Glymphatic System Dysfunction in Myelin Oligodendrocyte Glycoprotein Immunoglobulin G Antibody-Associated Disorders: Association with Clinical Disability.

BACKGROUND AND PURPOSE: Impaired glymphatic function has been suggested to be implicated in the pathophysiology of MS and aquaporin-4 immunoglobulin G-positive neuromyelitis optica spectrum disorder. This study aimed to investigate the interstitial fluid dynamics in the brain in patients with myelin oligodendrocyte glycoprotein antibody disorders (MOGAD), another demyelinating disorder, using a noninvasive imaging technique called the diffusivity along the perivascular space (ALPS) index. MATERIALS AND METHODS: A prospective study was conducted on 16 patients with MOGAD in remission and 22 age- and sex-matched healthy control subjects. MR imaging was performed using a 3T scanner, and the ALPS index was calculated using diffusion MR imaging data with a b-value of 1000 s/mm2. The ALPS index and gray matter volumes were compared between the 2 groups, and these parameters were correlated with the Expanded Disability Status Scale. RESULTS: The mean ALPS index of patients with MOGAD was significantly lower than that of healthy controls (Cohen d = 0.93, false discovery rate-corrected P = .02). The lower mean ALPS index was significantly associated with a worse Expanded Disability Status Scale score (Spearman ρ = -0.51; 95% CI, -0.85 to -0.02; P = .03). However, cortical volume and deep gray matter volume were not significantly different between the 2 groups, and they were not correlated with the Expanded Disability Status Scale. CONCLUSIONS: This study suggests that patients with MOGAD may have impaired glymphatic function, as measured by the ALPS index, which is associated with patient disability. Further study is warranted with a larger sample size.

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. PURPOSE: We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters. STUDY TYPE: Retrospective. SUBJECTS: The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing. FIELD STRENGTH/SEQUENCE: Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence. ASSESSMENT: An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index. RESULTS: Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions. CONCLUSION: This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Investigation of time-dependent diffusion in extra-axial brain tumors using oscillating-gradient spin-echo.

Oscillating gradient spin-echo (OGSE) sequences provide access to short diffusion times and may provide insight into micro-scale internal structures of pathologic lesions based on an analysis of changes in diffusivity with differing diffusion times. We hypothesized that changes in diffusivity acquired with a shorter diffusion time may permit elucidation of properties related to the internal structure of extra-axial brain tumors. This study aimed to investigate the utility of changes in diffusivity between short and long diffusion times for characterizing extra-axial brain tumors. In total, 12 patients with meningothelial meningiomas, 13 patients with acoustic neuromas, and 11 patients with pituitary adenomas were scanned with a 3 T magnetic resonance imaging (MRI) scanner with diffusion-weighted imaging (DWI) using OGSE and pulsed gradient spin-echo (PGSE) (effective diffusion times [Δeff]: 6.5 ms and 35.2 ms) with b-values of 0 and 1000 s/mm2. Relative percentage changes between shorter and longer diffusion times were calculated using region-of-interest (ROI) analysis of brain tumors on λ1, λ2, λ3, and mean diffusivity (MD) maps. The diffusivities of PGSE, OGSE, and relative percentage changes were compared among each tumor type using a multiple comparisons Steel-Dwass test. The mean (standard deviation) MD at Δeff of 6.5 ms was 1.07 ± 0.23 10-3 mm2/s, 1.19 ± 0.18 10-3 mm2/s, 1.19 ± 0.21 10-3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) MD at Δeff of 35.2 ms was 0.93 ± 0.22 10-3 mm2/s, 1.07 ± 0.19 10-3 mm2/s, 0.82 ± 0.21 10-3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) of the relative percentage change was 15.7 ± 4.4%, 12.4 ± 8.2%, 46.8 ± 11.3% for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. Compared to meningiomas and acoustic neuromas, pituitary adenoma exhibited stronger diffusion time-dependence with diffusion times between 6.5 ms and 35.2 ms (P < 0.05). In conclusion, differences in diffusion time-dependence may be attributed to differences in the internal structures of brain tumors. DWI with a short diffusion time may provide additional information on the microstructure of each tumor and contribute to tumor diagnosis.

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord.

Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI.This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.

Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics.

PURPOSE: We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS: We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS: MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION: These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.

Time-dependent Diffusion in Brain Abscesses Investigated with Oscillating-gradient Spin-echo.

Oscillating-gradient spin-echo sequences enable the measurement of diffusion weighting with a short diffusion time and can provide indications of internal structures. We report two cases of brain abscess in which the apparent diffusion coefficient (ADC) values appear higher at short diffusion times in comparison with those at long diffusion times. Diffusion time dependence of the ADC in brain abscesses suggests not only substrate viscosity but also restricted diffusion due to the structure within the lesions.

Time-dependent Diffusion in Transient Splenial Lesion: Comparison between Oscillating-gradient Spin-echo Measurements and Monte-Carlo Simulation.

The microstructural underpinnings of reduced diffusivity in transient splenial lesion remain unclear. Here, we report findings from oscillating gradient spin-echo (OGSE) diffusion imaging in a case of transient splenial lesion. Compared with normal-appearing white matter, the splenial lesion exhibited greater differences between diffusion time t = 6.5 and 35.2 ms, indicating microstructural changes occurring within the corresponding length scale. We also conducted 2D Monte-Carlo simulation. The results suggested that emergence of small and non-exchanging compartment, as often imagined in intramyelinic edema, does not fit well with the in vivo observation. Simulations with axonal swelling and microglial infiltration yielded results closer to the in vivo observations. The present report exemplifies the importance of controlling t for more specific radiological image interpretations.

Differentiation of high-grade and low-grade intra-axial brain tumors by time-dependent diffusion MRI.

INTRODUCTION: Oscillating gradient spin-echo (OGSE) sequences enable acquisitions with shorter diffusion times. There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) values in patients with cancer. However, little evidence exists regarding its usefulness for differentiating between high-grade and low-grade brain tumors. The purpose of this study is to investigate the utility of changes in the ADC value between short and long diffusion times in distinguishing low-grade and high-grade brain tumors. MATERIAL AND METHODS: Eleven patients with high-grade brain tumors and ten patients with low-grade brain tumors were scanned using a 3 T magnetic resonance imaging with diffusion-weighted imaging (DWI) using OGSE and PGSE (effective diffusion time [Δeff]: 6.5 ms and 35.2 ms) and b-values of 0 and 1000 s/mm2. Using a region of interest (ROI) analysis of the brain tumors, we measured the ADC for two Δeff (ADCΔeff) values and computed the subtraction ADC (ΔADC = ADC6.5 ms - ADC35.2 ms) and the relative ADC (ΔADC = (ADC6.5 ms - ADC35.2 ms) / ADC35.2 ms × 100). The maximum values for the subtraction ADC (ΔADCmax) and the relative ADC (rADCmax) on the ROI were compared between low-grade and high-grade tumors using the Wilcoxon rank-sum test. A P-value <.05 was considered significant. The ROIs were also placed in the normal white matter of patients with high- and low-grade brain tumors, and ΔADCmax values were determined. RESULTS: High-grade tumors had significantly higher ΔADCmax and rADCmax than low-grade tumors. The ΔADCmax values of the normal white matter were lower than the ΔADCmax of high- and low-grade brain tumors. CONCLUSION: The dependence of ADC values on diffusion time between 6.5 ms and 35.2 ms was stronger in high-grade tumors than in low-grade tumors, suggesting differences in internal tissue structure. This finding highlights the importance of reporting diffusion times in ADC evaluations and might contribute to the grading of brain tumors using DWI.

Myelin Measurement Using Quantitative Magnetic Resonance Imaging: A Correlation Study Comparing Various Imaging Techniques in Patients with Multiple Sclerosis.

Evaluation of myelin by magnetic resonance imaging (MRI) is a difficult challenge, but holds promise in demyelinating diseases, such as multiple sclerosis (MS). Although multiple techniques have been developed, no gold standard has been established. This study aims to evaluate the correlation between synthetic MRI myelin volume fraction (SyMRIMVF) and myelin fraction estimated by other techniques, i.e., magnetization transfer saturation (MTsat), T1-weighted images divided by T2-weighted images (T1w/T2w), and radial diffusivity (RD) in patients with MS. We also compared the sensitivities of these techniques for detecting MS-related myelin damage. SyMRIMVF, MTsat, T1w/T2w, and RD were averaged on plaque, periplaque white matter, and normal-appearing white matter (NAWM). Pairwise correlation was calculated using Spearman's correlation analysis. For all segmented regions, strong correlations were found between SyMRIMVF and T1w/T2w (Rho = 0.89), MTsat (Rho = 0.82), or RD (Rho = -0.75). For each technique, the average estimated myelin differed significantly among regions, but the percentage change of NAWM from both periplaque white matter and plaque were highest in SyMRIMVF. SyMRIMVF might be suitable for myelin evaluation in MS patients, with relevant results as compared to other well-studied techniques. Moreover, it presented better sensitivity for the detection of the difference between plaque or periplaque white matter and NAWM.

A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning have been conducted. The aim of this study was to differentiate iNPH and AD using a residual extraction approach in the deep learning method. METHODS: Twenty-three patients with iNPH, 23 patients with AD and 23 healthy controls were included in this study. All patients and volunteers underwent brain MRI with a 3T unit, and we used only whole-brain three-dimensional (3D) T1-weighted images. We designed a fully automated, end-to-end 3D deep learning classifier to differentiate iNPH, AD and control. We evaluated the performance of our model using a leave-one-out cross-validation test. We also evaluated the validity of the result by visualizing important areas in the process of differentiating AD and iNPH on the original input image using the Gradient-weighted Class Activation Mapping (Grad-CAM) technique. RESULTS: Twenty-one out of 23 iNPH cases, 19 out of 23 AD cases and 22 out of 23 controls were correctly diagnosed. The accuracy was 0.90. In the Grad-CAM heat map, brain parenchyma surrounding the lateral ventricle was highlighted in about half of the iNPH cases that were successfully diagnosed. The medial temporal lobe or inferior horn of the lateral ventricle was highlighted in many successfully diagnosed cases of AD. About half of the successful cases showed nonspecific heat maps. CONCLUSION: Residual extraction approach in a deep learning method achieved a high accuracy for the differential diagnosis of iNPH, AD, and healthy controls trained with a small number of cases.

Signal Intensity within Cerebral Venous Sinuses on Synthetic MRI.

PURPOSE: Flowing blood sometimes appears bright on synthetic T1-weighted images, which could be misdiagnosed as a thrombus. This study aimed to investigate the frequency of hyperintensity within cerebral venous sinuses on synthetic MR images and to evaluate the influence of increasing flow rates on signal intensity using a flow phantom. MATERIALS AND METHODS: Imaging data, including synthetic and conventional MRI scans, from 22 patients were retrospectively analyzed. Signal intensities at eight locations of cerebral venous sinuses on synthetic images were graded using the following three-point scale: 0, "dark vessel"; 1, "hyperintensity within the walls"; and 2, "hyperintensity within the lumen." A phantom with gadolinium solution inside a U-shaped tube was acquired without flow and then with increasing flow rates (60, 100, 200, 300, 400 ml/min). RESULTS: Considering all sinus locations, the venous signal intensity on synthetic T1-weighted images was graded as 2 in 79.8% of the patients. On synthetic T2-weighted images, all sinuses were graded as 0. On fluid-attenuated inversion recovery (FLAIR) images, sinuses were almost always graded as 0 (99.4%). In the phantom study, the signal initially became brighter on synthetic T1-weighted images as the flow rate increased. Above a certain flow rate, the signal started to decrease. CONCLUSION: High signal intensity within the cerebral venous sinuses is a frequent finding on synthetic T1-weighted images. This corresponds to the hyperintensity noted at certain flow rates in the phantom experiment.

Three-dimensional high-resolution simultaneous quantitative mapping of the whole brain with 3D-QALAS: An accuracy and repeatability study.

BACKGROUND: Previous methods for the quantification of brain tissue properties by magnetic resonance imaging were mainly based on two-dimensional acquisitions and were thus limited to a relatively low resolution in the slice direction compared to three-dimensional (3D) acquisitions. The 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence may allow for simultaneous acquisition of relaxometry parameters in high spatial resolution. PURPOSE: To evaluate bias, linearity, and day-to-day repeatability of relaxometry parameters, as well as tissue fraction maps, acquired with 3D-QALAS. MATERIALS AND METHODS: Scan-rescan test of the 3D-QALAS sequence was performed on a 1.5-T scanner with the International Society for Magnetic Resonance in Medicine/National institute of Standards and Technology system phantom and 10 healthy volunteers (7 male, 3 female; mean age, 23.2 ±â€¯3.6 years). Simple linear regression analysis, Bland-Altman plots, and intrasubject coefficients of variation (CV) were used to assess the reliability of 3D-QALAS sequence-derived parameters. The T1, T2, proton density (PD), and myelin volume fraction (MVF) of in vivo brain regions were compared with values obtained using the multidynamic multi-echo sequence. RESULTS: In the phantom study, the T1, T2, and PD values measured by 3D-QALAS showed strong linearity with the reference values (R2 = 0.998, 0.998, and 0.960 for T1, T2, and PD, respectively) and high repeatability (mean CV of 1.2%, 2.8%, and 2.9% for T1, T2, and PD, respectively). The T1, T2, PD, and MVF values of in vivo brain regions obtained with 3D-QALAS were highly consistent within subjects, with mean intrasubject CVs of 0.5%, 0.5%, 0.4%, and 1.6% for the T1, T2, PD, and MVF values, respectively. CONCLUSION: 3D-QALAS enables reliable measurement of T1, T2, PD, and MVF values of the whole brain in high spatial resolution across a clinically-relevant dynamic range.

Aberrant myelination in patients with Sturge-Weber syndrome analyzed using synthetic quantitative magnetic resonance imaging.

PURPOSE: Accelerated myelination in the affected hemisphere has been demonstrated previously in patients with Sturge-Weber syndrome (SWS). This prospective study investigated myelin-related changes in patients with unilateral SWS using synthetic quantitative magnetic resonance imaging (qMRI). METHODS: Fourteen children with unilateral SWS were categorized according to age, i.e., ≤ 2 years (group A, n = 5, mean age 1.1 years, 3 males) and > 2 years (group B, n = 9, mean age 3.9 years, 4 males). All children underwent two-dimensional synthetic qMRI. The myelin volume in the cerebral hemisphere and white matter (WM) myelin volume fraction (MVF), proton density (PD), R1 and R2 relaxation rates ipsilateral to the leptomeningeal enhancement, and/or a port-wine birthmark were compared with the corresponding values in the contralateral hemisphere. RESULTS: In group A, 3 patients had a higher myelin volume in the ipsilateral hemisphere and a higher MVF, R1, and R2 and lower PD in the ipsilateral WM than on the contralateral side; the findings were the opposite in the remaining two patients. All patients in group B had a significantly lower myelin volume in the ipsilateral hemisphere (P < 0.05) and a lower MVF and R1 and higher PD in the ipsilateral WM than on the contralateral side (P < 0.0125). CONCLUSION: Higher estimated myelin was observed on the ipsilateral side in some patients aged ≤ 2 years and lower myelin on the ipsilateral side in all older patients. Synthetic qMRI might be useful for showing myelin-related abnormalities in SWS.

Brain tissue and myelin volumetric analysis in multiple sclerosis at 3T MRI with various in-plane resolutions using synthetic MRI.

PURPOSE: Synthetic MRI (SyMRI) enables automatic brain tissue and myelin volumetry based on the quantification of R1 and R2 relaxation rates and proton density. This study aimed to determine the validity of SyMRI brain tissue and myelin volumetry using various in-plane resolutions at 3T in patients with multiple sclerosis (MS). METHODS: We scanned 19 MS patients and 10 healthy age- and gender-matched controls using a 3T MR scanner with in-plane resolutions of 0.8, 1.8, and 3.6 mm. The acquisition times were 5 min 8 s, 2 min 52 s, and 2 min 1 s, respectively. White matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and myelin and non-WM/GM/CSF (NoN) volumes; brain parenchymal volume (BPV); and intracranial volume (ICV) were compared between different in-plane resolutions. These parameters were also compared between both groups, after ICV normalization. RESULTS: No significant differences in measured volumes were noted between the 0.8 and 1.8 mm in-plane resolutions, except in NoN and CSF for healthy controls and NoN for MS patients. Meanwhile, significant volumetric differences were noted in most brain tissues when compared between the 3.6 and 0.8 or 1.8 mm resolution for both healthy controls and MS patients. The normalized WM volume, myelin volume, and BPV showed significant differences between controls and MS patients at in-plane resolutions of 0.8 and 1.8 mm. CONCLUSIONS: SyMRI brain tissue and myelin volumetry with in-plane resolution as low as 1.8 mm can be useful in the evaluation of MS with a short acquisition time of < 3 min.

White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging.

PURPOSE: Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales. METHODS: Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm2). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined. RESULTS: The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social-emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi. CONCLUSIONS: Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.

3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T1 -weighted images.

BACKGROUND: Previous quantitative synthetic MRI of the brain has been solely performed in 2D. PURPOSE: To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis. STUDY TYPE: Reproducibility/repeatability study. SUBJECTS: Twenty-one healthy volunteers (35.6 ± 13.8 years). FIELD STRENGTH/SEQUENCE: 3D T1 -weighted fast spoiled gradient recalled echo (FSPGR) sequence was performed once, and 3D-QALAS sequence was performed twice with a 3T scanner. ASSESSMENT: FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS. STATISTICAL TESTS: Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements. RESULTS: Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. DATA CONCLUSION: 3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.

Review of synthetic MRI in pediatric brains: Basic principle of MR quantification, its features, clinical applications, and limitations.

Quantitative magnetic resonance imaging (MRI) with multislice, multi-echo, and multi-delay acquisition enables simultaneous quantification of R1 and R2 relaxation rates, proton density, and the B1 field in a single acquisition, and requires only about 6 minutes for full-head coverage. Using dedicated SyMRI software, radiologists can generate any contrast-weighted image by manipulating the acquisition parameters, including repetition time, echo time, and inversion time. Moreover, automatic brain tissue segmentation, volumetry, and myelin measurement can also be performed. Using the SyMRI approach, a shorter scan time, an objective examination, and personalized MR imaging parameters can be obtained in daily clinical pediatric imaging. Here we summarize and review the use of SyMRI in imaging of the pediatric brain, including the basic principles of MR quantification along with its features, clinical applications, and limitations.

Estimation of Gadolinium-based Contrast Agent Concentration Using Quantitative Synthetic MRI and Its Application to Brain Metastases: A Feasibility Study.

PURPOSE: Gadolinium-based contrast agents (GBCA) provide valuable information for assessing and differentiating lesions in the body. However, contrast enhancement evaluation on conventional MRI is qualitative because the signal intensity uses an arbitrary scale. An approach that allows more quantitative assessment of tissue enhancement that can be integrated into clinical use is desirable. This study aimed to provide a method that can estimate GBCA concentration in a clinically applicable scan-time. METHODS: Gadolinium-based contrast agent concentrations were quantified in phantoms containing water and nine different concentrations of Gadoteridol (Gd-HP-DO3A), ranging from 0.02 to 1.00 mmol/L, using quantitative synthetic MRI. Simple linear regression analysis between the estimated GBCA concentration and the reference values were performed to assess the accuracy. We performed region of interest analysis on each phantom, and recorded the mean and standard deviation. We evaluated the precision of the GBCA map by calculating the coefficient of variation (CV) for each concentration. The GBCA concentration quantification method was applied for 10 patients with metastatic brain tumors to demonstrate the feasibility of this method. RESULTS: For the phantom study, estimated GBCA concentrations were in a strong linear relationship (R2 = 0.998) with reference values, with a slope and intercept on simple linear regression analysis of 0.98 and 0.02, respectively. On precision assessment, the CV was <5%, with the exception of concentrations under 0.07 mmol/L. In the range of 0.07-0.99 mmol/L, the mean CV was 1.5 ± 1.2%. For application to brain metastases, the maximum estimated GBCA concentration in the metastases was 0.73 mmol/L, which was under the upper limit evaluated in the phantom study (i.e. -0.99 mmol/L). CONCLUSION: The concentration of Gd-HP-DO3A in the range of 0.07-0.99 mmol/L can be measured in a clinically applicable scan time using quantitative synthetic MRI, even though this study's results are only preliminary due to several limitations.

Choroid plexus cysts analyzed using diffusion-weighted imaging with short diffusion-time.

INTRODUCTION: Oscillating gradient spin-echo (OGSE) sequences can shorten diffusion times by replacing the long-lasting diffusion-sensitizing gradients used in pulsed gradient spin-echo (PGSE) methods with rapidly oscillating gradients. To obtain information regarding the internal structure of choroid plexus cysts that appear hyperintense on diffusion-weighted imaging (DWI), we investigated the apparent diffusion coefficient (ADC) values acquired with a shorter diffusion time using an OGSE sequence. MATERIAL AND METHODS: Twenty-seven patients with choroid plexus cysts were scanned using a 3 T magnetic resonance scanner. DWI was performed with both OGSE and PGSE, with effective diffusion times (Δeff) of 6.5 and 35.2 ms, respectively. ADC values for choroid plexus cysts, white matter (WM), and cerebrospinal fluid (CSF) were measured. The ADC values obtained with the shorter and longer diffusion times were compared using the Wilcoxon signed-rank test. P < .05 was considered significant. RESULTS: The ADC values of choroid plexus cysts and WM were significantly higher at the Δeff of 6.5 ms on OGSE than with the Δeff of 35.2 ms on PGSE. The ADC values of CSF were significantly lower at the Δeff of 6.5 ms on OGSE than with the Δeff of 35.2 ms on PGSE. The ADC values of choroid plexus cysts were lower than the ADC values of CSF with Δeff of 35.2 and 6.5 ms. CONCLUSIONS: The dependence of ADC values on the diffusion time in choroid plexus cysts suggested spatially restricted diffusion. In measurements obtained with short diffusion times, the lower ADC values for choroid plexus cysts in comparison with the CSF indicated the presence of spatially restricted diffusion and increased cyst viscosity.

Linearity, Bias, Intrascanner Repeatability, and Interscanner Reproducibility of Quantitative Multidynamic Multiecho Sequence for Rapid Simultaneous Relaxometry at 3 T: A Validation Study With a Standardized Phantom and Healthy Controls.

OBJECTIVES: The aim of this study was to evaluate the linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative values derived from a multidynamic multiecho (MDME) sequence for rapid simultaneous relaxometry. MATERIALS AND METHODS: The NIST/ISMRM (National Institute of Standards and Technology/International Society for Magnetic Resonance in Medicine) phantom, containing spheres with standardized T1 and T2 relaxation times and proton density (PD), and 10 healthy volunteers, were scanned 10 times on different days and 2 times during the same session, using the MDME sequence, on three 3 T scanners from different vendors. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. The measured phantom values were compared with reference values; volunteer values were compared with their averages across 3 scanners. RESULTS: The linearity of both phantom and volunteer measurements in T1, T2, and PD values was very strong (R = 0.973-1.000, 0.979-1.000, and 0.982-0.999, respectively) The highest intrascanner coefficients of variation (CVs) for T1, T2, and PD were 2.07%, 7.60%, and 12.86% for phantom data, and 1.33%, 0.89%, and 0.77% for volunteer data, respectively. The highest interscanner CVs of T1, T2, and PD were 10.86%, 15.27%, and 9.95% for phantom data, and 3.15%, 5.76%, and 3.21% for volunteer data, respectively. Variation of T1 and T2 tended to be larger at higher values outside the range of those typically observed in brain tissue. The highest intrascanner and interscanner CVs for brain tissue volumetry were 2.50% and 5.74%, respectively, for cerebrospinal fluid. CONCLUSIONS: Quantitative values derived from the MDME sequence are overall robust for brain relaxometry and volumetry on 3 T scanners from different vendors. Caution is warranted when applying MDME sequence on anatomies with relaxometry values outside the range of those typically observed in brain tissue.