Search

To explore the feasibility of using correlation-based time-delay (CTD) maps produced from time-resolved MR angiography (TRMRA) to diagnose perfusion abnormalities in patients suspected to have steno-occlusive lesions in the craniocervical arteries. Twenty-seven patients who were suspected to have steno-occlusive lesions in the craniocervical arteries underwent both TRMRA and brain single-photon emission computed tomography (SPECT). TRMRA was performed on the supra-aortic area after intravenous injection of a 0.03 mmol/kg gadolinium-based contrast agent. Time-to-peak (TTP) maps and CTD maps of the brain were automatically generated from TRMRA data, and their quality was assessed. Detection of perfusion abnormalities was compared between CTD maps and the time-series maximal intensity projection (MIP) images from TRMRA and TTP maps. Correlation coefficients between quantitative changes in SPECT and parametric maps for the abnormal perfusion areas were calculated. The CTD maps were of significantly superior quality than TTP maps (p < 0.01). For perfusion abnormality detection, CTD maps (kappa 0.84, 95% confidence interval [CI] 0.67-1.00) showed better agreement with SPECT than TTP maps (0.66, 0.46-0.85). For perfusion deficit detection, CTD maps showed higher accuracy (85.2%, 95% CI 66.3-95.8) than MIP images (66.7%, 46-83.5), with marginal significance (p = 0.07). In abnormal perfusion areas, correlation coefficients between SPECT and CTD (r = 0.74, 95% CI 0.34-0.91) were higher than those between SPECT and TTP (r = 0.66, 0.20-0.88). CTD maps generated from TRMRA were of high quality and offered good diagnostic performance for detecting perfusion abnormalities associated with steno-occlusive arterial lesions in the craniocervical area. • Generation of perfusion parametric maps from time-resolved MR angiography is clinically useful. • Correlation-based delay maps can be used to detect perfusion abnormalities associated with steno-occlusive craniocervical arteries. • Estimation of correlation-based delay is robust for low signal-to-noise 4D MR data.

Myelin water fraction (MWF) mapping with a multi-echo gradient echo (mGRE) sequence using complex-value based model fitting approach was recently described, in which the phase of the data plays an important role in the accuracy of the fitting results. Thus, influences coming from the undesirable phase components need to be reduced. Targeted for improved MWF mapping, methods to combat these phase related issues which include offset correction, main magnetic field (B0) inhomogeneity related correction, and flow compensation have been developed. For offset correction, a coil combine method with bipolar readout gradients has been devised. For B0 related artifact, a voxel spread function correction approach along with a navigator echo acquisition was utilized. Finally, flow compensation gradients were used to reduce the effects of flow from regions including the veins. The correction methods led to reduced residual fitting error and improved quality of the resultant MWF maps. Quantitative analysis shows increased reliability when the corrections were used. Data from normal volunteers showed improved MWF mapping with the integrated method developed in this work.

BACKGROUND AND PURPOSE To test whether nigrosome-1 imaging using high-resolution quantitative susceptibility mapping (QSM) combined with histogram analysis can improve the diagnostic accuracy in early-stage idiopathic Parkinson's disease (IPD) patients. METHODS Three-dimensional multiecho gradient-recalled echo images (0.5×0.5×1.0 mm³) were obtained at 3 T for QSM in 38 patients with IPD and 25 healthy subjects. To segment the substantia nigra (SN), regions of interest (ROIs) were semiautomatically drawn at the location below the red nucleus, and the normal-appearing nigrosome-1 was determined by manual correction. QSM histograms were obtained within the ROI. The segmented SN regions on the right and left that had higher mean susceptibility values and fewer voxels with susceptibility values lower than 60, 65, 70, 75, and 80 ppb were chosen for comparisons between the IPD patients and healthy subjects. These results were compared with those of the visual assessments of nigrosome-1 in susceptibility map-weighted imaging (SMWI) by analyzing receiver operating characteristics curves. RESULTS The proportion of voxels with susceptibility values lower than 70 ppb showed the best diagnostic performance, with its value differing significantly between the IPD patients (median=0, interquartile range=0-0.23) and healthy subjects (median=10.67, interquartile range=5.98-21.57) (p

Myelin, which consists of lipid bilayers, is one of the major constituents of white matter in the brain and has been suggested as a primary source of magnetic susceptibility contrasts. In this study, a new R 2 * model that simultaneously explains the effects of fiber orientation and myelin concentration is proposed and tested. In addition, a new approach that produces R 2 * maps without the effects of myelin is suggested. Experimental results demonstrate that the model reveals a high goodness of fit for the R 2 * distribution of white matter compared to a model that explains either fiber orientation or myelin concentration. The proposed R 2 * map shows a relatively uniform spatial distribution of R 2 * compared to the uncorrected R 2 * map and the fiber orientation or myelin concentration corrected R 2 * map.

In this study, the prevalence of abnormality in putative nigrosome 1 and nigrosome 4 (N1 and N4, respectively) was investigated in early versus late-stage idiopathic Parkinson's disease (IPD) patients. A total of 128 IPD patients (early stage[n = 89]; late stage[n = 39]) and 15 healthy subjects were scanned for high-resolution (0.5 × 0.5 × 1.0 mm3 ) multiecho gradient-recalled echo MRI and dopamine transporter PET imaging. The MRI data were processed for susceptibility map-weighted imaging (SMWI) to improve a contrast-to-noise ratio, and the images were resliced at 0.5 mm to define N1 and N4. When each side of N1 and N4 was assessed separately for the loss of hyperintensity by two independent reviewers, the consensus review results showed that in early-stage IPD (178 substantia nigras [SNs]), the loss of hyperintensity was observed more often in only the N1 region (65.2%) when compared to in both N1 and N4 regions (34.8%). In late-stage IPD (78 SNs), on the other hand, the loss in only the N1 region (25.6%) was less prevalent than in both N1 and N4 (74.4%) (P < 0.0001). Additionally, intact SNs (both in N1 and N4) were observed 17 SNs (9.6%) of the early-stage IPD patients, whereas it was not found in any SNs of the late-stage IPD patients (P = 0.005). Moreover, involvement of both N1 and N4 on both sides was found in 19.1% of the early-stage IPD patients, whereas its incidence was higher (61.5%) in the late-stage IPD patients (P < 0.0001), suggesting that the loss of hyperintensity in IPD progresses from N1 to N4 as the disease advances. Hum Brain Mapp 39:542-553, 2018. © 2017 Wiley Periodicals, Inc.

The purpose of this study was to investigate the differences in motor cortex susceptibility among patients with amyotrophic lateral sclerosis (ALS), cerebrovascular disease (CVD), and healthy controls using quantitative susceptibility mapping (QSM). We retrospectively reviewed 78 QSM images from 26 patients with ALS, 26 age- and sex-matched patients with CVD, and 26 healthy controls. A region of interest was drawn in the hand lobule of both the motor cortexes and subcortical white matter. The relative susceptibility (RS) of the motor cortex was obtained by subtracting the susceptibility of the subcortical white matter from that of the motor cortex. We compared the cortexmean, cortexmax, subcortical white mattermean, RSmean, and RSmax values among the three groups using analysis of variance and Tukey’s post hoc test. Receiver operating characteristic (ROC) curve analysis was also performed. There were significant differences in the cortexmean, cortexmax, RSmean, and RSmax among the three groups, with higher values in patients with ALS (p = 0.01, p = 0.004, p

BACKGROUND The liver is a central organ for the metabolism of iron and manganese and the places where those metals are commonly deposited overlap in the brain. PURPOSE/HYPOTHESIS To elucidate the relationship between pallidal T1 hyperintensity and iron deposition in the deep gray matter of liver cirrhosis patients using quantitative susceptibility mapping (QSM). STUDY TYPE Retrospective case–control study SUBJECTS: In all, 38 consecutive liver cirrhosis patients who received brain magnetic resonance imaging (MRI) as pretransplant evaluation. FIELD STRENGTH/SEQUENCE QSM was reconstructed from 3D multi- or single-echo phase images at 3T. T1-weighted images were used for the assessment of pallidal hyperintensity and pallidal index (PI). ASSESSMENT Patients were divided into two groups according to the presence of pallidal hyperintensity by consensus of two radiologists. Susceptibility values were acquired for five deep gray matter structures. STATISTICAL TEST QSM measures were compared between two groups using the t-test. We also calculated Pearson correlations between QSM measures and PI. RESULTS In all, 26 patients showed pallidal hyperintensity (T1h group) and 12 did not (T1n group). The susceptibility of the globus pallidus (GP) in the T1h group (120.6 ± 38.1 ppb) was significantly lower than that in the T1n group (150.0 ± 35.2, P = 0.030). The susceptibility of the dentate nucleus (DN) in the T1h group (88.1 ± 31.0) was significantly lower than that in the T1n group (125.6 ± 30.6, P = 0.001). Negative correlation between the susceptibility of GP (r = –0.37, P = 0.022) and the PI, and between DN (r = –0.43, P < 0.001) and the PI was found. DATA CONCLUSION Liver cirrhosis patients with pallidal T1 hyperintensity had lower susceptibility values in the GP and DN than those without it. This suggests a possible interaction between iron and manganese in the brains of liver cirrhosis patients. Level of Evidence: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017.

Recently, deep neural network-powered quantitative susceptibility mapping (QSM), QSMnet, successfully performed ill-conditioned dipole inversion in QSM and generated high-quality susceptibility maps. In this paper, the network, which was trained by healthy volunteer data, is evaluated for hemorrhagic lesions that have substantially higher susceptibility than healthy tissues in order to test “linearity” of QSMnet for susceptibility. The results show that QSMnet underestimates susceptibility in hemorrhagic lesions, revealing degraded linearity of the network for the untrained susceptibility range. To overcome this limitation, a data augmentation method is proposed to generalize the network for a wider range of susceptibility. The newly trained network, which is referred to as QSMnet+, is assessed in computer-simulated lesions with an extended susceptibility range (−1.4 ​ppm to +1.4 ​ppm) and also in twelve hemorrhagic patients. The simulation results demonstrate improved linearity of QSMnet+ over QSMnet (root mean square error of QSMnet+: 0.04 ​ppm vs. QSMnet: 0.36 ​ppm). When applied to patient data, QSMnet+ maps show less noticeable artifacts to those of conventional QSM maps. Moreover, the susceptibility values of QSMnet+ in hemorrhagic lesions are better matched to those of the conventional QSM method than those of QSMnet when analyzed using linear regression (QSMnet+: slope ​= ​1.05, intercept ​= ​−0.03, R2 ​= ​0.93; QSMnet: slope ​= ​0.68, intercept ​= ​0.06, R2 ​= ​0.86), consolidating improved linearity in QSMnet+. This study demonstrates the importance of the trained data range in deep neural network-powered parametric mapping and suggests the data augmentation approach for generalization of network. The new network can be applicable for a wide range of susceptibility quantification.

We investigated the narrow‐sense heritability of MRI‐visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138 monozygotic, 79 dizygotic twin pairs, and 133 nontwin sibling pairs; 28.7 ± 3.6 years) from the Human Connectome Project. dPVS volumes within basal ganglia (BGdPVS) and white matter (WMdPVS) were automatically calculated on three‐dimensional T2‐weighted MRI. In univariate analysis, heritability estimates of BGdPVS and WMdPVS after age and sex adjustment were 65.8% and 90.2%. In bivariate analysis, both BGdPVS and WMdPVS showed low to moderate genetic correlations (.30–.43) but high shared heritabilities (71.8–99.9%) with corresponding regional volumes, intracranial volumes, and other regional dPVS volumes. Older age was significantly associated with larger dPVS volume in both regions even after adjusting for clinical and volumetric variables, while blood pressure was not associated with dPVS volume although there was weak genetic correlation. dPVS volume, particularly WMdPVS, was highly heritable in healthy young adults, adding evidence of a substantial genetic contribution in dPVS development and differential effect by location. Age affects dPVS volume even in young adults, while blood pressure might have limited role in dPVS development in its normal range., dPVS volume, particularly WMdPVS, was highly heritable in healthy young adults, adding evidence of a substantial genetic contribution in dPVS development and differential effect by location.

Although age-related changes of cerebral arteries were observed in in vivo magnetic resonance angiography (MRA), standard tools or methods measuring those changes were limited. In this study, we developed and evaluated a model to measure age-related changes in the cerebral arteries from 3D MRA using a 3D deep convolutional neural network. From participants without any medical abnormality, training (n = 800) and validation sets (n = 88) of 3D MRA were built. After preprocessing and data augmentation, a 3D convolutional neural network was trained to estimate each subject's chronological age from in vivo MRA data. There was good correlation between chronological age and predicted age (r = 0.83) in an independent test set (n = 354). The predicted age difference (PAD) of the test set was 2.41 ± 6.22. Interaction term between age and sex was significant for PAD (p = 0.008). After correcting for age and interaction term, men showed higher PAD (p0.001). Hypertension was associated with higher PAD with marginal significance (p = 0.073). We suggested that PAD might be a potential measurement of cerebral vascular aging.

Background Predicting neurological outcomes after cardiac arrest is important to guide therapeutic decisions. We assessed the prognostic value of phase information of 2D T2*-weighted gradient echo imaging (T2*WI) of the brain in CA survivors. Methods This study included cardiac arrest survivors who had undergone MRI for prognostication. After application of homodyne filtering to T2*WI phase images, the contrast of three venous structures was assessed as normal (score 0) or abnormal (score 1): the superior sagittal sinus, the cortical veins, and the thalamostriate veins. The scores were summarized into a gradient-recalled echo (GRE) summary score. The prognostic performances of T2*WI, diffusion-weighted imaging (DWI), electroencephalography and serum biomarkers were evaluated using receiver operating characteristic (ROC) curves. Results Of the 39 enrolled patients, 12 (31%) had good outcomes and 27 (69%) had poor outcomes. ROC curve analysis showed that T2*WI had good prognostic performance; the area under the curve (AUC) of the GRE summary score (0.980, 95% confidence interval CI 0.950–1.000) was comparable to those of conventional outcome predictors, including DWI patterns (0.949, 95% CI 0.889–1.000). The AUC increased when the summary GRE score was added to DWI patterns (0.991, 95% CI 0.973–1.000), although the difference was not statistically significant (P = 0.117). Most subjects with isoelectric electroencephalography (5/6) showed abnormally high phase contrast in the cerebral veins. Conclusions Filtered phase images of T2*WI showed good prognostic value and can reveal various features of the cerebral metabolic consequences of cardiac arrest, such as decreased neuronal activity and brain death-like patterns.

ObjectivesThe extent of peritumoral tumor cell infiltrations in glioblastoma contributes to poor prognosis. We aimed to assess additive prognostic value of Minkowski functionals in analyzing heterogeneity of peritumoral hyperintensity on T2WI in glioblastoma patients.MethodsClinical data (age, sex, extent of surgical resection), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and pre-operative T2WI of 113 pathologically confirmed glioblastoma patients (from our institution, n = 61; from the Cancer Imaging Archive, n = 52) were retrospectively reviewed. The patients were randomly grouped into a training set (n = 80) and a test set (n = 33). Peritumoral T2 hyperintensity was manually segmented and Minkowski functionals-a texture analysis method capturing heterogeneity of MR images-were computed as a function of 11 grayscale thresholds. The Cox proportional hazards models were fitted with clinical variables, Minkowski functionals features as well as both combined. The risk prediction performances of the Minkowski functionals and combined models were validated on a separate test dataset. The sex-specific survival difference of the entire cohort was analyzed according to MGMT methylation status via Kaplan-Meier survival curves.ResultsThirty-three Minkowski features (11 area, 11 perimeter and 11 genus) for each patient were acquired giving a total of 3729 features. Cox regression models fitted with clinical data, Minkowski features, and both combined had incremental concordance indices of 0.577 (P = 0.02), 0.706 (P = 0.02) and 0.714 (P = 0.01) respectively. The prediction error rate of the combined model-having clinical and Minkowski features-was lower than that of Minkowski functionals model (0.135 and 0.161, respectively) when validated on a test dataset. No sex-specific survival difference was found according to MGMT methylation status (male, P = 0.2; female, P = 0.22).ConclusionsMinkowski functionals features computed from peritumoral hyperintensity can capture heterogeneity of glioblastoma on T2WI and have additive prognostic value in predicting survival, demonstrating their potential in complementing currently available prognostic parameters.

Objective To determine whether susceptibility map-weighted imaging (SMWI) was superior to conventional susceptibility-weighted imaging (SWI) in the diagnosis of Parkinson’s disease (PD) and in its correlation with 123I-2bcarbomethoxy-3b-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane single photon emission computerized tomography (123I-FP-CIT SPECT). Methods Between May 2017 and February 2018, 125 consecutive patients diagnosed with idiopathic PD, vascular pseudoparkinsonism, essential tremor, or drug-induced parkinsonism and who underwent 123I-FP-CIT SPECT imaging and 3 T SWI on the same day or within 3 months were included in this retrospective study. In all patients, SMWI images were generated from SWI images. On both MRIs, two neuroradiologists independently evaluated the status of nigral hyperintensity on each side of substantia nigra. Inter-observer agreements for the nigral hyperintensity were tested. Using consensus reading, concordance between SWI, SMWI, and 123I-FP-CIT SPECT were evaluated, and the diagnostic performance between SWI and SMWI for PD was compared. Results Inter-observer agreement for the nigral hyperintensity was higher for SMWI (right, κ = 0.919; left, κ = 0.984) than for SWI (right, κ = 0.918; left, κ = 0.902). SMWI (right 67.2 %, left 68.0 %) showed a higher concordance rate with the results of 123I-FP-CIT SPECT than SWI (right 60.0 %, left 59.2 %). SMWI (area under curve [AUC], 0.791) provided significantly higher diagnostic performance for PD than SWI (AUC, 0.720; P = 0.0005). Conclusion SMWI may be a superior assessment tool for nigral hyperintensity than SWI and may be an improved diagnostic imaging modality for patients with suspected PD.

Purpose To enhance the visibility of nigrosome 1 in substantia nigra, which has recently been suggested as an imaging biomarker for Parkinson's disease (PD) at 3T magnetic resonance imaging (MRI). Materials and Methods The substantia nigra structure was visualized at 3T MRI using multiecho susceptibility map-weighted imaging (SMWI) in 15 healthy volunteers and 6 patients with Parkinson's disease (PD). The visibility of nigrosome 1 was further enhanced by acquiring data in an oblique-coronal imaging plane at a high spatial resolution (0.5 × 0.5 × 1.0 mm3). To compare the visibility, the contrast-to-noise ratios (CNR) of the nigrosome 1 structure relative to the neighboring substantia nigra structure were evaluated in the SMWI and other conventional susceptibility contrast images (magnitude, frequency, quantitative susceptibility map [QSM] and susceptibility-weighted image). Results In healthy volunteers, the CNRs of the nigrosome 1 structure were 1.04 ± 0.38, 0.84 ± 0.32, 1.04 ± 0.40, 0.86 ± 0.41, and 1.45 ± 0.48 for magnitude, frequency, quantitative susceptibility map, susceptibility-weighted image, and SMWI, respectively. Compared to conventional susceptibility contrast images, the SMWI method significantly improved the CNR of nigrosome 1 (P = 0.014 for magnitude, P = 0.030 for QSM, and P < 0.001 for frequency and SWI, respectively). The magnetic susceptibility difference between nigrosome 1 and neighboring substantia nigra structures was 0.037 ± 0.016 ppm (measured in QSM, P < 0.001) in healthy volunteers. In the PD patients, the visibility of the nigrosome 1 structures was reduced. Conclusion The SMWI method enhances the visibility of nigrosome 1 structures at 3T MRI when compared to conventional susceptibility contrast images. Level of Evidence: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:528–536

Ultrasmallsuperparamagnetic iron oxide (USPIO) has been suggested to be a negative MR contrast agent to detect metastatic lymph nodes. Previously reported studies have evaluated the diagnostic performance of USPIO-enhanced MR lymph node imaging based on signal intensity. In this study, we investigate the specific performance of three different parametric approaches (normalized signal intensity, R2* and susceptibility) using 3D multi-echo gradient echo to quantify the USPIO particles in lymph nodes. Nine rabbits with VX2 tumor implants were scanned before and after USPIO injection. From 3D multi-echo GRE magnitude and phase data, we generated multi-echo combined T2*-weighted images, an R2* map, and a quantitative susceptibility map. Eighteen lymph nodes (nine reactive and nine metastatic) were evaluated and showed remarkable signal drops in the area of USPIO accumulation. On parametric analysis, the R2* difference before and after USPIO injection was significantly different (p

Purpose This study aimed to determine whether MR-based radiomics of glioblastoma can predict the isocitrate dehydrogenase-1 (IDH1) mutation status and compare predictive performances between manual and fully automatic deep-learning segmentations. Method Forty-five glioblastoma patients with pretreatment T2-weighted MRIs were retrospectively evaluated. Manual segmentations of glioblastoma and peri-tumoral edema were trained via a deep neural network (V-Net). An independent external cohort of 137 glioblastoma patients from the Cancer Imaging Archive was also included (test set 1, n = 46; test set 2, n = 91). Test set 1—without known IDH1 status—was used to calculate dice similarity coefficients (DSC) between the two segmentation methods (manual & V-Net). From test set 2, all-relevant radiomic features were selected via a random forest-based wrapper algorithm for IDH1 prediction. Receiver operating characteristics (ROC) curves with areas under the curve (AUC) were plotted as performance metrics for both methods. Results Among 136 patients (45 and 91 patients from our institution and test set 2, respectively), 17 patients (11.2 %) had IDH1 mutations. The mean DSC of test set 1 was 0.78 ± 0.14 (range, 0.34−0.94). A subset of 9 all-relevant features (8.4 %, 9/107) was selected. V-Net segmentation of the test set 2 yielded similar performance in predicting IDH1 mutation as compared to manual segmentation (V-Net AUC = 0.86 vs. manual AUC = 0.90). The optimal cut-point threshold of AUC yielded 86.8 % accuracy for manual segmentation and 75.8 % for V-Net segmentation. Conclusions V-Net showed robust segmentation capability of glioblastoma on T2-weighted MRI. All-relevant radiomics features from both segmentation methods yielded a similar performance in IDH1 prediction.

Numerous studies have suggested that quantitative susceptibility mapping (QSM) and transverse relaxation rates (To investigate the improvement of reproducibility of QSM andReproducibility study.Ten controls.3T/multiecho gradient echo sequence.Intrascan reproducibility of QSM andReproducibility was obtained by the square of voxel-wise correlation coefficients between scans. A paired t-test was performed for comparison between before and after the respiration correction and between QSM andBased on the ROI analysis, reproducibility increased after the respiration correction. Reproducibility in the white matter (11.89% increased in QSM and 23.38% inRespiration-induced error correction significantly improved reproducibility in QSM and4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

In MRI, physiological noise which originates from cardiac and respiratory functions can induce substantial errors in detecting small signals in the brain. In this work, we explored the effects of the physiological noise and their compensation methods in gradient-echo myelin water imaging (GRE-MWI). To reduce the cardiac function induced inflow noise, flow saturation RF pulses were applied to the inferior portion of the head, saturating inflow blood signals. For the respiratory function induced B0 fluctuation compensation, a navigator echo was acquired, and respiration induced phase errors were corrected during reconstruction. After the compensations, the resulting myelin water images show substantially improved image quality and reproducibility. These improvements confirm the importance and usefulness of the physiological noise compensations in GRE-MWI.

Purpose To determine the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted (DW) magnetic resonance imaging (MRI) parameters in predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients. Materials and methods Forty-six patients with stage II or III breast cancer underwent MRI including DW imaging with 10 b values before and after 2 cycles of NAC. Apparent diffusion coefficient (ADC) and IVIM parameters (D, D*, and f) were obtained using histogram analysis derived from whole-tumor volumes. After surgery, imaging parameters were compared with histopathologic responses using the Miller-Payne grading system. Results Before NAC, Dmean, D50, and D75 were higher in good responders than in minor responders (P ≤ 0.043). After NAC, ADCmean, ADC50, ADC75, Dmean, D25, D50, and D75 were higher in good responders (P ≤ 0.037). Skewness of ADC and D were lower in good responders after NAC (P ≤ 0.005). Most histogram metrics of posttreatment ADC and D had similar AUC values with reasonable accuracy for prediction of good response (AUC ≥ 0.7, P Conclusion D and ADC are useful for the prediction of response to NAC in breast cancer patients. Additional information is obtained by application of the IVIM model in DW imaging analysis and histogram analysis using whole-tumor volume data.

The liver is a central organ for the metabolism of iron and manganese and the places where those metals are commonly deposited overlap in the brain.To elucidate the relationship between pallidal TRetrospective case-control study SUBJECTS: In all, 38 consecutive liver cirrhosis patients who received brain magnetic resonance imaging (MRI) as pretransplant evaluation.QSM was reconstructed from 3D multi- or single-echo phase images at 3T. TPatients were divided into two groups according to the presence of pallidal hyperintensity by consensus of two radiologists. Susceptibility values were acquired for five deep gray matter structures.QSM measures were compared between two groups using the t-test. We also calculated Pearson correlations between QSM measures and PI.In all, 26 patients showed pallidal hyperintensity (TLiver cirrhosis patients with pallidal T3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1342-1349.

MR g-ratio, which measures the ratio of the aggregate volume of axons to that of fibers in a voxel, is a potential biomarker for white matter microstructures. In this study, a new approach for acquiring an in-vivo whole human brain g-ratio map is proposed. To estimate the g-ratio, myelin volume fraction and axonal volume fraction are acquired using multi-echo gradient echo myelin water imaging (GRE-MWI) and neurite orientation dispersion and density imaging (NODDI), respectively. In order to translate myelin water fraction measured in GRE-MWI into myelin volume fraction, a new scaling procedure is proposed and validated. This scaling approach utilizes geometric measures of myelin structure and, therefore, provides robustness over previous methods. The resulting g-ratio map reveals an expected range of g-ratios (0.71-0.85 in major fiber bundles) with a small inter-subject coefficient of variance (less than 2%). Additionally, a few fiber bundles (e.g. cortico-spinal tract and optic radiation) show different constituents of myelin volume fraction and axonal volume fraction, indicating potentials to utilize the measures for deciphering fiber tracking.

Myelin, which consists of lipid bilayers, is one of the major constituents of white matter in the brain and has been suggested as a primary source of magnetic susceptibility contrasts. In this study, a new R

Purpose: To develop and apply a method to measure in vivo electrical conductivity values using magnetic resonance imaging (MRI) in subjects with breast cancer. Materials and Methods: A recently developed technique named MREPT (MR electrical properties tomography) together with a novel coil combination process was used to quantify the conductivity values. The overall technique was validated using a phantom study. In addition, 90 subjects were imaged (50 subjects with previously biopsy-confirmed breast tumor and 40 normal subjects), which was approved by our institutional review board (IRB). A routine clinical protocol, specifically a T2-weighted FSE (fast spin echo) imaging data, was used for reconstruction of conductivity. Results: By employing the coil combination, the relative error in the conductivity map was reduced from � 70% to 10%. The average conductivity values in breast cancers regions (0.89 60.33S/m) was higher compared to parenchymal tissue (0.43 S/m, P < 0.0001) and fat (0.07 S/m, P < 0.00005) regions. Malignant cases (0.89 S/m, n= 30) showed increased conductivity compared to benign cases (0.56 S/m, n= 5) (P < 0.05). In addition, invasive cancers (0.96 S/m) showed higher mean conductivity compared to in situ cancers (0.57 S/m) (P < 0.0005). Conclusion: This study shows that conductivity mapping of breast cancers is feasible using a noninvasive in vivo MREPT technique combined with a coil combination process. The method may provide a tool in the MR diagnosis of breast cancer. J. MAGN. RESON. IMAGING 2014;00:000–000. T he dielectric properties of breast tissue, especially its electrical conductivity (denoted as r in units of Siemens/meter (S/m)), have long been investigated in vitro and in vivo using electrical impedance tomography (EIT) systems. 1–7 Findings have consistently shown that malignant breast cancers present elevated conductivity values when compared to normal tissue. The conductivities of malignant mammary samples are typically in the range of 0.8 � 1.4 S/ m, while those of normal tissue are between 0.1 � 0.2 S/m at a frequency of � 100 MHz. 3–5 The biological mechanism

Purpose To introduce macroscopic B0 field inhomogeneity-compensated volumetric R2* mapping method with a three-dimensional (3D) z-shim multi-echo acquisition. Methods The proposed z-shim sequence acquired conventional and z-shimmed echoes alternately with bipolar readout gradients. A constant-valued z-shim gradient was applied prior to each negative readout gradient lobe. A phase combination algorithm was also proposed based on this pulse sequence, which acquires a B0 inhomogeneity-compensated field map that was shown to play a critical role for accurate R2* mapping. A modified signal model based on recently suggested model for 3D acquisition was proposed for R2* quantification. Results To validate the performance of the proposed method, phantom and in vivo experiments were performed and compared with other methods. An increase in the range of field inhomogeneity correction was shown in the phantom results. For in vivo studies, the proposed method showed enhanced R2* map quality for the different subjects. Conclusion The proposed method improves R2* estimation, especially in the frontal and temporal regions. Magn Reson Med 73:1164–1170, 2015. © 2014 Wiley Periodicals, Inc.

Purpose On MR imaging, peritumoral T2 hyperintensity surrounding glioblastoma is known to contain tumor cell infiltrates, thus contributing to poor prognosis. This study aimed to determine the incremental prognostic value of radiomics on peritumoral T2 hyperintensity in pretreatment glioblastoma. Methods One hundred fourteen pathologically confirmed glioblastoma patients were retrospectively selected from March 2008 to May 2018 (our institution, n = 61; the Cancer Imaging Archive, n = 53). All patients were randomly divided into either training (n = 80) or test set (n = 34). Manually segmented peritumoral T2 hyperintensity yielded 106 radiomic features per patient. A random forest variable selection was used to select the most relevant radiomic features. Four Cox proportional hazards models were fitted with clinical features, clinical features with tumor/peritumoral volumes, radiomics, and all of them combined. Kaplan-Meier survival curves of the models were plotted with log-rank tests. All models were validated on a test set using prediction error curves over survival times. Results A random forest variable selection yielded five relevant features among the 106 radiomic features (two shape, two gray-level and one first order features). These radiomic features increased survival prediction accuracy when they were added onto clinical and tumor/peritumoral volumetric features (combined model, P = 0.011). On test set, the combined model showed lower mean survival prediction error rate (0.14) than clinical (0.191) or radiomic (0.178) model. Conclusions The clinical model with radiomic features demonstrated improved survival predictive performance than the model without radiomic features, thus suggesting incremental prognostic value of peritumoral radiomics as MR imaging biomarker in pretreatment glioblastoma.

Objective For localization of the motor cortex, seed-based resting-state functional MRI (rsfMRI) uses the contralateral motor cortex as a seed. However, research has shown that the location of the motor cortex could differ according to anatomical variations. The purpose of this study was to compare the results of rsfMRI using two seeds: a template seed (the anatomically expected location of the contralateral motor cortex) and a functional seed (the actual location of the contralateral motor cortex determined by task-based functional MRI [tbfMRI]). Materials and Methods Eight patients (4 with glioma, 3 with meningioma, and 1 with arteriovenous malformation) and 9 healthy volunteers participated. For the patients, tbfMRI was performed unilaterally to activate the healthy contralateral motor cortex. The affected ipsilateral motor cortices were mapped with rsfMRI using seed-based and independent component analysis (ICA). In the healthy volunteer group, both motor cortices were mapped with both-hands tbfMRI and rsfMRI. We compared the results between template and functional seeds, and between the seed-based analysis and ICA with visual and quantitative analysis. Results For the visual analysis, the functional seed showed significantly higher scores compared to the template seed in both the patients (p = 0.002) and healthy volunteers (p < 0.001). Although no significant difference was observed between the functional seed and ICA, the ICA results showed significantly higher scores than the template seed in both the patients (p = 0.01) and healthy volunteers (p = 0.005). In the quantitative analysis, the functional seed exhibited greater similarity to tbfMRI than the template seed and ICA. Conclusion Using the contralateral motor cortex determined by tbfMRI as a seed could enhance visual delineation of the motor cortex in seed-based rsfMRI.

Objective A developmental venous anomaly (DVA) is a vascular malformation of ambiguous clinical significance. We aimed to quantify the susceptibility of draining veins (χvein) in DVA and determine its significance with respect to oxygen metabolism using quantitative susceptibility mapping (QSM). Materials and Methods Brain magnetic resonance imaging of 27 consecutive patients with incidentally detected DVAs were retrospectively reviewed. Based on the presence of abnormal hyperintensity on T2-weighted images (T2WI) in the brain parenchyma adjacent to DVA, the patients were grouped into edema (E+, n = 9) and non-edema (E−, n = 18) groups. A 3T MR scanner was used to obtain fully flow-compensated gradient echo images for susceptibility-weighted imaging with source images used for QSM processing. The χvein was measured semi-automatically using QSM. The normalized χvein was also estimated. Clinical and MR measurements were compared between the E+ and E− groups using Student's t-test or Mann-Whitney U test. Correlations between the χvein and area of hyperintensity on T2WI and between χvein and diameter of the collecting veins were assessed. The correlation coefficient was also calculated using normalized veins. Results The DVAs of the E+ group had significantly higher χvein (196.5 ± 27.9 vs. 167.7 ± 33.6, p = 0.036) and larger diameter of the draining veins (p = 0.006), and patients were older (p = 0.006) than those in the E− group. The χvein was also linearly correlated with the hyperintense area on T2WI (r = 0.633, 95% confidence interval 0.333–0.817, p < 0.001). Conclusion DVAs with abnormal hyperintensity on T2WI have higher susceptibility values for draining veins, indicating an increased oxygen extraction fraction that might be associated with venous congestion.

Objective To compare apparent diffusion coefficients (ADCs) of brain segments by using two diffusion-weighted imaging acquisition modes, single-shot echo-planar imaging (ss-EPI) and read-out-segmented echo-planar imaging (rs-EPI), and to assess their correlation and agreement in healthy controls. Materials and Methods T2-weighted (T2W) images, rs-EPI, and ss-EPI of 30 healthy subjects were acquired using a 3T magnetic resonance scanner. The T2W images were co-registered to the rs-EPI and ss-EPI, which were then segmented into the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) to generate masking templates. ADC maps of rs-EPI and ss-EPI were also segmented into the GM, WM, and CSF by using the generated templates. ADCs of rs-EPI and ss-EPI were compared using Student's t tests and correlated using Pearson's correlation coefficients. Bland-Altman plots were used to assess the agreement between acquisitions. Results ADCs of rs-EPI and ss-EPI were significantly different in the GM (p < 0.001) and WM (p < 0.001). ADCs showed high agreement and correlation in the whole brain and CSF (r > 0.988; p < 0.001). ADC of the WM showed the least correlation (r = 0.894; p < 0.001), and ADCs of the WM and GM showed poor agreement. Pearson's correlation equations for each brain segment were y = 1.1x - 59.4 (GM), y = 1.45x - 255 (WM), and y = 0.98x - 63.5 (CSF), where x and y indicated ADCs of rs-EPI and ss-EPI, respectively. Conclusion While ADCs of rs-EPI and ss-EPI showed high correlation and agreement in the whole brain and CSF, ADCs of the WM and GM showed significant differences and large variability, reflecting brain parenchymal inhomogeneity due to different regional microenvironments. ADCs of different acquisition methods should be interpreted carefully, especially in intra-individual comparisons.

Purpose To introduce novel acquisition and postprocessing approaches for susceptibility weighted imaging (SWI) to remove background field inhomogeneity artifacts in both magnitude and phase data. Methods The proposed method acquires three echoes in a three-dimensional gradient echo (GRE) sequence, with a field compensation gradient (z-shim gradient) applied to the third echo. The artifacts in the magnitude data are compensated by signal estimation from all three echoes. The artifacts in phase signals are removed by modeling the background phase distortions using Gaussians. The method was applied in vivo and compared with conventional SWI. Results The method successfully compensates for background field inhomogeneity artifacts in magnitude and phase images, and demonstrated improved SWI images. In particular, vessels in frontal lobe, which were not observed in conventional SWI, were identified in the proposed method. Conclusion The new method improves image quality in SWI by restoring signal in the frontal and temporal regions. Magn Reson Med 72:452–458, 2014. © 2013 Wiley Periodicals, Inc.

Objectives: The objective of this study was to develop a computer-aided detection system for automated brain metastases detection using magnetic resonance black-blood imaging and compare its applicability with conventional magnetization-prepared rapid gradient echo (MP-RAGE) imaging. Materials and Methods: Twenty-six patients with brain metastases were imaged with a contrast-enhanced, 3-dimensional, whole-brain magnetic resonance black-blood pulse sequence. Approval from the institutional review board and informed consent from the patients were obtained. Preprocessing steps included B1 inhomogeneity correction and brain extraction. The computer-aided detection system used 3-dimensional template matching, which measured normalized cross-correlation coefficient to generate possible metastases candidates. An artificial neural network was used for classification after various volume features were extracted. The same detection procedure was tested with contrast-enhanced MP-RAGE, which was also acquired from the same patients. Results: The performance of the proposed detection method was measured by the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity values. In the black-blood case, detection process displayed an AUROC of 0.9355, a sensitivity value of 81.1%, and a specificity value of 98.2%. Magnetization-prepared rapid gradient echo data showed an AUROC of 0.6508, a sensitivity value of 30.2%, and a specificity value of 99.97%. Conclusions: The results demonstrate that accurate automated detection of metastatic brain tumors using contrast-enhanced black-blood imaging sequence is possible compared with using conventional contrast-enhanced MPRAGE sequence.

Accurate quantification of R₂(*) (=1/T₂(*)) is important for many applications in neuroimaging. However, R₂(*) measurements made using conventional multi-echo gradient echo imaging are hampered by macroscopic field inhomogeneities. Several methods for compensation of macroscopic field inhomogeneities have been introduced, most of them requiring increased scan time. In this paper, an R₂(*) estimation process using a modified multi-echo gradient echo sequence that includes bipolar compensation gradients and does not require additional data acquisition time is proposed. A post-processing algorithm based on an excitation-profile weighted signal model is used. The optimal amount of compensation gradients and performance was investigated by numerical simulation and phantom tests. Multi-slice R₂(*) maps were obtained from 11 human volunteers at 3T. Simulation results demonstrated that this method successfully removes the effects of macroscopic field inhomogeneities of up to ± 300μT/m within an error range of ± 8%. ROI analysis revealed R₂(*) values of 30.4 ± 3.0s⁻¹ (substantia nigra), 25.8 ± 2.7s⁻¹ (red nuclei), 23.2 ± 1.0s⁻¹ (genu), 20.8 ± 1.2s⁻¹ (putamen), 34.2 ± 3.4s⁻¹ (globus pallidus), and 21.8 ± 1.4s⁻¹ (splenium) using the proposed method, with statistically significant differences compared to conventional method in the regions of the substantia nigra, red nucleus, genu, putamen, and globus pallidus (p

To enhance the visibility of nigrosome 1 in substantia nigra, which has recently been suggested as an imaging biomarker for Parkinson's disease (PD) at 3T magnetic resonance imaging (MRI).The substantia nigra structure was visualized at 3T MRI using multiecho susceptibility map-weighted imaging (SMWI) in 15 healthy volunteers and 6 patients with Parkinson's disease (PD). The visibility of nigrosome 1 was further enhanced by acquiring data in an oblique-coronal imaging plane at a high spatial resolution (0.5 × 0.5 × 1.0 mmIn healthy volunteers, the CNRs of the nigrosome 1 structure were 1.04 ± 0.38, 0.84 ± 0.32, 1.04 ± 0.40, 0.86 ± 0.41, and 1.45 ± 0.48 for magnitude, frequency, quantitative susceptibility map, susceptibility-weighted image, and SMWI, respectively. Compared to conventional susceptibility contrast images, the SMWI method significantly improved the CNR of nigrosome 1 (P = 0.014 for magnitude, P = 0.030 for QSM, and P0.001 for frequency and SWI, respectively). The magnetic susceptibility difference between nigrosome 1 and neighboring substantia nigra structures was 0.037 ± 0.016 ppm (measured in QSM, P0.001) in healthy volunteers. In the PD patients, the visibility of the nigrosome 1 structures was reduced.The SMWI method enhances the visibility of nigrosome 1 structures at 3T MRI when compared to conventional susceptibility contrast images.3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:528-536.

Ultrasmallsuperparamagnetic iron oxide (USPIO) has been suggested to be a negative MR contrast agent to detect metastatic lymph nodes. Previously reported studies have evaluated the diagnostic performance of USPIO-enhanced MR lymph node imaging based on signal intensity. In this study, we investigate the specific performance of three different parametric approaches (normalized signal intensity, R

Purpose: To improve the mapping of myelin water fraction (MWF) despite the presence of measurement noise, and to increase the visibility of fine structures in MWF maps. Materials and Methods: An anisotropic diffusion filter (ADF) was effectively combined with a spatially regularized nonnegative least squares algorithm (srNNLS) for robust MWF mapping. Synthetic data simulations were performed to assess the effectiveness of this new method. Experimental measurements of signal decay curves were obtained and MWF maps were estimated using the new method and compared with maps estimated using other methods. Results: MWF mapping was substantially improved in both simulations and experimental data when ADF was combined with the srNNLS algorithm. MWF variability decreased with the use of the proposed method, which in turn resulted in increased visibility of small focal lesions and structures in the MWF maps. Conclusion: This study demonstrates that the benefits of ADF and srNNLS algorithms can be effectively combined in a synergic way for robust mapping of MWF in the presence of noise. Substantial improvements to MWF mapping can be made using the proposed method. J. Magn. Reson. Imaging 2011;. © 2011 Wiley-Liss, Inc.

The double inversion recovery (DIR) imaging technique has various applications such as black blood magnetic resonance imaging and gray/white matter imaging. Recent clinical studies show the promise of DIR for high resolution three dimensional (3D) gray matter imaging. One drawback in this case however is the long data acquisition time needed to obtain the fully sampled 3D spatial frequency domain (k-space) data. In this paper, we propose a method to solve this problem using the compressed sensing (CS) algorithm with contourlet transform. The contourlet transform is an effective sparsifying transform especially for images with smooth contours. Therefore, we applied this algorithm to undersampled DIR images and compared with a CS algorithm using wavelet transform by evaluating the reconstruction performance of each algorithm for undersampled k-space data. The results show that the proposed CS algorithm achieves a more accurate reconstruction in terms of the mean structural similarity index and root mean square error than the CS algorithm using wavelet transform.

Objective To determine the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and DCE ultrasound (DCE-US) for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients. Materials and Methods This Institutional Review Board-approved prospective study was performed between 2014 and 2016. Thirty-nine women with breast cancer underwent DCE-US and DCE-MRI before the NAC, follow-up DCE-US after the first cycle of NAC, and follow-up DCE-MRI after the second cycle of NAC. DCE-MRI parameters (transfer constant [Ktrans], reverse constant [kep], and leakage space [Ve]) were assessed with histograms. From DCE-US, peak-enhancement, the area under the curve, wash-in rate, wash-out rate, time to peak, and rise time (RT) were obtained. After surgery, all the imaging parameters and their changes were compared with histopathologic response using the Miller-Payne Grading (MPG) system. Data from minor and good responders were compared using Wilcoxon rank sum test, chi-square test, or Fisher's exact test. Receiver operating characteristic curve analysis was used for assessing diagnostic performance to predict good response. Results Twelve patients (30.8%) showed a good response (MPG 4 or 5) and 27 (69.2%) showed a minor response (MPG 1–3). The mean, 25th, 50th, and 75th percentiles of Ktrans and Kep of post-NAC DCE-MRI differed between the two groups. These parameters showed fair to good diagnostic performance for the prediction of response to NAC (AUC 0.76–0.81, p ≤ 0.007). Among DCE-US parameters, the percentage change in RT showed fair prediction (AUC 0.71, p = 0.023). Conclusion Quantitative analysis of DCE-MRI and DCE-US was helpful for early prediction of response to NAC.

In MRI, structurally aligned molecular or micro-organization (e.g. axonal fibers) can be a source of substantial signal variations that depend on the structural orientation and the applied magnetic field. This signal anisotropy gives us a unique opportunity to explore information that exists at a resolution several orders of magnitude smaller than that of typical MRI. In this review, one of the signal anisotropies, T

In gradient echo (GRE) imaging, three compartment water modeling (myelin water, axonal water and extracellular water) in white matter has been demonstrated to show different frequency shifts that depend on the relative orientation of fibers and the B0 field. This finding suggests that in GRE-based myelin water imaging, a signal model may need to incorporate frequency offset terms and become a complex-valued model. In the current study, three different signal models and fitting approaches (a magnitude model fitted to magnitude data, a complex model fitted to magnitude data, and a complex model fitted to complex data) were investigated to address the reliability of each model in the estimation of the myelin water signal. For the complex model fitted to complex data, a new fitting approach that does not require background phase removal was proposed. When the three models were compared, the results from the new complex model fitting showed the most stable parameter estimation.

In vivo optogenetics provides unique, powerful capabilities in the dissection of neural circuits implicated in neuropsychiatric disorders. Conventional hardware for such studies, however, physically tethers the experimental animal to an external light source, limiting the range of possible experiments. Emerging wireless options offer important capabilities that avoid some of these limitations, but the current size, bulk, weight, and wireless area of coverage is often disadvantageous. Here, we present a simple but powerful setup based on wireless, near-field power transfer and miniaturized, thin, flexible optoelectronic implants, for complete optical control in a variety of behavioral paradigms. The devices combine subdermal magnetic coil antennas connected to microscale, injectable light-emitting diodes (LEDs), with the ability to operate at wavelengths ranging from UV to blue, green-yellow, and red. An external loop antenna allows robust, straightforward application in a multitude of behavioral apparatuses. The result is a readily mass-producible, user-friendly technology with broad potential for optogenetics applications.

To develop and apply a method to measure in vivo electrical conductivity values using magnetic resonance imaging (MRI) in subjects with breast cancer.A recently developed technique named MREPT (MR electrical properties tomography) together with a novel coil combination process was used to quantify the conductivity values. The overall technique was validated using a phantom study. In addition, 90 subjects were imaged (50 subjects with previously biopsy-confirmed breast tumor and 40 normal subjects), which was approved by our institutional review board (IRB). A routine clinical protocol, specifically a T2 -weighted FSE (fast spin echo) imaging data, was used for reconstruction of conductivity.By employing the coil combination, the relative error in the conductivity map was reduced from ~70% to 10%. The average conductivity values in breast cancers regions (0.89 ± 0.33S/m) was higher compared to parenchymal tissue (0.43 S/m, P0.0001) and fat (0.07 S/m, P0.00005) regions. Malignant cases (0.89 S/m, n = 30) showed increased conductivity compared to benign cases (0.56 S/m, n = 5) (P0.05). In addition, invasive cancers (0.96 S/m) showed higher mean conductivity compared to in situ cancers (0.57 S/m) (P0.0005).This study shows that conductivity mapping of breast cancers is feasible using a noninvasive in vivo MREPT technique combined with a coil combination process. The method may provide a tool in the MR diagnosis of breast cancer.

Recently, Social Network Service market is getting bigger and bigger. Then there are many security threats by malicious users. In addition, because sensitive data is concentrated on the central server, privacy can be exposed to SNS provider as well as malicious users. To overcome this problem, many previous researches suggest decentralized systems for SNS. In these systems, sensitive data may not be stored in central server. When a user transmits a message, the server does not interfere with the process. Thus, the user who transmits a message needs way to manage the keys that are used for message encryption scheme. In this paper, we suggest the efficient key management scheme using Dynamic Identity-Based Broadcast Encryption. Using this scheme, it is possible to communicate securely between users in decentralized social network.