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.

Coarse-to-fine registration and time-intensity curves constraint for liver DCE-MRI synthesis.

Image registration plays a crucial role in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), used as a fundamental step for the subsequent diagnosis of benign and malignant tumors. However, the registration process encounters significant challenges due to the substantial intensity changes observed among different time points, resulting from the injection of contrast agents. Furthermore, previous studies have often overlooked the alignment of small structures, such as tumors and vessels. In this work, we propose a novel DCE-MRI registration framework that can effectively align the DCE-MRI time series. Specifically, our DCE-MRI registration framework consists of two steps, i.e., a de-enhancement synthesis step and a coarse-to-fine registration step. In the de-enhancement synthesis step, a disentanglement network separates DCE-MRI images into a content component representing the anatomical structures and a style component indicating the presence or absence of contrast agents. This step generates synthetic images where the contrast agents are removed from the original images, alleviating the negative effects of intensity changes on the subsequent registration process. In the registration step, we utilize a coarse registration network followed by a refined registration network. These two networks facilitate the estimation of both the coarse and refined displacement vector fields (DVFs) in a pairwise and groupwise registration manner, respectively. In addition, to enhance the alignment accuracy for small structures, a voxel-wise constraint is further conducted by assessing the smoothness of the time-intensity curves (TICs). Experimental results on liver DCE-MRI demonstrate that our proposed method outperforms state-of-the-art approaches, offering more robust and accurate alignment results.

A robust and efficient AI assistant for breast tumor segmentation from DCE-MRI via a spatial-temporal framework.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows screening, follow up, and diagnosis for breast tumor with high sensitivity. Accurate tumor segmentation from DCE-MRI can provide crucial information of tumor location and shape, which significantly influences the downstream clinical decisions. In this paper, we aim to develop an artificial intelligence (AI) assistant to automatically segment breast tumors by capturing dynamic changes in multi-phase DCE-MRI with a spatial-temporal framework. The main advantages of our AI assistant include (1) robustness, i.e., our model can handle MR data with different phase numbers and imaging intervals, as demonstrated on a large-scale dataset from seven medical centers, and (2) efficiency, i.e., our AI assistant significantly reduces the time required for manual annotation by a factor of 20, while maintaining accuracy comparable to that of physicians. More importantly, as the fundamental step to build an AI-assisted breast cancer diagnosis system, our AI assistant will promote the application of AI in more clinical diagnostic practices regarding breast cancer.

Transport pathways and kinetics of cerebrospinal fluid tracers in mouse brain observed by dynamic contrast-enhanced MRI.

Recent studies have suggested the glymphatic system as a key mechanism of waste removal in the brain. Dynamic contrast-enhanced MRI (DCE-MRI) using intracisternally administered contrast agents is a promising tool for assessing glymphatic function in the whole brain. In this study, we evaluated the transport kinetics and distribution of three MRI contrast agents with vastly different molecular sizes in mice. Our results demonstrate that oxygen-17 enriched water (H217O), which has direct access to parenchymal tissues via aquaporin-4 water channels, exhibited significantly faster and more extensive transport compared to the two gadolinium-based contrast agents (Gd-DTPA and GadoSpin). Time-lagged correlation and clustering analyses also revealed different transport pathways for Gd-DTPA and H217O. Furthermore, there were significant differences in transport kinetics of the three contrast agents to the lateral ventricles, reflecting the differences in forces that drive solute transport in the brain. These findings suggest the size-dependent transport pathways and kinetics of intracisternally administered contrast agents and the potential of DCE-MRI for assessing multiple aspects of solute transport in the glymphatic system.

Fast and low-dose medical imaging generation empowered by hybrid deep-learning and iterative reconstruction.

Fast and low-dose reconstructions of medical images are highly desired in clinical routines. We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework and apply it for fast magnetic resonance imaging (MRI), fast positron emission tomography (PET), and low-dose computed tomography (CT) image generation tasks. First, in a retrospective MRI study (6,066 cases), we demonstrate its capability of handling 3- to 10-fold under-sampled MR data, enabling organ-level coverage with only 10- to 100-s scan time; second, a low-dose CT study (142 cases) shows that our framework can successfully alleviate the noise and streak artifacts in scans performed with only 10% radiation dose (0.61 mGy); and last, a fast whole-body PET study (131 cases) allows us to faithfully reconstruct tumor-induced lesions, including small ones (<4 mm), from 2- to 4-fold-accelerated PET acquisition (30-60 s/bp). This study offers a promising avenue for accurate and high-quality image reconstruction with broad clinical value.

Transport Pathways and Kinetics of Cerebrospinal Fluid Tracers in Mouse Brain Observed by Dynamic Contrast-Enhanced MRI.

Background: Recent studies have suggested the glymphatic system as a solute transport pathway and waste removal mechanism in the brain. Imaging intracisternally administered tracers provides the opportunity of assessing various aspects of the glymphatic function. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows the evaluation of both the kinetics and spatial distribution of tracer transport in the whole brain. However, assessing mouse glymphatic function by DCE-MRI has been challenged by the small size of a mouse brain and the limited volume of fluids that can be delivered intracisternally without significantly altering the intracranial pressure. Further, previous studies in rats suggest that assessment of glymphatic function by DCE-MRI is dependent on the molecular size of the contrast agents. Methods: We established and validated an intracisternal infusion protocol in mice that allowed the measurements of the entire time course of contrast agent transport for 2 hours. The transport kinetics and distribution of three MRI contrast agents with drastically different molecular weights (MWs): Gd-DTPA (MW=661.8 Da, n=7), GadoSpin-P (MW=200 kDa, n=6), and oxygen-17 enriched water (H 2 17 O, MW=19 Da, n=7), were investigated. Results: The transport of H 2 17 O was significantly faster and more extensive than the two gadolinium-based contrast agents. Time-lagged correlation analysis and clustering analysis comparing the kinetics of Gd-DTPA and H 2 17 O transport also showed different cluster patterns and lag time between different regions of the brain, suggesting different transport pathways for H 2 17 O because of its direct access to parenchymal tissues via the aquaporin-4 water channels. Further, there were also significant differences in the transport kinetics of the three tracers to the lateral ventricles, which reflects the differences in forces that drive tracer transport in the brain. Conclusions: Comparison of the transport kinetics and distribution of three MRI contrast agents with different molecular sizes showed drastically different transport profiles and clustering patterns, suggesting that the transport pathways and kinetics in the glymphatic system are size-dependent.

Three-dimensional high-resolution T1 and T2 mapping of whole macaque brain at 9.4 T using magnetic resonance fingerprinting.

PURPOSE: Quantitative T1 and T2 mapping in non-human primates with whole-brain coverage is challenged by the requirement of sub-millimeter resolution and the inhomogeneity of the transmit magnetic field (B1+ ) covering a large field of view. The goal of the current study is to develop a magnetic resonance fingerprinting (MRF) method for simultaneous T1 and T2 mapping of the entire macaque brain within feasible scan time. METHODS: A three-dimensional (3D) MRF sequence with both inversion- and T2 -preparation modules was developed and evaluated on a 9.4 T preclinical scanner. Data acquisition used a 3D stack-of-spirals trajectory, with undersampling along both the in-plane and the through-plane directions. The effect of B1+ inhomogeneity was accounted for by matching the acquired fingerprint to a dictionary simulated with the B1+ factors measured from a separate scan. In vitro and ex vivo studies were performed to evaluate the accuracy and the undersampling capacity of the MRF method. The application of the MRF method for in vivo, brain-wide T1 and T2 mapping was demonstrated on macaques at 4, 6, and 12 years of age. RESULTS: The MRF method enabled highly repeatable T1 and T2 mapping at high spatial resolution (0.35 × 0.35 × 1 mm3 ) with an acceleration factor of 24. In vivo studies showed significant age-related T2 reduction in deep gray nuclei including the globus pallidus, the putamen, and the caudate nucleus. CONCLUSIONS: This study demonstrates the first MRF study for brain-wide, multi-parametric quantification in non-human primates with sub-millimeter resolution.

Quantification of creatine kinase reaction rate in mouse hindlimb using phosphorus-31 magnetic resonance spectroscopic fingerprinting.

The goal of this study was to evaluate the accuracy, reproducibility, and efficiency of a 31 P magnetic resonance spectroscopic fingerprinting (31 P-MRSF) method for fast quantification of the forward rate constant of creatine kinase (CK) in mouse hindlimb. The 31 P-MRSF method acquired spectroscopic fingerprints using interleaved acquisition of phosphocreatine (PCr) and γATP with ramped flip angles and a saturation scheme sensitive to chemical exchange between PCr and γATP. Parameter estimation was performed by matching the acquired fingerprints to a dictionary of simulated fingerprints generated from the Bloch-McConnell model. The accuracy of 31 P-MRSF measurements was compared with the magnetization transfer (MT-MRS) method in mouse hindlimb at 9.4 T (n = 8). The reproducibility of 31 P-MRSF was also assessed by repeated measurements. Estimation of the CK rate constant using 31 P-MRSF (0.39 ± 0.03 s-1 ) showed a strong agreement with that using MT-MRS measurements (0.40 ± 0.05 s-1 ). Variations less than 10% were achieved with 2 min acquisition of 31 P-MRSF data. Application of the 31 P-MRSF method to mice subjected to an electrical stimulation protocol detected an increase in CK rate constant in response to stimulation-induced muscle contraction. These results demonstrated the potential of the 31 P-MRSF framework for rapid, accurate, and reproducible quantification of the chemical exchange rate of CK in vivo.

Dynamic oxygen-17 MRI with adaptive temporal resolution using golden-means-based 3D radial sampling.

PURPOSE: The aim of this study was to develop a high-resolution 3D oxygen-17 (17 O) MRI method to delineate the kinetics of 17 O-enriched water (H217 O) across the entire mouse brain after a bolus injection via the tail vein. METHODS: The dynamic 17 O signal was acquired with a golden-means-based 3D radial sampling scheme. To achieve adequate temporal resolution with preserved spatial resolution, a k-space-weighted view sharing strategy was used in image reconstruction with an adaptive window size tailored to the kinetics of the 17 O signal. Simulation studies were performed to determine the adequate image reconstruction parameters. The established method was applied to delineating the kinetics of intravenously injected H217 O in vivo in the post-stroke mouse brain. RESULTS: The proposed dynamic 17 O-MRI method achieved an isotropic resolution of 1.21 mm (0.77 mm nominal) in mouse brain at 9.4T, with the temporal resolution increased gradually from 3 s at the initial phase of rapid signal increase to 15 s at the steady-state. The high spatial resolution enabled the delineation of the heterogeneous H217 O uptake and washout kinetics in stroke-affected mouse brain. CONCLUSION: The current study demonstrated a 3D 17 O-MRI method for dynamic monitoring of 17 O signal changes with high spatial and temporal resolution. The method can be utilized to quantify physiological parameters such as cerebral blood flow and blood-brain barrier permeability by tracking injected H217 O. It can also be used to measure oxygen consumption rate in 17 O-oxygen inhalation studies.

High-Resolution Dynamic 31P-MR Spectroscopic Imaging for Mapping Mitochondrial Function.

OBJECTIVE: To enable non-invasive dynamic metabolic mapping in rodent model studies of mitochondrial function using 31P-MR spectroscopic imaging (MRSI). METHODS: We developed a novel method for high-resolution dynamic 31P-MRSI. The method synergistically integrates physics-based models of spectral structures, biochemical modeling of molecular dynamics, and subspace learning to capture spatiospectral variations. Fast data acquisition was achieved using rapid spiral trajectories and sparse sampling of (k, t, T)-space; image reconstruction was accomplished using a low-rank tensor-based framework. RESULTS: The proposed method provided high-resolution dynamic metabolic mapping in rat hindlimb at spatial and temporal resolutions of 4[Formula: see text]2 mm3 and 1.28 s, respectively. This allowed for in vivo mapping of the time-constant of phosphocreatine resynthesis, a well established index of mitochondrial oxidative capacity. Multiple rounds of in vivo experiments were performed to demonstrate reproducibility, and in vitro experiments were used to validate the accuracy of the estimated metabolite maps. CONCLUSIONS: A new model-based method is proposed to achieve high-resolution dynamic 31P-MRSI. The proposed method's ability to delineate metabolic heterogeneity was demonstrated in rat hindlimb. SIGNIFICANCE: Abnormal mitochondrial metabolism is a key cellular dysfunction in many prevalent diseases such as diabetes and heart disease; however, current understanding of mitochondrial function is mostly gained from studies on isolated mitochondria under nonphysiological conditions. The proposed method has the potential to open new avenues of research by allowing in vivo and longitudinal studies of mitochondrial dysfunction in disease development and progression.

Dynamic, Simultaneous Concentration Mapping of Multiple MRI Contrast Agents with Dual Contrast - Magnetic Resonance Fingerprinting.

Synchronous assessment of multiple MRI contrast agents in a single scanning session would provide a new "multi-color" imaging capability similar to fluorescence imaging but with high spatiotemporal resolution and unlimited imaging depth. This multi-agent MRI technology would enable a whole new class of basic science and clinical MRI experiments that simultaneously explore multiple physiologic/molecular events in vivo. Unfortunately, conventional MRI acquisition techniques are only capable of detecting and quantifying one paramagnetic MRI contrast agent at a time. Herein, the Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF) methodology was extended for in vivo application and evaluated by simultaneously and dynamically mapping the intra-tumoral concentration of two MRI contrast agents (Gd-BOPTA and Dy-DOTA-azide) in a mouse glioma model. Co-registered gadolinium and dysprosium concentration maps were generated with sub-millimeter spatial resolution and acquired dynamically with just over 2-minute temporal resolution. Mean tumor Gd and Dy concentration measurements from both single agent and dual agent DC-MRF studies demonstrated significant correlations with ex vivo mass spectrometry elemental analyses. This initial in vivo study demonstrates the potential for DC-MRF to provide a useful dual-agent MRI platform.

Physalis Mottle Virus-like Nanoparticles for Targeted Cancer Imaging.

One of the greatest challenges in nanomedicine is the low efficiency with which nanoparticles are delivered to lesions such as tumors in vivo. Here, we show that Physalis mottle virus (PhMV)-like nanoparticles can be developed as bimodal contrast agents to achieve long circulation, specific targeting capability, and efficient delivery to tumors in vivo. The self-assembling coat protein nanostructure offers various opportunities to modify the internal and external surfaces separately. After loading the internal cavity of the particles with the fluorescent dye Cy5.5 and paramagnetic Gd(III) complexes, we modified the outer surface by PEGylation and conjugation with targeting peptides. Using this combined approach, we were able to monitor a human prostate tumor model for up to 10 days by near-infrared fluorescence and magnetic resonance imaging, with up to 6% of the injection dose remaining. Our results show that PhMV-like nanoparticles provide a promising and innovative platform for the development of next-generation diagnostic and therapeutic agents.

Fast magnetic resonance fingerprinting for dynamic contrast-enhanced studies in mice.

PURPOSE: The goal of this study was to develop a fast MR fingerprinting (MRF) method for simultaneous T1 and T2 mapping in DCE-MRI studies in mice. METHODS: The MRF sequences based on balanced SSFP and fast imaging with steady-state precession were implemented and evaluated on a 7T preclinical scanner. The readout used a zeroth-moment-compensated variable-density spiral trajectory that fully sampled the entire k-space and the inner 10 × 10 k-space with 48 and 4 interleaves, respectively. In vitro and in vivo studies of mouse brain were performed to evaluate the accuracy of MRF measurements with both fully sampled and undersampled data. The application of MRF to dynamic T1 and T2 mapping in DCE-MRI studies were demonstrated in a mouse model of heterotopic glioblastoma using gadolinium-based and dysprosium-based contrast agents. RESULTS: The T1 and T2 measurements in phantom showed strong agreement between the MRF and the conventional methods. The MRF with spiral encoding allowed up to 8-fold undersampling without loss of measurement accuracy. This enabled simultaneous T1 and T2 mapping with 2-minute temporal resolution in DCE-MRI studies. CONCLUSION: Magnetic resonance fingerprinting provides the opportunity for dynamic quantification of contrast agent distribution in preclinical tumor models on high-field MRI scanners.

Regularly incremented phase encoding - MR fingerprinting (RIPE-MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting.

PURPOSE: The regularly incremented phase encoding-magnetic resonance fingerprinting (RIPE-MRF) method is introduced to limit the sensitivity of preclinical MRF assessments to pulsatile and respiratory motion artifacts. METHODS: As compared to previously reported standard Cartesian-MRF methods (SC-MRF), the proposed RIPE-MRF method uses a modified Cartesian trajectory that varies the acquired phase-encoding line within each dynamic MRF dataset. Phantoms and mice were scanned without gating or triggering on a 7T preclinical MRI scanner using the RIPE-MRF and SC-MRF methods. In vitro phantom longitudinal relaxation time (T1 ) and transverse relaxation time (T2 ) measurements, as well as in vivo liver assessments of artifact-to-noise ratio (ANR) and MRF-based T1 and T2 mean and standard deviation, were compared between the two methods (n = 5). RESULTS: RIPE-MRF showed significant ANR reductions in regions of pulsatility (P < 0.005) and respiratory motion (P < 0.0005). RIPE-MRF also exhibited improved precision in T1 and T2 measurements in comparison to the SC-MRF method (P < 0.05). The RIPE-MRF and SC-MRF methods displayed similar mean T1 and T2 estimates (difference in mean values < 10%). CONCLUSION: These results show that the RIPE-MRF method can provide effective motion artifact suppression with minimal impact on T1 and T2 accuracy for in vivo small animal MRI studies. Magn Reson Med 79:2176-2182, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Dysprosium-Modified Tobacco Mosaic Virus Nanoparticles for Ultra-High-Field Magnetic Resonance and Near-Infrared Fluorescence Imaging of Prostate Cancer.

The increasing prevalence of ultra-high-field magnetic resonance imaging (UHFMRI) in biomedical research and clinical settings will improve the resolution and diagnostic accuracy of MRI scans. However, better contrast agents are needed to achieve a satisfactory signal-to-noise ratio. Here, we report the synthesis of a bimodal contrast agent prepared by loading the internal cavity of tobacco mosaic virus (TMV) nanoparticles with a dysprosium (Dy3+) complex and the near-infrared fluorescence (NIRF) dye Cy7.5. The external surface of TMV was conjugated with an Asp-Gly-Glu-Ala (DGEA) peptide via a polyethylene glycol linker to target integrin α2ß1. The resulting nanoparticle (Dy-Cy7.5-TMV-DGEA) was stable and achieved a high transverse relaxivity in ultra-high-strength magnetic fields (326 and 399 mM-1 s-1 at 7 and 9.4 T, respectively). The contrast agent was also biocompatible (low cytotoxicity) and targeted PC-3 prostate cancer cells and tumors in vitro and in vivo as confirmed by bimodal NIRF imaging and T2-mapping UHFMRI. Our results show that Dy-Cy7.5-TMV-DGEA is suitable for multiscale MRI scanning from the cellular level to the whole body, particularly in the context of UHFMRI applications.

High-resolution dynamic 31 P-MRSI using a low-rank tensor model.

PURPOSE: To develop a rapid 31 P-MRSI method with high spatiospectral resolution using low-rank tensor-based data acquisition and image reconstruction. METHODS: The multidimensional image function of 31 P-MRSI is represented by a low-rank tensor to capture the spatial-spectral-temporal correlations of data. A hybrid data acquisition scheme is used for sparse sampling, which consists of a set of "training" data with limited k-space coverage to capture the subspace structure of the image function, and a set of sparsely sampled "imaging" data for high-resolution image reconstruction. An explicit subspace pursuit approach is used for image reconstruction, which estimates the bases of the subspace from the "training" data and then reconstructs a high-resolution image function from the "imaging" data. RESULTS: We have validated the feasibility of the proposed method using phantom and in vivo studies on a 3T whole-body scanner and a 9.4T preclinical scanner. The proposed method produced high-resolution static 31 P-MRSI images (i.e., 6.9 × 6.9 × 10 mm3 nominal resolution in a 15-min acquisition at 3T) and high-resolution, high-frame-rate dynamic 31 P-MRSI images (i.e., 1.5 × 1.5 × 1.6 mm3 nominal resolution, 30 s/frame at 9.4T). CONCLUSIONS: Dynamic spatiospectral variations of 31 P-MRSI signals can be efficiently represented by a low-rank tensor. Exploiting this mathematical structure for data acquisition and image reconstruction can lead to fast 31 P-MRSI with high resolution, frame-rate, and SNR. Magn Reson Med 78:419-428, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Assessing tissue metabolism by phosphorous-31 magnetic resonance spectroscopy and imaging: a methodology review.

Many human diseases are caused by an imbalance between energy production and demand. Magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI) provide the unique opportunity for in vivo assessment of several fundamental events in tissue metabolism without the use of ionizing radiation. Of particular interest, phosphate metabolites that are involved in ATP generation and utilization can be quantified noninvasively by phosphorous-31 (31P) MRS/MRI. Furthermore, 31P magnetization transfer (MT) techniques allow in vivo measurement of metabolic fluxes via creatine kinase (CK) and ATP synthase. However, a major impediment for the clinical applications of 31P-MRS/MRI is the prohibitively long acquisition time and/or the low spatial resolution that are necessary to achieve adequate signal-to-noise ratio. In this review, current 31P-MRS/MRI techniques used in basic science and clinical research are presented. Recent advances in the development of fast 31P-MRS/MRI methods are also discussed.