Isotropic Resolution Research Articles

Ultrahigh Resolution fMRI at 7T Using Radial-Cartesian TURBINE Sampling.

PurposeWe investigate the use of TURBINE, a 3D radial‐Cartesian acquisition scheme in which EPI planes are rotated about the phase‐encoding axis to acquire a cylindrical k‐space for high‐fidelity ultrahigh isotropic resolution fMRI at 7 Tesla with minimal distortion and blurring.MethodsAn improved, completely self‐navigated version of the TURBINE sampling scheme was designed for fMRI at 7 Telsa. To demonstrate the image quality and spatial specificity of the acquisition, thin‐slab visual and motor BOLD fMRI at 0.67 mm isotropic resolution (16 mm slab, TRvol = 2.32 s), and 0.8 × 0.8 × 2.0 mm (whole‐brain, TRvol = 2.4 s) data were acquired. To prioritize the high spatial fidelity, we employed a temporally regularized reconstruction to improve sensitivity without any spatial bias.ResultsTURBINE images provide high structural fidelity with almost no distortion, dropout, or T2* blurring for the thin‐slab acquisitions compared to conventional 3D EPI owing to the radial sampling in‐plane and the short echo train used. This results in activation that can be localized to pre‐ and postcentral gyri in a motor task, for example, with excellent correspondence to brain structure measured by a T1‐MPRAGE. The benefits of TURBINE (low distortion, dropout, blurring) are reduced for the whole‐brain acquisition due to the longer EPI train. We demonstrate robust BOLD activation at 0.67 mm isotropic resolution (thin‐slab) and also anisotropic 0.8 × 0.8 × 2.0 mm (whole‐brain) acquisitions.ConclusionTURBINE is a promising acquisition approach for high‐resolution, minimally distorted fMRI at 7 Tesla and could be particularly useful for fMRI in areas of high B0 inhomogeneity.

3D Transcranial Ultrasound Localization Microscopy in the Rat Brain With a Multiplexed Matrix Probe.

Ultrasound Localization Microscopy (ULM) provides images of the microcirculation in-depth in living tissue. However, its implementation in two-dimension is limited by the elevation projection and tedious plane-by-plane acquisition. Volumetric ULM alleviates these issues and can map the vasculature of entire organs in one acquisition with isotropic resolution. However, its optimal implementation requires many independent acquisition channels, leading to complex custom hardware. In this article, we implemented volumetric ultrasound imaging with a multiplexed 32 × 32 probe driven by a single commercial ultrasound scanner. We propose and compare three different sub-aperture multiplexing combinations for localization microscopy in silico and in vitro with a flow of microbubbles in a canal. Finally, we evaluate the approach for micro-angiography of the rat brain. The "light" combination allows a higher maximal volume rate than the "full" combination while maintaining the field of view and resolution. In the rat brain, 100,000 volumes were acquired within 7 min with a dedicated ultrasound sequence and revealed vessels down to 31 μm in diameter with flows from 4.3 mm/s to 28.4 mm/s. This work demonstrates the ability to perform a complete angiography with unprecedented resolution in the living rat's brain with a simple and light setup through the intact skull. We foresee that it might contribute to democratize 3D ULM for both preclinical and clinical studies.

Improved detection of multiple sclerosis lesions with T2-prepared double inversion recovery at 3T.

Background and PurposeDouble inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal‐to‐noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.MethodsDIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2‐preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.ResultsDIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.ConclusionsDIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon.

Single-particle analysis (SPA) by cryo-electron microscopy (cryo-EM) is now a mainstream technique for high-resolution structural biology. Structure determination by SPA relies upon obtaining multiple distinct views of a macromolecular object vitrified within a thin layer of ice. Ideally, a collection of uniformly distributed random projection orientations would amount to all possible views of the object, giving rise to reconstructions characterized by isotropic directional resolution. However, in reality, many samples suffer from preferentially oriented particles adhering to the air-water interface. This leads to non-uniform angular orientation distributions in the dataset and inhomogeneous Fourier-space sampling in the reconstruction, translating into maps characterized by anisotropic resolution. Tilting the specimen stage provides a generalizable solution to overcoming resolution anisotropy by virtue of improving the uniformity of orientation distributions, and thus the isotropy of Fourier space sampling. The present protocol describes a tilted-stage automated data collection strategy using Leginon, a software for automated image acquisition. The procedure is simple to implement, does not require any additional equipment or software, and is compatible with most standard transmission electron microscopes (TEMs) used for imaging biological macromolecules.

Magic angle effect on diffusion tensor imaging in ligament and brain

PurposeTo evaluate the magic angle effect on diffusion tensor imaging (DTI) measurements in rat ligaments and mouse brains. MethodsThree rat knee joints and three mouse brains were scanned at 9.4 T using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 μm. The b value was 1000 s/mm2 for rat knee and 4000 s/mm2 for mouse brain. DTI model was used to investigate the quantitative metrics at different orientations with respect to the main magnetic field. The collagen fiber structure of the ligament was validated with polarized light microscopy (PLM) imaging. ResultsThe signal intensity, signal-to-noise ratio (SNR), and DTI metrics in the ligament were strongly dependent on the collagen fiber orientation with respect to the main magnetic field from both simulation and actual MRI scans. The variation of fractional anisotropy (FA) was about ~32%, and the variation of mean diffusivity (MD) was ~11%. These findings were further validated with the numerical simulation at different SNRs (~10.0 to 86.0). Compared to the ligament, the DTI metrics showed little orientation dependence in mouse brains. ConclusionMagic angle effect plays an important role in DTI measurements in the highly ordered collagen-rich tissues, while MD showed less orientation dependence than FA.

Characterizing thalamic and basal ganglia nuclei in medically intractable focal epilepsy by MR fingerprinting.

Magnetic resonance fingerprinting (MRF) is a novel, quantitative, and noninvasive technique to measure brain tissue properties. We aim to use MRF for characterizing normal-appearing thalamic and basal ganglia nuclei in the epileptic brain. A three-dimensional (3D) MRF protocol (1 mm3 isotropic resolution) was acquired from 48 patients with unilateral medically intractable focal epilepsy and 39 healthy controls (HCs). Whole-brain T1 and T2 maps (containing T1 and T2 relaxation times) were reconstructed for each subject. Ten subcortical nuclei in the thalamus and basal ganglia were segmented as regions of interest (ROIs), within which the mean T1 and T2 values, as well as their coefficient of variation (CV) were compared between the patients and HCs at the group level. Subgroup and correlation analyses were performed to examine the relationship between significant MRF measures and various clinical characteristics. Using significantly abnormal MRF measures from the group-level analyses, support vector machine (SVM) and logistic regression machine learning models were built and tested with 5-fold and 10-fold cross-validations, to separate patients from HCs, and to separate patients with left-sided and right-sided epilepsy, at the individual level. MRF revealed increased T1 mean value in the ipsilateral thalamus and nucleus accumbens; increased T1 CV in the bilateral thalamus, bilateral pallidum, and ipsilateral caudate; and increased T2 CV in the ipsilateral thalamus in patients compared to HCs (p < .05, false discovery rate [FDR] corrected). The SVM classifier produced 78.2% average accuracy to separate individual patients from HCs, with an area under the curve (AUC) of 0.83. The logistic regression classifier produced 67.4% average accuracy to separate patients with left-sided and right-sided epilepsy, with an AUC of 0.72. MRF revealed bilateral tissue-property changes in the normal-appearing thalamus and basal ganglia, with ipsilateral predominance and thalamic preference, suggesting subcortical involvement/impairment in patients with medically intractable focal epilepsy. The individual-level performance of the MRF-based machine-learning models suggests potential opportunities for predicting lateralization.

Microstructure in patients with visual snow syndrome: an ultra-high field morphological and quantitative MRI study.

Visual snow syndrome is a neurological condition characterized by continuous visual disturbance and a range of non-visual symptoms, including tinnitus and migraine. Little is known about the pathological mechanisms underlying visual snow syndrome. Here, we assessed brain morphometry and microstructure in visual snow syndrome patients using high-resolution structural and quantitative MRI. Forty visual snow syndrome patients (22 with migraine) and 43 controls underwent 7-Tesla MRI (MP2RAGE, 0.75 mm isotropic resolution). Volumetric and quantitative T1 values were extracted for white and grey matter regions and compared between groups. Where regions were significantly different between groups (false discovery rate corrected for multiple comparisons), post hoc comparisons were examined between patients with and without migraine. For visual snow syndrome patients, significant MRI variables were correlated with clinical severity (number of visual symptoms, perceived visual snow intensity, disruptiveness, fatigue and quality of life) and psychiatric symptoms prevalent in visual snow syndrome (depression, anxiety and depersonalization). Finally, cortical regions and individual thalamic nuclei were studied. Compared with controls, visual snow syndrome patients demonstrated a trend towards larger brain and white matter volumes and significantly lower T1 values for the entire cortex (P < 0.001), thalamus (P = 0.001) and pallidum (P = 0.001). For the patient group, thalamic T1 correlated with number of visual symptoms (P = 0.019, r = 0.390) and perceived disruptiveness of visual snow (P = 0.010, r = 0.424). These correlations did not survive multiple comparison corrections. As for specificity in visual snow syndrome group, T1 changes were most evident in caudal regions (occipital cortices) followed by parietal, temporal and prefrontal cortices. T1 values differed between groups for most individual thalamic nuclei. No differences were revealed between patients with and without migraine. In visual snow syndrome patients, we observed no changes in morphometry, instead widespread changes in grey matter microstructure, which followed a caudal-rostral pattern and affected the occipital cortices most profoundly. Migraine did not appear to independently affect these changes. Lower T1 values may potentially result from higher neurite density, myelination or increased iron levels in the visual snow syndrome brain. Further investigation of these changes may enhance our understanding of the pathogenesis of visual snow syndrome, ultimately leading to new treatment strategies.

Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging.

PurposePatient‐induced inhomogeneities in the magnetic field cause distortions and blurring during acquisitions with long readouts such as in susceptibility‐weighted imaging (SWI). Most correction methods require collecting an additional ΔB0 field map to remove these artifacts.TheoryThe static ΔB0 field map can be approximated with an acceptable error directly from a single echo acquisition in SWI. The main component of the observed phase is linearly related to ΔB0 and the echo time (TE), and the relative impact of non‐ ΔB0 terms becomes insignificant with TE >20 ms at 3 T for a well‐tuned system.MethodsThe main step is to combine and unfold the multi‐channel phase maps wrapped many times, and several competing algorithms are compared for this purpose. Four in vivo brain data sets collected using the recently proposed 3D spreading projection algorithm for rapid k‐space sampling (SPARKLING) readouts are used to assess the proposed method.ResultsThe estimated 3D field maps generated with a 0.6 mm isotropic spatial resolution provide overall similar off‐resonance corrections compared to reference corrections based on an external ΔB0 acquisitions, and even improved for 2 of 4 individuals. Although a small estimation error is expected, no aftermath was observed in the proposed corrections, whereas degradations were observed in the references.ConclusionA static ΔB0 field map estimation method was proposed to take advantage of acquisitions with long echo times, and outperformed the reference technique based on an external field map. The difference can be attributed to an inherent robustness to mismatches between volumes and external ΔB0 maps, and diverse other sources investigated.

The new X-ray/visible microscopy MAXWELL technique for fast three-dimensional nanoimaging with isotropic resolution

Microscopy by Achromatic X-rays With Emission of Laminar Light (MAXWELL) is a new X-ray/visible technique with attractive characteristics including isotropic resolution in all directions, large-volume imaging and high throughput. An ultrathin, laminar X-ray beam produced by a Wolter type I mirror irradiates the sample stimulating the emission of visible light by scintillating nanoparticles, captured by an optical system. Three-dimensional (3D) images are obtained by scanning the specimen with respect to the laminar beam. We implemented and tested the technique with a high-brightness undulator at SPring-8, demonstrating its validity for a variety of specimens. This work was performed under the Synchrotrons for Neuroscience—an Asia–Pacific Strategic Enterprise (SYNAPSE) collaboration.

Adaptive dual-speed ultrasound and photoacoustic computed tomography

Full-ring dual-modal ultrasound and photoacoustic computed tomography has unique advantages of nearly isotropic spatial resolution, complementary contrast, deep penetration, and full-view detection. However, the imaging quality may be deteriorated by the inaccurate sound speed estimation. Automatic determining and compensation for sound speed has been a long-standing problem in image reconstruction. Here, we present new adaptive dual-speed ultrasound and photoacoustic computed tomography (ADS-USPACT) to address this challenge. The system features full-view coverage (360°), high-speed dual-modal imaging (10-Hz), automated dual sound speed correction, and synergistic high imaging quality. To correct the sound speed, we develop a two-compartment method that can automatically segment the sample boundary and search for the optimal sound speed based on the rich ultrasonic pulse-echo signals. The method does not require the operator’s intervention. We validate this technique in numerical simulation, phantom study, and in vivo experiments. The ADS-USPACT represents significant progress in dual-modal imaging.

OSCILLATE: A low-rank approach for accelerated magnetic resonance elastography.

MR elastography (MRE) is a technique to characterize brain mechanical properties in vivo. Due to the need to capture tissue deformation in multiple directions over time, MRE is an inherently long acquisition, which limits achievable resolution and use in challenging populations. The purpose of this work is to develop a method for accelerating MRE acquisition by using low-rank image reconstruction to exploit inherent spatiotemporal correlations in MRE data. The proposed MRE sampling and reconstruction method, OSCILLATE (Observing Spatiotemporal Correlations for Imaging with Low-rank Leveraged Acceleration in Turbo Elastography), involves alternating which k-space points are sampled between each repetition by a reduction factor, ROSC. Using a predetermined temporal basis from a low-resolution navigator in a joint low-rank image reconstruction, all images can be accurately reconstructed from a reduced amount of k-space data. Decomposition of MRE displacement data demonstrated that, on average, 96.1% of all energy from an MRE dataset is captured at rank L=12 (reduced from a full rank of 24). Retrospectively undersampling data with ROSC =2 and reconstructing at low-rank (L=12) yields highly accurate stiffness maps with voxel-wise error of 5.8% ± 0.7%. Prospectively undersampled data at ROSC =2 were successfully reconstructed without loss of material property map fidelity, with average global stiffness error of 1.0% ± 0.7% compared to fully sampled data. OSCILLATE produces whole-brain MRE data at 2 mm isotropic resolution in 1min 48 s.

Scan-Specific Generative Neural Network for MRI Super-Resolution Reconstruction.

The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time-consuming and costly, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) is one of the most widely used methods in MRI since it allows for the trade-off between high spatial resolution, high SNR, and reduced scan times. Deep learning has emerged for improved SRR as compared to conventional methods. However, current deep learning-based SRR methods require large-scale training datasets of high-resolution images, which are practically difficult to obtain at a suitable SNR. We sought to develop a methodology that allows for dataset-free deep learning-based SRR, through which to construct images with higher spatial resolution and of higher SNR than can be practically obtained by direct Fourier encoding. We developed a dataset-free learning method that leverages a generative neural network trained for each specific scan or set of scans, which in turn, allows for SRR tailored to the individual patient. With the SRR from three short duration scans, we achieved high quality brain MRI at an isotropic spatial resolution of 0.125 cubic mm with six minutes of imaging time for T2 contrast and an average increase of 7.2 dB (34.2%) in SNR to these short duration scans. Motion compensation was achieved by aligning the three short duration scans together. We assessed our technique on simulated MRI data and clinical data acquired from 15 subjects. Extensive experimental results demonstrate that our approach achieved superior results to state-of-the-art methods, while in parallel, performed at reduced cost as scans delivered with direct high-resolution acquisition.

High-Resolution Single Tooth MRI With an Inductively Coupled Intraoral Coil-Can MRI Compete With CBCT?

The aims of this study were to quantify T1/T2-relaxation times of the dental pulp, develop a realistic tooth model, and compare image quality between cone-beam computed tomography (CBCT) and high-resolution magnetic resonance imaging (MRI) of single teeth using a wireless inductively coupled intraoral coil. T1/T2-relaxometry was performed at 3 T in 10 healthy volunteers (283 teeth) to determine relaxation times of healthy dental pulp and develop a realistic tooth model using extracted human teeth. Eight MRI sequences (DESS, CISS, TrueFISP, FLASH, SPACE, TSE, MSVAT-SPACE, and UTE) were optimized for clinically applicable high-resolution imaging of the dental pulp. In model, image quality of all sequences was assessed quantitatively (contrast-to-noise ratio) and qualitatively (visibility of anatomical structures and extent of susceptibility artifacts using a 5-point scoring scale). Cone-beam computed tomography served as the reference modality for qualitative assessment. Statistical analysis was performed using 2-way analysis of variance, Fisher exact test, and Cohen κ. In vivo, relaxometry of dental pulps revealed T1/T2 relaxation times at 3 T of 738 ± 100/171 ± 36 milliseconds. For all sequences, an isotropic resolution of (0.21 mm) 3 was achieved, with acquisition times ranging from 6:19 to 8:02 minutes. In model, the highest contrast-to-noise ratio values were observed for UTE, followed by TSE and CISS. The best image/artifact quality, however, was found for DESS (mean ± SD: 1.3 ± 0.3/2.2 ± 0.0), FLASH (1.5 ± 0.3/2.4 ± 0.1), and CISS (1.5 ± 0.4/2.5 ± 0.1), at a level comparable to CBCT (1.2 ± 0.3/2.1 ± 0.1). Optimized MRI protocols using an intraoral coil at 3 T can achieve an image quality comparable to reference modality CBCT within clinically applicable acquisition times. Overall, DESS revealed the best results, followed by FLASH and CISS.

Fiber orientation downsampling compromises the computation of white matter tract-related deformation

Incorporating neuroimaging-revealed structural details into finite element (FE) head models opens vast new opportunities to better understand brain injury mechanisms. Recently, growing efforts have been made to integrate fiber orientation from diffusion tensor imaging (DTI) into FE models to predict white matter (WM) tract-related deformation that is biomechanically characterized by tract-related strains. Commonly used approaches often downsample the spatially enriched fiber orientation to match the FE resolution with one orientation per element (i.e., element-wise orientation implementation). However, the validity of such downsampling operation and corresponding influences on the computed tract-related strains remain elusive. To address this, the current study proposed a new approach to integrate voxel-wise fiber orientation from one DTI atlas (isotropic resolution of 1 mm3) into FE models by embedding orientations from multiple voxels within one element (i.e., voxel-wise orientation implementation). By setting the responses revealed by the newly proposed voxel-wise orientation implementation as the reference, we evaluated the reliability of two previous downsampling approaches by examining the downsampled fiber orientation and the computationally predicted tract-related strains secondary to one concussive impact. Two FE models with varying element sizes (i.e., 6.4 ± 1.6 mm and 1.3 ± 0.6 mm, respectively) were incorporated. The results showed that, for the model with a large voxel-mesh resolution mismatch, the downsampled element-wise fiber orientation, with respect to its voxel-wise counterpart, exhibited an absolute deviation over 30° across the WM/gray matter interface and the pons regions. Accordingly, this orientation deviation compromised the computation of tract-related strains with normalized root-mean-square errors up to 30% and underestimated the peak tract-related strains up to 10%. For the other FE model with finer meshes, the downsampling-induced effects were lower, both on the fiber orientation and tract-related strains. Taken together, the voxel-wise orientation implementation is recommended in future studies as it leverages the DTI-delineated fiber orientation to a larger extent than the element-wise orientation implementation. Thus, this study yields novel insights on integrating neuroimaging-revealed fiber orientation into FE models and may better inform the computation of WM tract-related deformation.

Enhanced spatial resolution in magnetic resonance imaging by dynamic nuclear polarization at 5 K

Spatial resolution in MRI is ultimately limited by the signal detection sensitivity of NMR, since resolution equal to ρiso in all three dimensions requires the detection of NMR signals from a volume ρiso3. With inductively detected NMR at room temperature, it has therefore proven difficult to achieve isotropic resolution better than ρiso = 3.0 μm, even with radio-frequency microcoils, optimized samples, high magnetic fields, optimized pulse sequence methods, and data acquisition times around 60 h. Here we show that spatial resolution can be improved and data acquisition times can be reduced substantially by performing MRI measurements at 5 K and using dynamic nuclear polarization (DNP) to enhance sensitivity. We describe the experimental apparatus and methods, and we report images of test samples with ρiso = 2.6 μm and ρiso = 1.7 μm, with signal-to-noise ratios greater than 15, acquired in 31.5 and 81.6 h, respectively. Image resolutions are verified by quantitative comparisons with simulations. These results establish a promising direction for high-resolution MRI of small samples. With further improvements in the experimental apparatus and in paramagnetic dopants for DNP, DNP-enhanced low-temperature MRI with ρiso < 1.0 μm is likely to become feasible, potentially enabling informative studies of structures within typical eukaryotic cells, cell clusters, and tissue samples.

Optical flow driven interpolation for isotropic FIB-SEM reconstructions

Background and Objective: Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) allows three-dimensional ultrastructural analysis of cells and tissues at the nanoscale. The technique iteratively removes a section of the sample with a FIB and takes an SEM image from the exposed surface. The section thickness is usually higher than the image pixel size to reduce acquisition time, thus resulting in anisotropic resolution. In this work, we explore novel interpolation methods along the sectioning direction to produce isotropic resolution and facilitate proper interpretation of the FIB-SEM 3D volumes.Methods: Classical interpolation methods are usually applied in this context under the assumption that the changes through successive images are relatively smooth. However, the actual 3D arrangement of the structures in the sample may cause significant changes in the biological features between consecutive images of the FIB-SEM stacks. We have developed a novel interpolation strategy that accounts for this variation by using the Optical Flow (OF) to estimate it. As an intermediate stage, OF-compensated images are produced by aligning the spatial regions of the biological structures. Interpolated images are then generated from these OF-compensated images. The final isotropic stack is assembled by interleaving the interpolated images with the original images of the anisotropic stack.Results: OF-driven and classical interpolation methods were compared using an objective assessment based on Pearson Correlation Coefficient (PCC) and a qualitative evaluation based on visual results, using public datasets and representative anisotropy conditions. The objective assessment demonstrated that the OF-driven interpolation always yields higher PCC values, with interpolated images closer to the ground truth. The qualitative evaluation corroborated those results and confirmed that classical interpolation may blur areas with substantial changes between consecutive images whereas OF-driven interpolation provides sharpness.Conclusions: We have developed an OF-driven interpolation approach to generating FIB-SEM stacks with isotropic resolution from experimental anisotropic data. It adapts to the rapid variation of the biological structures observed through the images of the FIB-SEM stack. Our approach outperforms classical interpolation and manages to produce sharp interpolated views in cases where there are significant changes between consecutive experimental images.

Fluid and White Matter Suppression: New Sensitive 3 T Magnetic Resonance Imaging Contrasts for Cortical Lesion Detection in Multiple Sclerosis.

Cortical lesions are common in multiple sclerosis (MS), but their visualization is challenging on conventional magnetic resonance imaging. The uniform image derived from magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE uni ) detects cortical lesions with a similar rate as the criterion standard sequence, double inversion recovery. Fluid and white matter suppression (FLAWS) provides multiple reconstructed contrasts acquired during a single acquisition. These contrasts include FLAWS minimum image (FLAWS min ), which provides an exquisite sensitivity to the gray matter signal and therefore may facilitate cortical lesion identification, as well as high contrast FLAWS (FLAWS hco ), which gives a contrast that is similar to one of MP2RAGE uni . In this study, we compared the manual detection rate of cortical lesions on MP2RAGE uni , FLAWS min , and FLAWS hco in MS patients. Furthermore, we assessed whether the combined detection rate on FLAWS min and FLAWS hco was superior to MP2RAGE uni for cortical lesions identification. Last, we compared quantitative T1 maps (qT1) provided by both MP2RAGE and FLAWS in MS lesions. We included 30 relapsing-remitting MS patients who underwent MP2RAGE and FLAWS magnetic resonance imaging with isotropic spatial resolution of 1 mm at 3 T. Cortical lesions were manually segmented by consensus of 3 trained raters and classified as intracortical or leukocortical lesions on (1) MP2RAGE uniform/flat images, (2) FLAWS min , and (3) FLAWS hco . In addition, segmented lesions on FLAWS min and FLAWS hco were merged to produce a union lesion map (FLAWS min + hco ). Number and volume of all cortical, intracortical, and leukocortical lesions were compared among MP2RAGE uni , FLAWS min , and FLAWS hco using Friedman test and between MP2RAGE uni and FLAWS min + hco using Wilcoxon signed rank test. The FLAWS T1 maps were then compared with the reference MP2RAGE T1 maps using relative differences in percentage. In an exploratory analysis, individual cortical lesion counts of the 3 raters were compared, and interrater variability was quantified using Fleiss ϰ. In total, 633 segmentations were made on the 3 contrasts, corresponding to 355 cortical lesions. The median number and volume of single cortical, intracortical, and leukocortical lesions were comparable among MP2RAGE uni , FLAWS min , and FLAWS hco . In patients with cortical lesions (22/30), median cumulative lesion volume was larger on FLAWS min (587 μL; IQR, 1405 μL) than on MP2RAGE uni (490 μL; IQR, 990 μL; P = 0.04), whereas there was no difference between FLAWS min and FLAWS hco , or FLAWS hco and MP2RAGE uni . FLAWS min + hco showed significantly greater numbers of cortical (median, 4.5; IQR, 15) and leukocortical (median, 3.5; IQR, 12) lesions than MP2RAGE uni (median, 3; IQR, 10; median, 2.5; IQR, 7; both P < 0.001). Interrater agreement was moderate on MP2RAGE uni (ϰ = 0.582) and FLAWS hco (ϰ = 0.584), but substantial on FLAWS min (ϰ = 0.614). qT1 in lesions was similar between MP2RAGE and FLAWS. Cortical lesions identification in FLAWS min and FLAWS hco was comparable to MP2RAGE uni . The combination of FLAWS min and FLAWS hco allowed to identify a higher number of cortical lesions than MP2RAGE uni , whereas qT1 maps did not differ between the 2 acquisition schemes.

Examining the effect of chronic intranasal oxytocin administration on the neuroanatomy and behavior of three autism-related mouse models

Although initially showing great potential, oxytocin treatment has encountered a translational hurdle in its promise of treating the social deficits of autism. Some debate surrounds the ability of oxytocin to successfully enter the brain, and therefore modify neuroanatomy. Moreover, given the heterogeneous nature of autism, treatment will only amerliorate symptoms in a subset of patients. Therefore, to determine whether oxytocin changes brain circuitry, and whether it does so variably, depending on genotype, we implemented a large randomized, blinded, placebo-controlled, preclinical study on chronic intranasal oxytocin treatment in three different mouse models related to autism with a focus on using neuroanatomical phenotypes to assess and subset treatment response. Intranasal oxytocin (0.6IU) was administered daily, for 28 days, starting at 5 weeks of age to the 16p11.2 deletion, Shank3 (exon 4–9) knockout, and Fmr1 knockout mouse models. Given the sensitivity of structural magnetic resonance imaging (MRI) to the neurological effects of interventions like drugs, along with many other advantages, the mice underwent in vivo longitudinal and high-resolution ex vivo imaging with MRI. The scans included three in vivo T1weighted, 90 um isotropic resolution scans and a T2-weighted, 3D fast spin echo with 40um isotropic resolution ex vivo scan to assess the changes in neuroanatomy using established automated image registration and deformation based morphometry approaches in response to oxytocin treatment. The behavior of the mice was assessed in multiple domains, including social behaviours and repetitive behaviours, among others. Treatment effect on the neuroanatomy did not reach significance, although the pattern of trending effects was promising. No significant effect of treatment was found on social behavior in any of the strains, although a significant effect of treatment was found in the Fmr1 mouse, with treatment normalizing a grooming deficit. No other treatment effect on behavior was observed that survived multiple comparisons correction. Overall, chronic treatment with oxytocin had limited effects on the three mouse models related to autism, and no promising pattern of response susceptibility emerged.

Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography.

The pial arterial vasculature of the human brain is the only blood supply to the neocortex, but quantitative data on the morphology and topology of these mesoscopic arteries (diameter 50-300 µm) remains scarce. Because it is commonly assumed that blood flow velocities in these vessels are prohibitively slow, non-invasive time-of-flight magnetic resonance angiography (TOF-MRA)-which is well suited to high 3D imaging resolutions-has not been applied to imaging the pial arteries. Here, we provide a theoretical framework that outlines how TOF-MRA can visualize small pial arteries in vivo, by employing extremely small voxels at the size of individual vessels. We then provide evidence for this theory by imaging the pial arteries at 140 µm isotropic resolution using a 7 Tesla (T) magnetic resonance imaging (MRI) scanner and prospective motion correction, and show that pial arteries one voxel width in diameter can be detected. We conclude that imaging pial arteries is not limited by slow blood flow, but instead by achievable image resolution. This study represents the first targeted, comprehensive account of imaging pial arteries in vivo in the human brain. This ultra-high-resolution angiography will enable the characterization of pial vascular anatomy across the brain to investigate patterns of blood supply and relationships between vascular and functional architecture.

Sparse Angle CBCT Reconstruction Based on Guided Image Filtering.

Cone-beam Computerized Tomography (CBCT) has the advantages of high ray utilization and detection efficiency, short scan time, high spatial and isotropic resolution. However, the X-rays emitted by CBCT examination are harmful to the human body, so reducing the radiation dose without damaging the reconstruction quality is the key to the reconstruction of CBCT. In this paper, we propose a sparse angle CBCT reconstruction algorithm based on Guided Image FilteringGIF, which combines the classic Simultaneous Algebra Reconstruction Technique(SART) and the Total p-Variation (TpV) minimization. Due to the good edge-preserving ability of SART and noise suppression ability of TpV minimization, the proposed method can suppress noise and artifacts while preserving edge and texture information in reconstructed images. Experimental results based on simulated and real-measured CBCT datasets show the advantages of the proposed method.