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•A new framework, LARO, is introduced to accelerate multi-echo gradient echo (mGRE) sequence for quantitative susceptibility mapping.•LARO optimizes a Cartesian multi-echo k-space sampling pattern with a deep reconstruction network.•The optimized sampling pattern is implemented in an mGRE sequence for prospective scans.•LARO uses a recurrent temporal feature fusion module to capture signal redundancies along echoes.•LARO is robust with new pathologies and different sequence parameters in the test dataset. Quantitative susceptibility mapping (QSM) involves acquisition and reconstruction of a series of images at multi-echo time points to estimate tissue field, which prolongs scan time and requires specific reconstruction technique. In this paper, we present our new framework, called Learned Acquisition and Reconstruction Optimization (LARO), which aims to accelerate the multi-echo gradient echo (mGRE) pulse sequence for QSM. Our approach involves optimizing a Cartesian multi-echo k-space sampling pattern with a deep reconstruction network. Next, this optimized sampling pattern was implemented in an mGRE sequence using Cartesian fan-beam k-space segmenting and ordering for prospective scans. Furthermore, we propose to insert a recurrent temporal feature fusion module into the reconstruction network to capture signal redundancies along echo time. Our ablation studies show that both the optimized sampling pattern and proposed reconstruction strategy help improve the quality of the multi-echo image reconstructions. Generalization experiments show that LARO is robust on the test data with new pathologies and different sequence parameters. Our code is available at https://github.com/Jinwei1209/LARO-QSM.git.

Gradient echo myelin water imaging (GRE-MWI) is an MRI technique to measure myelin concentration and involves the analysis of signal decay characteristics of the multi-echo gradient echo data. The method provides a myelin water fraction as a quantitative biomarker for myelin. In this work, a new sequence and post-processing methods were proposed to generate high quality GRE-MWI images at 3T and 7T. In order to capture the rapidly decaying myelin water signals, a bipolar readout GRE sequence was designed with \"gradient pairing,\" compensating for the eddy current effects. The flip angle dependency from the multi-compartmental T1 effects was explored and avoided using a 2D multi-slice acquisition with a long TR. Additionally, the sequence was tested for the effects of inflow and magnetization transfer and demonstrated robustness to these error sources. Lastly, the temporal and spatial B0 inhomogeneity effects were mitigated by using the B0 navigator and field inhomogeneity corrections. Using the method, high-quality myelin water images were successfully generated for the in-vivo human brain at both field strengths. When the myelin water fraction at 3T and 7T were compared, they showed a good correlation (R2≥ 0.88; p < 0.001) with a larger myelin water fraction at 7T. The proposed method also opens the possibility of high resolution (isotropic 1.5 mm resolution) myelin water mapping at 7T. •Proposed a sequence for high quality GRE-MWI maps at 3T and 7T.•Developed gradient pairing for eddy current compensations.•Optimized the sequence for physiological noise, flip angle, and MT effects.•Achieved 1.5 mm isotropic resolution myelin water images at 7T.

Magnetic resonance imaging (MRI) often uses gadolinium-based contrast agents (GBCAs) to improve the characterization of imaging contrast, owing to their strong paramagnetic properties. Magnetic resonance electrical properties tomography (MREPT) visualizes the conductivity distribution of biological tissues at the Larmor frequency using the field phase signal. In this paper, we investigate the effect of GBCA on brain conductivity. To compare the differences of reconstructed noisy conductivity maps before and after the GBCA injection, we propose a method to remove the background low-frequency noise artifact based on an elliptic partial differential equation. By analyzing the relationship between electrical conductivity and magnetic permeability, the objective of this study is to develop a cost-effective and accessible initial screening imaging tool for diagnosing and monitoring the treatment of Alzheimer’s disease (AD) pathophysiology. To investigate vascular damage in AD, we define a conductivity heterogeneity volume fraction (CHVF) caused by GBCA leakage. Using CHVF, we develop three indices to characterize mild cognitive impairment (MCI) and AD. To verify the proposed method, we studied a total of 42 participants, including 14 individuals diagnosed with AD, 18 participants with MCI, and 10 cognitively normal (CN) participants. Finally, we designed a radar chart informed by the CHVF analysis, to exhibit the pertinent parameters for MCI and AD patients, facilitating the evaluation and ongoing monitoring of each patient’s diagnosis and treatment regimen.

The effective transverse relaxation rate (R 2 *) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R 2 * degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R 2,iso *) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β 1 , can be biophysically related to R 2,iso * when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β 1 can estimate R 2,iso * using meGRE with long maximum-echo time (TE max  ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β 1 that reduced the error to 12% for ex vivo compartmental R 2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R 2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R 2 *-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TE max  ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TE max  ≈ 54 ms are required before M2 can be used to estimate R 2,iso * in subjects.

Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T2∗ is consistent across the corpus callosum sub-regions, whilst myelin frequency shift varies. The results show that the variation in water fraction, T2∗ and frequency shift for the myelin signal compartment across the corpus callosum is smaller than for the axonal and extracellular signal compartments. The computed g-ratio was comparable to previously published studies in the corpus callosum. Our study suggests that a multi-echo GRE approach in vivo combined with a complex three-compartment model is sensitive to microstructural parameter variations across the human corpus callosum. •White matter organisation influences signal compartmentalization.•Myelin water fraction and g-ratio showed similar values across subregions of corpus callosum.•Myelin and axonal frequency shifts vary across the corpus callosum.•Axonal water fraction is higher at the middle of the corpus callosum.

Purpose 3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF). Methods Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence. Results Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43–40%, respectively, p  > 0.05). Rating of lesion conspicuity was higher with cTOF (4.5 ± 1.0) as compared with pTOF (4.0 ± 0.7), but this was not significantly different ( p  = 0.06). Diagnostic confidence was rated higher with cTOF (4.8 ± 0.5) than that of pTOF (3.7 ± 0.6; p  < 0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (κ = 0.98, 96% CI 0.8–1.0). Conclusions In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.

Myelination of axons in the central nervous system is critical for human cognition and behavior. The predominant protein in myelin is proteolipid protein—making PLP1 , the gene that encodes for proteolipid protein, one of the primary candidate genes for white matter structure in the human brain. Here, we investigated the relation of genetic variation within PLP1 and white matter microstructure as assessed with myelin water fraction imaging, a neuroimaging technique that has the advantage over conventional diffusion tensor imaging in that it allows for a more direct assessment of myelin content. We observed significant asymmetries in myelin water fraction that were strongest and rightward in the parietal lobe. Importantly, these parietal myelin water fraction asymmetries were associated with genetic variation in PLP1 . These findings support the assumption that genetic variation in PLP1 affects white matter myelination in the healthy human brain.

The aim of the present study was to analyze the distribution and severity of cartilage damage (CD) and bone marrow edema (BME) of the patellofemoral and tibiofemoral joints (PFJ and TFJ, respectively) in patients with knee osteoarthritis (OA), and to determine whether a correlation exists between BME and CD in knee OA, using magnetic resonance imaging (MRI). Forty-five patients diagnosed with knee OA (KOA group) and 20 healthy individuals (control group) underwent sagittal multi-echo recalled gradient echo sequence scans, in addition to four conventional MR sequence scans. Knee joints were divided into 15 subregions by the whole-organ MRI scoring method. MRIs of each subregion were analyzed for the presence of CD, CD score and BME score. The knee joint activity functional score was determined using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) in the KOA group. Statistical analyses were used to compare the CD incidence; CD score and BME score between the PFJ and TFJ. Whether a correlation existed among body mass index, BME score, WOMAC pain score and CD score was also examined. Among the 675 subregions analyzed in the KOA group, 131 exhibited CD (CD score, 1-6). These 131 subregions were primarily in the PFJ (80/131, 61.07%), with the remainder in the TFJ (51/131, 38.93%). Thirty-three subregions had a CD score of 1, including 24 PFJ subregions (72.73%) and 9 TFJ subregions (27.27%). Among the 103 subregions with BME, the PFJ accounted for 60 (58.25%) and the TFJ for 43 (41.75%). A significant positive correlation was found between the BME and CD scores. In conclusion, CD and BME occurred earlier and more often in the PFJ compared to the TFJ in knee OA, and BME is an indirect sign of CD.

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Gradient-recalled echo (GRE) echo-planar imaging (EPI) is an efficient MRI pulse sequence that is commonly used for several enticing applications, including functional MRI (fMRI), susceptibility-weighted imaging (SWI), and proton resonance frequency (PRF) thermometry. These applications are typically not performed in the mid-field (<1 T) as longer T2* and lower polarization present significant challenges. However, recent developments of mid-field scanners equipped with high-performance gradient sets offer the possibility to re-evaluate the feasibility of these applications. The paper introduces a metric “T2* contrast efficiency” for this evaluation, which minimizes dead time in the EPI sequence while maximizing T2* contrast so that the temporal and pseudo signal-to-noise ratios (SNRs) can be attained, which could be used to quantify experimental parameters for future fMRI experiments in the mid-field. To guide the optimization, T2* measurements of the cortical gray matter are conducted, focusing on specific regions of interest (ROIs). Temporal and pseudo SNR are calculated with the measured time-series EPI data to observe the echo times at which the maximum T2* contrast efficiency is achieved. T2* for a specific cortical ROI is reported at 0.5 T. The results suggest the optimized echo time for the EPI protocols is shorter than the effective T2* of that region. The effective reduction of dead time prior to the echo train is feasible with an optimized EPI protocol, which will increase the overall scan efficiency for several EPI-based applications at 0.5 T.