Evaluation of gadolinium deposition in cortical bone using three-dimensional ultrashort echo time quantitative susceptibility mapping: A preliminary study.

The aim of the current study was to investigate the feasibility of three-dimensional ultrashort echo time quantitative susceptibility mapping (3D UTE-QSM) for the assessment of gadolinium (Gd) deposition in cortical bone. To this end, 40 tibial bovine cortical bone specimens were divided into five groups then soaked in phosphate-buffered saline (PBS) solutions with five different Gd concentrations of 0, 0.4, 0.8, 1.2, and 1.6 mmol/L for 48 h. Additionally, eight rabbits were randomly allocated into three groups, consisting of a normal-dose macrocyclic gadolinium-based contrast agent (GBCA) group (n = 3), a high-dose macrocyclic GBCA group (n = 3), and a control group (n = 2). All bovine and rabbit tibial bone samples underwent magnetic resonance imaging (MRI) on a 3-T clinical MR system. A 3D UTE-Cones sequence was utilized to acquire images with five different echo times (i.e., 0.032, 0.2, 0.4, 0.8, and 1.2 ms). The UTE images were subsequently processed with the morphology-enabled dipole inversion algorithm to yield a susceptibility map. The average susceptibility was calculated in three regions of interest in the middle of each specimen, and the Pearson's correlation between the estimated susceptibility and Gd concentration was calculated. The bone samples soaked in PBS with higher Gd concentrations exhibited elevated susceptibility values. A mean susceptibility value of -2.47 ± 0.23 ppm was observed for bovine bone soaked in regular PBS, while the mean QSM value increased to -1.75 ± 0.24 ppm for bone soaked in PBS with the highest Gd concentration of 1.6 mmol/L. A strong positive correlation was observed between Gd concentrations and QSM values. The mean susceptibility values of rabbit tibial specimens in the control group, normal-dose GBCA group, and high-dose GBCA group were -4.11 ± 1.52, -3.85 ± 1.33, and -3.39 ± 1.35 ppm, respectively. In conclusion, a significant linear correlation between Gd in cortical bone and QSM values was observed. The preliminary results suggest that 3D UTE-QSM may provide sensitive noninvasive assessment of Gd deposition in cortical bone.

Disparate Radiation-Induced Microstructural Injuries in Whole-Brain White Matter of Patients With Nasopharyngeal Carcinoma: A Longitudinal Study Using Multishell Diffusion MRI.

BACKGROUND: Evidence for prevention strategies of radiotherapy (RT)-related injury in patients with nasopharyngeal carcinoma (NPC) was lacking. Understanding the dynamic alterations in the cerebral white matter (WM) microstructure after RT may be helpful. PURPOSE: To investigate the dynamic alterations in the whole brain WM microstructure in patients with NPC in the 12 months after RT using multishell diffusion MRI (MS-dMRI). STUDY TYPE: Single-center longitudinal study. POPULATION: A total of 28 treatment-naïve patients with pathologically confirmed NPC (age: 39.68 ± 8.93 years, 11 female) and 20 healthy controls (age: 40.65 ± 9.76 years, 7 female). FIELD STRENGTH/SEQUENCES: A 3 T, MS-dMRI using a single-shot echo planar imaging sequence. ASSESSMENT: MS-dMRI was acquired at baseline for the NPC patients and healthy controls, at 0-3 (acute, AC), 6 (early delayed, ED) and 12 months (late delayed, LD) after RT for the NPC patients. The mean and maximum radiation doses to the temporal lobe were acquired. The quality of images was reviewed. MS-dMRI was analyzed using tract-based spatial statistics (TBSS). The presentations of injury were defined by the findings of TBSS. STATISTICAL TESTS: Chi-square, t tests, repeated ANOVA, and Spearman-rank correlation analysis were used. P < 0.05 was considered to be statistically significant. RESULTS: TBSS showed two WM injuries (injuries 1 and 2). Injury 1 emerged in the ED phase in the bilateral temporal poles and persisted throughout the ED and LD phases. Injury 2 developed from the AC to ED phase in the bilateral hemisphere and partially recovered in the LD phase. In the ED and LD phases, the multiple diffusion metrics were well correlated (r > 0.5 or <-0.5) with the RT dose, especially in the WM tracts in the temporal lobes. DATA CONCLUSION: Disparate WM injuries were observed in NPC patients after RT. The injuries may be primarily or secondarily induced by radiation. Injury 1 may be irreversible, while injury 2 seems to partially recover. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 4.

Cholecystokinin receptor antagonist challenge elicits brain-wide functional connectome modulation with micronetwork hippocampal decreased calcium transients.

The cortical distribution and functional role of cholecystokinin (CCK) are largely unknown. Here, a CCK receptor antagonist challenge paradigm was developed to assess functional connectivity and neuronal responses. Structural-functional magnetic resonance imaging and calcium imaging were undertaken in environmental enrichment (EE) and standard environment (SE) groups (naïve adult male mice, n = 59, C57BL/B6J, P = 60). Functional connectivity network-based statistics and pseudo-demarcation Voronoi tessellations to cluster calcium signals were used to derive region of interest metrics based on calcium transients, firing rate, and location. The CCK challenge elicited robust changes to structural-functional networks, decreased neuronal calcium transients, and max firing rate (5 s) of dorsal hippocampus in SE mice. However, the functional changes were not observed in EE mice, while the decreased neuronal calcium transients and max firing rate (5 s) were similar to SE mice. Decreased gray matter alterations were observed in multiple brain regions in the SE group due to CCK challenge, while no effect was observed in the EE group. The networks most affected by CCK challenge in SE included within isocortex, isocortex to olfactory, isocortex to striatum, olfactory to midbrain, and olfactory to thalamus. The EE group did not experience network changes in functional connectivity due to CCK challenge. Interestingly, calcium imaging revealed a significant decrease in transients and max firing rate (5 s) in the dorsal CA1 hippocampus subregion after CCK challenge in EE. Overall, CCK receptor antagonists affected brain-wide structural-functional connectivity within the isocortex, in addition to eliciting decreased neuronal calcium transients and max firing rate (5 s) in CA1 of the hippocampus. Future studies should investigate the CCK functional networks and how these processes affect isocortex modulation. Significance Statement  Cholecystokinin is a neuropeptide predominately found in the gastrointestinal system. Albeit abundantly expressed in neurons, the role and distribution of cholecystokinin are largely unknown. Here, we demonstrate cholecystokinin affects brain-wide structural-functional networks within the isocortex. In the hippocampus, the cholecystokinin receptor antagonist challenge decreases neuronal calcium transients and max firing rate (5 s) in CA1. We further demonstrate that mice in environmental enrichment do not experience functional network changes to the CCK receptor antagonist challenge. Environmental enrichment may afford protection to the alterations observed in control mice due to CCK. Our results suggest that cholecystokinin is distributed throughout the brain, interacts in the isocortex, and demonstrates an unexpected functional network stability for enriched mice.

3D-EPI blip-up/down acquisition (BUDA) with CAIPI and joint Hankel structured low-rank reconstruction for rapid distortion-free high-resolution T 2 * mapping.

PURPOSE: This work aims to develop a novel distortion-free 3D-EPI acquisition and image reconstruction technique for fast and robust, high-resolution, whole-brain imaging as well as quantitative T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. METHODS: 3D Blip-up and -down acquisition (3D-BUDA) sequence is designed for both single- and multi-echo 3D gradient recalled echo (GRE)-EPI imaging using multiple shots with blip-up and -down readouts to encode B0 field map information. Complementary k-space coverage is achieved using controlled aliasing in parallel imaging (CAIPI) sampling across the shots. For image reconstruction, an iterative hard-thresholding algorithm is employed to minimize the cost function that combines field map information informed parallel imaging with the structured low-rank constraint for multi-shot 3D-BUDA data. Extending 3D-BUDA to multi-echo imaging permits T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. For this, we propose constructing a joint Hankel matrix along both echo and shot dimensions to improve the reconstruction. RESULTS: Experimental results on in vivo multi-echo data demonstrate that, by performing joint reconstruction along with both echo and shot dimensions, reconstruction accuracy is improved compared to standard 3D-BUDA reconstruction. CAIPI sampling is further shown to enhance image quality. For T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping, parameter values from 3D-Joint-CAIPI-BUDA and reference multi-echo GRE are within limits of agreement as quantified by Bland-Altman analysis. CONCLUSIONS: The proposed technique enables rapid 3D distortion-free high-resolution imaging and T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. Specifically, 3D-BUDA enables 1-mm isotropic whole-brain imaging in 22 s at 3T and 9 s on a 7T scanner. The combination of multi-echo 3D-BUDA with CAIPI acquisition and joint reconstruction enables distortion-free whole-brain T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping in 47 s at 1.1 × 1.1 × 1.0 mm3 resolution.

Multi-Parametric MRI for Evaluating Variations in Renal Structure, Function, and Endogenous Metabolites in an Animal Model With Acute Kidney Injury Induced by Ischemia Reperfusion.

BACKGROUND: Ischemia reperfusion injury (IRI)-induced acute kidney injury (AKI) may occur after renal ischemic injury. There is a lack of an accurate and comprehensive detection technique for IRI-AKI. PURPOSE: To longitudinally evaluate IRI-AKI in rats by renal structure, function, and metabolites using multi-parametric MRI (mpMRI). STUDY TYPE: Prospective. ANIMAL MODEL: Forty-eight rats undergoing IRI-AKI. FIELD STRENGTH/SEQUENCE: 7-T, T1 mapping, and arterial spin labeling (ASL): echo planar imaging (EPI) sequence; blood oxygen level-dependent (BOLD): gradient recalled echo (GRE) sequence; T2 mapping, quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST): rapid acquisition with relaxation enhancement (RARE) sequence. ASSESSMENT: The mpMRI for IRI-AKI was conducted at 0 (control), 1, 3, 7, 14, and 28 days, all included eight rats. The longitudinal mpMRI signal of manually outlined cortex, outer stripe of the outer medulla (OSOM), inner stripe of the outer medulla, and medulla plus pelvis were calculated and compared, their diagnosis performance for IRI-AKI also been evaluated. STATISTICAL TESTS: Pearson correlations analysis for correlation between mpMRI signal and renal injury, unpaired t-tests for comparing the signal changes, and receiver operating characteristics (ROC) analysis was used to identify most sensitive indicator of mpMRI. A P-value <0.05 was considered statistically significant. RESULTS: Compared with control kidneys, the T1 and T2 values of the cortex and medulla in IRI kidneys increased and reached their highest values on day 14, and the kidneys also showed the most severe edema and segments blurred. The RBF in the cortex and OSOM showed a significant decline after day 3. The BOLD signal in the OSOM largest increased on day 28. The cortical PSR and the amine-CEST both decreased with IRI-AKI progression, and amine-CEST achieved the highest AUC for the diagnosis (0.899). DATA CONCLUSION: Multi-parametric MRI may show comprehensive variations in IRI-AKI, and amine-CEST may exhibit the highest accuracy for diagnosis of IRI-AKI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

MRI Deep Learning-Based Automatic Segmentation of Interventricular Septum for Black-Blood Myocardial T2* Measurement in Thalassemia.

BACKGROUND: The T2* value of interventricular septum is routinely reported for grading myocardial iron load in thalassemia major, and automatic segmentation of septum could shorten analysis time and reduce interobserver variability. PURPOSE: To develop a deep learning-based method for automatic septum segmentation from black-blood MR images for the myocardial T2* measurement of thalassemia patients. STUDY TYPE: Retrospective. POPULATION/SUBJECTS: One hundred forty-six transfusion-dependent thalassemia patients with cardiac MR examinations from two centers. Data from Center 1 (1.5 T) were assigned to the training (100 examinations) and internal testing (20 examinations) sets; data from Center 2 were assigned to the external testing set (26 examinations; 10 at 1.5 T and 16 at 3.0 T). FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T, multiecho gradient-echo sequence. ASSESSMENT: A modified attention U-Net for septum segmentation was constructed and trained, and its performance evaluated on unseen internal and external datasets. T2* was measured by fitting the average septum signal, separately segmented by automatic and manual methods. STATISTICAL TESTS: Agreement between manual and automatic septum segmentations was assessed with the Dice coefficient, and T2* agreement was assessed using the Bland-Altman plot and the coefficient of variation (CoV). RESULTS: The median Dice coefficient of deep network-based septum segmentation was 0.90 [0.05] on the internal dataset, 0.82 [0.10] on the external 1.5 T dataset, and 0.86 [0.14] on the external 3.0 T dataset. T2* measurements using automatic segmentation corresponded with those from manual segmentation, with a mean difference of 0.02 (95% LoA: -0.74 to 0.79) msec, 0.43 (95% LoA: -2.1 to 3.0) msec, and 0.36 (95% LoA: -0.72 to 1.4) msec on the three datasets. The CoVs between the two methods were 3.1%, 7.0%, and 6.1% on the internal and two external datasets, respectively. DATA CONCLUSIONS: The proposed septum segmentation yielded myocardial T2* measurements which were highly consistent with those obtained by manual segmentation. This automatic approach may facilitate data processing and avoid operator-dependent variability in practice. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Environmental enrichment leads to behavioral circadian shifts enhancing brain-wide functional connectivity between sensory cortices and eliciting increased hippocampal spiking.

Environmental enrichment induces widespread neuronal changes, but the initiation of the cascade is unknown. We ascertained the critical period of divergence between environmental enriched (EE) and standard environment (SE) mice using continuous infrared (IR) videography, functional magnetic resonance imaging (fMRI), and neuron level calcium imaging. Naïve adult male mice (n = 285, C57BL/6J, postnatal day 60) were divided into SE and EE groups. We assessed the linear time-series of motion activity using a novel structural break test which examined the dataset for change in circadian and day-by-day motion activity. fMRI was used to map brain-wide response using a functional connectome analysis pipeline. Awake calcium imaging was performed on the dorsal CA1 pyramidal layer. We found the preeminent behavioral feature in EE was a forward shift in the circadian rhythm, prolongation of activity in the dark photoperiod, and overall decreased motion activity. The crepuscular period of dusk was seen as the critical period of divergence between EE and SE mice. The functional processes at dusk in EE included increased functional connectivity in the visual cortex, motor cortex, retrosplenial granular cortex, and cingulate cortex using seed-based analysis. Network based statistics found a modulated functional connectome in EE concentrated in two hubs: the hippocampal formation and isocortical network. These hubs experienced a higher node degree and significant enhanced edge connectivity. Calcium imaging revealed increased spikes per second and maximum firing rate in the dorsal CA1 pyramidal layer, in addition to location (anterior-posterior and medial-lateral) effect size differences between EE and SE. The emergence of functional-neuronal changes due to enrichment consisted of enhanced hippocampal-isocortex functional connectivity and CA1 neuronal increased spiking linked to a circadian shift during the dusk period. Future studies should explore the molecular consequences of enrichment inducing shifts in the circadian period.

Early detection of increased marrow adiposity with age in rats using Z-spectral MRI at ultra-high field (7 T).

BACKGROUND: Nowadays, the drive towards high-field MRI is fueled by the pursuit of higher signal-to-noise ratio, spatial resolution, and imaging speed. However, high field strength is associated with field inhomogeneity, acceleration of T2 * decay, and increased chemical shift, which may pose challenges to conventional MRI for fat quantification in complex tissues such as bone marrow. With proton MRI spectroscopy (1 H-MRS), on the other hand, it is difficult to produce high resolution. As a novel alternative fat quantification method, high-resolution Z-spectral MRI (ZS-MRI) can achieve fat quantification by acquiring direct saturated images of both fat and water under the same TE , which may be less affected by T2 * decay and field inhomogeneity. PURPOSE: To demonstrate ZS-MRI for marrow adipose tissue (MAT) quantification in rat's lumbar spine and the early detection of MAT changes with age. METHODS: The accuracy of ZS-MRI for fat quantification at ultra-high-field MRI (7 T) was verified with MRS and conventional Dixon MRI in water-oil mixed phantoms with varying fat fraction (FF). Dixon MRI data were processed with iterative decomposition of water and fat with echo asymmetry and least-squares estimation. ZS-MRI was then used to longitudinally monitor the adiposity in the lumbar spine of young healthy rats at 13, 17, and 21 weeks to detect the early changes of FF with age in MAT. Hematoxylin-eosin staining of lumbar spines from separated rat groups was performed for verification. RESULTS: In ex vivo phantom experiments, both Dixon MRI and ZS-MRI were well correlated with 1 H-MRS for the quantification of FF at 7 T (R > 0.99). Compared with Dixon MRI, ZS-MRI showed reduced image artifacts due to field inhomogeneity and presented better agreement with 1 H-MRS for the early detection of increased MAT due to age at 7 T (ZS-MRI R = 0.78 versus Dixon MRI R = 0.34). The increased MAT FF due to age was confirmed by histology. CONCLUSION: ZS-MRI proves itself as an alternative fat quantification method for bone marrow in rats at 7 T.

Diffusion-weighted magnetic resonance imaging in rat kidney using two-dimensional navigated, interleaved echo-planar imaging at 7.0 T.

The purpose of this study was to investigate the feasibility of two-dimensional (2D) navigated, interleaved multishot echo-planar imaging (EPI) to enhance kidney diffusion-weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four-shot EPI with 2D navigators was tailored for kidney DWI (Sprague-Dawley rats, n = 7) on a 7.0-T small bore preclinical scanner. The image quality of four-shot EPI was compared with T2 -weighted rapid acquisition with relaxation enhancement (RARE) (reference) and single-shot EPI (ss-EPI) without and with parallel imaging (PI). The contrast-to-noise ratio (CNR) was examined to assess the image quality for the EPI approaches. The Dice similarity coefficient and the Hausdorff distance were used for evaluation of image distortion. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for renal cortex and medulla for all DWI approaches. The corticomedullary difference of MD and FA were assessed by Wilcoxon signed-rank test. Four-shot EPI showed the highest CNR among the three EPI variants and lowest geometric distortion versus T2 -weighted RARE (mean Dice: 0.77 for ss-EPI without PI, 0.88 for ss-EPI with twofold undersampling, and 0.92 for four-shot EPI). The FA map derived from four-shot EPI clearly identified a highly anisotropic region corresponding to the inner stripe of the outer medulla. Four-shot EPI successfully discerned differences in both MD and FA between renal cortex and medulla. In conclusion, 2D navigated, interleaved multishot EPI facilitates high-quality rat kidney DWI with clearly depicted intralayer and interlayer structure and substantially reduced image distortion. This approach enables the anatomic integrity of DWI-MRI in small rodents and has the potential to benefit the characterization of renal microstructure in preclinical studies.

Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.

OBJECTIVES: Develop and evaluate a deep learning-based automatic meningioma segmentation method for preoperative meningioma differentiation using radiomic features. METHODS: A retrospective multicentre inclusion of MR examinations (T1/T2-weighted and contrast-enhanced T1-weighted imaging) was conducted. Data from centre 1 were allocated to training (n = 307, age = 50.94 ± 11.51) and internal testing (n = 238, age = 50.70 ± 12.72) cohorts, and data from centre 2 external testing cohort (n = 64, age = 48.45 ± 13.59). A modified attention U-Net was trained for meningioma segmentation. Segmentation accuracy was evaluated by five quantitative metrics. The agreement between radiomic features from manual and automatic segmentations was assessed using intra class correlation coefficient (ICC). After univariate and minimum-redundancy-maximum-relevance feature selection, L1-regularized logistic regression models for differentiating between low-grade (I) and high-grade (II and III) meningiomas were separately constructed using manual and automatic segmentations; their performances were evaluated using ROC analysis. RESULTS: Dice of meningioma segmentation for the internal testing cohort were 0.94 ± 0.04 and 0.91 ± 0.05 for tumour volumes in contrast-enhanced T1-weighted and T2-weighted images, respectively; those for the external testing cohort were 0.90 ± 0.07 and 0.88 ± 0.07. Features extracted using manual and automatic segmentations agreed well, for both the internal (ICC = 0.94, interquartile range: 0.88-0.97) and external (ICC = 0.90, interquartile range: 0.78-70.96) testing cohorts. AUC of radiomic model with automatic segmentation was comparable with that of the model with manual segmentation for both the internal (0.95 vs. 0.93, p = 0.176) and external (0.88 vs. 0.91, p = 0.419) testing cohorts. CONCLUSIONS: The developed deep learning-based segmentation method enables automatic and accurate extraction of meningioma from multiparametric MR images and can help deploy radiomics for preoperative meningioma differentiation in clinical practice. KEY POINTS: • A deep learning-based method was developed for automatic segmentation of meningioma from multiparametric MR images. • The automatic segmentation method enabled accurate extraction of meningiomas and yielded radiomic features that were highly consistent with those that were obtained using manual segmentation. • High-grade meningiomas were preoperatively differentiated from low-grade meningiomas using a radiomic model constructed on features from automatic segmentation.

Joint calibrationless reconstruction of highly undersampled multicontrast MR datasets using a low-rank Hankel tensor completion framework.

PURPOSE: To jointly reconstruct highly undersampled multicontrast two-dimensional (2D) datasets through a low-rank Hankel tensor completion framework. METHODS: A multicontrast Hankel tensor completion (MC-HTC) framework is proposed to exploit the shareable information in multicontrast datasets with respect to their highly correlated image structure, common spatial support, and shared coil sensitivity for joint reconstruction. This is achieved by first organizing multicontrast k-space datasets into a single block-wise Hankel tensor. Subsequent low-rank tensor approximation via higher-order singular value decomposition (HOSVD) uses the image structural correlation by considering different contrasts as virtual channels. Meanwhile, the HOSVD imposes common spatial support and shared coil sensitivity by treating data from different contrasts as from additional k-space kernels. The missing k-space data are then recovered by iteratively performing such low-rank approximation and enforcing data consistency. This joint reconstruction framework was evaluated using multicontrast multichannel 2D human brain datasets (T1 -weighted, T2 -weighted, fluid-attenuated inversion recovery, and T1 -weighted-inversion recovery) of identical image geometry with random and uniform undersampling schemes. RESULTS: The proposed method offered high acceleration, exhibiting significantly less residual errors when compared with both single-contrast SAKE (simultaneous autocalibrating and k-space estimation) and multicontrast J-LORAKS (joint parallel-imaging-low-rank matrix modeling of local k-space neighborhoods) low-rank reconstruction. Furthermore, the MC-HTC framework was applied uniquely to Cartesian uniform undersampling by incorporating a novel complementary k-space sampling strategy where the phase-encoding direction among different contrasts is orthogonally alternated. CONCLUSION: The proposed MC-HTC approach presents an effective tensor completion framework to jointly reconstruct highly undersampled multicontrast 2D datasets without coil-sensitivity calibration.

Calibrationless parallel imaging reconstruction for multislice MR data using low-rank tensor completion.

PURPOSE: To provide joint calibrationless parallel imaging reconstruction of highly accelerated multislice 2D MR k-space data. METHODS: Adjacent image slices in multislice MR data have similar coil sensitivity maps, spatial support, and image content. Such similarities can be utilized to improve image quality by reconstructing multiple slices jointly with low-rank tensor completion. Specifically, the multichannel k-space data from multiple slices are constructed into a block-wise Hankel tensor and iteratively updated by promoting tensor low-rankness through higher-order SVD. This multislice block-wise Hankel tensor completion was implemented for 2D spiral and Cartesian k-space undersampling where sampling patterns vary between adjacent slices. The approach was evaluated with human brain MR data and compared to the traditional single-slice simultaneous autocalibrating and k-space estimation reconstruction. RESULTS: The proposed multislice block-wise Hankel tensor completion approach robustly reconstructed highly undersampled multislice 2D spiral and Cartesian data. It produced substantially lower level of artifacts compared to the traditional single-slice simultaneous autocalibrating and k-space estimation reconstruction. Quantitative evaluation using error maps and root mean square error demonstrated its significantly improved performance in terms of residual artifacts and root mean square error. CONCLUSION: Our proposed multislice block-wise Hankel tensor completion method exploits the similar coil sensitivity and image content within multislice MR data through a tensor completion framework. It offers a new and effective approach to acquire and reconstruct highly undersampled multislice MR data in a calibrationless manner.

Physiological system analysis of the kidney by high-temporal-resolution T2∗ monitoring of an oxygenation step response.

PURPOSE: Examine the feasibility of characterizing the regulation of renal oxygenation using high-temporal-resolution monitoring of the T2∗ response to a step-like oxygenation stimulus. METHODS: For T2∗ mapping, multi-echo gradient-echo imaging was used (temporal resolution = 9 seconds). A step-like renal oxygenation challenge was applied involving sequential exposure to hyperoxia (100% O2 ), hypoxia (10% O2 + 90% N2 ), and hyperoxia (100% O2 ). In vivo experiments were performed in healthy rats (N = 10) and in rats with bilateral ischemia-reperfusion injury (N = 4). To assess the step response of renal oxygenation, a second-order exponential model was used (model parameters: amplitude [A], time delay [Δt], damping constant [D], and period of the oscillation [T]) for renal cortex, outer stripe of the outer medulla, inner stripe of the outer medulla, and inner medulla. RESULTS: The second-order exponential model permitted us to model the exponential T2∗ recovery and the superimposed T2∗ oscillation following renal oxygenation stimulus. The in vivo experiments revealed a difference in Douter medulla between healthy controls (D < 1, indicating oscillatory recovery) and ischemia-reperfusion injury (D > 1, reflecting aperiodic recovery). The increase in Douter medulla by a factor of 3.7 (outer stripe of the outer medulla) and 10.0 (inner stripe of the outer medulla) suggests that this parameter might be rather sensitive to (patho)physiological oxygenation changes. CONCLUSION: This study demonstrates the feasibility of monitoring the dynamic oxygenation response of renal tissues to a step-like oxygenation challenge using high-temporal-resolution T2∗ mapping. Our results suggest that the implemented system analysis approach may help to unlock questions regarding regulation of renal oxygenation, with the ultimate goal of providing imaging means for diagnostics and therapy of renal diseases.

Detection of gadolinium deposition in cortical bone with ultrashort echo time T1 mapping: an ex vivo study in a rabbit model.

OBJECTIVES: To investigate the capacity of ultrashort echo time (UTE) T1 mapping to non-invasively assess gadolinium deposition in cortical bone after gadolinium-based contrast agent (GBCA) administration. METHODS: Twenty-eight New Zealand rabbits (male, 3.0-3.5 kg) were randomly allocated into control, macrocyclic, high-dose macrocyclic, and linear GBCA groups (n = 7 for each group), and respectively given daily doses of 0.9 ml/kg bodyweight saline, 0.3 mmol/kg bodyweight gadobutrol, 0.9 mmol/kg bodyweight gadobutrol, and 0.3 mmol/kg bodyweight gadopentetate dimeglumine for five consecutive days per week over a period of 4 weeks. After a subsequent 4 weeks of recovery, the rabbits were sacrificed and their tibiae harvested. T1 value of cortical bone was measured using a combination of UTE actual flip angle imaging and variable repetition time on a 7T animal scanner. Gadolinium concentration in cortical bone was measured using inductively coupled plasma mass spectrometry (ICP-MS). Pearson's correlation between R1 value (R1 = 1/T1) and gadolinium concentration in cortical bone was assessed. RESULTS: Bone T1 values were significantly lower in the lower-dose macrocyclic (329.2 ± 21.0 ms, p < 0.05), higher-dose macrocyclic (316.8 ± 21.7 ms, p < 0.01), and linear (296.8 ± 24.1 ms, p < 0.001) GBCA groups compared with the control group (356.3 ± 19.4 ms). Gadolinium concentrations measured by ICP-MS in the control, lower-dose macrocyclic, higher-dose macrocyclic, and linear GBCA groups were 0.04 ± 0.02 µg/g, 2.60 ± 0.48 µg/g, 4.95 ± 1.17 µg/g, and 13.62 ± 1.55 µg/g, respectively. There was a strong positive correlation between R1 values and gadolinium concentrations in cortical bone (r = 0.73, p < 0.001). CONCLUSIONS: These results suggest that UTE T1 mapping has the potential to provide a non-invasive assessment of gadolinium deposition in cortical bone following GBCA administration. KEY POINTS: • Changes in T1 value related to gadolinium deposition were found in bone after both linear and macrocyclic GBCA administrations. • R1 relaxometry correlates strongly with gadolinium concentration in cortical bone. • UTE T1 mapping provides a potential tool for non-invasively monitoring gadolinium deposition in cortical bone.

C-X-C motif chemokine receptor 4 aggravates renal fibrosis through activating JAK/STAT/GSK3ß/ß-catenin pathway.

Chronic kidney disease (CKD) has a high prevalence worldwide. Renal fibrosis is the common pathological feature in various types of CKD. However, the underlying mechanisms are not determined. Here, we adopted different CKD mouse models and cultured human proximal tubular cell line (HKC-8) to examine the expression of C-X-C motif chemokine receptor 4 (CXCR4) and ß-catenin signalling, as well as their relationship in renal fibrosis. In CKD mice and humans with a variety of nephropathies, CXCR4 was dramatically up-regulated in tubules, with a concomitant activation of ß-catenin. CXCR4 expression level was positively correlated with the expression of ß-catenin target MMP-7. AMD3100, a CXCR4 receptor blocker, and gene knockdown of CXCR4 significantly inhibited the activation of JAK/STAT and ß-catenin signalling, protected against tubular injury and renal fibrosis. CXCR4-induced renal fibrosis was inhibited by treatment with ICG-001, an inhibitor of ß-catenin signalling. In HKC-8 cells, overexpression of CXCR4 induced activation of ß-catenin and deteriorated cell injury. These effects were inhibited by ICG-001. Stromal cell-derived factor (SDF)-1α, the ligand of CXCR4, stimulated the activation of JAK2/STAT3 and JAK3/STAT6 signalling in HKC-8 cells. Overexpression of STAT3 or STAT6 decreased the abundance of GSK3ß mRNA. Silencing of STAT3 or STAT6 significantly blocked SDF-1α-induced activation of ß-catenin and fibrotic lesions. These results uncover a novel mechanistic linkage between CXCR4 and ß-catenin activation in renal fibrosis in association with JAK/STAT/GSK3ß pathway. Our studies also suggest that targeted inhibition of CXCR4 may provide better therapeutic effects on renal fibrosis by inhibiting multiple downstream signalling cascades.

Sensory evoked fMRI paradigms in awake mice.

Mouse fMRI has become increasingly popular in the small animal imaging field. However, compared to the more commonly used rat fMRI, it is challenging for mouse fMRI to obtain robust and specific functional imaging results. In the meantime, in other neuroscience modalities such as optical imaging, functional recording in the awake mice is common and becoming standard. Therefore, in the current study we developed comprehensive setups and analysis pipeline for multi-sensory fMRI paradigms in the awake mice. Customized setups of somatosensory (whisker), auditory and olfactory stimulation were developed for use in the cryogenic coil in the awake mouse fMRI setting. After carefully evaluating head motion and motion artefacts, the nuisance regression approach was optimized for reducing the confounding effect of motion. The high temporal resolution data (TR = 0.35 s) revealed fast temporal dynamics (time-to-peak ~2 s) of evoked BOLD responses in most brain regions. Using the derived awake mouse specific hemodynamic response functions, high spatial resolution data revealed robust, specific and consistent cortical and subcortical activations in response to somatosensory, auditory and olfactory stimulations, respectively. Overall, we present comprehensive methods for acquiring and analyzing sensory evoked awake mouse fMRI data. The establishment of multi-sensory paradigms in awake mouse fMRI provides valuable tools for examining spatiotemporal characteristics and neural mechanisms of BOLD signals in the future.

Non-Gaussian Diffusion Models and T1 rho Quantification in the Assessment of Hepatic Sinusoidal Obstruction Syndrome in Rats.

BACKGROUND: Non-Gaussian diffusion models and T1 rho quantification may reflect the changes in tissue heterogeneity in hepatic sinusoidal obstruction syndrome (SOS). PURPOSE: To investigate the feasibility of diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and T1 rho quantification in detecting and staging SOS in a monocrotaline (MCT)-induced rat model. STUDY TYPE: Animal study. POPULATION: Thirty male Sprague-Dawley rats gavaged with MCT to induce hepatic SOS and six male rats without any intervention. FIELD STRENGTH/SEQUENCE: 3.0T, DWI with five b-values (0-2000 s/mm2 ) and T1 rho with five spin lock times (1-60 msec). ASSESSMENT: MRI was performed 1 day before and 1, 3, 5, 7, and 10 days after MCT administration. The corrected apparent diffusion coefficient (Dapp ), kurtosis coefficient (Kapp ), distributed diffusion coefficient (DDC), and intravoxel water molecular diffusion heterogeneity (α) were calculated from the corresponding non-Gaussian diffusion model. The T1 rho value was calculated using a monoexponential model. Specimens obtained from the six timepoints were categorized into normal liver (n = 6), early-stage (n = 16), and late-stage (n = 14) SOS in accordance with the pathological score. STATISTICAL TESTS: Parametric statistical methods and receiver operating characteristic (ROC) curves were employed to determine diagnostic accuracy. RESULTS: The Dapp , Kapp , DDC, α, and T1 rho values were correlated with pathological score with r values of -0.821, 0.726, -0.828, -0.739, and 0.714 (all P < 0.001), respectively. DKI (combined Dapp and Kapp ) and SEM (combined DDC and α) were better than T1 rho for staging SOS. The areas under the ROC curve of DKI, SEM, and T1 rho for differentiating normal liver and early-stage SOS were 0.97, 1.00, and 0.79, whereas those of DKI, SEM, and T1 rho for differentiating early-stage and late-stage SOS were 1.00, 0.97, and 0.92, respectively. DATA CONCLUSION: DKI, SEM, and T1 rho may be helpful in staging SOS. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1110-1121.

Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI.

BACKGROUND: It is difficult to prospectively differentiate between benign (World Health Organization [WHO] I) and nonbenign (WHO II and III) meningiomas. PURPOSE: To evaluate the feasibility of preoperative differentiation between benign and nonbenign meningiomas by using texture analysis from multiparametric MR data. STUDY TYPE: Retrospective. SUBJECTS: In all, 184 patients with meningioma (139 benign and 45 nonbenign) were included as the training cohort and 79 patients with meningioma (60 benign and 19 nonbenign) were included as the external validation cohort. FIELD STRENGTH/SEQUENCE: T1 -weighted, T2 -weighted, and contrast-enhanced T1 -weighted imaging were performed on 1.5 or 3.0T MR systems from two centers. ASSESSMENT: Tumor segmentation and radiological characteristic (RC) evaluation were performed by experienced radiologists. The texture features were extracted from preprocessed images and combined with RCs, and then the combined features were reduced by using a two-step feature selection. Three single-sequence models and a multiparametric MRI (the combination of single sequences) model were constructed and then evaluated with the external validation cohort. STATISTICAL TESTS: Area under receiver operating characteristic curve (AUC), accuracy (Acc), f1-score (F1), sensitivity (Sen), and specificity (Spec), were calculated to quantify the performance of the models. RESULTS: Among the four texture models, the multiparametric MRI model demonstrated the best performance for differentiating between benign and nonbenign meningiomas in both the training and external validation cohorts (AUC 0.91, Acc 89%, F1 0.88, Sen 0.93, and Spec 0.87 in the training cohort; AUC 0.83, Acc 80%, F1 0.77, Sen 0.84, and Spec 0.78 in the validation cohort). DATA CONCLUSION: Nonbenign meningiomas might be preoperatively differentiated from benign meningiomas by using texture analysis from multiparametric MR data. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1810-1820.

Differential coupling between subcortical calcium and BOLD signals during evoked and resting state through simultaneous calcium fiber photometry and fMRI.

Task based and resting state fMRI has been widely utilized to study brain functions. As the foundation of fMRI, the underlying neural basis of the BOLD signal has been extensively studied, but the detailed mechanism remains elusive, particularly during the resting state. To examine the neurovascular coupling, it is important to simultaneously record neural and vascular signals. Here we developed a novel setup of camera based, scalable simultaneous calcium fiber photometry and fMRI in rats. Using this setup, we recorded calcium signals of superior colliculus (SC) and lateral geniculate nucleus (LGN) and fMRI simultaneously during visual stimulation and the resting state. Our results revealed robust, region-specific coupling between calcium and BOLD signals in the task state and weaker, whole brain correlation in the resting state. Interestingly, the spatial specificity of such correlation in the resting state was improved upon regression of white matter, ventricle signals and global signals in fMRI data. Overall, our results suggest differential coupling of calcium and BOLD signals for subcortical regions between evoked and resting states, and the coupling relationship in the resting state was related with resting state BOLD preprocessing strategies.

MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.

PURPOSE: To develop a machine learning approach using convolutional neural network for reducing MRI Gibbs-ringing artifact. THEORY AND METHODS: Gibbs-ringing artifact in MR images is caused by insufficient sampling of the high frequency data. Existing methods exploit smooth constraints to reduce intensity oscillations near sharp edges at the cost of blurring details. In this work, we developed a machine learning approach for removing the Gibbs-ringing artifact from MR images. The ringing artifact was extracted from the original image using a deep convolutional neural network and then subtracted from the original image to obtain the artifact-free image. Finally, its low-frequency k-space data were replaced with measured counterparts to enforce data fidelity further. We trained the convolutional neural network using 17,532 T2-weighted (T2W) normal brain images and evaluated its performance on T2W images of normal and tumor brains, diffusion-weighted brain images, and T2W knee images. RESULTS: The proposed method effectively removed the ringing artifact without noticeable smoothing in T2W and diffusion-weighted images. Quantitatively, images produced by the proposed method were closer to the fully-sampled reference images in terms of the root-mean-square error, peak signal-to-noise ratio, and structural similarity index, compared with current state-of-the-art methods. CONCLUSION: The proposed method presents a novel and effective approach for Gibbs-ringing reduction in MRI. The convolutional neural network-based approach is simple, computationally efficient, and highly applicable in routine clinical MRI.