T1 and T2 in the brain of healthy subjects, patients with Parkinson disease, and patients with multiple system atrophy: relation to iron content

Dependence of brain-tissue R2 on MRI field strength

PURPOSE

To quantify T2 relaxation in the brain at 3 T and 7 T to study its field dependence and correlation with iron content, and to investigate whether iron can be separated from other sources of T2 relaxation based on this field dependence.

METHODS

Nine subjects were scanned at both field strengths with the same acquisition technique, which used multiple gradient-echo sampling of a spin echo. This allowed for separation of T2 relaxation from static dephasing by B0 field inhomogeneities and the effects of radiofrequency refocusing imperfections. The average relaxation rates (R2 = 1/T2) in multiple regions of interest in the brain were fitted with a model linear in B0 and correlated with literature iron values.

RESULTS

The relationship between the R2 values at the two field strengths appeared to be linear over all regions of interest. The R2 values (in s-1) in the regions of interest for which both an iron and a lipid mass fraction have been documented in the literature were fitted asR 2 = 9 + 0.9 + 2 · 10 4 [ Fe ] + 5.7 [ lipid ] · B 0 $$ {\mathrm{R}}_2=9+\left(0.9+2\cdotp {10}^4\left[\mathrm{Fe}\right]+5.7\left[\mathrm{lipid}\right]\right)\cdotp {\mathrm{B}}_0 $$ , where[ Fe ] $$ \left[\mathrm{Fe}\right] $$ and[ lipid ] $$ \left[\mathrm{lipid}\right] $$ indicate the putative mass fractions of iron and lipid.

CONCLUSION

The R2 relaxation rate is well described by a constant plus a term linear in B0, with both iron and lipid content contributing to the slope. This indicates that the contributions of lipid and iron to R2 cannot be separated based solely on the field dependence of R2 in the field range of 3-7 T.

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing

PURPOSE

To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy.

METHOD

A deep learning approach based on a modified one-dimensional U-Net, termed Z-spectral compressed sensing (CS), was proposed to recover dense Z-spectra from sparse ones. The neural network was trained using simulated Z-spectra generated by the Bloch equation with various parameter settings. Its feasibility and effectiveness were validated through numerical simulations and in vivo rat brain experiments, compared with commonly used linear, pchip, and Lorentzian interpolation methods. The proposed method was applied to detect metabolism-related changes in the 6-hydroxydopamine PD model with multipool CEST MRI, including APT, CEST@2 ppm, nuclear Overhauser enhancement, direct saturation, and magnetization transfer, and the prediction performance was evaluated by area under the curve.

RESULTS

The numerical simulations and in vivo rat-brain experiments demonstrated that the proposed method could yield superior fidelity in retrieving dense Z-spectra compared with existing methods. Significant differences were observed in APT, CEST@2 ppm, nuclear Overhauser enhancement, and direct saturation between the striatum regions of wild-type and PD models, whereas magnetization transfer exhibited no significant difference. Receiver operating characteristic analysis demonstrated that multipool CEST achieved better predictive performance compared with individual pools. Combined with Z-spectral CS, the scan time of multipool CEST MRI can be reduced to 33% without distinctly compromising prediction accuracy.

CONCLUSION

The integration of Z-spectral CS with multipool CEST MRI can enhance the prediction accuracy of PD and maintain the scan time within a reasonable range.

High SNR full brain relaxometry at 7T by accelerated MR-STAT

PURPOSE

To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T.

METHODS

To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measuredB 1 + $$ {B}_1^{+} $$ -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity toB 1 + $$ {B}_1^{+} $$ inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency.

RESULTS

The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including theB 1 + $$ {B}_1^{+} $$ -mapping. AfterB 1 + $$ {B}_1^{+} $$ -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%-2.1% (WM-GM) for T1 and 4.3%-5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency.

CONCLUSION

We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T.

T1 mapping in patients with cervical spinal canal stenosis with and without decompressive surgery: A longitudinal study

BACKGROUND AND PURPOSE

Cervical spinal canal stenosis (cSCS) is a common cause of spinal impairment in the elderly. With conventional magnetic resonance imaging (MRI) suffering from various limitations, high-resolution single-shot T1 mapping has been proposed as a novel MRI technique in cSCS diagnosis. In this study, we investigated the effect of conservative and surgical treatment on spinal cord T1 relaxation times in cSCS.

METHODS

T1-mapping was performed in 54 patients with cSCS at 3 Tesla MRI at the maximum-, above and below the stenosis. Subsequently, intraindividual T1-differences (ΔT1) intrastenosis were calculated. Twenty-four patients received follow-up scans after 6 months.

RESULTS

Surgically treated patients showed higher ΔT1 at baseline (154.9 ± 81.6 vs. 95.3 ± 60.7), while absolute T1-values within the stenosis were comparable between groups (863.7 ± 89.3 milliseconds vs. 855.1 ± 62.2 milliseconds). In surgically treated patients, ΔT1 decreased inverse to stenosis severity. After 6 months, ΔT1 significantly decreased in the surgical group (154.9 ± 81.6 milliseconds to 85.7 ± 108.9 milliseconds, p = .021) and remained unchanged in conservatively treated patients. Both groups showed clinical improvement at the 6-month follow-up.

CONCLUSIONS

Baseline difference of T1 relaxation time (ΔT1) might serve as a supporting marker for treatment decision and change of T1 relaxation time might reflect relief of spinal cord narrowing indicating regenerative processes. Quantitative T1-mapping represents a promising additional imaging method to indicate a surgical treatment plan and to validate treatment success.

Rapid quantitative magnetization transfer imaging: Utilizing the hybrid state and the generalized Bloch model

PURPOSE

To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model parameters.

THEORY AND METHODS

We combine two recently proposed models in a Bloch-McConnell equation: the dynamics of the free spin pool are confined to the hybrid state, and the dynamics of the semi-solid spin pool are described by the generalized Bloch model. We numerically optimize the flip angles and durations of a train of radio frequency pulses to enhance the encoding of three qMT parameters while accounting for all eight parameters of the two-pool model. We sparsely sample each time frame along this spin dynamics with a three-dimensional radial koosh-ball trajectory, reconstruct the data with subspace modeling, and fit the qMT model with a neural network for computational efficiency.

RESULTS

We extracted qMT parameter maps of the whole brain with an effective resolution of 1.24 mm from a 12.6-min scan. In lesions of multiple sclerosis subjects, we observe a decreased size of the semi-solid spin pool and longer relaxation times, consistent with previous reports.

CONCLUSION

The encoding power of the hybrid state, combined with regularized image reconstruction, and the accuracy of the generalized Bloch model provide an excellent basis for efficient quantitative magnetization transfer imaging with few constraints on model parameters.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

To what extent may aminochrome increase the vulnerability of dopaminergic neurons in the context of Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder that progresses over time and is characterized by preferential reduction of dopaminergic neurons in the substantia nigra. Although the precise mechanisms leading to cell death in neurodegenerative disorders, such as PD, are not fully understood, it is widely accepted that increased oxidative stress may be a prevalent factor contributing to the deterioration of the nigrostriatal dopaminergic fibers in such conditions. Aminochrome, generated from dopamine (DA) metabolism, plays an important role in multiple pathogenic mechanisms associated with PD. Its capacity to induce a gradual reduction in dopaminergic neurons is due to its endogenous neurotoxicity. The formation of aminochrome results in the production of various reactive oxygen species (ROS), including pro-inflammatory factors, superoxide, nitric oxide, and hydroxyl radicals. This, in turn, causes loss of dopaminergic neurons, reducing DA uptake, and reduced numbers and shortened dendrites. Notably, o-quinones, which are more cytotoxic, arise from the oxidation of DA and possess a higher capacity to impede cellular defense mechanisms, thereby resulting in the death of neuronal cells. Aminochrome potentially contributes to the pathophysiology of PD by forming adducts with various proteins. All of the aforementioned effects suggest that aminochrome may play a crucial role in the pathophysiology of PD. Thus, aminochrome may serve as a more relevant preclinical model for PD, facilitating a better understanding of its pathophysiological processes and identification of novel therapeutic strategies aimed at preventing or slowing disease progression.

Non-invasive assessment of normal and impaired iron homeostasis in the brain

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.

P2T2: A physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI

Estimating T₂ relaxation time distributions from multi-echo T₂-weighted MRI (T₂W) data can provide valuable biomarkers for assessing inflammation, demyelination, edema, and cartilage composition in various pathologies, including neurodegenerative disorders, osteoarthritis, and tumors. Deep neural network (DNN) based methods have been proposed to address the complex inverse problem of estimating T₂ distributions from MRI data, but they are not yet robust enough for clinical data with low Signal-to-Noise ratio (SNR) and are highly sensitive to distribution shifts such as variations in echo-times (TE) used during acquisition. Consequently, their application is hindered in clinical practice and large-scale multi-institutional trials with heterogeneous acquisition protocols. We propose a physically-primed DNN approach, called P₂T₂, that incorporates the signal decay forward model in addition to the MRI signal into the DNN architecture to improve the accuracy and robustness of T₂ distribution estimation. We evaluated our P₂T₂ model in comparison to both DNN-based methods and classical methods for T₂ distribution estimation using 1D and 2D numerical simulations along with clinical data. Our model improved the baseline model's accuracy for low SNR levels (SNR<80) which are common in the clinical setting. Further, our model achieved a ∼35% improvement in robustness against distribution shifts in the acquisition process compared to previously proposed DNN models. Finally, Our P₂T₂ model produces the most detailed Myelin-Water fraction maps compared to baseline approaches when applied to real human MRI data. Our P₂T₂ model offers a reliable and precise means of estimating T₂ distributions from MRI data and shows promise for use in large-scale multi-institutional trials with heterogeneous acquisition protocols. Our source code is available at: https://github.com/Hben-atya/P2T2-Robust-T2-estimation.git.

Neuromelanin magnetic resonance imaging of substantia nigra and locus coeruleus in Parkinson's disease with freezing of gait

Background

The downregulation of monoamines, especially dopamine in substantia nigra (SN) and norepinephrine in locus coeruleus (LC), may be responsible for freezing of gait (FOG) pathological basis in Parkinson's disease (PD).

Methods

Thirty-two Parkinson's disease patients with freezing of gait (PD-FOG), 32 Parkinson's disease patients without freezing of gait (PD-NFOG) and 32 healthy controls (HC) underwent neuromelanin magnetic resonance imaging (NM-MRI). The volume, surface area and contrast to noise ratio (CNR) of SN and LC were measured and compared. The correlation analyses were conducted between the measurements of SN and LC with clinical symptoms. We plotted the receiver operating characteristic (ROC) curve and determined the sensitivity and specificity of the CNR of SN and LC for discriminating the PD-FOG from the PD-NFOG.

Results

Both PD-FOG and PD-NFOG showed decreased volume, surface area and CNR of SN compared with HC. The PD-FOG exhibited decreased volume and surface area of LC compared with both PD-NFOG and HC groups, and decreased CNR of LC compared with HC group. The volume, surface area and CNR of SN were negatively correlated with the Unified Parkinson's Disease Rating Scale part III scores. The illness durations in PD patients were negatively correlated with the volume, surface area of SN, while not the CNR. And the volume and surface area of LC were negatively correlated with new freezing of gait questionnaire scores. ROC analyses indicated that the area under the curve (AUC) was 0.865 and 0.713 in the CNR of SN and LC, respectively, in PD versus HC, whereas it was 0.494 and 0.637 respectively, in PD-FOG versus PD-NFOG. Among these, for discriminating the PD from the HC, the sensitivity and specificity in the CNR of the SN was 90.6 and 71.9%, respectively, when the cut-off value was set at 2.101; the sensitivity and specificity in the CNR of the LC was 90.6 and 50.0%, respectively, when the cut-off value for CNR was set at 1.411.

Conclusion

The dopaminergic changes in the SN were found across both PD-FOG and PD-NFOG, whilst LC noradrenergic neuron reduction was more evident in PD-FOG.

Evaluating whole-brain tissue-property changes in MRI-negative pharmacoresistant focal epilepsies using MR fingerprinting

OBJECTIVE

We aim to quantify whole-brain tissue-property changes in patients with magnetic resonance imaging (MRI)-negative pharmacoresistant focal epilepsy by three-dimensional (3D) magnetic resonance fingerprinting (MRF).

METHODS

We included 30 patients with pharmacoresistant focal epilepsy and negative MRI by official radiology report, as well as 40 age- and gender-matched healthy controls (HCs). MRF scans were obtained with 1 mm³ isotropic resolution. Quantitative T1 and T2 relaxometry maps were reconstructed from MRF and registered to the Montreal Neurological Institute (MNI) space. A two-sample t test was performed in Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) to evaluate significant abnormalities in patients comparing to HCs, with correction by the threshold-free cluster enhancement (TFCE) method. Subgroups analyses were performed for extra-temporal epilepsy/temporal epilepsy (ETLE/TLE), and for those with/without subtle abnormalities detected by morphometric analysis program (MAP), to investigate each subgroup's pattern of MRF changes. Correlation analyses were performed between the mean MRF values in each significant cluster and seizure-related clinical variables.

RESULTS

Compared to HCs, patients exhibited significant group-level T1 increase ipsilateral to the epileptic origin, in the mesial temporal gray matter (GM) and white matter (WM), temporal pole GM, orbitofrontal GM, hippocampus, and amygdala, with scattered clusters in the neocortical temporal and insular GM. No significant T2 changes were detected. The ETLE subgroup showed a T1-increase pattern similar to the overall cohort, with additional involvement of the ipsilateral anterior cingulate GM. The subgroup of MAP+ patients also showed a T1-increase pattern similar to the overall cohort, with additional cluster in the ipsilateral lateral orbitofrontal GM. Higher T1 was associated with younger seizure-onset age, longer epilepsy duration, and higher seizure frequency.

SIGNIFICANCE

MRF revealed group-level T1 increase in limbic/paralimbic structures ipsilateral to the epileptic origin, in patients with pharmacoresistant focal epilepsy and no apparent lesions on MRI, suggesting that these regions may be commonly affected by seizures in the epileptic brain. The significant association between T1 increase and higher seizure burden may reflect progressive tissue damage.

Quantitative Relaxometry Metrics for Brain Metastases Compared to Normal Tissues: A Pilot MR Fingerprinting Study

The purpose of the present pilot study was to estimate T1 and T2 metric values derived simultaneously from a new, rapid Magnetic Resonance Fingerprinting (MRF) technique, as well as to assess their ability to characterize-brain metastases (BM) and normal-appearing brain tissues. Fourteen patients with BM underwent MRI, including prototype MRF, on a 3T scanner. In total, 108 measurements were analyzed: 42 from solid parts of BM's (21 each on T1 and T2 maps) and 66 from normal-appearing brain tissue (11 ROIs each on T1 and T2 maps for gray matter [GM], white matter [WM], and cerebrospinal fluid [CSF]). The BM's mean T1 and T2 values differed significantly from normal-appearing WM (p < 0.05). The mean T1 values from normal-appearing GM, WM, and CSF regions were 1205 ms, 840 ms, and 4233 ms, respectively. The mean T2 values were 108 ms, 78 ms, and 442 ms, respectively. The mean T1 and T2 values for untreated BM (n = 4) were 2035 ms and 168 ms, respectively. For treated BM (n = 17) the T1 and T2 values were 2163 ms and 141 ms, respectively. MRF technique appears to be a promising and rapid quantitative method for the characterization of free water content and tumor morphology in BMs.

Blip up-down acquisition for spin- and gradient-echo imaging (BUDA-SAGE) with self-supervised denoising enables efficient T2 , T2 *, para- and dia-magnetic susceptibility mapping

PURPOSE

To rapidly obtain high resolution T₂ , T₂ *, and quantitative susceptibility mapping (QSM) source separation maps with whole-brain coverage and high geometric fidelity.

METHODS

We propose Blip Up-Down Acquisition for Spin And Gradient Echo imaging (BUDA-SAGE), an efficient EPI sequence for quantitative mapping. The acquisition includes multiple T₂ *-, T₂ '-, and T₂ -weighted contrasts. We alternate the phase-encoding polarities across the interleaved shots in this multi-shot navigator-free acquisition. A field map estimated from interim reconstructions was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to eliminate distortion. A self-supervised neural network (NN), MR-Self2Self (MR-S2S), was used to perform denoising to boost SNR. Using Slider encoding allowed us to reach 1 mm isotropic resolution by performing super-resolution reconstruction on volumes acquired with 2 mm slice thickness. Quantitative T₂ (=1/R₂ ) and T₂ * (=1/R₂ *) maps were obtained using Bloch dictionary matching on the reconstructed echoes. QSM was estimated using nonlinear dipole inversion on the gradient echoes. Starting from the estimated R₂ /R₂ * maps, R₂ ' information was derived and used in source separation QSM reconstruction, which provided additional para- and dia-magnetic susceptibility maps.

RESULTS

In vivo results demonstrate the ability of BUDA-SAGE to provide whole-brain, distortion-free, high-resolution, multi-contrast images and quantitative T₂ /T₂ * maps, as well as yielding para- and dia-magnetic susceptibility maps. Estimated quantitative maps showed comparable values to conventional mapping methods in phantom and in vivo measurements.

CONCLUSION

BUDA-SAGE acquisition with self-supervised denoising and Slider encoding enables rapid, distortion-free, whole-brain T₂ /T₂ * mapping at 1 mm isotropic resolution under 90 s.

Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends

Quantitative mapping of MR tissue parameters such as the spin-lattice relaxation time (T1 ), the spin-spin relaxation time (T2 ), and the spin-lattice relaxation in the rotating frame (T1ρ ), referred to as MR relaxometry in general, has demonstrated improved assessment in a wide range of clinical applications. Compared with conventional contrast-weighted (eg T1 -, T2 -, or T1ρ -weighted) MRI, MR relaxometry provides increased sensitivity to pathologies and delivers important information that can be more specific to tissue composition and microenvironment. The rise of deep learning in the past several years has been revolutionizing many aspects of MRI research, including image reconstruction, image analysis, and disease diagnosis and prognosis. Although deep learning has also shown great potential for MR relaxometry and quantitative MRI in general, this research direction has been much less explored to date. The goal of this paper is to discuss the applications of deep learning for rapid MR relaxometry and to review emerging deep-learning-based techniques that can be applied to improve MR relaxometry in terms of imaging speed, image quality, and quantification robustness. The paper is comprised of an introduction and four more sections. Section 2 describes a summary of the imaging models of quantitative MR relaxometry. In Section 3, we review existing "classical" methods for accelerating MR relaxometry, including state-of-the-art spatiotemporal acceleration techniques, model-based reconstruction methods, and efficient parameter generation approaches. Section 4 then presents how deep learning can be used to improve MR relaxometry and how it is linked to conventional techniques. The final section concludes the review by discussing the promise and existing challenges of deep learning for rapid MR relaxometry and potential solutions to address these challenges.

BUDA-MESMERISE: Rapid acquisition and unsupervised parameter estimation for T1 , T2 , M0 , B0 , and B1 maps

PURPOSE

Rapid acquisition scheme and parameter estimation method are proposed to acquire distortion-free spin- and stimulated-echo signals and combine the signals with a physics-driven unsupervised network to estimate T₁ , T₂ , and proton density (M₀ ) parameter maps, along with B₀ and B₁ information from the acquired signals.

THEORY AND METHODS

An imaging sequence with three 90° RF pulses is utilized to acquire spin- and stimulated-echo signals. We utilize blip-up/-down acquisition to eliminate geometric distortion incurred by the effects of B₀ inhomogeneity on rapid EPI acquisitions. For multislice imaging, echo-shifting is applied to utilize dead time between the second and third RF pulses to encode information from additional slice positions. To estimate parameter maps from the spin- and stimulated-echo signals with high fidelity, 2 estimation methods, analytic fitting and a novel unsupervised deep neural network method, are developed.

RESULTS

The proposed acquisition provided distortion-free T₁ , T₂ , relative proton density (M0), B₀ , and B₁ maps with high fidelity both in phantom and in vivo brain experiments. From the rapidly acquired spin- and stimulated-echo signals, analytic fitting and the network-based method were able to estimate T₁ , T₂ , M₀ , B₀ , and B₁ maps with high accuracy. Network estimates demonstrated noise robustness owing to the fact that the convolutional layers take information into account from spatially adjacent voxels.

CONCLUSION

The proposed acquisition/reconstruction technique enabled whole-brain acquisition of coregistered, distortion-free, T₁ , T₂ , M₀ , B₀ , and B₁ maps at 1 × 1 × 5 mm³ resolution in 50 s. The proposed unsupervised neural network provided noise-robust parameter estimates from this rapid acquisition.

Aberrant Cerebral Iron Trafficking Co-morbid With Chronic Inflammation: Molecular Mechanisms and Pharmacologic Intervention

The redox properties that make iron an essential nutrient also make iron an efficient pro-oxidant. Given this nascent cytotoxicity, iron homeostasis relies on a combination of iron transporters, chaperones, and redox buffers to manage the non-physiologic aqueous chemistry of this first-row transition metal. Although a mechanistic understanding of the link between brain iron accumulation (BIA) and neurodegenerative diseases is lacking, BIA is co-morbid with the majority of cognitive and motor function disorders. The most prevalent neurodegenerative disorders, including Alzheimer's Disease (AD), Parkinson's Disease (PD), Multiple System Atrophy (MSA), and Multiple Sclerosis (MS), often present with increased deposition of iron into the brain. In addition, ataxias that are linked to mutations in mitochondrial-localized proteins (Friedreich's Ataxia, Spinocerebellar Ataxias) result in mitochondrial iron accumulation and degradation of proton-coupled ATP production leading to neuronal degeneration. A comorbidity common in the elderly is a chronic systemic inflammation mediated by primary cytokines released by macrophages, and acute phase proteins (APPs) released subsequently from the liver. Abluminal inflammation in the brain is found downstream as a result of activation of astrocytes and microglia. Reasonably, the iron that accumulates in the brain comes from the cerebral vasculature via the microvascular capillary endothelial cells whose tight junctions represent the blood-brain barrier. A premise amenable to experimental interrogation is that inflammatory stress alters both the trans- and para-cellular flux of iron at this barrier resulting in a net accumulation of abluminal iron over time. This review will summarize the evidence that lends support to this premise; indicate the mechanisms that merit delineation; and highlight possible therapeutic interventions based on this model.

Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps

PURPOSE

A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast parametric maps. We sought to reduce the acquisition time for QSM and macromolecular tissue volume by acquiring both contrasts simultaneously by leveraging their redundancies. The joint virtual coil concept with GRAPPA (JVC-GRAPPA) was applied to reduce acquisition time further.

METHODS

Three adult volunteers were imaged on a 3 Tesla scanner using a multi-echo 3D GRE sequence acquired at 3 head orientations. Macromolecular tissue volume, QSM, R2∗ , T₁ , and proton density maps were reconstructed. The same sequence (GRAPPA R = 4) was performed in subject 1 with a single head orientation for comparison. Fully sampled data was acquired in subject 2, from which retrospective undersampling was performed (R = 6 GRAPPA and R = 9 JVC-GRAPPA). Prospective undersampling was performed in subject 3 (R = 6 GRAPPA and R = 9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes.

RESULTS

Subject 1's multi-orientation and single-orientation macromolecular tissue volume maps were not significantly different based on RMSE. For subject 2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject 3. Using QSM, R2∗ , and macromolecular tissue volume, the contributions of myelin and iron content to susceptibility were estimated.

CONCLUSION

We have developed a novel strategy to simultaneously acquire data for the reconstruction of 5 intrinsically coregistered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 min using JVC-GRAPPA.

A Spatial Off-Resonance Correction in Spirals for Magnetic Resonance Fingerprinting

In MR Fingerprinting (MRF), balanced Steady-State Free Precession (bSSFP) has advantages over unbalanced SSFP because it retains the spin history achieving a higher signal-to-noise ratio (SNR) and scan efficiency. However, bSSFP-MRF is not frequently used because it is sensitive to off-resonance, producing artifacts and blurring, and affecting the parametric map quality. Here we propose a novel Spatial Off-resonance Correction (SOC) approach for reducing these artifacts in bSSFP-MRF with spiral trajectories. SOC-MRF uses each pixel's Point Spread Function to create system matrices that encode both off-resonance and gridding effects. We iteratively compute the inverse of these matrices to reduce the artifacts. We evaluated the proposed method using brain simulations and actual MRF acquisitions of a standardized T1/T2 phantom and five healthy subjects. The results show that the off-resonance distortions in T1/T2 maps were considerably reduced using SOC-MRF. For T2, the Normalized Root Mean Square Error (NRMSE) was reduced from 17.3 to 8.3% (simulations) and from 35.1 to 14.9% (phantom). For T1, the NRMS was reduced from 14.7 to 7.7% (simulations) and from 17.7 to 6.7% (phantom). For in-vivo, the mean and standard deviation in different ROI in white and gray matter were significantly improved. For example, SOC-MRF estimated an average T2 for white matter of 77ms (the ground truth was 74ms) versus 50 ms of MRF. For the same example the standard deviation was reduced from 18 ms to 6ms. The corrections achieved with the proposed SOC-MRF may expand the potential applications of bSSFP-MRF, taking advantage of its better SNR property.

T1 Mapping for Microstructural Assessment of the Cervical Spinal Cord in the Evaluation of Patients with Degenerative Cervical Myelopathy

BACKGROUND AND PURPOSE

Although current radiologic evaluation of degenerative cervical myelopathy by conventional MR imaging accurately demonstrates spondylosis or degenerative disc disease causing spinal cord dysfunction, conventional MR imaging still fails to provide satisfactory anatomic and clinical correlations. In this context, we assessed the potential value of quantitative cervical spinal cord T1 mapping regarding the evaluation of patients with degenerative cervical myelopathy.

MATERIALS AND METHODS

Twenty patients diagnosed with mild and moderate-to-severe degenerative cervical myelopathy and 10 healthy subjects were enrolled in a multiparametric MR imaging protocol. Cervical spinal cord T1 mapping was performed with the MP2RAGE sequence procedure. Retrieved data were processed and analyzed regarding the global spinal cord and white and anterior gray matter on the basis of the clinical severity and the spinal canal stenosis grading.

RESULTS

Noncompressed levels in healthy controls demonstrated significantly lower T1 values than noncompressed, mild, moderate, and severe stenotic levels in patients. Concerning the entire spinal cord T1 mapping, patients with moderate-to-severe degenerative cervical myelopathy had higher T1 values compared with healthy controls. Regarding the specific levels, patients with moderate-to-severe degenerative cervical myelopathy demonstrated a T1 value increase at C1, C7, and the level of maximal compression compared with healthy controls. Patients with mild degenerative cervical myelopathy had lower T1 values than those with moderate-to-severe degenerative cervical myelopathy at the level of maximal compression. Analyses of white and anterior gray matter confirmed similar results. Strong negative correlations between individual modified Japanese Orthopaedic Association scores and T1 values were also observed.

CONCLUSIONS

In this preliminary study, 3D-MP2RAGE T1 mapping demonstrated increased T1 values in the pathology tissue samples, with diffuse medullary alterations in all patients with degenerative cervical myelopathy, especially relevant at C1 (nonstenotic level) and at the maximal compression level. Encouraging correlations observed with the modified Japanese Orthopaedic Association score make this novel approach a potential quantitative biomarker related to clinical severity in degenerative cervical myelopathy. Nevertheless, patients with mild degenerative cervical myelopathy demonstrated nonsignificant results compared with healthy controls and should now be studied in multicenter studies with larger patient populations.

Efficient T2 mapping with blip-up/down EPI and gSlider-SMS (T2 -BUDA-gSlider)

PURPOSE

To rapidly obtain high isotropic-resolution T₂ maps with whole-brain coverage and high geometric fidelity.

METHODS

A T₂ blip-up/down EPI acquisition with generalized slice-dithered enhanced resolution (T₂ -BUDA-gSlider) is proposed. A RF-encoded multi-slab spin-echo (SE) EPI acquisition with multiple TEs was developed to obtain high SNR efficiency with reduced TR. This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and used for T₂ quantification.

RESULTS

In vivo results demonstrated that the T₂ values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated.

CONCLUSION

BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T₂ mapping in 2 min at ~1 mm³ isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications.

Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations

Once an MRS dataset has been acquired, several important steps must be taken to obtain the desired metabolite concentration measures. First, the data must be preprocessed to prepare them for analysis. Next, the intensity of the metabolite signal(s) of interest must be estimated. Finally, the measured metabolite signal intensities must be converted into scaled concentration units employing a quantitative reference signal to allow meaningful interpretation. In this paper, we review these three main steps in the post-acquisition workflow of a single-voxel MRS experiment (preprocessing, analysis and quantification) and provide recommendations for best practices at each step.

Bloch modelling enables robust T2 mapping using retrospective proton density and T2-weighted images from different vendors and sites

T2 quantification is commonly attempted by applying an exponential fit to proton density (PD) and transverse relaxation (T2)-weighted fast spin echo (FSE) images. However, inter-site studies have noted systematic differences between vendors in T2 maps computed via standard exponential fitting due to imperfect slice refocusing, different refocusing angles and transmit field (B1⁺) inhomogeneity. We examine T2 mapping at 3T across 13 sites and two vendors in healthy volunteers from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using both a standard exponential and a Bloch modelling approach. The standard exponential approach resulted in highly variable T2 values across different sites and vendors. The two-echo fitting method based on Bloch equation modelling of the pulse sequence with prior knowledge of the nominal refocusing angles, slice profiles, and estimated B1⁺ maps yielded similar T2 values across sites and vendors by accounting for the effects of indirect and stimulated echoes. By modelling the actual refocusing angles used, T2 quantification from PD and T2-weighted images can be applied in studies across multiple sites and vendors.

Deep learning-enhanced T1 mapping with spatial-temporal and physical constraint

PURPOSE

To propose a reconstruction framework to generate accurate T₁ maps for a fast MR T₁ mapping sequence.

METHODS

A deep learning-enhanced T₁ mapping method with spatial-temporal and physical constraint (DAINTY) was proposed. This method explicitly imposed low-rank and sparsity constraints on the multiframe T₁ -weighted images to exploit the spatial-temporal correlation. A deep neural network was used to efficiently perform T₁ mapping as well as denoise and reduce undersampling artifacts. Additionally, the physical constraint was used to build a bridge between low-rank and sparsity constraint and deep learning prior, so the benefits of constrained reconstruction and deep learning can be both available. The DAINTY method was trained on simulated brain data sets, but tested on real acquired phantom, 6 healthy volunteers, and 7 atherosclerosis patients, compared with the narrow-band k-space-weighted image contrast filter conjugate-gradient SENSE (NK-CS) method, kt-sparse-SENSE (kt-SS) method, and low-rank plus sparsity (L+S) method with least-squares T₁ fitting and direct deep learning mapping.

RESULTS

The DAINTY method can generate more accurate T₁ maps and higher-quality T₁ -weighted images compared with other methods. For atherosclerosis patients, the intraplaque hemorrhage can be successfully detected. The computation speed of DAINTY was 10 times faster than traditional methods. Meanwhile, DAINTY can reconstruct images with comparable quality using only 50% of k-space data.

CONCLUSION

The proposed method can provide accurate T₁ maps and good-quality T₁ -weighted images with high efficiency.

Quantitative imaging metrics derived from magnetic resonance fingerprinting using ISMRM/NIST MRI system phantom: An international multicenter repeatability and reproducibility study

PURPOSE

To compare the bias and inherent reliability of the quantitative (T₁ and T₂ ) imaging metrics generated from the magnetic resonance fingerprinting (MRF) technique using the ISMRM/NIST system phantom in an international multicenter setting.

METHOD

ISMRM/NIST MRI system phantom provides standard reference T₁ and T₂ relaxation values (vendor-provided) for each of the 14 vials in T₁ and T₂ arrays. MRF-SSFP scans repeated over 30 days on GE 1.5 and 3.0 T scanners at three collaborative centers. MRF estimated T_1, and T₂ values averaged over 30 days were compared with the phantom vendor-provided and spin-echo (SE) based convention gold standard (GS) method. Repeatability and reproducibility were characterized by the within-case coefficient of variation (wCV) of the MRF data acquired over 30 days, along with the biases.

RESULT

For the wide ranges of MRF estimated T₁ values, vials #1-8 (T₁ relaxation time between 2033 and 184 ms) exhibited a wCV less than 3% and 4%, respectively, on 3.0 and 1.5 T scanners. T₂ values in vials #1-8 (T₂ relaxation, 1044-45 ms) have shown wCV to be <7% on both 3.0 and 1.5 T scanners. A stronger linear correlation overall for T₁ (R²  = 0.9960 and 0.9963 at center-1 and center-2 on 3.0 T scanner, and R²  = 0.9951 and 0.9988 at center-1 and center-3 on 1.5 T scanner) compared to T₂ (R²  = 0.9971 and 0.9972 at center-1 and center-2 on 3.0 T scanner, and R²  = 0.9815 and 0.9754 at center-1 and center-3 on 1.5 T scanner). Bland-Altman (BA) analysis showed MRF based T₁ and T₂ values were within the limit of agreement (LOA) except for one data point. The mean difference or bias and 95% lower bound (LB) and upper bound (UB) LOA are reported in the format; mean bias: 95% LB LOA: 95% UB LOA. The biases for T₁ values were 21.34: -50.00: 92.69, 21.32: -47.29: 89.94 ms, and for T₂ values were -19.88: -42.37: 2.61, -19.06: -43.58: 5.45 ms on 3.0 T scanner at center-1 and center-2, respectively. Similarly, on 1.5 T scanner biases for T₁ values were 26.54: -53.41: 106.50, 9.997: -51.94: 71.94 ms, and for T₂ values were -23.84: -135.40: 87.76, -37.30: 134.30: 59.73 ms at center-1 and center-3, respectively. Additionally, the correlation between the SE based GS and MRF estimated T₁ and T₂ values (R²  = 0.9969 and 0.9977) showed a similar trend as we observed between vendor-provided and MRF estimated T₁ and T₂ values (R²  = 0.9963 and 0.9972). In addition to correlation, BA analysis showed that all the vials are within the LOA between the GS and vendor-provided for the T₁ values and except one vial for T₂ . All the vials are within the LOA between GS and MRF except one vial in T₁ and T₂ array. The wCV for reproducibility was <3% for both T₁ and T₂ values in vials #1-8, for all the 14 vials, wCV calculated for reproducibility was <4% for T₁ values and <5% for T₂ .

CONCLUSION

This study shows that MRF is highly repeatable (wCV <4% for T₁ and <7% for T₂ ) and reproducible (wCV < 3% for both T₁ and T₂ ) in certain vials (vials #1-8).

No Changes in T1 Relaxometry After a Mean of 11 Administrations of Gadobutrol

OBJECTIVES

Quantitative T1 relaxometry is the benchmark in imaging potential gadolinium deposition and known to be superior to semiquantitative signal intensity ratio analyses. However, T1 relaxometry studies are rare, commonly limited to a few target structures, and reported results are inconsistent.We systematically investigated quantitative T1 relaxation times (qT1) of a variety of brain nuclei after serial application of gadobutrol.

MATERIALS AND METHODS

Retrospectively, qT1 measurements were performed in a patient cohort with a mean number of 11 gadobutrol applications (n = 46) and compared with a control group with no prior gadolinium-based contrast agent administration (n = 48). The following target structures were evaluated: dentate nucleus, globus pallidus, thalamus, hippocampus, putamen, caudate, amygdala, and different white matter areas. Subsequently, multivariate regression analysis with adjustment for age, presence of brain metastases and previous cerebral radiotherapy was performed.

RESULTS

No assessed site revealed a significant correlation between qT1 and number of gadobutrol administrations in multivariate regression analysis. However, a significant negative correlation between qT1 and age was found for the globus pallidus as well as anterior and lateral thalamus (P < 0.05 each).

CONCLUSIONS

No T1 relaxation time shortening due to gadobutrol injection was found in any of the assessed brain structures after serial administration of 11 doses of gadobutrol.

Upper brainstem GABA levels in Parkinson's disease

OBJECTIVE

The dopaminergic pathology of Parkinson's disease (PD) impacts circuits involving GABAergic neurons, especially in the brainstem, where the disease manifests early. The aim of this study is to test the hypothesis that levels of gamma-aminobutyric acid (GABA) in the upper brainstem are reduced in patients with PD compared to healthy controls, using edited magnetic resonance spectroscopy (MRS of GABA +).

MATERIALS AND METHODS

GABA + levels were examined in 18 PD patients and 18 age- and sex-matched healthy controls (HCs). GABA + -edited MRS was performed in 7.5-ml voxels in the upper brainstem, and the spectra were processed using the Gannet software. Differences in GABA + levels between the two groups were analyzed using independent t test analysis.

RESULTS

GABA + levels were significantly lower (p < 0.05) in the upper brainstem of the patients with PD (4.57 ± 0.94 mM) than the HCs (5.89 ± 1.16 mM).

CONCLUSION

The lower GABA + levels in the upper brainstem of the PD patients suggest that a GABAergic deficit in the brainstem may contribute to the pathology in PD.

Brain Structural Changes in Patients with Pulmonary Arterial Hypertension

BACKGROUND AND PURPOSE

Patients with pulmonary arterial hypertension (PAH) frequently present with anxiety, depression, autonomic, and cognitive deterioration, which may indicate brain changes in regions that control these functions. However, the precise regional brain-injury in sites that regulate cognitive, autonomic, and mood functions in PAH remains unclear. We examined the shifts in regional gray matter (GM) volume, using high-resolution T1-weighted images, and brain tissue alterations, using T2-relaxometry procedures, in PAH compared to healthy subjects.

METHODS

We collected two high-resolution T1-weighted series, and proton-density and T2-weighted images using a 3.0-Tesla magnetic resonance imaging scanner from 9 PAH and 19 healthy subjects. Both high-resolution T1-weighted images were realigned and averaged, partitioned to GM tissue type, normalized to a common space, and smoothed. Using proton-density and T2-weighted images, T2-relaxation maps were calculated, normalized to a common space, and smoothed. Whole-brain GM volume and T2-relaxation maps were compared between PAH and controls using analysis of covariance (covariates, age, sex, and total-brain-volume; false discover rate corrections).

RESULTS

Significantly decreased GM volumes, indicating tissue injury, emerged in multiple brain regions, including the hippocampus, insula, cerebellum, parahippocampus, temporal, frontal, and occipital gyri, cingulate, amygdala, and thalamus. Higher T2-relaxation values, suggesting tissue damage, appeared in the cerebellum, hippocampus, parahippocampus, frontal, lingual, and temporal and occipital gyri, and cingulate areas in PAH compared to healthy subjects.

CONCLUSIONS

PAH patients showed significant GM injury and brain tissue changes in sites that regulate cognition, autonomic, and mood functions. These findings indicate a brain structural basis for functional deficits in PAH patients.

Single-dose L-dopa increases upper brainstem GABA in Parkinson's disease: A preliminary study

PURPOSE

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder, characterized by the dysfunction between dopaminergic and GABAergic neuronal activities. Dopamine (DA) replacement by its precursor L-dopa remains the primary treatment for PD. In this preliminary study, we test the hypotheses that GABA+ levels would be lower in PD patients than controls, and normalized by L-dopa.

METHODS

Eleven PD patients and eleven age-and gender-matched healthy controls underwent a ¹H-MRS scan of the upper brainstem using a J-difference-edited sequence to resolve signals of GABA. PD patients did not take all dopaminergic medicines for at least twelve hours prior to the first scan, and were scanned again after resuming L -dopa (pre- and post-L-dopa). MRS data were processed using the Gannet. Differences of GABA+ (GABA, macromolecules, and homocarnosine) levels within-subject (PD: pre- and post-L-dopa) and between-subjects (HC vs. PD-pre or PD-post) were tested using linear mixed-effects models with Holm-Bonferroni correction applied to pairwise comparisons.

RESULTS

Significant increased GABA+ levels were observed in the upper brainstem of PD patients post-L-dopa compared with pre-L-dopa (p < 0.001). Patients' GABA+ levels before administration of L-dopa were significantly lower than HCs (p = 0.001). Increased GABA+ level by administration of L-dopa in PD patients (post-L-dopa) was lower compared with HCs, but not significantly (p = 0.52).

CONCLUSION

Increased GABA+ levels were present in the upper brainstem with PD patients post-L-dopa, suggesting dopaminergic therapy capable of improving dopamine may improve the GABA+ levels in the upper brainstem, thereby achieving the effect of modulating the GABAergic system in the treatment of PD.

The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the single-compartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T_1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T_1t is fixed to a population average. This approach can cause CBF quantification errors, as T_1t can vary significantly inter- and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T_1t , the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T_1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T_1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T_1t value between population averages of T_1t and the longitudinal relaxation time of blood T_1b .

An information theory model for optimizing quantitative magnetic resonance imaging acquisitions

Acquisition parameter selection is currently performed empirically for many quantitative MRI (qMRI) acquisitions. Tuning parameters for different scan times, tissues, and resolutions requires some amount of trial and error. There is an opportunity to quantitatively optimize these acquisition parameters in order to minimize variability of quantitative maps and post-processing techniques such as synthetic image generation. The objective of this work is to introduce and evaluate a quantitative method for selecting parameters that minimize image variability. An information theory framework was developed for this purpose and applied to a 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) signal model for qMRI. In this framework, mutual information is used to measure the information gained by a measurement as a function of acquisition parameters, quantifying the information content of potential acquisitions and allowing informed parameter selection. The information theory framework was tested on artificial data generated from a representative mathematical phantom, measurements acquired on a qMRI multiparametric imaging standard phantom, and in vivo measurements in a human brain. The phantom measurements showed that higher mutual information calculated by the model correlated with smaller coefficient of variation in the reconstructed parametric maps, and in vivo measurements demonstrated that information-based calibration of acquisition parameters resulted in a decrease in parametric map variability consistent with model predictions.

A pilot study of magnetic resonance fingerprinting in Parkinson's disease

Parkinson's disease (PD) affects more than six million people, but reliable MRI biomarkers with which to diagnose patients have not been established. Magnetic resonance fingerprinting (MRF) is a recent quantitative technique that can provide relaxometric maps from a single sequence. The purpose of this study is to assess the potential of MRF to identify PD in patients and their disease severity, as well as to evaluate comfort during MRF. Twenty-five PD patients and 25 matching controls underwent 3 T MRI, including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 maps were generated by voxel-wise matching the measured MRF signal to a precomputed dictionary. All participants also received standard inversion recovery T1 and multi-echo T2 mapping. An ROI-based analysis of relaxation times was performed. Differences between patients and controls as well as techniques were determined by logistic regression, Spearman correlation and t-test. Patients were asked to estimate the subjective comfort of the MRF sequence. Both MRF-based T1 and T2 mapping discriminated patients from controls: T1 relaxation times differed most in cortical grey matter (PD 1337 ± 38 vs. control 1386 ± 37 ms; mean ± SD; P = .0001) and, in combination with normal-appearing white matter, enabled correct discrimination in 85.7% of cases (sensitivity 83.3%; specificity 88.0%; receiver-operating characteristic [ROC]) area under the curve [AUC] 0.87), while for T2 mapping the left putamen was the strongest classifier (40.54 ± 6.28 vs. 34.17 ± 4.96 ms; P = .0001), enabling differentiation of groups in 84.0% of all cases (sensitivity 80.0%; specificity 88.0%; ROC AUC 0.87). Relaxation time differences were not associated with disease severity. Standard mapping techniques generated significantly different relaxation time values and identified other structures as different between groups other than MRF. Twenty-three out of 25 PD patients preferred the MRF examination instead of a standard MRI. MRF-based mapping can identify PD patients with good comfort but needs further assessment regarding disease severity identification and its potential for comparability with standard mapping technique results.

Unsupervised learning for magnetization transfer contrast MR fingerprinting: Application to CEST and nuclear Overhauser enhancement imaging

PURPOSE

To develop a fast, quantitative 3D magnetization transfer contrast (MTC) framework based on an unsupervised learning scheme, which will provide baseline reference signals for CEST and nuclear Overhauser enhancement imaging.

METHODS

Pseudo-randomized RF saturation parameters and relaxation delay times were applied in an MR fingerprinting framework to generate transient-state signal evolutions for different MTC parameters. Prospectively compressed sensing-accelerated (four-fold) MR fingerprinting images were acquired from 6 healthy volunteers at 3 T. A convolutional neural network framework in an unsupervised fashion was designed to solve an inverse problem of a two-pool MTC Bloch equation, and was compared with a conventional Bloch equation-based fitting approach. The MTC images synthesized by the convolutional neural network architecture were used for amide proton transfer and nuclear Overhauser enhancement imaging as a reference baseline image.

RESULTS

The fully unsupervised learning scheme incorporated with the two-pool exchange model learned a set of unique features that can describe the MTC-MR fingerprinting input, and allowed only small amounts of unlabeled data for training. The MTC parameter values estimated by the unsupervised learning method were in excellent agreement with values estimated by the conventional Bloch fitting approach, but dramatically reduced computation time by ~1000-fold.

CONCLUSION

Given the considerable time efficiency compared to conventional Bloch fitting, unsupervised learning-based MTC-MR fingerprinting could be a powerful tool for quantitative MTC and CEST/nuclear Overhauser enhancement imaging.

Three-dimensional whole-brain simultaneous T1, T2, and T1ρ quantification using MR Multitasking: Method and initial clinical experience in tissue characterization of multiple sclerosis

PURPOSE

To develop a 3D whole-brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co-registered multiparametric maps in 9 min.

METHODS

MR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low-rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan-rescan repeatability. Initial clinical validation was performed in age-matched relapsing-remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast-weighted images was also examined.

RESULTS

Our framework produced high quality, co-registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland-Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2-weighted, T2-FLAIR, double inversion recovery, and a novel "T1ρ-FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone.

CONCLUSION

MR Multitasking simultaneously quantifies whole-brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS.

Measurement of baseline locomotion and other behavioral traits in a common marmoset model of Parkinson's disease established by a single administration regimen of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine: providing reference data for efficacious preclinical evaluations

Supplemental Digital Content is available in the text.

Baseline locomotion and behavioral traits in the common marmoset Parkinson's disease model were examined to provide basic information for preclinical evaluations of medical treatments. A single regimen of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine at a cumulative dose of 5 mg/kg as the free base over three consecutive days was administered subcutaneously to 10 marmosets. Data obtained from these marmosets were compared to pre-1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine levels or 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine free marmosets. After the single regimen, reduced daily locomotion, a measure of immobility (a primary sign of Parkinsonism), was observed for more than a year. A moving tremor was also observed by visual inspection during this period. When apomorphine (0.13 mg/kg, s.c.) was administered, either right or left circling behavior was observed in a cylindrical chamber in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine marmosets, suggestive of unequal neural damage between the two brain hemispheres to different extents. MRI revealed that T1 relaxation time in the right substantia nigra correlated with right circling in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine marmosets. Histology was supportive of dopaminergic neural loss in the striatum. These results increase our understanding of the utility and limitations of the Parkinson's disease model in marmosets with a single 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine regimen, and provide reference data for efficacious preclinical evaluations.

Increased iron-deposition in lateral-ventral substantia nigra pars compacta: A promising neuroimaging marker for Parkinson's disease

BACKGROUND

To date there are no validated MRI biomarkers to assist diagnosis of Parkinson's disease (PD). Our aim was to investigate PD related iron changes in the substantia nigra pars compacta (SNpc) as defined by neuromelanin-sensitive MR contrast.

METHODS

Thirty-nine PD participants and 33 healthy controls were scanned at 3.0-T using a 16-echo gradient echo sequence to create R2* maps for the evaluation of iron content to find the overlap with a neuromelanin based SNpc mask. The SNpc overlap percentage with the R2* map, and the R2* values in both the whole SNpc and the overlap volume were compared between PD and control groups, and correlated with clinical features for PD participants. Finally, the diagnostic performance of the SNpc overlap percentage was evaluated using ROC analysis.

RESULTS

PD related iron changes mostly occur in the lateral-ventral part of the neuromelanin SNpc. The R2* values in the whole SNpc and the SNpc overlap volume, and the SNpc overlap percentage were larger in PD participants than in controls. Furthermore, the SNpc overlap percentage was positively correlated with the disease duration in PD. The SNpc overlap percentage provided excellent diagnostic accuracy for discriminating PD participants from controls (AUC = 0.93), while the R2* values in the whole SNpc or the overlap volume were less effective.

CONCLUSION

The overlap between the iron content as determined by R2* mapping and neuromelanin in the substantia nigra pars compacta has the potential to be a neuroimaging biomarker for diagnosing Parkinson's disease.

Multi-parametric artificial neural network fitting of phase-cycled balanced steady-state free precession data

PURPOSE

Standard relaxation time quantification using phase-cycled balanced steady-state free precession (bSSFP), eg, motion-insensitive rapid configuration relaxometry (MIRACLE), is subject to a considerable underestimation of tissue T₁ and T₂ due to asymmetric intra-voxel frequency distributions. In this work, an artificial neural network (ANN) fitting approach is proposed to simultaneously extract accurate reference relaxation times (T₁ , T₂ ) and robust field map estimates ( B 1 + , ΔB₀ ) from the bSSFP profile.

METHODS

Whole-brain bSSFP data acquired at 3T were used for the training of a feedforward ANN with N = 12, 6, and 4 phase-cycles. The magnitude and phase of the Fourier transformed complex bSSFP frequency response served as input and the multi-parametric reference set [T₁ , T₂ , B 1 + , ∆B₀ ] as target. The ANN predicted relaxation times were validated against the target and MIRACLE.

RESULTS

The ANN prediction of T₁ and T₂ for trained and untrained data agreed well with the reference, even for only four acquired phase-cycles. In contrast, relaxometry based on 4-point MIRACLE was prone to severe off-resonance-related artifacts. ANN predicted B 1 + and ∆B₀ maps showed the expected spatial inhomogeneity patterns in high agreement with the reference measurements for 12-point, 6-point, and 4-point bSSFP phase-cycling schemes.

CONCLUSION

ANNs show promise to provide accurate brain tissue T₁ and T₂ values as well as reliable field map estimates. Moreover, the bSSFP acquisition can be accelerated by reducing the number of phase-cycles while still delivering robust T₁ , T₂ , B 1 + , and ∆B₀ estimates.

B0-field dependence of MRI T1 relaxation in human brain

Tissue longitudinal relaxation characterized by recovery time T1 or rate R1 is a fundamental MRI contrast mechanism that is increasingly being used to study the brain's myelination patterns in both health and disease. Nevertheless, the quantitative relationship between T1 and myelination, and its dependence on B0 field strength, is still not well known. It has been theorized that in much of brain tissue, T1 field-dependence is driven by that of macromolecular protons (MP) through a mechanism called magnetization transfer (MT). Despite the explanatory power of this theory and substantial support from in-vitro experiments at low fields (<3 ​T), in-vivo evidence across clinically relevant field strengths is lacking. In this study, T1-weighted MRI was acquired in a group of eight healthy volunteers at four clinically relevant field strengths (0.55, 1.5, 3 and 7 ​T) using the same pulse sequence at a single site, and jointly analyzed based on the two-pool model of MT. MP fraction and free-water pool T1 were obtained in several brain structures at 3 and 7 ​T, which allowed distinguishing between contributions from macromolecular content and iron to tissue T1. Based on this, the T1 of MP in white matter, indirectly determined by assuming a field independent T1 of free water, was shown to increase approximately linearly with B0. This study advances our understanding of the T1 contrast mechanism and its relation to brain myelin content across the wide range of currently available MRI strengths, and it has the potential to inform design of T1 mapping methods for improved reproducibility in the human brain.

Clioquinol improves motor and non-motor deficits in MPTP-induced monkey model of Parkinson's disease through AKT/mTOR pathway

Despite decades of research into the pathology mechanisms of Parkinson’s disease (PD), disease-modifying therapy of PD is scarce. Thus, searching for new drugs or more effective neurosurgical treatments has elicited much interest. Clioquinol (CQ) has been shown to have therapeutic benefits in rodent models of neurodegenerative disorders. However, it’s neuroprotective role and mechanisms in PD primate models and PD patients, especially in the advanced stages, are not fully understood. Furthermore, issues such as spontaneous recovery of motor function and high symptom variability in different monkeys after the same toxic protocol, has not been resolved before the present study. In this study, we designed a chronic and long-term progressive protocol to generate a stabilized PD monkey model showed with classic motor and non-motor deficits, followed by treatment analysis of CQ. We found that CQ could remarkably improve the motor and non-motor deficits, which were based on the reduction of iron content and ROS level in the SN and further improvement in pathology. Meanwhile, we also showed that ferroptosis was probably involved in the pathogenesis of PD. In addition, the study shows a positive effect of CQ on AKT/mTOR survival pathway and a blocking effect on p53 medicated cell death in vivo and in vitro.

Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction

Magnetic resonance (MR) imaging tasks often involve multiple contrasts, such as T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) data. These contrasts capture information associated with the same underlying anatomy and thus exhibit similarities in either structure level or gray level. In this paper, we propose a coupled dictionary learning based multi-contrast MRI reconstruction (CDLMRI) approach to leverage the dependency correlation between different contrasts for guided or joint reconstruction from their under-sampled k -space data. Our approach iterates between three stages: coupled dictionary learning, coupled sparse denoising, and enforcing k -space consistency. The first stage learns a set of dictionaries that not only are adaptive to the contrasts, but also capture correlations among multiple contrasts in a sparse transform domain. By capitalizing on the learned dictionaries, the second stage performs coupled sparse coding to remove the aliasing and noise in the corrupted contrasts. The third stage enforces consistency between the denoised contrasts and the measurements in the k -space domain. Numerical experiments, consisting of retrospective under-sampling of various MRI contrasts with a variety of sampling schemes, demonstrate that CDLMRI is capable of capturing structural dependencies between different contrasts. The learned priors indicate notable advantages in multi-contrast MR imaging and promising applications in quantitative MR imaging such as MR fingerprinting.

Clinical and Neuropathological Features Associated With Loss of RAB39B

BACKGROUND

Pathogenic variants in the small GTPase Ras Analogue in Brain 39b (RAB39B) have been linked to the development of early-onset parkinsonism. The study was aimed at delineating the clinical and neuropathological features associated with a previously reported pathogenic variant in RAB39B (c.503C>A p.T168K) and testing for dysregulation of RAB39B in idiopathic PD.

METHODS

Clinical details of a male individual hemizygous for the T168K variant were collected by systematic review of medical records. Neuropathological studies of fixed brain tissue were performed and steady-state RAB39B levels were determined by western blot analysis.

RESULTS

Neuropathological examination showed extensive dopaminergic neuron loss, widespread Lewy pathology, and iron accumulation in the substantia nigra. Additional pathology was observed in the hippocampus and thalamus. Western blot analysis demonstrated that the T168K variant results in loss of RAB39B. In individuals with idiopathic PD (n = 10, 6 male/4 female), steady-state RAB39B was significantly reduced in the prefrontal cortex and substantia nigra.

CONCLUSIONS

T168K RAB39B is unstable in vivo and associated with dopaminergic neuron loss and Lewy pathology. Dysregulation of RAB39B in the prefrontal cortex and substantia nigra of individuals with idiopathic PD potentially implicates the protein more broadly in the pathological mechanisms underlying PD and related Lewy body disorders. © 2020 International Parkinson and Movement Disorder Society.

[Method for Quantitative Evaluation of the Substantia Nigra Using Phase-sensitive Inversion Recovery in 1.5 T Magnetic Resonance Imaging]

PURPOSE

Parkinson's disease is a neurodegenerative disease with movement disorders caused by degeneration of the substantia nigra (SN) in the midbrain. Magnetic resonance imaging (MRI) is used to exclude similar diseases. Recently, neuro-melanin imaging (NMI) has been proposed as an imaging method for evaluating the SN. However, the evaluation of the image using this is qualitative, and normal SN cannot be visualized at 1.5 T. This study aimed to investigate whether the SN can be quantitatively evaluated by using phase-sensitive inversion recovery (PSIR) at 1.5 T.

METHOD

The phantom was imaged by PSIR and the accuracy of T₁ value was verified. Next, the healthy volunteers were imaged by PSIR, and the T₁ value and area of the SN were measured.

RESULT

As a result of the phantom study, the difference of the T₁value between PSIR and inversion recovery spin-echo in the range of the T₁ value the SN and the cerebral peduncle (500 to 1000 ms) was lesser than ±10%. The difference between the average of T₁ values of the SN measured by PSIR and the previously reported T₁ values of the SN was about 1.1%. Furthermore, the average of the area of the SN measured by PSIR was measured independently of imaging parameters by using the T₁ value as a reference.

CONCLUSION

These results indicate the possibility of a quantitative evaluation of the SN by measuring its area and T₁ value by using PSIR at 1.5 T.

Submillimeter MR fingerprinting using deep learning-based tissue quantification

PURPOSE

To develop a rapid 2D MR fingerprinting technique with a submillimeter in-plane resolution using a deep learning-based tissue quantification approach.

METHODS

A rapid and high-resolution MR fingerprinting technique was developed for brain T₁ and T₂ quantification. The 2D acquisition was performed using a FISP-based MR fingerprinting sequence and a spiral trajectory with 0.8-mm in-plane resolution. A deep learning-based method was used to replace the standard template matching method for improved tissue characterization. A novel network architecture (i.e., residual channel attention U-Net) was proposed to improve high-resolution details in the estimated tissue maps. Quantitative brain imaging was performed with 5 adults and 2 pediatric subjects, and the performance of the proposed approach was compared with several existing methods in the literature.

RESULTS

In vivo measurements with both adult and pediatric subjects show that high-quality T₁ and T₂ mapping with 0.8-mm in-plane resolution can be achieved in 7.5 seconds per slice. The proposed deep learning method outperformed existing algorithms in tissue quantification with improved accuracy. Compared with the standard U-Net, high-resolution details in brain tissues were better preserved by the proposed residual channel attention U-Net. Experiments on pediatric subjects further demonstrated the potential of the proposed technique for fast pediatric neuroimaging. Alongside reduced data acquisition time, a 5-fold acceleration in tissue property mapping was also achieved with the proposed method.

CONCLUSION

A rapid and high-resolution MR fingerprinting technique was developed, which enables high-quality T₁ and T₂ quantification with 0.8-mm in-plane resolution in 7.5 seconds per slice.

Regional T1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence

The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T₁ contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T₁ determination with minimal B₁⁺ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T₁ reproducibility and preliminary evidences of age- and tract-related T₁ variations in the healthy spinal cord.

The Association of Iron and the Pathologies of Parkinson's Diseases in MPTP/MPP+-Induced Neuronal Degeneration in Non-human Primates and in Cell Culture

Despite much efforts in the last few decades, the mechanism of degeneration of dopamine (DA) neurons in the substantia nigra (SN) in Parkinson’s disease (PD) remains unclear. This represents a major knowledge gap in idiopathic and genetic forms of PD. Among various possible key factors postulated, iron metabolism has been widely suggested to be involved with fueling oxidative stress, a known factor in the pathogenesis of PD. However, the correlation between iron and DA neuron loss, specifically in the SN, has not been described in experimental animal models with great detail, with most studies utilizing rodents and, rarely, non-human primates. In the present study, aiming to gain further evidence of a pathological role of iron in PD, we have examined the correlation of iron with DA neuron loss in a non-human primate model of PD induced by MPTP. We report a significant iron accumulation accompanied by both DA degeneration in the SN and motor deficits in the monkey that displayed the most severe PD pathology and behavioral deficits. The other two monkeys subjected to MPTP displayed less severe PD pathologies and motor deficits, however, their SN iron levels were significantly lower than controls. These findings suggest that high iron may indicate and contribute to heightened MPP⁺-induced PD pathology in late or severe stages of PD, while depressed levels of iron may signal an early stage of disease. Similarly, using a cell culture preparation, we have found that high doses of ferric ammonium citrate (FAC), a factor known to enhance iron accumulation, increased MPP⁺-induced cell death in U251 and SH-SY5Y cells, and even in control cells. However, at low dose FAC restored or increased the viability of U251 and SH-SY5Y cells in the absence or presence of MPP⁺. These observations imply that high levels of iron likely contribute to or heighten MPP⁺ toxicity in the later stages of PD. While we report reduced iron levels in the earlier stages of MPTP induced PD, the significance of these changes remains to be determined.

Multi T1-weighted contrast MRI with fluid and white matter suppression at 1.5 T

INTRODUCTION

The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted co-registered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1.5 T. In this study, the FLAWS sequence was optimized for use at 1.5 T. In addition, the contrast-enhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the division (FLAWS-div) and the high contrast (FLAWS-hc) image.

METHODS

FLAWS sequence parameters were optimized for 1.5 T imaging using an approach based on the use of a profit function under constraints for brain tissue signal and contrast maximization. MR experiments were performed on eleven healthy volunteers (age 18-30). Contrast (CN) and contrast to noise ratio (CNR) between brain tissues were measured in each volunteer. Furthermore, a qualitative assessment was performed to ensure that the separation between the internal globus pallidus (GPi) and the external globus pallidus (GPe) is identifiable in FLAWS1.

RESULTS

The optimized set of sequence parameters for FLAWS at 1.5 T provided contrasts similar to those obtained in a previous study at 3 T. The separation between the GPi and the GPe was clearly identified in FLAWS1. The CN of FLAWS-hc was higher than that of FLAWS1 and FLAWS2, but was not different from the CN of FLAWS-div. The CNR of FLAWS-hc was higher than that of FLAWS-div.

CONCLUSION

Both qualitative and quantitative assessments validated the optimization of the FLAWS sequence at 1.5 T. Quantitative assessments also showed that FLAWS-hc provides an enhanced contrast compared to FLAWS1 and FLAWS2, with a higher CNR than FLAWS-div.

Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T

Fully-quantitative MR imaging methods are useful for longitudinal characterization of disease and assessment of treatment efficacy. However, current quantitative MRI protocols have not been widely adopted in the clinic, mostly due to lengthy scan times. Magnetic Resonance Fingerprinting (MRF) is a new technique that can reconstruct multiple parametric maps from a single fast acquisition in the transient state of the MR signal. Due to the relative novelty of this technique, the repeatability and reproducibility of quantitative measurements obtained using MRF has not been extensively studied. Our study acquired test/retest data from the brains of nine healthy volunteers, each scanned on five MRI systems (two at 3.0 T and three at 1.5 T, all from a single vendor) located at two different centers. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived M0, T1 and T2 maps to an anatomical atlas, coefficients-of-variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated an excellent repeatability (CVs of 2-3% for T1, 5-8% for T2, 3% for normalized-M0) and a good reproducibility (CVs of 3-8% for T1, 8-14% for T2, 5% for normalized-M0) in grey and white matter.