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Background: Recurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI)., Materials and Methods: 48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence., Results: The parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De ⊥ ), extra-axonal parallel diffusivity (De ∥ ) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De ⊥ ) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De ⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96., Conclusion: Preoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De ⊥ of SMI might be a valuable marker., (© 2024. The Author(s).)

The purpose of this study is to investigate the feasibility of using a continuous-time random-walk (CTRW) diffusion model, together with a quartile histogram analysis, for assessing glioma malignancy by probing tissue heterogeneity as well as cellularity. In this prospective study, 91 patients (40 females, 51 males) with histopathologically proven gliomas underwent MRI at 3 T. The cohort included 42 grade II (GrII), 19 grade III (GrIII) and 29 grade IV (GrIV) gliomas. Echo-planar diffusion-weighted imaging was conducted using 17 b-values (0-4000 s/mm 2 ). Three CTRW model parameters, including an anomalous diffusion coefficient D m , and two parameters related to temporal and spatial diffusion heterogeneity α and β, respectively, were obtained. The mean parameter values within the tumor regions of interest (ROIs) were computed by utilizing the first quartile of the histograms as well as the full ROI for comparison. A Bonferroni-Holm-corrected Mann-Whitney U-test was used for the group comparisons. Individual and combinations of the CTRW parameters were evaluated for the characterization of gliomas with a receiver operating characteristic analysis. All first-quartile mean CTRW parameters yielded significant differences (p-values < 0.05) between pair-wise comparisons of GrII (D m : 1.14 ± 0.37 μm 2 /ms; α: 0.904 ± 0.03, β: 0.913 ± 0.06), GrIII (D m : 0.88 ± 0.21 μm 2 /ms; α: 0.888 ± 0.01, β: 0.857 ± 0.06) and GrIV gliomas (D m : 0.73 ± 0.22 μm 2 /ms; α: 0.878 ± 0.01; β: 0.791 ± 0.07). The highest sensitivity, specificity, accuracy and area-under-the-curve of using the combinations of the first-quartile parameters were 84.2%, 78.5%, 75.4% and 0.76 for GrII and GrIII classification; 86.2%, 89.4%, 75% and 0.76 for GrIII and GrIV classification; and 86.2%, 85.7%, 84.5% and 0.90 for GrII and GrIV classification, respectively. Quartile-based analysis produced higher accuracy and area-under-the-curve than the full ROI-based analysis in all classifications. The CTRW diffusion model, together with a quartile-based histogram analysis, offers a new way for probing tumor structural heterogeneity at a subvoxel level, and has potential for in vivo assessment of glioma malignancy to complement histopathology., (© 2021 John Wiley & Sons, Ltd.)

Purpose: The current study aimed to investigate the associations between diffusion dynamics of ischemic lesions and clinical functional outcome of acute and early subacute stroke., Material and Methods: A total of 80 patients with first ever infarcts in the territory of the middle cerebral artery underwent multi-b-values diffusion-weighted imaging and diffusion kurtosis imaging. Multiple diffusion parameters were generated in postprocessing using different diffusion models. Long-term functional outcome was evaluated with modified Rankin scale (mRS) at 6 months post-stroke. Good functional outcome was defined as mRS score ≤ 2 and poor functional outcome was defined as mRS score ≥ 3. Univariate analysis was used to compare the diffusion parameters and clinical features between patients with poor and good functional outcome. Significant parameters were further analyzed for correlations with functional outcome using partial correlation., Results: In univariate analyses, standard-b-values apparent diffusion coefficient (ADC st ) ratio and fractional anisotropy (FA) ratio of acute stroke, ADC st ratio and mean kurtosis (MK) ratio of early subacute stroke were statistically different between patients with poor outcome and good outcome (P < 0.05). When the potential confounding factor of lesion volume was controlled, only FA ratio of acute stroke, ADC st ratio and MK ratio of early subacute stroke remained correlated with the functional outcome (P < 0.05)., Conclusion: Diffusion dynamics are correlated with the clinical functional outcome of ischemic stroke. This correlation is independent of the effect of lesion volume and is specific to the time period between symptom onset and imaging. More effort is needed to further investigate the predictive value of diffusion-weighted imaging.

Objectives: To demonstrate the feasibility of the neurite orientation dispersion and density imaging (NODDI) technique in characterizing the microstructural changes in brain tissues during ischemic stroke and to compare its sensitivity with diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI)., Methods: Seventy-one patients with hyperacute/acute/subacute ischemic stroke were enrolled in the study. A multishell diffusion magnetic resonance imaging (dMRI) protocol was performed for each subject. Diffusion data were analyzed using the NODDI and diffusional kurtosis estimator toolboxes. Then, NODDI metrics between the lesions and the contralateral tissues were compared to evaluate their values in ischemic stroke. NODDI metrics among different stroke periods and the correlations between NODDI and the duration since stroke onset were analyzed as well. To compare the NODDI's sensitivity with established diffusion techniques, paired t-tests were performed to determine the absolute percentage changes of diffusion metrics between NODDI and DTI/DKI., Results: Compared with the contralateral tissues, lesions showed significantly increased values of intracellular volume fraction (V ic ) and orientation dispersion index (ODI) and decreased values of isotropic volume fraction (V iso ). ODI value was significantly different among three periods and showed fair to good positive correlation with the duration since stroke onset (R = 0.450). NODDI metrics showed significantly larger absolute percentage changes than that of DTI and DKI (P < 0.05, respectively)., Conclusion: NODDI allowed efficient evaluation of microstructural changes in brain tissues during ischemic stroke and showed increased sensitivity compared with DTI and DKI. The possible biophysical mechanisms underlying ischemia could be further elucidated using this advanced diffusion technique., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Diffusion-weighted MRI (dMRI) is a key component of clinical radiology. When analyzing diffusion-weighted images, radiologists often seek to infer microscopic tissue structure through measurements of the diffusion coefficient, D 0 (mm 2 /s). This multi-scale problem is framed by the creation of diffusion models of signal decay based on physical laws, histological structure, and biophysical constraints. The purpose of this paper is to simplify the model building process by focusing on the observed decay in the effective diffusion coefficient as a function of diffusion weighting (b-value), D(b), that is often observed in complex biological tissues. We call this approach the varying diffusion curvature (VDC) model. Since this is a heuristic model, the exact functional form of this decay is not important, so here we examine a simple exponential function, D(b) = D 0 exp(-bD 1 ), where D 0 and D 1 capture aspects of hindered and restricted diffusion, respectively. As an example of the potential of the VDC model, we applied it to dMRI data collected from normal and diseased human brain tissue using Stejskal-Tanner diffusion gradient pulses. In order to illustrate the connection between D 0 and D 1 and the sub-voxel structure we also analyzed dMRI data from families of Sephadex beads selected with increasing tortuosity. Finally, we applied the VDC model to dMRI simulations of nested muscle fiber phantoms whose permeability, atrophy, and fiber size distribution could be changed. These results demonstrate that the VDC model is sensitive to sub-voxel tissue structure and composition (porosity, tortuosity, and permeability), hence can capture tissue complexity in a manner that could be easily applied in clinical dMRI., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas., Methods: Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (α) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis., Results: The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (0.979) and H (0.594), indicating an improved performance for tumor differentiation., Conclusion: The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Purpose: To demonstrate the capability of the fractional motion (FM) model for describing anomalous diffusion in cerebral gliomas and to assess the potential feasibility of FM for grading these tumors., Methods: Diffusion MRI images were acquired from brain tumor patients using a special Stejskal-Tanner diffusion sequence with variable diffusion gradient amplitudes and separation times. Patients with histopathologically confirmed gliomas, including astrocytic and oligoastrocytic tumors, were selected. The FM-related parameters, including the Noah exponent ( α), the Hurst exponent ( H), and the memory parameter ( μ=H-1/α), were calculated and compared between low- and high-grade gliomas using a two-sample t-test. The grading performance was evaluated using the receiver operating characteristic analysis., Results: Twenty-two patients were included in the present study. The calculated α, H, and μ permitted the separation of tumor lesions from surrounding normal tissues in parameter maps and helped differentiate glioma grades. Moreover, α showed greater sensitivity and specificity in distinguishing low- and high-grade gliomas compared with the apparent diffusion coefficient., Conclusion: The FM model could improve the diagnostic accuracy in differentiating low- and high-grade gliomas. This improved diffusion model may facilitate future studies of neuro-pathological changes in clinical populations. Magn Reson Med 78:1944-1949, 2017. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Objectives: The aim of this study was to use DKI to detect the microstructural change of the discs in matured normal rats., Methods: Total 24 normal SD rats (12 males/12 females) underwent DWI/DKI and T2 sequences with a 3T MRI scanner to get the values of ADC, FA, MD, Da, Dr, MK, Ka and Kr. The discs were categorized using a five-grade degeneration grading system in the T2-images. The height of the discs and the parameters in DWI/DKI were measured to compare between the different grades and sexes. The histological images and the images of fiber tracking were also done in the discs., Results: There were 30 Grade 1 and 18 Grade 2 in the discs. Compared with Grade 1, decreased ADC, increased FA and MK values were observed in Grade 2 (P<0.05). By the ROC analysis of grades of the discs, there was low diagnostic accuracy in ADC value, while FA and MK showed higher accuracy. In Grade 1, there were lower ADC value, lower Dr, higher MK, Ka and Kr in male's group than them in female's group. There were no differences in the parameters except the ADC value in the two sexes in Grade 2. The different microstructure of the normal discs in the male and female rats had been proved by the histological images and the images of fiber tracking., Conclusion: DKI is a noninvasive and sustainable means to test the changes of intervertebral discs. The discs in Grade 2 were also found in the normal matured SD rat tails. The assessment of the grade of the discs in T2-images should be done before the experimental management. There was microstructural difference in the nucleus pulposus in the discs in Grade 1 and 2. FA and MK showed higher diagnostic accuracy. The laboratory rats should be the same sex because the microstructure of the normal discs weren't the same., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features., Materials and Methods: This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC., Results: Mean ADC, median ADC, 5 th percentile ADC, 25 th percentile ADC, 75 th percentile ADC, 95 th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10 -6 mm 2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5 th percentile ADC, and 25 th percentile ADC. The 5 th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10 -6 mm 2 /s for differentiating between PTCs with and without extrathyroidal extension., Conclusion: Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: Diffusional kurtosis imaging (DKI), as a non-Gaussian diffusion model, has been applied in human and animal studies of ischemic stroke. This study aimed to intensively characterize the temporal evolution of DKI-derived variables in an experimental middle cerebral artery occlusion (MCAO) model, and to explore its potential application in ischemic stroke., Materials and Methods: Eleven MCAO rats and ten control rats underwent DKI and diffusion weighted imaging (DWI) scans, at different time points of 0.5, 2, 6, 12, 24 and 72h after operation respectively. The infarct area in DKI- and DWI-derived variables was compared among different time points, and between different groups [INFARCTION, MIRROR, CONTROL-R (right side of the control group, the same side as in the infarction group), CONTROL-L (left side of the control group)] using repeated measures analysis of variance (ANOVA). The percent changes from normal to that in ischemic tissues and histology were also evaluated., Results: In the infarct region, from 0.5 to 72h, MK, K∥, K⊥ demonstrated irregular high signal, whereas relative homogeneous low signals were revealed by MD, D∥, D⊥ and ADC. Compared with the MIRROR and CONTROL-R group, MK, K∥, K⊥ in the infarcted area increased aggressively which peaked at 12h and gradually decreased; MD, D∥, D⊥ and ADC decreased gradually until 12h and then began to increase gradually; FA decreased rapidly from 0.5 to 72h. MD, D∥ and ADC were significantly different between Mirror and CONTROL-L group (P<0.05)., Conclusion: DKI can provide more detailed information to describe ischemic lesion, and has great potential application in ischemic stroke., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To determine the utility of intravoxel incoherent motion (IVIM) imaging in grading gliomas and compare IVIM perfusion metrics with arterial spin labeling (ASL)-derived cerebral blood flow (CBF)., Materials and Methods: Fifty-two patients with pathologically confirmed gliomas underwent IVIM and ASL imaging at 3.0T. IVIM perfusion-related diffusivity (D*), perfusion fraction (f), product of f and D*(f×D*), true diffusivity (D), and apparent diffusion coefficient (ADC) were obtained to distinguish glioma grades. The CBF derived from pseudocontinuous ASL within the solid tumor was compared and correlated with IVIM perfusion metrics for grading of gliomas. Values were also normalized to the contralateral normal-appearing white matter. Receiver-operating characteristic was performed to determine diagnostic efficiency. The reliability was estimated with intraclass coefficient, coefficient of variance, and Bland-Altman plots., Results: IVIM perfusion metrics and CBF were significantly higher in the high-grade than the low-grade gliomas (P < 0.001), ADC and D were significantly lower in the high-grade than the low-grade gliomas (P < 0.001). f×D* differed significantly between grades II through IV (P < 0.05 for all). The other metrics showed significant difference between grade II and grade III (P < 0.05 for all). Area under the curve (AUC) was largest for f×D* in distinguishing high-grade from low-grade gliomas (AUC = 0.979, P < 0.001) and between grade II and grade III (AUC = 0.957, P < 0.001). f×D* improved diagnostic performance of CBF in grading gliomas and showed strong correlation with CBF (r = 0.696, P < 0.001)., Conclusion: IVIM-derived metrics are promising biomarkers in preoperative grading gliomas. IVIM imaging may be an additive method to ASL and ADC for evaluating tumor perfusion and diffusion. J. Magn. Reson. Imaging 2016;44:620-632., (© 2016 International Society for Magnetic Resonance in Medicine.)

Objective: To explore the parametric characteristics of diffusional kurtosis imaging (DKI) in the brain development of healthy preterm infants., Materials and Methods: Conventional magnetic resonance imaging (MRI) and DKI were performed in 35 preterm (29 to 36 weeks gestational age [GA]; scanned at 33 to 44 weeks postmenstrual age [PMA]) and 10 term infants (37.4 to 40.7 weeks GA; scanned at 38.3 to 42.9 weeks PMA). Fractional anisotropy (FA), mean diffusivity (MD) and mean kurtosis (MK) values from 8 regions of interest, including both white matter (WM) and gray matter (GM), were obtained., Results: MK and FA values were positively correlated with PMA in most selected WM regions, such as the posterior limbs of the internal capsule (PLIC) and the splenium of the corpus callosum (SCC). The positive correlation between MK value and PMA in the deep GM region was higher than that between FA and PMA. The MK value gradually decreased from the PLIC to the cerebral lobe. In addition, DKI parameters exhibited subtle differences in the parietal WM between the preterm and term control groups., Conclusions: MK may serve as a more reliable imaging marker of the normal myelination process and provide a more robust characterization of deep GM maturation.

Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.

Background: Corticospinal tract (CST) injury has been shown to exert a major influence on functional recovery after ischemic stroke. Purpose To evaluate the prognostic value of CST injury estimated using a recent developed tractometry‐based method. Study Type: Prospective. Population: Forty‐eight patients with CST damage induced by stroke lesion who underwent brain magnetic resonance imaging within 7 days from onset. Sequence Diffusion‐weighted imaging (b = 1000 seconds/mm2) and diffusion kurtosis imaging (DKI) spin‐echo echo‐planar sequence with three b‐values (0, 1250, and 2500 seconds/mm2) at 3.0 T. Assessment A recently developed approach that combines tract segmentation and orientation mapping was used for CST‐specific tractography and tractometry. CST injury was estimated using the proposed method with diffusion metrics extracted from DKI sequence and with the first principal component (PC1) of the metrics. We also calculated the weighted lesion load (wLL) for comparison. Clinical evaluation included the National Institutes of Health Stroke Score in the acute phase and the modified Rankin scale at 3 months post‐stroke. The correlations between CST injury and initial motor impairment, as well as the prognostic values of CST injury for functional outcomes were evaluated. Statistical Tests: Pearson correlation and logistic regression. Area under the receiver operating characteristic curve. P < 0.05 was considered statistically significant. Results: CST injury calculated with diffusion metrics except fractional anisotropy all showed significant correlations with initial motor impairment. PC1 achieved the largest correlation coefficient (R = 0.65) compared with wLL and other diffusion metrics. In addition to wLL, DKI_AK, AFD_total, and PC1 maximum all showed predictive values for functional outcomes. Data Conclusion: Structural injury to CST is important for the assessment of the extent of injury and the prediction of functional outcome. The method proposed in our study could provide an imaging indicator to quantify the CST injury after ischemic stroke. Level of Evidence: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Objectives: To compare the efficacy of parameters from multiple diffusion magnetic resonance imaging (dMRI) for prediction of isocitrate dehydrogenase 1 (IDH1) genotype and assessment of cell proliferation in gliomas. Methods: Ninety-one patients with glioma underwent diffusion weighted imaging (DWI), multi- b -value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) on 3.0T MRI. Each parameter was compared between IDH1-mutant and IDH1 wild-type groups by Mann–Whitney U test in lower-grade gliomas (LrGGs) and glioblastomas (GBMs), respectively. Further, performance of each parameter was compared for glioma grading under the same IDH1 genotype. Spearman correlation coefficient between Ki-67 labeling index (LI) and each parameter was calculated. Results: The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in LrGGs, with statistically insignificant AUC values from 0.750 to 0.817. In GBMs, no difference between the two groups was found. For IDH1-mutant group, all parameters, except for fractional anisotropy (FA) and D∗, significantly discriminated LrGGs from GBMs (P < 0.05). However, for IDH1 wild-type group, only ADC statistically discriminated the two (P = 0.048). In addition, MK has maximal correlation coefficient (r = 0.567, P < 0.001) with Ki-67 LI. Conclusion: dMRI-derived parameters are promising biomarkers for predicting IDH1 genotype in LrGGs, and MK has shown great potential in assessing glioma cell proliferation. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the spatiotemporal evolution of oxygen extraction fraction (OEF) in ischemic stroke with a newly developed cluster analysis of time evolution (CAT) for a combined quantitative susceptibility mapping and quantitative blood oxygen level-dependent model (QSM + qBOLD, QQ). Method: One hundred and fifteen patients in different ischemic stroke phases were retrospectively collected for measurement of OEF of the infarcted area defined on diffusion-weighted imaging (DWI). Clinical severity was assessed using the National Institutes of Health Stroke Scale (NIHSS). Of the 115 patients, 11 underwent two longitudinal MRI scans, namely, three-dimensional (3D) multi-echo gradient recalled echo (mGRE) and 3D pseudo-continuous arterial spin labeling (pCASL), to evaluate the reversal region (RR) of the initial diffusion lesion (IDL) that did not overlap with the final infarct (FI). The temporal evolution of OEF and the cerebral blood flow (CBF) in the IDL, the RR, and the FI were assessed. Results: Compared to the contralateral mirror area, the OEF of the infarcted region was decreased regardless of stroke phases (p < 0.05) and showed a declining tendency from the acute to the chronic phase (p = 0.022). Five of the 11 patients with longitudinal scans showed reversal of the IDL. Relative oxygen extraction fraction (rOEF, compared to the contralateral mirror area) of the RR increased from the first to the second MRI (p = 0.044). CBF was about 1.5-fold higher in the IDL than in the contralateral mirror area in the first MRI. Two patients showed penumbra according to the enlarged FI volume. The rOEF of the penumbra fluctuated around 1.0 at earlier scan times and then decreased, while the CBF decreased continuously. Conclusion: The spatiotemporal evolution of OEF and perfusion in ischemic lesions is heterogeneous, and the CAT-based QQ method is feasible to capture cerebral oxygen metabolic information. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the difference in wall shear stress (WSS) (axial, circumferential, and 3D) between high-risk and low-risk plaques in patients with moderate carotid artery stenosis and to identify which time points and directions play the dominant roles in determining the risk associated with plaques. Forty carotid arteries in 30 patients were examined in this study. All patients underwent high-resolution vessel wall (HRVW) imaging, diffusion-weighted imaging (DWI), and 4D flow MRI; HRVW imaging and DWI were used to separate low- and high-risk plaque. Twenty-four high-risk plaques and 16 low-risk plaques were enrolled. An independent-sample t -test was used to compare WSS between low- and high-risk plaques in the whole cardiac cycle and at 20 different time points in the cardiac cycle. The study found that patients with high-risk plaques had higher WSS than those with low-risk plaques throughout the entire cardiac cycle (p < 0.05), but the changes varied at the 20 different time points. The number of non-significant differences (p > 0.05) was less in diastole than in systole across different time points. The axial WSS values were higher than the circumferential WSS values; the difference in axial WSS values between high- and low-risk plaques was more significant than the difference in circumferential WSS, whereas 3D WSS values best reflected the difference between high-risk and low-risk plaques because they showed significant differences at every time point. In conclusion, increased WSS, especially during the diastolic period and in the axial direction, may be a signal of a high-risk plaque and may cause cerebrovascular events in patients with moderate carotid artery stenosis. Additionally, WSS can provide hemodynamic information and help clinicians make more appropriate decisions for patients with plaques. [ABSTRACT FROM AUTHOR]

• MUSE-DTI acquired a better image quality compared to traditional DTI. • MUSE-DTI parameters of the spinal cord at MCL in CSM patients were significantly grade-dependent and all correlated with clinical JOA scores. • The AD C2 values can reflect the secondary damage of distal spinal cord. The most frequent type of spinal cord injury is cervical spondylotic myelopathy (CSM). Conventional structural magnetic resonance imaging (MRI) is the gold diagnosis standard for CSM. Diffusion tensor imaging (DTI) could reflect microstructural changes in the spinal cord by tracing water molecular diffusion in early stages of CSM. However, due to the complex local anatomical structure and small field of view of the spinal cord, the imaging effect of traditional DTI imaging on the spinal cord is limited. MUSE (MUltiplexed Sensitivity-Encoding) -DTI is a novel diffusion-weighted imaging (DWI) sequence that achieves higher signal intensity through multiple excitation acquisition. MUSE sequence may improve the quality of spinal cord DTI imaging. Prospective study. This study aimed to investigate the clinical diagnosis value of a novel protocol of MUSE-DTI in patients with cervical spondylotic myelopathy (CSM). From August 2021 to March 2022, a total of 60 subjects (22–71 years) were enrolled, including 51 CSM patients (22 males, 29 females) and 9 healthy subjects (4 males and 5 females). Each subject underwent a MUSE-DTI examination and a clinical Japanese Orthopedic Association (JOA) scale. We measured values of FA (Fractional Anisotropy), MD (Mean Diffusivity), AD (Axial Diffusivity), and RD (Radial Diffusivity), and collected the clinical JOA scores of each subject before the MR examination. A 3.0T MR scanner (Signa Architect, GE Healthcare) performed the MUSE-DTI sequence on each subject. The cervical canal stenosis of subjects was classified from grade 0 to grade Ⅲ according to the method of an MRI grading system. FA, MD, AD, and RD maps were generated by postprocessing MUSE-DTI data on the GE workstation. Regions of interest (ROIs) were manually drawn at the C2 vertebral body level and C2/3-C6/7 intervertebral disc levels by covering the whole spinal cord. The clinical severity of myelopathy of subjects was assessed by the clinical Japanese Orthopedic Association scale (JOA). MUSE-DTI can acquire a high-resolution diffusion image compared to traditional DTI. The FA MCL values showed a decreasing trend from grade 0 to grade Ⅲ, while the MD MCL , AD MCL , and RD MCL values showed an overall increasing trend. Significant differences in MD MCL , AD MCL , and RD MCL values were found between adjacent groups among grades Ⅰ-Ⅲ (p<.05). The AD C2 values in CSM patients (grade I–Ⅲ) were significantly lower than in healthy individuals (grade 0) (p=.019). The clinical JOA score has a significant correlation with FA MCL (p=.035), MD MCL (p<.001), AD MCL (p<.001), and RD MCL (p<.001) values. MUSE-DTI displayed a better image quality compared to traditional DTI. MUSE-DTI parameters displayed a grade-dependent trend. All the MUSE-DTI parameters at MCL were correlated with the clinical JOA scores. The AD C2 values can reflect the secondary damage of distal spinal cord. Therefore, MUSE-DTI could be a reliable biomarker for clinical auxiliary diagnosis of spinal cord injury severity in cervical spondylotic myelopathy. [ABSTRACT FROM AUTHOR]

Purpose: To compare the main parameters derived from monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) with respect to diagnostic performance for tumor grading and proliferation assessment in diffuse astrocytic tumors (DATs).Materials and Methods: Fifty-eight pathologically confirmed DAT patients who underwent DWI and DKI on a 3-T scanner were prospectively collected and retrospectively reviewed. Measurements including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) were compared between tumor grades (Ⅱ, Ⅲ, and Ⅳ) by using a Jonckheere-Terpstra test. Receiver operating characteristic (ROC) curves were used to assess the diagnostic efficacy of these parameters. Spearman's rho with the Ki-67 labeling index (LI) was calculated for each parameter.Results: MK values differed significantly between all DAT subtypes and increased with grade. The ADC, D, f, DDC, α and MD values were significantly higher in grade Ⅱ tumors than in grade Ⅲ/Ⅳ tumors. D* values were significantly lower in grade Ⅱ tumors than in grade Ⅳ tumors (all P < 0.05). In discriminating between grade Ⅱ and Ⅲ tumors, α, MK, MD, D and f had significantly greater area under the ROC curve (AUC) values than D* and FA (0.927, 0.901, 0.896, 0.895, and 0.889, respectively vs 0.659 and 0.598, respectively, P < 0.05). In discriminating between grade Ⅲ and Ⅳ tumors, only MK demonstrated acceptable discrimination (AUC = 0.711). MK and D showed a strong correlation with the Ki-67 LI (ρ = 0.791 and -0.789, respectively, P < 0.001). D*, f, MD, ADC, DDC and α showed a moderate correlation (|ρ| ranged from 0.415 to 0.698, P < 0.05).Conclusion: MK and D have considerable potential to predict the degree of proliferation of DATs. MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading. [ABSTRACT FROM AUTHOR]

• Proton exchange rate (k e x) imaging was proposed based on water direct saturation (DS)-removed omega plots. • k e x MRI can differentiate infarcts from contralateral normal brain tissues. • k e x MRI was different from conventional MRI contrasts. To map and quantify the proton exchange rate (k e x) of brain tissues using improved omega plots in ischemic stroke patients and to investigate whether k e x can serve as a potential endogenous surrogate imaging biomarker for detecting the metabolic state and the pathologic changes due to ischemic stroke. Three sets of Z-spectra were acquired from seventeen ischemic stroke patients using a spin echo-echo planar imaging sequence with pre-saturation chemical exchange saturation transfer (CEST) pulse at B 1 of 1.5, 2.5, and 3.5 μ T , respectively. Pixel-wise k e x was calculated from improved omega plot of water direct saturation (DS)-removed Z-spectral signals. The derived k e x maps can differentiate infarcts from contralateral normal brain tissues with significantly increased signal (893 ± 52 s - 1 vs. 739 ± 34 s - 1 , P < 0.001). The k e x maps were found to be different from conventional contrasts from diffusion-weighted imaging (DWI), CEST, and semi-solid magnetization transfer (MT) MRI. In brief, k e x MRI showed larger lesion areas than DWI with different degrees and different lesion contrast compared to CEST and MT. In this preliminary translational research, the k e x MRI based on DS-removed omega plots has been demonstrated for in vivo imaging of clinical ischemic stroke patients. As a noninvasive and unique MRI contrast, k e x MRI at 3 T may serve as a potential surrogate imaging biomarker for the metabolic changes of stroke and help for monitoring the evolution and the treatment of stroke. [ABSTRACT FROM AUTHOR]