Dynamics for High-Sensitivity Detection of Free Radicals in Primary Bronchial Epithelial Cells upon Stimulation with Cigarette Smoke Extract.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is caused by chronic exposure to toxic particles and gases, such as cigarette smoke. Free radicals, which are produced during a stress response to toxic particles, play a crucial role in disease progression. Measuring these radicals is difficult since the complex mixture of chemicals within cigarette smoke interferes with radical detection. We used a new quantum sensing technique called relaxometry to measure free radicals with nanoscale resolution on cells from COPD patients and healthy controls exposed to cigarette smoke extract (CSE) or control medium. Epithelial cells from COPD patients display a higher free radical load than those from healthy donors and are more vulnerable to CSE. We show that epithelial cells of COPD patients are more susceptible to the damaging effects of cigarette smoke, leading to increased release of free radicals.

Nitrogen-Vacancy Magnetic Relaxometry of Nanoclustered Cytochrome C Proteins.

Nitrogen-vacancy (NV) magnetometry offers an alternative tool to detect paramagnetic centers in cells with a favorable combination of magnetic sensitivity and spatial resolution. Here, we employ NV magnetic relaxometry to detect cytochrome C (Cyt-C) nanoclusters. Cyt-C is a water-soluble protein that plays a vital role in the electron transport chain of mitochondria. Under ambient conditions, the heme group in Cyt-C remains in the Fe3+ state, which is paramagnetic. We vary the concentration of Cyt-C from 6 to 54 µM and observe a reduction of the NV spin-lattice relaxation time (T1) from 1.2 ms to 150 µs, which is attributed to the spin noise originating from the Fe3+ spins. NV T1 imaging of Cyt-C drop-casted on a nanostructured diamond chip allows us to detect the relaxation rates from the adsorbed Fe3+ within Cyt-C.

Room Temperature Relaxometry of Single Nitrogen Vacancy Centers in Proximity to α-RuCl3 Nanoflakes.

Nitrogen vacancy (NV) center-based magnetometry has been proven to be a versatile sensor for various classes of magnetic materials in broad temperature and frequency ranges. Here, we use the longitudinal relaxation time T1 of single NV centers to investigate the spin dynamics of nanometer-thin flakes of α-RuCl3 at room temperature. We observe a significant reduction in the T1 in the presence of α-RuCl3 in the proximity of NVs, which we attribute to paramagnetic spin noise confined in the 2D hexagonal planes. Furthermore, the T1 time exhibits a monotonic increase with an applied magnetic field. We associate this trend with the alteration of the spin and charge noise in α-RuCl3 under an external magnetic field. These findings suggest that the influence of the spin dynamics of α-RuCl3 on the T1 of the NV center can be used to gain information about the material itself and the technique to be used on other 2D materials.

A Cellular Ground Truth to Develop MRI Signatures in Glioma Models by Correlative Light Sheet Microscopy and Atlas-Based Coregistration.

Glioblastoma is the most common malignant primary brain tumor with poor overall survival. Magnetic resonance imaging (MRI) is the main imaging modality for glioblastoma but has inherent shortcomings. The molecular and cellular basis of MR signals is incompletely understood. We established a ground truth-based image analysis platform to coregister MRI and light sheet microscopy (LSM) data to each other and to an anatomic reference atlas for quantification of 20 predefined anatomic subregions. Our pipeline also includes a segmentation and quantification approach for single myeloid cells in entire LSM datasets. This method was applied to three preclinical glioma models in male and female mice (GL261, U87MG, and S24), which exhibit different key features of the human glioma. Multiparametric MR data including T2-weighted sequences, diffusion tensor imaging, T2 and T2* relaxometry were acquired. Following tissue clearing, LSM focused on the analysis of tumor cell density, microvasculature, and innate immune cell infiltration. Correlated analysis revealed differences in quantitative MRI metrics between the tumor-bearing and the contralateral hemisphere. LSM identified tumor subregions that differed in their MRI characteristics, indicating tumor heterogeneity. Interestingly, MRI signatures, defined as unique combinations of different MRI parameters, differed greatly between the models. The direct correlation of MRI and LSM allows an in-depth characterization of preclinical glioma and can be used to decipher the structural, cellular, and, likely, molecular basis of tumoral MRI biomarkers. Our approach may be applied in other preclinical brain tumor or neurologic disease models, and the derived MRI signatures could ultimately inform image interpretation in a clinical setting.SIGNIFICANCE STATEMENT We established a histologic ground truth-based approach for MR image analyses and tested this method in three preclinical glioma models exhibiting different features of glioblastoma. Coregistration of light sheet microscopy to MRI allowed for an evaluation of quantitative MRI data in histologically distinct tumor subregions. Coregistration to a mouse brain atlas enabled a regional comparison of MRI parameters with a histologically informed interpretation of the results. Our approach is transferable to other preclinical models of brain tumors and further neurologic disorders. The method can be used to decipher the structural, cellular, and molecular basis of MRI signal characteristics. Ultimately, information derived from such analyses could strengthen the neuroradiological evaluation of glioblastoma as they enhance the interpretation of MRI data.

Distance from main arteries influences microstructural and functional brain tissue characteristics.

Given the substantial dependence of neurons on continuous supply of energy, the distribution of major cerebral arteries opens a question whether the distance from the main supply arteries constitutes a modulating factor for the microstructural and functional properties of brain tissue. To tackle this question, multimodal MRI acquisitions of 102 healthy volunteers over the full adult age span were utilised. Relaxation along a fictitious field in the rotating frame of rank n = 4 (RAFF4), adiabatic T1ρ, T2ρ,  and intracellular volume fraction (fICVF) derived from diffusion-weighted imaging were implemented to quantify microstructural (cellularity, myelin density, iron concentration) tissue characteristics and degree centrality and fractional amplitude of low-frequency fluctuations to probe for functional metrics. Inverse correlation of arterial distance with robust homogeneity was detected for T1ρ, T2ρ and RAFF4 for cortical grey matter and white matter, showing substantial complex microstructural differences between brain tissue close and farther from main arterial trunks. Albeit with wider variability, functional metrics pointed to increased connectivity and neuronal activity in areas farther from main arteries. Surprisingly, multiple of these microstructural and functional distance-based gradients diminished with higher age, pointing to uniformization of brain tissue with ageing. All in all, this pilot study provides a novel insight on brain regionalisation based on artery distance, which merits further investigation to validate its biological underpinnings.

Anisotropy of T2 and T1ρ relaxation time in articular cartilage at 3 T.

PURPOSE: The anisotropy of R2 and R1ρ relaxation rates in articular cartilage contains information about the collagenous structure of the tissue. Here we determine and study the anisotropic and isotropic components of T2 and T1ρ relaxation parameters in articular cartilage with a clinical 3T MRI device. Furthermore, a visual representation of the topographical variation in anisotropy is given via anisotropy mapping. METHODS: Eight bovine stifle joints were imaged at 22 orientations with respect to the main magnetic field using T2, continuous-wave (CW) T1ρ, and adiabatic T1ρ mapping sequences. Relaxation rates were separated into isotropic and anisotropic relaxation components using a previously established relaxation anisotropy model. Pixel-wise anisotropy values were determined from the relaxation-time maps using Michelson contrast. RESULTS: The relaxation rates obtained from the samples displayed notable variation depending on the sample orientation, magnetization preparation, and cartilage layer. R2 demonstrated significant anisotropy, whereas CW-R1ρ (300 Hz) and CW-R1ρ (500 Hz) displayed a low degree of anisotropy. Adiabatic R1ρ was largely isotropic. In the deep cartilage regions, relaxation rates were generally faster and more anisotropic than in the cartilage closer to the tissue surface. The isotropic relaxation rate components were found to have similar values regardless of measurement sequence. CONCLUSIONS: The fitted relaxation model for T2 and T1ρ demonstrated varying amounts anisotropy, depending on magnetization preparation, and studied the articular cartilage layer. Anisotropy mapping of full joints showed varying amounts of anisotropy depending on the quantitative MRI parameter and topographical location, and in the case of T2, showed systematic changes in anisotropy across cartilage depth.

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.

In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences.

PURPOSE: We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements. METHODS: Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system. RESULTS: The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies. CONCLUSION: The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

Characterizing T1 in the fetal brain and placenta over gestational age at 0.55T.

PURPOSE: T1 mapping and T1-weighted contrasts have a complimentary but currently under utilized role in fetal MRI. Emerging clinical low field scanners are ideally suited for fetal T1 mapping. The advantages are lower T1 values which results in higher efficiency and reduced field inhomogeneities resulting in a decreased requirement for specialist tools. In addition the increased bore size associated with low field scanners provides improved patient comfort and accessibility. This study aims to demonstrate the feasibility of fetal brain T1 mapping at 0.55T. METHODS: An efficient slice-shuffling inversion-recovery echo-planar imaging (EPI)-based T1-mapping and postprocessing was demonstrated for the fetal brain at 0.55T in a cohort of 38 fetal MRI scans. Robustness analysis was performed and placental measurements were taken for validation. RESULTS: High-quality T1 maps allowing the investigation of subregions in the brain were obtained and significant correlation with gestational age was demonstrated for fetal brain T1 maps ( p < 0 . 05 $$ p<0.05 $$ ) as well as regions-of-interest in the deep gray matter and white matter. CONCLUSIONS: Efficient, quantitative T1 mapping in the fetal brain was demonstrated on a clinical 0.55T MRI scanner, providing foundations for both future research and clinical applications including low-field specific T1-weighted acquisitions.

Radiation damping at clinical field strength: Characterization and compensation in quantitative measurements.

PURPOSE: In any MR experiment, the bulk magnetization acts on itself, caused by the induced current in the RF receiver circuit that generates an oscillating damping field. This effect, known as "radiation damping" (RD), is usually weak and, therefore, unconsidered in MRI, but can affect quantitative studies performed with dedicated coils that provide a high SNR. The current work examined RD in a setup for investigations of small tissue specimens including a quantitative characterization of the spin-coil system. THEORY AND METHODS: A custom-made Helmholtz coil (radius and spacing 16 mm) was interfaced to a transmit-receive (Tx/Rx) switch with integrated passive feedback for modulation or suppression of RD similar to preamplifier decoupling. Pulse sequences included pulse-width arrays to demonstrate the absence/ presence of RD and difference techniques employing gradient pulses or composite RF pulses to quantify RD effects during free precession and transmission, respectively. Experiments were performed at 3T in small samples of MnCl2 solution. RESULTS: Significant RD effects may impact RF pulse application and evolution periods. Effective damping time constants were comparable to typical T2 * times or echo spacings in multi-echo sequences. Measurements of the phase relation showed that deviations from the commonly assumed 90° angle between the damping field and the transverse magnetization may occur. CONCLUSION: Radiation damping may affect the accuracy of quantitative MR measurements performed with dedicated RF coils. Efficient mitigation can be achieved hardware-based or by appropriate consideration in the pulse sequence.

Deep learning-assisted preclinical MR fingerprinting for sub-millimeter T1 and T2 mapping of entire macaque brain.

PURPOSE: Preclinical MR fingerprinting (MRF) suffers from long acquisition time for organ-level coverage due to demanding image resolution and limited undersampling capacity. This study aims to develop a deep learning-assisted fast MRF framework for sub-millimeter T1 and T2 mapping of entire macaque brain on a preclinical 9.4 T MR system. METHODS: Three dimensional MRF images were reconstructed by singular value decomposition (SVD) compressed reconstruction. T1 and T2 mapping for each axial slice exploited a self-attention assisted residual U-Net to suppress aliasing-induced quantification errors, and the transmit-field (B1 + ) measurements for robustness against B1 + inhomogeneity. Supervised network training used MRF images simulated via virtual parametric maps and a desired undersampling scheme. This strategy bypassed the difficulties of acquiring fully sampled preclinical MRF data to guide network training. The proposed fast MRF framework was tested on experimental data acquired from ex vivo and in vivo macaque brains. RESULTS: The trained network showed reasonable adaptability to experimental MRF images, enabling robust delineation of various T1 and T2 distributions in the brain tissues. Further, the proposed MRF framework outperformed several existing fast MRF methods in handling the aliasing artifacts and capturing detailed cerebral structures in the mapping results. Parametric mapping of entire macaque brain at nominal resolution of 0.35 × $$ \times $$ 0.35 × $$ \times $$ 1 mm3 can be realized via a 20-min 3D MRF scan, which was sixfold faster than the baseline protocol. CONCLUSION: Introducing deep learning to MRF framework paves the way for efficient organ-level high-resolution quantitative MRI in preclinical applications.

Fully automated planning for anatomical fetal brain MRI on 0.55T.

PURPOSE: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. METHODS: Deep learning-based detection of key brain landmarks on a whole-uterus echo planar imaging scan enables the subsequent fully automatic planning of the radiological single-shot Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on over 120 datasets from varying field strength, echo times, and resolutions and quantitatively evaluated. The entire automatic planning solution was tested prospectively in nine fetal subjects between 20 and 37 weeks. A comprehensive evaluation of all steps, the distance between manual and automatic landmarks, the planning quality, and the resulting image quality was conducted. RESULTS: Prospective automatic planning was performed in real-time without latency in all subjects. The landmark detection accuracy was 4.2 ± $$ \pm $$ 2.6 mm for the fetal eyes and 6.5 ± $$ \pm $$ 3.2 for the cerebellum, planning quality was 2.4/3 (compared to 2.6/3 for manual planning) and diagnostic image quality was 2.2 compared to 2.1 for manual planning. CONCLUSIONS: Real-time automatic planning of all three key fetal brain planes was successfully achieved and will pave the way toward simplifying the acquisition of fetal MRI thereby widening the availability of this modality in nonspecialist centers.

Tensor denoising of quantitative multi-parameter mapping.

PURPOSE: Quantitative multi-parameter mapping (MPM) provides maps of physical quantities representing physiologically meaningful tissue characteristics, which allows to investigate microstructure-function relationships reflecting normal or pathologic processes in the brain. However, the achievable spatial resolution and stability of MPM for basic research or clinical applications is severely constrained by SNR limits of the MR acquisition process, resulting in relatively long acquisition times. To increase SNR, we denoise MPM acquisitions using principal component analysis along tensors exploiting the Marchenko-Pastur law (tMPPCA). METHODS: tMPPCA denoising was applied to three sets of MPM raw data before the quantification of maps of proton density, magnetization transfer saturation, R1, and R2*. The regional SNR gain for high-resolution MPM was investigated as well as reproducibility gains for clinically optimized protocols with moderate and high acceleration factors at different image resolutions. RESULTS: Substantial noise reduction in raw data was achieved, resulting in reduced noise for quantitative mapping up to sixfold without introducing bias of mean values (below 1%). Scan-rescan fluctuations were reduced up to threefold. Denoising allowed to decrease the voxel volume fourfold at the same scan time or reduce the scan time twofold at same voxel volume without loss of sensitivity. CONCLUSIONS: tMPPCA denoising can (a) improve of fine spatial and temporal patterns, (b) considerably reduce scan time for clinical applications, or (c) increase resolution to potentially push cutting-edge MPM protocols from the upper to the lower limit of the mesoscopic scale.

Cross-vendor multiparametric mapping of the human brain using 3D-QALAS: A multicenter and multivendor study.

PURPOSE: To evaluate a vendor-agnostic multiparametric mapping scheme based on 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) for whole-brain T1, T2, and proton density (PD) mapping. METHODS: This prospective, multi-institutional study was conducted between September 2021 and February 2022 using five different 3T systems from four prominent MRI vendors. The accuracy of this technique was evaluated using a standardized MRI system phantom. Intra-scanner repeatability and inter-vendor reproducibility of T1, T2, and PD values were evaluated in 10 healthy volunteers (6 men; mean age ± SD, 28.0 ± 5.6 y) who underwent scan-rescan sessions on each scanner (total scans = 100). To evaluate the feasibility of 3D-QALAS, nine patients with multiple sclerosis (nine women; mean age ± SD, 48.2 ± 11.5 y) underwent imaging examination on two 3T MRI systems from different manufacturers. RESULTS: Quantitative maps obtained with 3D-QALAS showed high linearity (R2 = 0.998 and 0.998 for T1 and T2, respectively) with respect to reference measurements. The mean intra-scanner coefficients of variation for each scanner and structure ranged from 0.4% to 2.6%. The mean structure-wise test-retest repeatabilities were 1.6%, 1.1%, and 0.7% for T1, T2, and PD, respectively. Overall, high inter-vendor reproducibility was observed for all parameter maps and all structure measurements, including white matter lesions in patients with multiple sclerosis. CONCLUSION: The vendor-agnostic multiparametric mapping technique 3D-QALAS provided reproducible measurements of T1, T2, and PD for human tissues within a typical physiological range using 3T scanners from four different MRI manufacturers.

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

PURPOSE: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. THEORY AND METHODS: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images. RESULTS: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes. CONCLUSION: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Robust T2 estimation with balanced steady state free precession.

PURPOSE: To develop a novel signal representation for balanced steady state free precession (bSSFP) displaying its T2 independence on B1 and on magnetization transfer (MT) effects. METHODS: A signal model for bSSFP is developed that shows only an explicit dependence (up to a scaling factor) on E2 (and, therefore, T2) and a novel parameter c (with implicit dependence on the flip angle and E1). Moreover, it is shown that MT effects, entering the bSSFP signal via a binary spin bath model, can be captured by a redefinition of T1 and, therefore, leading to modification of E1, resulting in the same signal model. Various sets of phase-cycled bSSFP brain scans (different flip angles, different TR, different RF pulse durations, and different number of phase cycles) were recorded at 3 T. The parameters T2 (E2) and c were estimated using a variable projection (VARPRO) method and Monte-Carlo simulations were performed to assess T2 estimation precision. RESULTS: Initial experiments confirmed the expected independence of T2 on various protocol settings, such as TR, the flip angle, B1 field inhomogeneity, and the RF pulse duration. Any variation (within the explored range) appears to directly affect the estimation of the parameter c only-in agreement with theory. CONCLUSION: BSSFP theory predicts an extraordinary feature that all MT and B1-related variational aspects do not enter T2 estimation, making it a potentially robust methodology for T2 quantification, pending validation against existing standards.

Dynamic T 2 * relaxometry of hyperpolarized [1-13 C]pyruvate MRI in the human brain and kidneys.

PURPOSE: This study aimed to quantify T 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T. METHODS: Dynamic T 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamic T 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients. T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimated T 2 * $$ {T}_2^{\ast } $$ correction. RESULTS: The T 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas the T 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. The T 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and the T 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). The T 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys. CONCLUSION: Multi-echo dynamic imaging can quantify T 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in the T 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.

Simultaneous perfusion, diffusion, T2 *, and T1 mapping with MR fingerprinting.

PURPOSE: Quantitative mapping of brain perfusion, diffusion, T2 *, and T1 has important applications in cerebrovascular diseases. At present, these sequences are performed separately. This study aims to develop a novel MRI technique to simultaneously estimate these parameters. METHODS: This sequence to measure perfusion, diffusion, T2 *, and T1 mapping with magnetic resonance fingerprinting (MRF) was based on a previously reported MRF-arterial spin labeling (ASL) sequence, but the acquisition module was modified to include different TEs and presence/absence of bipolar diffusion-weighting gradients. We compared parameters derived from the proposed method to those derived from reference methods (i.e., separate sequences of MRF-ASL, conventional spin-echo DWI, and T2 * mapping). Test-retest repeatability and initial clinical application in two patients with stroke were evaluated. RESULTS: The scan time of our proposed method was 24% shorter than the sum of the reference methods. Parametric maps obtained from the proposed method revealed excellent image quality. Their quantitative values were strongly correlated with those from reference methods and were generally in agreement with values reported in the literature. Repeatability assessment revealed that ADC, T2 *, T1 , and B1 + estimation was highly reliable, with voxelwise coefficient of variation (CoV) <5%. The CoV for arterial transit time and cerebral blood flow was 16% ± 3% and 25% ± 9%, respectively. The results from the two patients with stroke demonstrated that parametric maps derived from the proposed method can detect both ischemic and hemorrhagic stroke. CONCLUSION: The proposed method is a promising technique for multi-parametric mapping and has potential use in patients with stroke.

A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging.

Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future.

Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies.

A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow-up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three-dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF-based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months-12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro-organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age-matched controls in both ROI-based and tract analysis. In conclusion, MRF-based MWF provides myelin-specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children.