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Objectives: We aimed to investigate the influence of magnetic resonance fingerprinting (MRF) dictionary design on radiomic features using in vivo human brain scans., Methods: Scan-rescans of three-dimensional MRF and conventional T1-weighted imaging were performed on 21 healthy volunteers (9 males and 12 females; mean age, 41.3 ± 14.6 years; age range, 22-72 years). Five patients with multiple sclerosis (3 males and 2 females; mean age, 41.2 ± 7.3 years; age range, 32-53 years) were also included. MRF data were reconstructed using various dictionaries with different step sizes. First- and second-order radiomic features were extracted from each dataset. Intra-dictionary repeatability and inter-dictionary reproducibility were evaluated using intraclass correlation coefficients (ICCs). Features with ICCs > 0.90 were considered acceptable. Relative changes were calculated to assess inter-dictionary biases., Results: The overall scan-rescan ICCs of MRF-based radiomics ranged from 0.86 to 0.95, depending on dictionary step size. No significant differences were observed in the overall scan-rescan repeatability of MRF-based radiomic features and conventional T1-weighted imaging (p = 1.00). Intra-dictionary repeatability was insensitive to dictionary step size differences. MRF-based radiomic features varied among dictionaries (overall ICC for inter-dictionary reproducibility, 0.62-0.99), especially when step sizes were large. First-order and gray level co-occurrence matrix features were the most reproducible feature classes among different step size dictionaries. T1 map-derived radiomic features provided higher repeatability and reproducibility among dictionaries than those obtained with T2 maps., Conclusion: MRF-based radiomic features are highly repeatable in various dictionary step sizes. Caution is warranted when performing MRF-based radiomics using datasets containing maps generated from different dictionaries., Key Points: • MRF-based radiomic features are highly repeatable in various dictionary step sizes. • Use of different MRF dictionaries may result in variable radiomic features, even when the same MRF acquisition data are used. • Caution is needed when performing radiomic analysis using data reconstructed from different dictionaries., (© 2022. The Author(s).)

The volumes of intracranial tissues of 40 healthy volunteers acquired from 0.3- and 3-T scanners were compared using intraclass correlation coefficients, correlation analyses, and Bland-Altman analyses. We found high intraclass correlation coefficients, high Pearson's correlation coefficients, and low percentage biases in all tissues and most of the brain regions, although small differences were observed in some areas. These findings may support the validity of brain volumetry with low-field magnetic resonance imaging.

Abstract: Low-field magnetic resonance imaging (MRI) systems have seen a renaissance recently due to improvements in technology (both hardware and software). Originally, the performance of low-field MRI systems was rated lower than their actual clinical usefulness, and they were viewed as low-cost but poorly performing systems. However, various applications similar to high-field MRI systems (1.5 T and 3 T) have gradually become possible, culminating with high-performance low-field MRI systems and their adaptations now being proposed that have unique advantages over high-field MRI systems in various aspects. This review article describes the physical characteristics of low-field MRI systems and presents both their advantages and disadvantages for clinical use (past to present), along with their cutting-edge clinical applications., Competing Interests: Conflicts of interest and sources of funding: The authors have no conflicts of interest to declare. This work was supported by JSPS KAKENHI grant number 19K08161, 19K17150, 18H02772, and JP16H06280; a research grant (2017-2020) from the Japanese Society of Neuroradiology; and AMED under grant number JP19lk1010025h9902., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.)

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) T 1 -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.

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 (SyMRI MVF ) 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. SyMRI MVF , 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 SyMRI MVF 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 SyMRI MVF . SyMRI MVF 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.

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 T 1 -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., (© 2019 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: This study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson's disease (PD) diagnosis., Methods: NM-MRI datasets from two different 3T-scanners were used: a "principal dataset" with 122 participants and an "external validation dataset" with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined., Results: For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets., Conclusion: U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method.

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 ± 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 (R 2  = 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., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Image contrast differs between conventional multislice turbo spin echo (conventional TSE) and multiband turbo spin echo (SMS-TSE). Difference in time interval between excitations for adjacent slices (SETI) might cause this difference. This study aimed to evaluate the influence of SETI on MT effect for conventional TSE and compare conventional TSE with SMS-TSE in this respect., Materials and Methods: Three different agar concentration phantoms were scanned with conventional TSE by adjusting SETI and TR. Signal change for different SETI was evaluated using Pearson's correlation analysis. SMS-TSE was acquired by changing TR similarly. Three human volunteers were scanned with similar settings to evaluate reproducibility of the phantom results in human brain., Results: In conventional TSE, shorter SETI induced larger signal reduction. Longer TR and higher agar concentration emphasized this characteristic. Significant linear correlation (P < 0.05) was found in the major cases. The SMS-TSE signal intensity in each TR and phantom was smaller than the assumable levels in conventional TSE when the slices were simultaneously excited. Similar characteristic was observed in human brain., Conclusion: Shorter SETI results in larger MT effect in conventional TSE. The contrast change in SMS-TSE was larger than the supposable level from simultaneous excitation, which needs consideration in clinics.

We report a case of uterine adenosarcoma demonstrated on magnetic resonance (MR) imaging. A 74-year-old woman with a large uterine mass underwent MR examination before total abdominal hysterectomy. Imaging revealed a markedly enlarged uterus with thin myometrium occupied by a large polypoid mass. The mass contained solid components with low intensity on T(1)-weighted images and high intensity on T(2)-weighted images compared to the myometrium and areas of small cysts.

Purpose: Among diabetes mellitus type 2 (DM2) patients, the frequency of cognitive dysfunction is higher and the relative risk of Alzheimer's disease (AD) is approximately twice that of nondiabetics. Cognitive impairment symptoms of AD are induced by limbic system dysfunction, and an early-stage AD brain without dementia has the potential for atrophy in the hippocampal region. In this study, we estimated potential hippocampal region atrophy in DM2 and pursued the association between DM2 and cognitive impairment/AD., Materials and Methods: Voxel-based morphometry analysis was performed in 28 diabetics (14 men, 14 women; ages 59-79 years, mean 70.7 years) and 28 sex- and agematched (+/-1 year) nondiabetics. Severity of gray matter loss in the hippocampal region and whole brain were investigated. Group analysis was performed using twotailed unpaired t-test; significance was assumed with less than 1% (P < 0.01) of the critical rate., Results: There was a significant difference between diabetics and nondiabetics regarding the severity of hippocampal region atrophy and whole-brain atrophy. Only diabetics showed a positive correlation for severity of hippocampal region atrophy and whole-brain atrophy (rs = 0.69, P < 0.0001)., Conclusion: Aged DM2 patients have the potential for hippocampal region atrophy, and its dysfunction can be related to the expression of a cognitive impairment that resembles AD.

Spot the Differences is a simple and popular game in which an observer compares a pair of similar pictures to detect the differences between them. Functional activation of the brain while playing this game has not been investigated. We used functional magnetic resonance imaging to investigate the main cortical regions involved in playing this game and compared the sites of cortical activation between a session of playing the game and a session of viewing 2 identical pictures. The right posterior parietal cortex showed more activation during game playing, and cortical activation volume correlated with game-playing accuracy. This cortical region may play an important role in awareness of differences between 2 similar pictures.

Background: Imaging diagnosis of Alzheimer disease (AD), the leading cause of dementia, requires evaluation of the extent of hippocampal atrophy. Coronal magnetic resonance (MR) images of patients with AD often demonstrate outward rotation of the hippocampus that is altered from a long horizontal elliptical to a long vertical elliptical shape. Such rotation may be related to the disease process of AD., Purpose and Methods: To determine whether hippocampal rotation is associated with AD, we investigated MR images from 11 patients with AD and 11 normal controls, measuring the hippocampal angle (HA) and the volume of the left hippocampus on coronal T(1)-weighted MR images. The HA is the angle between a horizontal line orthogonal to the falx cerebri and the uncal sulcus line between the deepest point of the uncal sulcus and the point nearest to the side of the ambient cistern in the uncal gyrus facing the uncal sulcus. The HA is measured on the most rostral slice in which the uncal sulcus can be identified and increases with hippocampal rotation., Results: We found correlation between the HA and standardized hippocampal volume in the AD group, but not in controls., Conclusion: Hippocampal rotation is a new marker associated with the pathology of AD.

Purpose: The aim of this retrospective study was to clarify the relation between the reversibility of posterior reversible encephalopathy syndrome (PRES) with three factors: the anatomical region of the brain involved, the background clinical cause, and the diffusion weighted image (DWI) intensity of PRES lesions., Material and Methods: This multicenter study, conducted by the PRES Study Group of the Neuroradiology Workshop, involved 52 cases from 28 institutions. Initial and follow-up magnetic resonance imaging were compared regarding the reversibility of PRES lesions according to anatomical location and clinical background. Initial DWI and apparent diffusion coefficient (ADC) maps were reviewed in 20 cases., Results: Reversibility was significantly lower (P < 0.01) in the brain stem (44%) and deep white matter (47%) compared to the other cortical and subcortical areas (76%-91%). The reversibility was greater in the eclampsia subgroup followed by the hypertension and chemotherapy subgroups. DWI, even with ADC maps, had limitations in predicting the outcome of PRES lesions., Conclusion: The typical cortical and subcortical PRES lesions showed reversibility, whereas the brain stem and deep white matter lesions showed less reversibility. PRES due to eclampsia showed maximum reversibility compared to hypertension- and drug-related PRES. DWI, even with ADC maps, had limitations in predicting the course of PRES.

Magnetic resonance (MR) imaging provides useful information for characterization of various ovarian masses as neoplastic or nonneoplastic and, when neoplastic, on a spectrum from benign to malignant. The use of MR imaging for diagnosis of ovarian masses includes consideration of morphologic characteristics and signal intensity characteristics on T1- and T2-weighted images. The morphologic characteristics of cystic masses, cystic and solid masses, and predominantly solid masses provide important information. In general, cystic masses represent benign tumors, whereas cystic and solid masses are strongly associated with malignancy. Predominantly solid masses include benign, borderline malignant, and malignant tumors. T1-weighted images provide useful information for characterization because hemorrhagic adnexal masses (eg, endometriotic cyst) and cystic teratomas can be correctly diagnosed when the mass has high signal intensity. Significant low signal intensity in solid masses on T2-weighted images is indicative of fibrothecomas and Brenner tumors because extensive fibrous tissue produces significant low signal intensity on T2-weighted images. A strategy for diagnosis of ovarian masses with MR imaging incorporates signal intensity characteristics into morphologic characteristics., (Copyright RSNA, 2006.)

Intravenous immunoglobulin therapy is useful against various immune system disorders and viral infections. It is generally safe, and serious adverse reactions are uncommon. We report a rare case of acute encephalopathy following intravenous immunoglobulin therapy for human herpes virus 6 infection in a child. MR imaging findings suggest that the dominant causative mechanism of acute encephalopathy is cytotoxic edema, and the findings indicate 2 primary mechanisms. Reversibility of the restriction of water diffusion (low apparent diffusion coefficient value) on diffusion-weighted MR imaging suggests intramyelinic edema in the myelin sheath, and an increase of glutamate and glutamine complex peak on MR spectroscopy suggests excitotoxic injury to the neurons and astrocytes.

Magnetic resonance (MR) imaging has extended the usefulness of imaging in evaluation of pelvic disorders associated with female infertility. The causes of female infertility include ovulatory disorders (ie, pituitary adenoma and polycystic ovarian syndrome), disorders of the fallopian tubes (ie, hydrosalpinx and pelvic inflammatory disease), uterine disorders (ie, müllerian duct anomaly, adenomyosis, and leiomyoma), and pelvic endometriosis. Although laparoscopy, hysteroscopy, hysterosalpingography, and transvaginal ultrasonography are the most effective techniques for evaluation of pelvic disorders related to female infertility, MR imaging is used in a variety of clinical settings in diagnosis, treatment, and management. The applications of MR imaging include evaluation of the functioning uterus and ovaries, visualization of pituitary adenomas, differentiation of müllerian duct anomalies, and accurate noninvasive diagnosis of adenomyosis, leiomyoma, and endometriosis. In addition, MR imaging helps predict the outcome of conservative treatment for adenomyosis, leiomyoma, and endometriosis and may lead to selection of better treatment plans and management. Finally, MR imaging may serve as an adjunct to diagnostic laparoscopy and hysterosalpingography in patients with hydrosalpinx, peritubal adhesions, or pelvic adhesions related to endometriosis., (Copyright RSNA, 2003)

MR imaging (MRI) has been reported to be a useful modality to characterize breast tumors and to evaluate disease extent. Contrast-enhanced dynamic MRI, in particular, allows breast lesions to be characterized with high sensitivity and specificity. Our study was designed to develop three-dimensional volumetric interpolated breath-hold examination (3D-VIBE) techniques for the evaluation of breast tumors. First, agarose/Gd-DTPA phantoms with various concentrations of Gd-DTPA were imaged using 3D-VIBE and turbo spin echo (TSE). Second, one of the phantoms was imaged with 3D-VIBE using different flip angles. Finally, water excitation (WE) and a chemical shift-selective (CHESS) pulse were applied to the images. Each image was analyzed for signal intensity, signal-to-noise ratio (1.25*Ms/Mb) (SNR), and contrast ratio [(Ms1-Ms2)/[(Ms1+Ms2)/2]]. The results showed that 3D-VIBE provided better contrast ratios with a linear fit than TSE, although 3D-VIBE showed a lower SNR. To reach the best contrast ratio, the optimized flip angle was found to be 30 degrees for contrast-enhanced dynamic study. Both WE and CHESS pulses were reliable for obtaining fat-suppressed images. In conclusion, the 3D-VIBE technique can image the entire breast area with high resolution and provide better contrast than TSE. Our phantom study suggests that optimized 3D-VIBE may be useful for the assessment of breast tumors.

Purpose: To compare the diagnostic ability of proton magnetic resonance spectroscopy (MRS) using an external surface coil with that using an endorectal surface coil in patients with prostate cancer., Materials and Methods: MR imaging (MRI) and two-dimensional chemical shift imaging (2D CSI) were performed in 5 healthy volunteers and in 35 patients with prostate cancer. The receiver coil was the anterior lower part of a phased-array coil or an endorectal surface coil., Results: Receiver-operating characteristic analysis for diagnosing prostate cancer showed no significant difference (P = 0.784) between the area under the curve of phased-array coil CSI and that of endorectal surface coil CSI., Conclusion: The phased-array coil CSI could provide comparable detection accuracy to endorectal surface coil CSI. In patients with rectal diseases or patients who could not tolerate the discomfort with insertion of an endorectal surface coil, we recommend the phased-array coil CSI., (Copyright 2002 Wiley-Liss, Inc.)

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 [ABSTRACT FROM AUTHOR]

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood–brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. Evidence Level: 3 Technical Efficacy: Stage 5 [ABSTRACT FROM AUTHOR]

Background: Two‐dimensional synthetic MRI of the breast has limited spatial coverage. Three‐dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast. Purpose: To evaluate the feasibility of 3D synthetic MRI using an interleaved Look–Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki‐67 expression in IDC. Study Type: Prospective observational study. Population: A total of 33 females with IDC of the breast (mean, 52.3 years). Field Strength/Sequence: A 3‐T, 3D‐QALAS gradient‐echo and fat‐suppressed T1‐weighted 3D fast spoiled gradient‐echo sequences. Assessment: Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1‐weighted images acquired from 3D‐QALAS. The mean T1 and T2 were measured for each IDC. Statistical Tests: Intraclass correlation coefficient for assessing interobserver agreement. Mann–Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant. Results: The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR‐positive and HR‐negative lesions, while the mean T2 value differed between HR‐positive and HR‐negative lesions, between the triple‐negative and HR‐positive or HER2‐positive lesions, and between the Ki‐67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR‐negative IDC than in HR‐positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple‐negative status, and Ki‐67 level. Data Conclusion: 3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast. Evidence Level: 1. Technical Efficacy: Stage 2. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Differentiating corticobasal degeneration presenting with corticobasal syndrome (CBD-CBS) from progressive supranuclear palsy with Richardson's syndrome (PSP-RS), particularly in early stages, is often challenging because the neurodegenerative conditions closely overlap in terms of clinical presentation and pathology. Although volumetry using brain magnetic resonance imaging (MRI) has been studied in patients with CBS and PSP-RS, studies assessing the progression of brain atrophy are limited. Therefore, we aimed to reveal the difference in the temporal progression patterns of brain atrophy between patients with CBS and those with PSP-RS purely based on cross-sectional data using Subtype and Stage Inference (SuStaIn)—a novel, unsupervised machine learning technique that integrates clustering and disease progression modeling. We applied SuStaIn to the cross-sectional regional brain volumes of 25 patients with CBS, 39 patients with typical PSP-RS, and 50 healthy controls to estimate the two disease subtypes and trajectories of CBS and PSP-RS, which have distinct atrophy patterns. The progression model and classification accuracy of CBS and PSP-RS were compared with those of previous studies to evaluate the performance of SuStaIn. SuStaIn identified distinct temporal progression patterns of brain atrophy for CBS and PSP-RS, which were largely consistent with previous evidence, with high reproducibility (99.7%) under cross-validation. We classified these diseases with high accuracy (0.875) and sensitivity (0.680 and 1.000, respectively) based on cross-sectional structural brain MRI data; the accuracy was higher than that reported in previous studies. Moreover, SuStaIn stage correctly reflected disease severity without the label of disease stage, such as disease duration. Furthermore, SuStaIn also showed the genialized performance of differentiation and reflection for CBS and PSP-RS. Thus, SuStaIn has potential for improving our understanding of disease mechanisms, accurately stratifying patients, and providing prognoses for patients with CBS and PSP-RS. [ABSTRACT FROM AUTHOR]

Purpose: The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan–rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors. Methods: Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23–37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan–rescan and inter-vendor reproducibilities of NODDI metrics. Results: The scan–rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3–14%) were lower than the scan–rescan reproducibility (CoV: scanner A = 0.8–3.8%; scanner B = 0.8–2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter. Conclusion: The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted. [ABSTRACT FROM AUTHOR]

Purpose: Micro fractional anisotropy (μFA) is more accurate than conventional fractional anisotropy (FA) for assessing microscopic tissue properties and can overcome limitations related to crossing white matter fibres. We compared μFA and FA for evaluating white matter changes in patients with Parkinson's disease (PD). Methods: We compared FA and μFA measures between 25 patients with PD and 25 age- and gender-matched healthy controls using tract-based spatial statistics (TBSS) analysis. We also examined potential correlations between changes, revealed by conventional FA or μFA, and disease duration or Unified Parkinson's Disease Rating Scale (UPDRS)-III scores. Results: Compared with healthy controls, patients with PD had significantly reduced μFA values, mainly in the anterior corona radiata (ACR). In the PD group, μFA values (primarily those from the ACR) were significantly negatively correlated with UPDRS-III motor scores. No significant changes or correlations with disease duration or UPDRS-III scores with tissue properties were detected using conventional FA. Conclusion: μFA can evaluate microstructural changes that occur during white matter degeneration in patients with PD and may overcome a key limitation of FA. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. Methods: Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. Results: In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. Conclusion: Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome. [ABSTRACT FROM AUTHOR]

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 [Δ eff ]: 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 λ 1 , λ 2 , λ 3 , 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 Δ eff 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 Δ eff 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. [ABSTRACT FROM AUTHOR]