index using receiver operating characteristic analysis. RESULTS: The index was optimal when voxels were extracted as increased susceptibility (AD > NC) in the parietal lobe and decreased gray matter volume (AD < NC) in the limbic system. The optimized proposed index showed excellent performance for discrimination between AD and NC (AUC = 0.94, p = 1.1 × 10-10) and good performance for MCI and NC (AUC = 0.87, p = 1.8 × 10-6), but poor performance for AD and MCI (AUC = 0.68, p = 0.018). Compared with the conventional index, AUCs were improved for all cases, especially for MCI and NC (p < 0.05). CONCLUSIONS: In this preliminary study, the proposed index based on QSM and VBM improved the diagnostic performance between MCI and NC groups compared with the VBM-based index. KEY POINTS: • We developed a novel diagnostic index for Alzheimer's disease based on quantitative susceptibility mapping (QSM) and voxel-based morphometry (VBM). • QSM and VBM images can be acquired simultaneously in a single sequence with little increasing scan time. • In this preliminary study, the proposed diagnostic index improved the discriminative performance between mild cognitive impairment and normal control groups compared with the conventional VBM-based index.

Low b-value diffusion tensor imaging for measuring pseudorandom flow of cerebrospinal fluid.

PURPOSE: Cerebrospinal fluid (CSF) plays an important role in the clearance system of the brain. Recently, low b-value diffusion tensor imaging (low-b DTI) has been reported to be useful in the observation of CSF flow; however, the precise flow property observed by low-b DTI has not been fully investigated. Accordingly, a mathematical framework of low-b DTI is proposed for investigating CSF and clarifying its pseudorandom flow. THEORY: The framework will show that the limit of the diffusion tensor as b-value decreases to zero approximately represents the covariance of the velocity distribution of the CSF's pseudorandom flow. METHODS: The low b-value diffusion tensor (DTL ) of whole-brain CSF was obtained using diffusion-weighted echo-planar imaging. Seven healthy volunteers were scanned for intersubject analysis; three of the volunteers was consecutively scanned for repeatability analysis. Obtained DTL was visually assessed by ellipsoid-representation map and was statistically evaluated by calculating mean diffusivity (MD) and fractional anisotropy (FA) in regions of interest (ROIs) representing intensive pseudorandom flow. RESULTS: Obtained DTL consistently shows large and anisotropic diffusivity in some segments of CSF, typically the ROIs around the foramen of Monro, the aqueduct, the prepontine cistern, the middle cerebral artery, and the Sylvian fissure throughout the study. The statistical analysis shows high repeatability and consistently high MD and FA in all the ROIs for all the volunteers. CONCLUSION: From the viewpoint of the proposed framework, the high and anisotropic DTL in the ROIs indicates large covariance of velocity distribution, which represents intensive pseudorandom flows of CSF.

Automated Detection of Cerebral Microbleeds on Two-dimensional Gradient-recalled Echo T2* Weighted Images Using a Morphology Filter Bank and Convolutional Neural Network.

PURPOSE: We present a novel algorithm for the automated detection of cerebral microbleeds (CMBs) on 2D gradient-recalled echo T2* weighted images (T2*WIs). This approach combines a morphology filter bank with a convolutional neural network (CNN) to improve the efficiency of CMB detection. A technical evaluation was performed to ascertain the algorithm's accuracy. METHODS: In this retrospective study, 60 patients with CMBs on T2*WIs were included. The gold standard was set by three neuroradiologists based on the Microbleed Anatomic Rating Scale guidelines. Images with CMBs were extracted from the training dataset comprising 30 cases using a morphology filter bank, and false positives (FPs) were removed based on the threshold of size and signal intensity. The extracted images were used to train the CNN (Vgg16). To determine the effectiveness of the morphology filter bank, the outcomes of the following two methods for detecting CMBs from the 30-case test dataset were compared: (a) employing the morphology filter bank and additional FP removal and (b) comprehensive detection without filters. The trained CNN processed both sets of initial CMB candidates, and the final CMB candidates were compared with the gold standard. The sensitivity and FPs per patient of both methods were compared. RESULTS: After CNN processing, the morphology-filter-bank-based method had a 95.0% sensitivity with 4.37 FPs per patient. In contrast, the comprehensive method had a 97.5% sensitivity with 25.87 FPs per patient. CONCLUSION: Through effective CMB candidate refinement with a morphology filter bank and FP removal with a CNN, we achieved a high CMB detection rate and low FP count. Combining a CNN and morphology filter bank may facilitate the accurate automated detection of CMBs on T2*WIs.

Region Expansion of Background Field Removal with Local Spherical Harmonics Approximation for Whole-brain Quantitative Susceptibility Mapping.

PURPOSE: Quantitative susceptibility mapping (QSM) is useful for obtaining biological information. To calculate susceptibility distribution, it is necessary to calculate the local field caused by the differences of susceptibility between the tissues. The local field can be obtained by removing a background field from a total field acquired by MR phase image. Conventional approaches based on spherical mean value (SMV) filtering, which are widely used for background field calculations, fail to calculate the background field of the brain surface region corresponding to the radius of the SMV kernel, and consequently cannot calculate the QSM of the brain surface region. Accordingly, a new method calculating the local field by expansively removing the background field is proposed for whole brain QSM. METHODS: The proposed method consists of two steps. First, the background field of the brain surface is calculated from the total field using a locally polynomial approximation of spherical harmonics. Second, the whole brain local field is calculated by SMV filtering with a constraint term of the background field of the brain surface. The parameters of the approximation were optimized to reduce calculation errors through simulations using both a numerical phantom and a measured human brain. Performance of the proposed method with the optimized parameters was quantitatively and visually compared with conventional methods in an experiment of five healthy volunteers. RESULTS: The proposed method showed the accurate local field over the expanded brain region in the simulation studies. It also showed consistent QSM with conventional methods inside of the brain surface and showed clear vein structures on the brain surface. CONCLUSION: The proposed method enables accurate calculation of whole brain QSM without eroding the brain surface region while maintaining same values inside of the brain surface as the conventional methods.

Low b-value Diffusion Tensor Imaging to Analyze the Dynamics of Cerebrospinal Fluid: Resolving Intravoxel Pseudorandom Motion into Ordered and Disordered Motions.

PURPOSE: Analysis of cerebrospinal fluid (CSF) dynamics may be beneficial for understanding the mechanisms and diagnosis of several neurological diseases. Low b-value diffusion tensor imaging (low-b DTI) is useful for observing the slow and complex motion of the CSF. Theoretically, a mathematical framework suggests that low-b DTI provides the variance of the pseudorandom motion of the CSF. Furthermore, low-b DTI could provide comprehensive information on fluid dynamics. Accordingly, we proposed an analysis technique that resolves intravoxel pseudorandom motion into ordered (linear) and disordered (random) motions based on the mathematical framework. METHODS: The proposed analysis technique helps measure low-b DTI with multiple diffusion times and linearly fits its mean diffusivity (MD) with the diffusion time to obtain two parameters, double-slope Vv and y-intersect Dr, which represent the variance of the velocity distribution of linear motion and the diffusion coefficient of random motion, respectively. Seven healthy subjects were scanned to evaluate the proposed technique and investigate fluid dynamics in several representative ROIs. RESULTS: The obtained data showed the validity of the technique, repeatability, and consistency across the subjects in ROIs, such as the lateral ventricle (LV), third ventricle (3V), fourth ventricle (4V), and Sylvian fissure (SF). The obtained parameters Vv and Dr highlighted different characteristics of fluid dynamics in the representative ROIs: low Vv and low Dr in the LV, high Vv and moderate Dr in the 3V, and moderate Vv and moderate Dr in the 4V and SF. CONCLUSION: The proposed analysis technique will facilitate a comprehensive investigation of the complex dynamics of the CSF using resolved parameters representing ordered and disordered motions.

Three-dimensional Multi-parameter Mapping of Relaxation Times and Susceptibility Using Partially RF-spoiled Gradient Echo.

PURPOSE: MR parameter mapping is a technique that obtains distributions of parameters such as relaxation time and proton density (PD) and is starting to be used for disease quantification in clinical diagnoses. Quantitative susceptibility mapping is also promising for the early diagnosis of brain disorders such as degenerative neurological disorders. Therefore, we developed an MR quantitative parameter mapping (QPM) method to map four tissue-related parameters (T1, T2*, PD, and susceptibility) and B1 simultaneously by using a 3D partially RF-spoiled gradient echo (pRSGE). We verified the accuracy and repeatability of QPM in phantom and volunteer experiments. METHODS: Tissue-related parameters are estimated by varying four scan parameters of the 3D pRSGE: flip angle, RF-pulse phase increment, TR and TE, performing multiple image scans, and finding a least-squares fit for an intensity function (which expresses the relationship between the scan parameters and intensity values). The intensity function is analytically complex, but by using a Bloch simulation to create it numerically, the least-squares fitting can be used to estimate the quantitative values. This has the advantage of shortening the image-reconstruction processing time needed to estimate the quantitative values than with methods using pattern matching. RESULTS: A 1.1-mm isotropic resolution scan covering the whole brain was completed with a scan time of approximately 12 minutes, and the reconstruction time using a GPU was approximately 1 minute. The phantom experiments confirmed that both the accuracy and repeatability of the quantitative values were high. The volunteer scans also confirmed that the accuracy of the quantitative values was comparable to that of conventional methods. CONCLUSION: The proposed QPM method can map T1, T2*, PD, susceptibility, and B1 simultaneously within a scan time that can be applied to human subjects.

Efficacy of Quantitative Susceptibility Mapping with Brain Surface Correction and Vein Removal for Detecting Increase Magnetic Susceptibility in Patients with Alzheimer's Disease.

PURPOSE: Studies on quantitative susceptibility mapping (QSM) have reported an increase in magnetic susceptibilities in patients with Alzheimer's disease (AD). Despite the pathological importance of the brain surface areas, they are sometimes excluded in QSM analysis. This study aimed to reveal the efficacy of QSM analysis with brain surface correction (BSC) and/or vein removal (VR) procedures. METHODS: Thirty-seven AD patients and 37 age- and sex-matched, cognitively normal (CN) subjects were included. A 3D-gradient echo sequence at 3T MRI was used to obtain QSM. QSM images were created with regularization enabled sophisticated harmonic artifact reduction for phase data (RESHARP) and constrained RESHARP with BSC and/or VR. We conducted ROI analysis between AD patients and CN subjects who did or did not undergo BSC and/or VR using a t-test, to compare the susceptibility values after gray matter weighting. RESULTS: The susceptibility values in RESHARP without BSC were significantly larger in AD patients than in CN subjects in one region (precentral gyrus, 8.1 ± 2.9 vs. 6.5 ± 2.1 ppb) without VR and one region with VR (precentral gyrus, 7.5 ± 2.8 vs. 5.9 ± 2.0 ppb). Three regions in RESHARP with BSC had significantly larger susceptibilities without VR (precentral gyrus, 7.1 ± 2.0 vs. 5.9 ± 2.0 ppb; superior medial frontal gyrus, 5.7 ± 2.6 vs. 4.2 ± 3.1 ppb; putamen, 47,8 ± 16.5 vs. 40.0 ± 15.9 ppb). In contrast, six regions showed significantly larger susceptibilities with VR in AD patients than in CN subjects (precentral gyrus, 6.4 ± 1.9 vs. 4.9 ± 2.7 ppb; superior medial frontal gyrus, 5.3 ± 2.7 vs. 3.7 ± 3.3 ppb; orbitofrontal cortex, -2.1 ± 2.7 vs. -3.6 ± 3.2 ppb; parahippocampal gyrus, 0.1 ± 3.6 vs. -1.7 ± 3.7 ppb; putamen, 45.0 ± 14.9 vs. 37.6 ± 14.6 ppb; inferior temporal gyrus, -3.4 ± 1.5 vs. -4.4 ± 1.5 ppb). CONCLUSION: RESHARP with BSC and VR showed more regions of increased susceptibility in AD patients than in CN subjects. This study highlights the efficacy of this method in facilitating the diagnosis of AD.

Prediction of amyloid positron emission tomography positivity using multiple regression analysis of quantitative susceptibility mapping.

PURPOSE: To develop a method for predicting amyloid positron emission tomography (PET) positivity based on multiple regression analysis of quantitative susceptibility mapping (QSM). MATERIALS AND METHODS: This prospective study included 39 patients with suspected dementia from four centers. QSM images were obtained through a 3-T, three-dimensional radiofrequency-spoiled gradient-echo sequence with multiple echoes. The cortical standard uptake value ratio (SUVR) was obtained using amyloid PET with 18F-flutemetamol, and susceptibility in the brain regions was obtained using QSM. A multiple regression model to predict cortical SUVR was constructed based on susceptibilities in multiple brain regions, with the constraint that cortical SUVR and susceptibility were positively correlated. The discrimination performance of the Aß-positive and Aß-negative cohorts was evaluated based on the predicted SUVR using the area under the receiver operating characteristic curve (AUC) and Mann-Whitney U test. RESULTS: The correlation coefficients between true and predicted SUVR were increased by incorporating the constraint, and the AUC to discriminate between the Aß-positive and Aß-negative cohorts reached to 0.79 (p < 0.01). CONCLUSION: These preliminary results suggest that a QSM-based multiple regression model can predict amyloid PET positivity with fair accuracy.

Simultaneous Arterial and Venous Imaging Using 3D Quantitative Parameter Mapping.

PURPOSE: To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution. METHODS: The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed. Arterial images are obtained by adding images using optimized weights to emphasize the arteries. A morphology filter is used to obtain venous images from the magnetic susceptibility maps. For evaluation, images obtained from four out of five healthy volunteers were used to optimize the weights used in the arterial-image calculation, and the optimized weights were applied to the images from the fifth volunteer to obtain an arterial image. Arterial images of the five volunteers were calculated using the leave-one-out method, and the contrast between the arterial and background regions defined using the reference time-of-flight (TOF) method was evaluated using the area under the receiver operation characteristic curve (AUC). The contrast between venous and background regions defined by a reference quantitative susceptibility mapping (QSM) method was also evaluated for the venous image. RESULTS: The AUC to discriminate blood vessels and background using the proposed method was 0.905 for the arterial image and 0.920 for the venous image. CONCLUSION: The results indicate that the arterial images and venous images have high signal intensity at the same region as determined from the reference TOF and QSM methods, demonstrating the possibility of acquiring vasculature images with quantitative parameter mapping through calculation in an integrated manner.

Quantitative susceptibility mapping of prostate with separate calculations for water and fat regions for reducing shading artifacts.

We propose a novel processing method for reducing shading artifacts in quantitative susceptibility mapping (QSM) for prostate imaging. In the conventional method, calculation errors in the boundary regions between water and fat cause shading artifacts that degrade the image quality for QSM. In the proposed method, water and fat regions are separated, and susceptibilities in these two regions are calculated separately and then combined. Susceptibility in the water regions is calculated by using the fat regions as a background susceptibility source to remove shading artifacts. Susceptibility in the fat regions is calculated by using the constraint that shading artifacts in the water regions are suppressed to improve accuracy. In quantitative evaluation of the method with a numerical simulation, calculation errors for the water and fat regions were reduced by 62% and 85%, respectively, compared with the conventional method. In visual evaluation using human prostate imaging, the proposed method also reduced the shading artifacts unlike the conventional method. The proposed method is expected to improve the performance of QSM in diagnosing such diseases as prostate cancer.

B1-control receive array coil (B-RAC) for reducing B1+ inhomogeneity in abdominal imaging at 3T-MRI.

B1+ inhomogeneity in the human body increases as the nuclear magnetic resonance (NMR) frequency increases. Various methods have thus been developed to reduce B1+ inhomogeneity, such as a dielectric pad, a coupling coil, parallel transmit, and radio-frequency (RF) shimming. However, B1+ inhomogeneity still remains in some cases of abdominal imaging. In this study, we developed a B1-control receive array coil (B-RAC). Unlike the conventional receive array coil, B-RAC reduces B1+ inhomogeneity by using additional PIN diodes to generate the inductive loop during the RF transmit period. The inductive loop can generate dense and sparse regions of the magnetic flux, which can be used to compensate for B1+ inhomogeneity. First, B-RAC is modeled in the numerical simulation, and the spatial distributions of B1+ in a phantom and a human model were analyzed. Next, we fabricated a 12-channel B-RAC and measured receive sensitivity and B1+ maps in a 3T-MRI experiment. It was demonstrated that B-RAC can reduce B1+ inhomogeneity in the phantom and human model without increasing the maximum local specific absorption rate (SAR) in the body. B-RAC was also found to have almost the same the receive sensitivity as the conventional receive coil. Using RF shimming combined with B-RAC was revealed to more effectively reduce B1+ inhomogeneity than using only RF shimming. Therefore, B-RAC can reduce B1+ inhomogeneity while maintaining the receive sensitivity.

Susceptibility difference weighted imaging in vertical-field MRI.

To realize susceptibility-weighted imaging in vertical-field magnetic resonance imaging (MRI), we developed an image-processing method called "susceptibility difference weighted imaging" (SDWI). In SDWI, contrasts are enhanced using a susceptibility map calculated by using a weighted least-square algorithm with a small iteration number. Experiments were performed on human volunteers to compare image contrast obtained from the conventional method (SWI) and SDWI. In horizontal-field MRI, SDWI results show that veins and deep-gray-matter nuclei were visualized as well as those with SWI. In vertical-field MRI, SDWI visualized veins and deep-gray-matter nuclei without severe streaking artifacts, while SWI did not. In our experiments, the time taken to calculate the susceptibility map in SDWI was less than 10 s. The results indicate that susceptibility-weighted imaging is feasible in vertical-field MRI using SDWI.

The Relationship between Neurite Density Measured with Confocal Microscopy in a Cleared Mouse Brain and Metrics Obtained from Diffusion Tensor and Diffusion Kurtosis Imaging.

PURPOSE: Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain. METHODS: One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis. RESULTS: Mean kurtosis (MK) (P = 5.2 × 10-9, r = 0.73) and radial kurtosis (P = 2.3 × 10-9, r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10-5, r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48). CONCLUSION: DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures.

Quantitative Susceptibility Mapping Using the Multiple Dipole-inversion Combination with k-space Segmentation Method.

Quantitative susceptibility mapping (QSM) is a new magnetic resonance imaging (MRI) technique for noninvasively estimating the magnetic susceptibility of biological tissue. Several methods for QSM have been proposed. One of these methods can estimate susceptibility with high accuracy in tissues whose contrast is consistent between magnitude images and susceptibility maps, such as deep gray-matter nuclei. However, the susceptibility of small veins is underestimated and not well depicted by using the above approach, because the contrast of small veins is inconsistent between a magnitude image and a susceptibility map. In order to improve the estimation accuracy and visibility of small veins without streaking artifacts, a method with multiple dipole-inversion combination with k-space segmentation (MUDICK) has been proposed. In the proposed method, k-space was divided into three domains (low-frequency, magic-angle, and high-frequency). The k-space data in low-frequency and magic-angle domains were obtained by L1-norm regularization using structural information of a pre-estimated susceptibility map. The k-space data in high-frequency domain were obtained from the pre-estimated susceptibility map in order to preserve small-vein contrasts. Using numerical simulation and human brain study at 3 Tesla, streaking artifacts and small-vein susceptibility were compared between MUDICK and conventional methods (MEDI and TKD). The numerical simulation and human brain study showed that MUDICK and MEDI had no severe streaking artifacts and MUDICK showed higher contrast and accuracy of susceptibility in small-veins compared to MEDI. These results suggest that MUDICK can improve the accuracy and visibility of susceptibility in small-veins without severe streaking artifacts.

See-through Brains and Diffusion Tensor MRI Clarified Fiber Connections: A Preliminary Microstructural Study in a Mouse with Callosal Agenesis.

Clearing methods that render the brain optically transparent allow high-resolution three-dimensional (3D) imaging of neural networks. We used diffusion tensor imaging (DTI) and two-photon imaging of cleared brains to analyze white matter in BTBR mice. We confirmed corpus callosum agenesis and identified an abnormal commissure close to the third ventricle. DTI and cleared-brain two-photon imaging revealed that these commissural fibers constituted a frontal clustering of the ventral hippocampal commissure and provided a detailed assessment of white matter structure in mice.

Diffusion-weighted line-scan echo-planar spectroscopic imaging technique to reduce motion artifacts in metabolite diffusion imaging.

Metabolite diffusion is expected to provide more specific microstructural and functional information than water diffusion. However, highly accurate measurement techniques have still not been developed, especially for reducing motion artifacts caused by cardiac pulsation and respiration. We developed a diffusion-weighted line-scan echo-planar spectroscopic imaging (DW-LSEPSI) technique to reduce such motion artifacts in measuring diffusion-weighted images (DWI) of metabolites. Our technique uses line-scan and echo-planar techniques to reduce phase errors induced by such motion during diffusion time. The phase errors are corrected using residual water signals in water suppression for each acquisition and at each spatial pixel specified by combining the line-scan and echo-planar techniques. We apply this technique to a moving phantom and a rat brain in vivo to demonstrate the reduction of motion artifacts in DWI and apparent diffusion coefficient (ADC) maps of metabolites. DW-LSEPSI will be useful for investigating a cellular diffusion environment using metabolites as probes.

Cardiac cine parallel imaging on a 0.7T open system.

BACKGROUND: Parallel imaging can be applied to cardiac imaging with a cylindrical MRI (magnetic resonance imaging) apparatus. Studies of open MRI, however, are few. This study sought to achieve cardiac cine parallel imaging (or RAPID, for "rapid acquisition through parallel imaging design") with an open 0.7T MRI apparatus. MATERIALS AND METHODS: Imaging time was shortened in all slice directions with the use of a dedicated four-channel RF receiving coil comprising solenoid coils and butterfly coils. Coil shape was designed through an RF-coil simulation that considered biological load. The auto-calibration of a 0.7T open MRI apparatus incorporated a modified image-domain reconstruction algorithm. Cine images were obtained with a BASG, or balanced SARGE (steady-state acquisition with rewound gradient echo), sequence. Image quality was evaluated with cylindrical phantoms and five healthy volunteers. RESULTS: Multi-slice phantom images showed no visible artifacts. Cine images taken under breath-hold with an acceleration factor of two were evaluated carefully. With auto-calibration, the images revealed no visible unfolded artifacts or motion artifacts. RAPID thus improved the acquisition speed, time resolution, and spatial resolution of short-axis, long-axis, and four-chamber images. CONCLUSION: The use of a dedicated RF coil enabled cardiac cine RAPID to be performed with an open MRI apparatus.

Double-tuned radiofrequency coil for (19)F and (1)H imaging.

We developed a double-tuned radiofrequency (RF) coil using a novel circuit method to double tune for fluorine-19 (19F) and 1H magnetic resonance imaging, whose frequencies are very close to each other. The RF coil consists of 3 parallel-connected series inductor capacitor circuits. A computer simulation for our double-tuned RF coil with a phantom demonstrated that the coil has tuned resonant frequency and high sensitivity for both 19F and 1H. Drug distribution was visualized at 7 tesla using this RF coil and a rat administered perfluoro 15-crown-5-ether emulsion. The double-tune RF coil we developed may be a powerful tool for 19F and 1H imaging.