Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R1·R2* and myelin water fraction in white matter.

OBJECTIVE: To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM). MATERIALS AND METHODS: Subjects were 12 healthy volunteers. On a 3 T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region. RESULTS: The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59 s-2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001). DISCUSSION: MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions.

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.

Nature of the Intracellular-contrast-enhancing Fat-saturated T1-weighted Gradient-echo (ICE-TIGRE) Sequence: A Fat-suppressed T1-weighted Technique with Motion-sensitised Driven-equilibrium for Improved Contrast Enhancement in Liver Imaging.

Gadoxetic acid is both an extracellular- and hepatocyte-specific contrast agent. Signals from the extracellular space may lower the contrast between lesions and the surrounding hepatic parenchyma. To improve hepatocyte-specific enhancement, we developed an intracellular contrast-enhancing fat-saturated T1-weighted gradient-echo nature of the sequence (ICE-TIGRE). It incorporates the motion-sensitized driven-equilibrium (MSDE) pulse to suppress signals from the blood flow. We investigated the optimal ICE-TIGRE scanning parameters, i.e., the order of the MSDE and the fat saturation pulses, the duration time, and the b value of the MSDE pulse, using a phantom and three volunteers without applying gadoxetic acid. ICE-TIGRE successfully increased the contrast between the liver parenchyma and the portal vein. To maintain fat saturation, the preparation pulse order should be MSDE-fat saturation. A duration time of 21 ms should be applied to minimize the effect of the T2 factor on the T1 contrast, and a b value of 60 s/mm2 should be applied to maximize the diffusion contrast for ICE-TIGRE with the imaging system used in this study.

Differences of white matter structure for diffusion kurtosis imaging using voxel-based morphometry and connectivity analysis.

Objectives: In a clinical study, diffusion kurtosis imaging (DKI) has been used to visualize and distinguish white matter (WM) structures' details. The purpose of our study is to evaluate and compare the diffusion tensor imaging (DTI) and DKI parameter values to obtain WM structure differences of healthy subjects. Methods: Thirteen healthy volunteers (mean age, 25.2 years) were examined in this study. On a 3-T MRI system, diffusion dataset for DKI was acquired using an echo-planner imaging sequence, and T1-weghted (T1w) images were acquired. Imaging analysis was performed using Functional MRI of the brain Software Library (FSL). First, registration analysis was performed using the T1w of each subject to MNI152. Second, DTI (eg, fractional anisotropy [FA] and each diffusivity) and DKI (eg, mean kurtosis [MK], radial kurtosis [RK], and axial kurtosis [AK]) datasets were applied to above computed spline coefficients and affine matrices. Each DTI and DKI parameter value for WM areas was compared. Finally, tract-based spatial statistics (TBSS) analysis was performed using each parameter. Results: The relationship between FA and kurtosis parameters (MK, RK, and AK) for WM areas had a strong positive correlation (FA-MK, R2 = 0.93; FA-RK, R2 = 0.89) and a strong negative correlation (FA-AK, R2 = 0.92). When comparing a TBSS connection, we found that this could be observed more clearly in MK than in RK and FA. Conclusions: WM analysis with DKI enable us to obtain more detailed information for connectivity between nerve structures. Advances in knowledge: Quantitative indices of neurological diseases were determined using segmenting WM regions using voxel-based morphometry processing of DKI images.

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.

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.

Characterization of Breast Tumors from MR Images Using Radiomics and Machine Learning Approaches.

Determining histological subtypes, such as invasive ductal and invasive lobular carcinomas (IDCs and ILCs) and immunohistochemical markers, such as estrogen response (ER), progesterone response (PR), and the HER2 protein status is important in planning breast cancer treatment. MRI-based radiomic analysis is emerging as a non-invasive substitute for biopsy to determine these signatures. We explore the effectiveness of radiomics-based and CNN (convolutional neural network)-based classification models to this end. T1-weighted dynamic contrast-enhanced, contrast-subtracted T1, and T2-weighted MR images of 429 breast cancer tumors from 323 patients are used. Various combinations of input data and classification schemes are applied for ER+ vs. ER-, PR+ vs. PR-, HER2+ vs. HER2-, and IDC vs. ILC classification tasks. The best results were obtained for the ER+ vs. ER- and IDC vs. ILC classification tasks, with their respective AUCs reaching 0.78 and 0.73 on test data. The results with multi-contrast input data were generally better than the mono-contrast alone. The radiomics and CNN-based approaches generally exhibited comparable results. ER and IDC/ILC classification results were promising. PR and HER2 classifications need further investigation through a larger dataset. Better results by using multi-contrast data might indicate that multi-parametric quantitative MRI could be used to achieve more reliable classifiers.

Utility of Wavelet Denoising with Geometry Factor Weighting for Gadoxetic Acid-enhanced Hepatobiliary-phase MR Imaging.

PURPOSE: The wavelet denoising with geometry factor weighting (g-denoising) method can reduce the image noise by adapting to spatially varying noise levels induced by parallel imaging. The aim of this study was to investigate the clinical applicability of g-denoising on hepatobiliary-phase (HBP) images with gadoxetic acid. METHODS: We subjected 53 patients suspected of harboring hepatic neoplastic lesions to gadoxetic acid-enhanced HBP imaging with and without g-denoising (g+HBP and g-HBP). The matrix size was reduced for g+HBP images to avoid prolonging the scanning time. Two radiologists calculated the SNR, the portal vein-, and paraspinal muscle contrast-to-noise ratio (CNR) relative to the hepatic parenchyma (liver-to-portal vein- and liver-to-muscle CNR). Two other radiologists independently graded the sharpness of the liver edge, the visibility of intrahepatic vessels, the image noise, the homogeneity of liver parenchyma, and the overall image quality using a 5-point scale. Differences between g-HBP and g+HBP images were determined with the two-sided Wilcoxon signed-rank test. RESULTS: The liver-to-portal- and liver-to-muscle CNR and the SNR were significantly higher on g+HBP- than g-HBP images (P < 0.01), as was the qualitative score for the image noise, homogeneity of liver parenchyma, and overall image quality (P < 0.01). Although there were no significant differences in the scores for the sharpness of the liver edge or the score assigned for the visibility of intrahepatic vessels (P = 0.05, 0.43), with g+HBP the score was lower in three patients for the sharpness of the liver edge and in six patients for the visibility of intrahepatic vessels. CONCLUSION: At gadoxetic acid-enhanced HBP imaging, g-denoising yielded a better image quality than conventional HBP imaging although the anatomic details may be degraded.

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.

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.

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.

Myelin-weighted imaging derived from quantitative parameter mapping.

PURPOSE: We developed a novel method which is applicable to visualize contrast according to myelin components in the human brain using relaxation time derived from quantitative parameter mapping magnetic resonance imaging (QPM-MRI). MATERIALS AND METHODS: Using healthy volunteer data (n = 10), we verified that our method demonstrated that the myelin-weighted contrast increased proportionally by products R1 and R2*, i.e., QPM-myelin-weighted image, in which modified T1-weighted/T2-weighted (T1w/T2w) ratio mapping method was applied. We compared measurement values in white matter (WM) and gray matter (GM) regions of the T1w/T2w ratio and R1·R2* product maps of healthy volunteers. Linear regression analysis between each value. Mann Whitney U test between WM and GM signals in each myelin map. In addition, Additionally, QPM-myelin-weighted image was applied to a 32-year-old female MS patient. RESULTS: Linear regression analysis showed a highly significant correlation between conventional T1w/T2w ratios and R1·R2* products derived from QPM (R = 0.73, P < 0.0001). Moreover, there is a significant difference between WM and GM structures in each myelin images (both, P < 0.0001). Additionally, in a clinical case, MS lesions enabled observation of not only MS plaques but also heterogeneous myelin signal loss associated with demyelination more clearly than T2w image and conventional T1w/T2w ratio image. CONCLUSION: Our myelin-weighted imaging technique using QPM may be useful for myelin visualization and is expected to become independent of measurement conditions due to having quantitative characteristics of QPM itself.

Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications.

Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ©RSNA, 2022.

Phase I Randomized Trial of 17 O-Labeled Water: Safety and Feasibility Study of Indirect Proton MRI for the Evaluation of Cerebral Water Dynamics.

BACKGROUND: 17 O-labeled water (PSO17) is a contrast agent developed to measure brain water dynamics and cerebral blood flow. PURPOSE: To evaluate the safety and feasibility of PSO17. STUDY TYPE: Prospective study. SUBJECTS: A total of 12 male healthy volunteers (23.1 ± 1.9 years) were assigned to three groups of four subjects: placebo (normal saline), PSO17 10%, and PSO17 20%. FIELD STRENGTH/SEQUENCE: Dynamic 3D fluid attenuated inversion recovery (FLAIR, fast spin echo with variable refocusing flip angle) scans of the brain were performed with 3-T MRI. ASSESSMENT: Contrast agents were injected 5 minutes after the start of a 10-minute scan. Any symptoms, vital signs, and blood and urine tests were evaluated at five timepoints from preinjection to 4 days after. Blood samples for pharmacokinetic analysis, including half-life (T1/2), maximum fraction (Cmax ), time-to-maximum fraction (Tmax ), and area under the curve (AUC), were collected at 13 timepoints from preinjection to 168 hours after. Regions of interest were set in the cerebral cortex (CC), basal ganglia/thalamus (BG/TM), and white matter (WM), and 17 O concentrations were calculated from signal changes and evaluated using Cmax . STATISTICAL TESTS: All items were compared among the three groups using Tukey-Kramer's honestly significant difference test. Statistical significance was defined as P < 0.5. RESULTS: No safety issues were noted with the intravenous administration of PSO17. The T1/2 was approximately 160 hours, and the AUCs were 1.77 ± 0.10 and 3.75 ± 0.36 in the PSO17 10% and 20% groups, respectively. 17 O fractions calculated from MRI signals were higher in the PSO17 20% group than in the 10% and placebo groups. Significant differences were noted between all pairs of groups in the CC and BG/TM, and between PSO17 20% and both placebo and 10% groups in the WM. DATA CONCLUSION: PSO17 might be considered safe as a contrast medium. Dynamic 3D-FLAIR might detect dose-dependent signal changes and estimate 17 O. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Quantitative parameter mapping of contrast agent concentration and relaxivity and brain tumor extracellular pH.

In clinical magnetic resonance imaging, gadolinium-based contrast agents are commonly used for detecting brain tumors and evaluating the extent of malignancy. We present a new method to evaluate relaxivity (r1) and contrast agent concentration separately in contrast-enhanced lesions using quantitative parameter mapping (QPM). Furthermore, we also aimed to estimate the extracellular pH (pHe) of tumor lesions. We demonstrated that it is possible to evaluate pathophysiological tumor changes due to therapeutic efficacy by measuring r1 in contrast-enhanced lesions. In this study, the primary brain tumor group showed significantly higher r1 values than other brain disease groups (P < 0.001). Moreover, mean pHe value showed a trend for tumor malignancy having a lower pHe value and primary brain tumor having a significantly lower pHe than other brain diseases (P < 0.001). Our results might suggest that QPM can separately quantify r1 and CA concentration in brain tumors and that pHe brain tumor mapping could serve as a tumor biomarker. In conclusion, our method has potential clinical applications for assessing the treatment effects.

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.

Quantitative Susceptibility Mapping versus R2*-based Histogram Analysis for Evaluating Liver Fibrosis: Preliminary Results.

PURPOSE: The staging of liver fibrosis is clinically important, and a less invasive method is preferred. Quantitative susceptibility mapping (QSM) has shown a great potential in estimating liver fibrosis in addition to R2* relaxometry. However, few studies have compared QSM analysis and liver fibrosis. We aimed to evaluate the feasibility of estimating liver fibrosis by using QSM and R2*-based histogram analyses by comparing it with ultrasound-based transient elastography and the stage of histologic fibrosis. METHODS: Fourteen patients with liver disease were enrolled. Data sets of multi-echo gradient echo sequence with breath-holding were acquired on a 3-Tesla scanner. QSM and R2* were reconstructed by water-fat separation method, and ROIs were analyzed for these images. Quantitative parameters with histogram features (mean, variance, skewness, kurtosis, and 1st, 10th, 50th, 90th, and 99th percentiles) were extracted. These data were compared with the elasticity measured by ultrasound transient elastography and histological stage of liver fibrosis (F0 to F4, based on the new Inuyama classification) determined by biopsy or hepatectomy. The correlation of histogram parameters with intrahepatic elasticity and histologically confirmed fibrosis stage was examined. Texture parameters were compared between subgroups divided according to fibrosis stage. Receiver operating characteristic (ROC) analysis was also performed. P < 0.05 indicated statistical significance. RESULTS: The six histogram parameters of both QSM and R2*were significantly correlated with intrahepatic elasticity. In particular, three parameters (variance, percentiles [90th and 99th]) of QSM showed high correlation (r = 0.818-0.844), whereas R2* parameters showed a moderate correlation with elasticity. Four parameters of QSM were significantly correlated with fibrosis stage (ρ = 0.637-0.723) and differentiated F2-4 from F0-1 fibrosis and F3-4 from F0-2 fibrosis with areas under the ROC curve of > 0.8, but those of R2* did not. CONCLUSION: QSM may serve as a promising surrogate indicator in detecting liver fibrosis.

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.

Utility of Radial Scanning for the Identification of Arterial Hypervascularity of Hepatocellular Carcinoma on Gadoxetic Acid-Enhanced Magnetic Resonance Images.

OBJECTIVES: This study aimed to compare the accuracy of assessing the arterial hypervascularity of hepatocellular carcinoma (HCC) on dynamic computed tomography (CT) scans and gadoxetic acid (EOB)-enhanced magnetic resonance imaging (MRI) scans performed with radial sampling. METHODS: We studied the images of 40 patients with hypervascular HCC. A radiologist recorded the standard deviation of the attenuation (or the signal intensity [SI]) in subcutaneous fat tissue as the image noise (N) and calculated the contrast-to-noise ratio (CNR) as follows: (CNR) = (n-ROIT - n-ROIL)/N, where n-ROIT is the mean attenuation (or SI) of the tumor divided by the mean attenuation (or SI) of the aorta and n-ROIL is the mean attenuation (or SI) of the liver parenchyma divided by the mean attenuation (or SI) of the aorta. RESULTS: The CNR was significantly higher on EOB-enhanced MRI than on dynamic CT scans. CONCLUSIONS: For the assessment of HCC vascularity, EOB-enhanced MRI scans acquired with radial sampling were more accurate than dynamic CT images.

Pseudo-random Trajectory Scanning Suppresses Motion Artifacts on Gadoxetic Acid-enhanced Hepatobiliary-phase Magnetic Resonance Images.

PURPOSE: Hepatobiliary-phase (HBP) MRI with gadoxetic acid facilitates the differentiation between lesions with and without functional hepatocytes. Thus, high-quality HBP images are required for the detection and evaluation of hepatic lesions. However, the long scan time may increase artifacts due to intestinal peristalsis, resulting in the loss of diagnostic information. Pseudo-random acquisition order disperses artifacts into the background. The aim of this study was to investigate the clinical applicability of pseudo-random trajectory scanning for the suppression of motion artifacts on T1-weighted images including HBP. METHODS: Our investigation included computer simulation, phantom experiments, and a clinical study. For computer simulation and phantom experiments a region of interest (ROI) was placed on the area with motion artifact and the standard deviation inside the ROI was measured as image noise. For clinical study we subjected 62 patients to gadoxetic acid-enhanced hepatobiliary-phase imaging with a circular- and a pseudo-random trajectory (c-HBP and p-HBP); two radiologists graded the motion artifacts, sharpness of the liver edge, visibility of intrahepatic vessels, and overall image quality using a five-point scale where 1 = unacceptable and 5 = excellent. Differences in the qualitative scores were determined using the two-sided Wilcoxon signed-rank test. RESULTS: The image noise was higher on the circular image compared with pseudo-random image (101.0 vs 60.9 on computer simulation image, 91.2 vs 67.7 on axial, 95.5 vs 86.9 on reformatted sagittal image for phantom experiments). For clinical study the score for motion artifacts was significantly higher with p-HBP than c-HBP imaging (left lobe: mean 3.4 vs 3.2, P < 0.01; right lobe: mean 3.6 vs 3.4, P < 0.01) as was the qualitative score for the overall image quality (mean 3.6 vs 3.3, P < 0.01). CONCLUSION: At gadoxetic acid-enhanced hepatobiliary-phase imaging, p-HBP scanning suppressed motion artifacts and yielded better image quality than c-HBP scanning.