DCE-Qnet: Deep Network Quantification of Dynamic Contrast Enhanced (DCE) MRI.

Introduction: Quantification of dynamic contrast-enhanced (DCE)-MRI has the potential to provide valuable clinical information, but robust pharmacokinetic modeling remains a challenge for clinical adoption. Methods: A 7-layer neural network called DCE-Qnet was trained on simulated DCE-MRI signals derived from the Extended Tofts model with the Parker arterial input function. Network training incorporated B1 inhomogeneities to estimate perfusion (Ktrans, vp, ve), tissue T1 relaxation, proton density and bolus arrival time (BAT). The accuracy was tested in a digital phantom in comparison to a conventional nonlinear least-squares fitting (NLSQ). In vivo testing was conducted in 10 healthy subjects. Regions of interest in the cervix and uterine myometrium were used to calculate the inter-subject variability. The clinical utility was demonstrated on a cervical cancer patient. Test-retest experiments were used to assess reproducibility of the parameter maps in the tumor. Results: The DCE-Qnet reconstruction outperformed NLSQ in the phantom. The coefficient of variation (CV) in the healthy cervix varied between 5-51% depending on the parameter. Parameter values in the tumor agreed with previous studies despite differences in methodology. The CV in the tumor varied between 1-47%. Conclusion: The proposed approach provides comprehensive DCE-MRI quantification from a single acquisition. DCE-Qnet eliminates the need for separate T1 scan or BAT processing, leading to a reduction of 10 minutes per scan and more accurate quantification.

Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain.

INTRODUCTION: This study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). METHODS: Data were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. RESULTS: Total scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. CONCLUSION: The PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.

Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review.

Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.

Quantitative longitudinal mapping of radiation-treated prostate cancer using MR fingerprinting with radial acquisition and subspace reconstruction.

MR fingerprinting (MRF) enables fast multiparametric quantitative imaging with a single acquisition and has been shown to improve diagnosis of prostate cancer. However, most prostate MRF studies were performed with spiral acquisitions that are sensitive to B0 inhomogeneities and consequent blurring. In this work, a radial MRF acquisition with a novel subspace reconstruction technique was developed to enable fast T1/T2 mapping in the prostate in under 4 min. The subspace reconstruction exploits the extensive temporal correlations in the MRF dictionary to pre-compute a low dimensional space for the solution and thus reduce the number of radial spokes to accelerate the acquisition. Iterative reconstruction with the subspace model and additional regularization of the signal representation in the subspace is performed to minimize the number of spokes and maintain matching quality and SNR. Reconstruction accuracy was assessed using the ISMRM NIST phantom. In-vivo validation was performed on two healthy subjects and two prostate cancer patients undergoing radiation therapy. The longitudinal repeatability was quantified using the concordance correlation coefficient (CCC) in one of the healthy subjects by repeated scans over 1 year. One prostate cancer patient was scanned at three time points, before initiating therapy and following brachytherapy and external beam radiation. Changes in the T1/T2 maps obtained with the proposed method were quantified. The prostate, peripheral and transitional zones, and visible dominant lesion were delineated for each study, and the statistics and distribution of the quantitative mapping values were analyzed. Significant image quality improvements compared with standard reconstruction methods were obtained with the proposed subspace reconstruction method. A notable decrease in the spread of the T1/T2 values without biasing the estimated mean values was observed with the subspace reconstruction and agreed with reported literature values. The subspace reconstruction enabled visualization of small differences in T1/T2 values in the tumor region within the peripheral zone. Longitudinal imaging of a volunteer subject yielded CCC of 0.89 for MRF T1, and 0.81 for MRF T2 in the prostate gland. Longitudinal imaging of the prostate patient confirmed the feasibility of capturing radiation treatment related changes. This work is a proof-of-concept for a high resolution and fast quantitative mapping using golden-angle radial MRF combined with a subspace reconstruction technique for longitudinal treatment response assessment in subjects undergoing radiation treatment.

Global deep learning optimization of chemical exchange saturation transfer magnetic resonance fingerprinting acquisition schedule.

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging technique but suffers from long scan times and complicated processing. CEST was recently combined with magnetic resonance fingerprinting (MRF) to address these shortcomings. However, the CEST-MRF signal depends on multiple acquisition and tissue parameters so selecting an optimal acquisition schedule is challenging. In this work, we propose a novel dual-network deep learning framework to optimize the CEST-MRF acquisition schedule. The quality of the optimized schedule was assessed in a digital brain phantom and compared with alternate deep learning optimization approaches. The effect of schedule length on the reconstruction error was also investigated. A healthy subject was scanned with optimized and random schedules and with a conventional CEST sequence for comparison. The optimized schedule was also tested in a subject with metastatic renal cell carcinoma. Reproducibility was assessed via test-retest experiments and the concordance correlation coefficient calculated for white matter (WM) and grey matter (GM). The optimized schedule was 12% shorter but yielded equal or lower normalized root mean square error for all parameters. The proposed optimization also provided a lower error compared with alternate methodologies. Longer schedules generally yielded lower error. In vivo maps obtained with the optimized schedule showed reduced noise and improved delineation of GM and WM. CEST curves synthesized from the optimized parameters were highly correlated (r = 0.99) with measured conventional CEST. The mean concordance correlation coefficient in WM/GM for all tissue parameters was 0.990/0.978 for the optimized schedule but only 0.979/0.975 for the random schedule. The proposed schedule optimization is widely applicable to MRF pulse sequences and provides accurate and reproducible tissue maps with reduced noise at a shorter scan time than a randomly generated schedule.

CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction.

PURPOSE: To develop a clinical CEST MR fingerprinting (CEST-MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. METHODS: A CEST-MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF reconstruction was performed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the six parameter DRONE reconstruction was tested in simulations using a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence, conventional MRF and CEST sequences for comparison. Reproducibility was assessed via test-retest experiments and the concordance correlation coefficient calculated for white matter and gray matter. The clinical utility of CEST-MRF was demonstrated on four patients with brain metastases in comparison to standard clinical imaging sequences. Tumors were segmented into edema, solid core, and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. RESULTS: DRONE reconstruction of the digital phantom yielded a normalized RMS error of ≤7% for all parameters. The CEST-MRF parameters were in good agreement with those from conventional MRF and CEST sequences and previous studies. The mean concordance correlation coefficient for all six parameters was 0.98 ± 0.01 in white matter and 0.98 ± 0.02 in gray matter. The CEST-MRF values in nearly all tumor regions were significantly different (P = 0.05) from each other and the contra-lateral side. CONCLUSION: Combination of EPI readout and deep learning reconstruction enabled fast, accurate and reproducible CEST-MRF in brain tumors.

Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.

Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with glioblastoma multiforme, the early apoptotic responses to oncolytic virotherapy (characterized by decreased cytosolic pH and reduced protein synthesis) can be rapidly detected via chemical-exchange-saturation-transfer magnetic resonance fingerprinting (CEST-MRF) aided by deep learning. By leveraging a deep neural network trained with simulated magnetic resonance fingerprints, CEST-MRF can generate quantitative maps of intratumoural pH and of protein and lipid concentrations by selectively labelling the exchangeable amide protons of endogenous proteins and the exchangeable macromolecule protons of lipids, without requiring exogenous contrast agents. We also show that in a healthy volunteer, CEST-MRF yielded molecular parameters that are in good agreement with values from the literature. Deep-learning-aided CEST-MRF may also be amenable to the characterization of host responses to other cancer therapies and to the detection of cardiac and neurological pathologies.

CEST MR-Fingerprinting: Practical considerations and insights for acquisition schedule design and improved reconstruction.

PURPOSE: To understand the influence of various acquisition parameters on the ability of CEST MR-Fingerprinting (MRF) to discriminate different chemical exchange parameters and to provide tools for optimal acquisition schedule design and parameter map reconstruction. METHODS: Numerical simulations were conducted using a parallel computing implementation of the Bloch-McConnell equations, examining the effect of TR, TE, flip-angle, water T1 and T2 , saturation-pulse duration, power, and frequency on the discrimination ability of CEST-MRF. A modified Euclidean distance matching metric was evaluated and compared to traditional dot product matching. L-Arginine phantoms of various concentrations and pH were scanned at 4.7T and the results compared to numerical findings. RESULTS: Simulations for dot product matching demonstrated that the optimal flip-angle and saturation times are 30∘ and 1100 ms, respectively. The optimal maximal saturation power was 3.4 µT for concentrated solutes with a slow exchange rate, and 5.2 µT for dilute solutes with medium-to-fast exchange rates. Using the Euclidean distance matching metric, much lower maximum saturation powers were required (1.6 and 2.4 µT, respectively), with a slightly longer saturation time (1500 ms) and 90∘ flip-angle. For both matching metrics, the discrimination ability increased with the repetition time. The experimental results were in agreement with simulations, demonstrating that more than a 50% reduction in scan-time can be achieved by Euclidean distance-based matching. CONCLUSIONS: Optimization of the CEST-MRF acquisition schedule is critical for obtaining the best exchange parameter accuracy. The use of Euclidean distance-based matching of signal trajectories simultaneously improved the discrimination ability and reduced the scan time and maximal saturation power required.

Rapid and quantitative chemical exchange saturation transfer (CEST) imaging with magnetic resonance fingerprinting (MRF).

PURPOSE: To develop a fast magnetic resonance fingerprinting (MRF) method for quantitative chemical exchange saturation transfer (CEST) imaging. METHODS: We implemented a CEST-MRF method to quantify the chemical exchange rate and volume fraction of the Nα -amine protons of L-arginine (L-Arg) phantoms and the amide and semi-solid exchangeable protons of in vivo rat brain tissue. L-Arg phantoms were made with different concentrations (25-100 mM) and pH (pH 4-6). The MRF acquisition schedule varied the saturation power randomly for 30 iterations (phantom: 0-6 µT; in vivo: 0-4 µT) with a total acquisition time of ≤2 min. The signal trajectories were pattern-matched to a large dictionary of signal trajectories simulated using the Bloch-McConnell equations for different combinations of exchange rate, exchangeable proton volume fraction, and water T1 and T2 relaxation times. RESULTS: The chemical exchange rates of the Nα -amine protons of L-Arg were significantly (P < 0.0001) correlated with the rates measured with the quantitation of exchange using saturation power method. Similarly, the L-Arg concentrations determined using MRF were significantly (P < 0.0001) correlated with the known concentrations. The pH dependence of the exchange rate was well fit (R2 = 0.9186) by a base catalyzed exchange model. The amide proton exchange rate measured in rat brain cortex (34.8 ± 11.7 Hz) was in good agreement with that measured previously with the water exchange spectroscopy method (28.6 ± 7.4 Hz). The semi-solid proton volume fraction was elevated in white (12.2 ± 1.7%) compared to gray (8.1 ± 1.1%) matter brain regions in agreement with previous magnetization transfer studies. CONCLUSION: CEST-MRF provides a method for fast, quantitative CEST imaging.

Ex vivo mouse brain microscopy at 15T with loop-gap RF coil.

The design of a loop-gap-resonator RF coil optimized for ex vivo mouse brain microscopy at ultra high fields is described and its properties characterized using simulations, phantoms and experimental scans of mouse brains fixed in 10% formalin containing 4 mM Magnevist™. The RF (B1) and magnetic field (B0) homogeneities are experimentally quantified and compared to electromagnetic simulations of the coil. The coil's performance is also compared to a similarly sized surface coil and found to yield double the sensitivity. A three-dimensional gradient-echo (GRE) sequence is used to acquire high resolution mouse brain scans at (47 µm)3 resolution in 1.8 h and a 20 × 20 × 19 µm3 resolution in 27 h. The high resolution obtained permitted clear visualization and identification of multiple structures in the ex vivo mouse brain and represents, to our knowledge, the highest resolution ever achieved for a whole mouse brain. Importantly, the coil design is simple and easy to construct.

Assessment of alveolar bone marrow fat content using 15 T MRI.

OBJECTIVES: Bone marrow fat is inversely correlated with bone mineral density. The aim of this study is to present a method to quantify alveolar bone marrow fat content using a 15 T magnetic resonance imaging (MRI) scanner. STUDY DESIGN: A 15 T MRI scanner with a 13-mm inner diameter loop-gap radiofrequency coil was used to scan seven 3-mm diameter alveolar bone biopsy specimens. A 3-D gradient-echo relaxation time (T1)-weighted pulse sequence was chosen to obtain images. All images were obtained with a voxel size (58 µm3) sufficient to resolve trabecular spaces. Automated volume of the bone marrow fat content and derived bone volume fraction (BV/TV) were calculated. Results were compared with actual BV/TV obtained from micro-computed tomography (CT) scans. RESULTS: Mean fat tissue volume was 20.1 ± 11%. There was a significantly strong inverse correlation between fat tissue volume and BV/TV (r = -0.68; P = .045). Furthermore, there was a strong agreement between BV/TV derived from MRI and obtained with micro-CT (interclass correlation coefficient = 0.92; P = .001). CONCLUSIONS: Bone marrow fat of small alveolar bone biopsy specimens can be quantified with sufficient spatial resolution using an ultra-high-field MRI scanner and a T1-weighted pulse sequence.

Magnetic Resonance Mediated Radiofrequency Ablation.

To introduce magnetic resonance mediated radiofrequency ablation (MR-RFA), in which the MRI scanner uniquely serves both diagnostic and therapeutic roles. In MR-RFA scanner-induced RF heating is channeled to the ablation site via a Larmor frequency RF pickup device and needle system, and controlled via the pulse sequence. MR-RFA was evaluated with simulation of electric and magnetic fields to predict the increase in local specific-absorption-rate (SAR). Temperature-time profiles were measured for different configurations of the device in agar phantoms and ex vivo bovine liver in a 1.5 T scanner. Temperature rise in MR-RFA was imaged using the proton resonance frequency method validated with fiber-optic thermometry. MR-RFA was performed on the livers of two healthy live pigs. Simulations indicated a near tenfold increase in SAR at the RFA needle tip. Temperature-time profiles depended significantly on the physical parameters of the device although both configurations tested yielded temperature increases sufficient for ablation. Resected livers from live ablations exhibited clear thermal lesions. MR-RFA holds potential for integrating RF ablation tumor therapy with MRI scanning. MR-RFA may add value to MRI with the addition of a potentially disposable ablation device, while retaining MRI's ability to provide real time procedure guidance and measurement of tissue temperature, perfusion, and coagulation.

Optimized inversion-time schedules for quantitative T1 measurements based on high-resolution multi-inversion EPI.

PURPOSE: Demonstrate an optimized multi-inversion echo-planar imaging technique to accelerate quantitative T1 mapping by judicious selection of inversion times for each slice. METHODS: Slice ordering is optimized to maximize discrimination between tissues with different T1 values. The optimized slice orderings are tested in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom and compared with an unoptimized 21-measurement acquisition. The utility of the method is demonstrated in a healthy subject in vivo at 3 T and validated with a gold-standard inversion-recovery sequence. The in vivo precision of our technique was tested by repeated scans of the same subject within a scan session and across scan sessions, occurring 28 days apart. RESULTS: Phantom measurements yielded good agreement (R2 = 0.99) between the T1 estimates from the proposed optimized protocol, reference values from the National Institute of Standards and Technology phantom and gold-standard inversion-recovery values, as well as a negligible estimation bias that was slightly lower than that from the unoptimized 21-measurement protocol (0.74 versus 19 ms). The range of values for the scan-rescan coefficient of variation was 0.86 to 0.93 (within session) and 0.83 to 0.92 (across sessions) across all scan durations tested. CONCLUSIONS: Optimized slice orderings allow faster quantitative T1 mapping. The optimized sequence yielded accurate and precise T1 maps. Magn Reson Med 79:2101-2112, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

MR Coagulation: A Novel Minimally Invasive Approach to Aneurysm Repair.

PURPOSE: To demonstrate a proof of concept of magnetic resonance (MR) coagulation, in which MR imaging scanner-induced radiofrequency (RF) heating at the end of an intracatheter long wire heats and coagulates a protein solution to effect a vascular repair by embolization. MATERIALS AND METHODS: MR coagulation was simulated by finite-element modeling of electromagnetic fields and specific absorption rate (SAR) in a phantom. A glass phantom consisting of a spherical cavity joined to the side of a tube was incorporated into a flow system to simulate an aneurysm and flowing blood with velocities of 0-1.7 mL/s. A double-lumen catheter containing the wire and fiberoptic temperature sensor in 1 lumen was passed through the flow system into the aneurysm, and 9 cm3 of protein solution was injected into the aneurysm through the second lumen. The distal end of the wire was laid on the patient table as an antenna to couple RF from the body coil or was connected to a separate tuned RF pickup coil. A high RF duty-cycle turbo spin-echo pulse sequence excited the wire such that RF energy deposited at the tip of the wire coagulated the protein solution, embolizing the aneurysm. RESULTS: The protein coagulation temperature of 60°C was reached in the aneurysm in ∼12 seconds, yielding a coagulated mass that largely filled the aneurysm. The heating rate was controlled by adjusting pulse-sequence parameters. CONCLUSIONS: MR coagulation has the potential to embolize vascular defects by coagulating a protein solution delivered by catheter using MR imaging scanner-induced RF heating of an intracatheter wire.

Algorithm comparison for schedule optimization in MR fingerprinting.

In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules.

Three-dimensional Hadamard-encoded proton spectroscopic imaging in the human brain using time-cascaded pulses at 3 Tesla.

PURPOSE: To reduce the specific-absorption-rate (SAR) and chemical shift displacement (CSD) of three-dimensional (3D) Hadamard spectroscopic imaging (HSI) and maintain its point spread function (PSF) benefits. METHODS: A 3D hybrid of 2D longitudinal, 1D transverse HSI (L-HSI, T-HSI) sequence is introduced and demonstrated in a phantom and the human brain at 3 Tesla (T). Instead of superimposing each of the selective Hadamard radiofrequency (RF) pulses with its N single-slice components, they are cascaded in time, allowing N-fold stronger gradients, reducing the CSD. A spatially refocusing 180° RF pulse following the T-HSI encoding block provides variable, arbitrary echo time (TE) to eliminate undesirable short T2 species' signals, e.g., lipids. RESULTS: The sequence yields 10-15% better signal-to-noise ratio (SNR) and 8-16% less signal bleed than 3D chemical shift imaging of equal repetition time, spatial resolution and grid size. The 13 ± 6, 22 ± 7, 24 ± 8, and 31 ± 14 in vivo SNRs for myo-inositol, choline, creatine, and N-acetylaspartate were obtained in 21 min from 1 cm(3) voxels at TE ≈ 20 ms. Maximum CSD was 0.3 mm/ppm in each direction. CONCLUSION: The new hybrid HSI sequence offers a better localized PSF at reduced CSD and SAR at 3T. The short and variable TE permits acquisition of short T2 and J-coupled metabolites with higher SNR.

Non-spin-echo 3D transverse hadamard encoded proton spectroscopic imaging in the human brain.

A non-spin-echo multivoxel proton MR localization method based on three-dimensional transverse Hadamard spectroscopic imaging is introduced and demonstrated in a phantom and the human brain. Spatial encoding is achieved with three selective 90° radiofrequency pulses along perpendicular axes: The first two create a longitudinal ±M(Z) Hadamard order in the volume of interest. The third pulse spatially Hadamard-encodes the ±M(Z)s in the volume of interest in the third direction while bringing them to the transverse plane to be acquired immediately. The approaching-ideal point spread function of Hadamard encoding and very short acquisition delay yield signal-to-noise-ratios of 20 ± 8, 23 ± 9, and 31 ± 10 for choline, creatine, and N-acetylaspartate in the human brain at 1.5 T from 1 cm(3) voxels in 21 min. The advantages of transverse Hadamard spectroscopic imaging are that unlike gradient (Fourier) phase-encoding: (i) the volume of interest does not need to be smaller than the field of view to prevent aliasing; (ii) the number of partitions in each direction can be small, 8, 4, or even 2 at no cost in point spread function; (iii) the volume of interest does not have to be contiguous; and (iv) the voxel profile depends on the available B1 and pulse synthesis paradigm and can, therefore, at least theoretically, approach "ideal" "1" inside and "0" elsewhere.