Prepolarized MRI of Hard Tissues and Solid-State Matter
J. M. González, J. Borreguero, E. Pallás, J. P. Rigla, J. M. Algarín, R. Bosch, F. Galve, D. Grau-Ruiz, R. Pellicer, A. Ríos, J. M. Benlloch, J. Alonso
备注：
8 pages, 8 figures. Some numbers in Sec. VI have been revised in v2
Prepolarized Magnetic Resonance Imaging (PMRI) is a long-established technique conceived to counteract the loss in signal-to-noise ratio (SNR) inherent to low-field MRI systems. When it comes to hard biological tissues and solid-state matter, PMRI is severely restricted by their ultra-short characteristic relaxation times. Here we demonstrate that efficient hard tissue prepolarization is within reach with a special-purpose 0.26 T scanner designed for dental MRI and equipped with suitable high-power electronics. We have characterized the performance of a 0.5 T prepolarizer module which can be switched on and off in just 200 us. To that end, we have used resin, dental and bone samples, all with T1 times in the order of 20 ms at our field strength. The measured SNR enhancement is in good agreement with a simple theoretical model, and small deviations in extreme regimes can be attributed to mechanical vibrations due to the magnetic interaction between the prepolarization and main magnets. Finally, we argue that these results can be applied to clinical dental imaging, opening the door to replacing hazardous X-ray systems with low-field PMRI scanners.
This study presents and validates a novel (non-ECG-triggered) MRI sequence based on SPAtial Modulation of the Magnetization (SPAMM) to non-invasively measure 3D (quasi-static) soft tissue deformations using only six acquisitions (three static and three indentations). In current SPAMM tagged MRI approaches data is typically constructed from many repeated motion cycles. This has so far restricted its application to the measurement of highly repeatable and periodic movements (e.g. cardiac deformation). In biomechanical applications where soft tissue deformation is artificially induced, often by i…
Quantitative MRI is highly desirable in terms of intrinsic tissue parameters such as T1, T2 and proton density. This approach promises to minimize diagnostic variability and differentiate normal and pathological tissues by comparing tissue parameters to the normal ranges. Also, absolute quantification can help segment MRI tissue images with better accuracy compared to traditional qualitative segmentation methods. Currently, there are several methods proposed to quantify tissue parameters; however, all of them require excessive scan time and thus are difficult to be applied in clinical applicat…
Two different dynamic decoupling strategies, the classic CPMG and the more recently proposed UDD protocol are compared in the context of magnetic resonance imaging (MRI). Both sequences were implemented on a 3T human MRI system and relaxometry was performed for a variety of tissue-mimicking agar and agarose gels. We find that CPMG provides moderately better decoupling than \UDD. The results are consistent with experimental noise spectra obtained from \textit{in vivo} spectroscopy results, which suggest that the type of noise spectra obtained would favor \CPMG. Theoretical coherence pathway ana…
Magnetic resonance imaging (MRI) offers superior soft tissue contrast and is widely used in biomedicine. However, conventional MRI is not quantitative, which presents a bottleneck in image analysis and digital healthcare. Typically, additional scans are required to disentangle the effect of multiple parameters of MR and extract quantitative tissue properties. Here we investigate a data-driven strategy Q^2 MRI (Qualitative and Quantitative MRI) to derive quantitative parametric maps from standard MR images without additional data acquisition. By taking advantage of the interdependency between v…
Purpose: To evaluate the feasibility of a 3-minute b-tensor encoding protocol for diffusion MRI-based assessment of the microscopic anisotropy and tissue heterogeneity in a wide range of intracranial tumors. Methods: B-tensor encoding was performed in 42 patients with intracranial tumors (gliomas, meningiomas, adenomas, metastases). Microscopic anisotropy and tissue heterogeneity were evaluated by estimating the anisotropic kurtosis ($MK_A$) and isotropic kurtosis ($MK_I$), respectively. An extensive imaging protocol was compared with a faster 3-minute protocol. Results: The fast imaging proto…
The purpose of this study was to develop a method for tissue elasticity imaging using tagged magnetic resonance imaging (MRI). First, we developed a cyclic pressure device that used air to remotely transmit the power to generate cyclic deformation in an object. The pressure induced by the cyclic pressure device was measured by MRI-compatible force sensors. Second, we developed a software to calculate Young's modulus from tagged MRI data using the harmonic phase (HARP) method and the finite element method (FEM). We also developed a software to extract tag-cross points from tagged MRI data. Fina…
As bone and air produce weak signals with conventional MR sequences, segmentation of these tissues particularly difficult in MRI. We propose to integrate patch-based anatomical signatures and an auto-context model into a machine learning framework to iteratively segment MRI into air, bone and soft tissue. The proposed semantic classification random forest (SCRF) method consists of a training stage and a segmentation stage. During training stage, patch-based anatomical features were extracted from registered MRI-CT training images, and the most informative features were identified to train a se…
Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models are based on the assumption of negligible water exchange between the intra- and extracellular compartments, which might not be valid in various brain tissues, including unmyelinated axons, gray matter, and tumors. The purpose of this work is to quantify the effect of membrane permeability on the estimates of two popular models neglecting exchange, and compare their performance …
OBJECTIVE: 2D Ultrasound (US) imaging has been recently investigated as a more accessible alternative to 3D Magnetic Resonance Imaging (MRI) for the estimation of soft issue motion under external mechanical loading. In the context of pressure ulcer prevention, the aim of this pilot MRI study was to design an experiment to characterize the sacral soft tissue motion under a controlled mechanical loading. Such an experiment targeted the estimation of the discrepancy between tissue motion assessed using a 2D imaging modality (echography) versus tissue motion assessed using a (reference) 3D imaging…
Objective: Soft-tissue sarcoma spreads preferentially along muscle fibers. We explore the utility of deriving muscle fiber orientations from diffusion tensor MRI (DT-MRI) for defining the boundary of the clinical target volume in muscle tissue. Approach: We recruited eight healthy volunteers to acquire MR images of the left and right thigh. The imaging session consisted of (a) two MRI spin-echo-based scans, T1- and T2-weighted; (b) a diffusion weighted (DW) spin-echo-based scan using an echo planar acquisition with fat suppression. The thigh muscles were auto-segmented using CNN. DT-MRI data w…
A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non-segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of 3 mutually orthogonal tagging directions, thus requiring only 3 repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface …
Qualitative and quantitative hard-tissue MRI with portable Halbach scanners
MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV)（分子成像与仪器研究所 (i3M)，西班牙国家研究理事会 (CSIC) 和瓦伦西亚理工大学 (UPV)）；Full Body Insight S.L.；PhysioMRI Tech S.L.
A to-date unsolved and highly limiting safety concern for Ultra High-Field (UHF) magnetic resonance imaging (MRI) is the deposition of radiofrequency (RF) power in the body, quantified by the specific absorption rate (SAR), leading to dangerous tissue heating/damage in the form of local SAR hotspots that cannot currently be measured/monitored, thereby severely limiting the applicability of the technology for clinical practice and in regulatory approval. The goal of this study has been to show proof of concept of an artificial intelligence (AI) based exam-integrated real-time MRI safety predict…
Medical College of Wisconsin（威斯康星医学院）；Marquette University（马凯特大学）
Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to infer estimates of local tissue magnetism (magnetic susceptibility), which has been shown useful to provide novel image contrast and as biomarkers of abnormal tissue. QSM requires addressing a challenging post-processing problem: filtering of image phase estimates and inversion of the phase to susceptibility relationship. A wide variety of quantification errors, robustness limitations, and artifacts plague QSM algorithms. To overcome these limitations, a robust deep-learning-based single-step QSM reconstruction approach is …
University of Central Florida（中佛罗里达大学）；National Cancer Institute, National Institutes of Health（美国国立卫生研究院国家癌症研究所）；Frederick National Laboratory for Cancer Research（弗雷德里克国家癌症研究实验室）
Abdominal fat quantification is critical since multiple vital organs are located within this region. Although computed tomography (CT) is a highly sensitive modality to segment body fat, it involves ionizing radiations which makes magnetic resonance imaging (MRI) a preferable alternative for this purpose. Additionally, the superior soft tissue contrast in MRI could lead to more accurate results. Yet, it is highly labor intensive to segment fat in MRI scans. In this study, we propose an algorithm based on deep learning technique(s) to automatically quantify fat tissue from MR images through a c…
We present a magnet and high power electronics for Prepolarized Magnetic Resonance Imaging (PMRI) in a home-made, special-purpose preclinical system designed for simultaneous visualization of hard and soft biological tissues. PMRI boosts the signal-to-noise ratio (SNR) by means of a long and strong magnetic pulse which must be rapidly switched off prior to the imaging pulse sequence, in timescales shorter than the spin relaxation (or T1) time of the sample. We have operated the prepolarizer at up to 0.5 T and demonstrated enhanced magnetization, image SNR and tissue contrast with PMRI of tap w…
Purpose: The impact of microscopic diffusional kurtosis ($μK$) - arising from restricted diffusion and/or structural disorder - remains a controversial issue in contemporary diffusion MRI (dMRI). Recently, Correlation Tensor MRI (CTI) was introduced to disentangle the sources contributing to diffusional kurtosis, without relying on a-priori assumptions. Here, we aimed to investigate $μK$ in in vivo rat brains and assess its impact on state-of-the-art methods ignoring $μK$. Methods: CTI harnesses double diffusion encoding (DDE) experiments, which were here improved for speed and minimal bias us…
Magnetic Resonance Imaging (MRI) of hard biological tissues is challenging due to the fleeting lifetime and low strength of their response to resonant stimuli, especially at low magnetic fields. Consequently, the impact of MRI on some medical applications, such as dentistry, continues to be limited. Here, we present three-dimensional reconstructions of ex-vivo human teeth, as well as a rabbit head and part of a cow femur, all obtained at a field strength of only 260 mT. These images are the first featuring soft and hard tissues simultaneously at sub-Tesla fields, and they have been acquired in…
Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI
University of Washington（华盛顿大学）；Fred Hutchinson Cancer Center（弗雷德·哈钦森癌症中心）
Magnetic resonance imaging (MRI) is a widely used biomedical imaging modality that derives much of its contrast from microscale magnetic field gradients in biological tissues. However, the connection between these sub-voxel field patterns and MRI contrast has not been studied experimentally. Here, we describe a new method to map subcellular magnetic fields in mammalian cells and tissues using nitrogen vacancy diamond magnetometry and connect these maps to voxel-scale MRI contrast, providing insights for in vivo imaging and contrast agent design.
Automatic quantification of abdominal subcutaneous and visceral adipose tissue in children, through MRI study, using total intensity maps and Convolutional Neural Networks
Background: Mammography is a specific type of breast imaging that uses low-dose X-rays to detect cancer in early stage. During the exam, the women breast is compressed between two plates in order to even out the breast thickness and to spread out the soft tissues. This technique improves exam quality but can be uncomfortable for the patient. The perceived discomfort can be assessed by the means of a breast biomechanical model. Alternative breast compression techniques may be computationally investigated trough finite elements simulations.Methods: The aim of this work is to develop and evaluate…
Characterization of microstructures in live tissues is one of the keys to diagnosing early stages of pathology and understanding disease mechanisms. However, the extraction of reliable information on biomarkers based on microstructure details is still a challenge, as the size of features that can be resolved with non-invasive Magnetic Resonance Imaging (MRI) is orders of magnitude larger than the relevant structures. Here we derive from quantum information theory the ultimate precision limits for obtaining such details by MRI probing of water-molecule diffusion. We show that already available …
We review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse-graining over an increasing diffusion length scale. From this perspective, we view research on quantifying brain microstructure as occurring along the three major avenues. The first avenue focusses on the transient, or time-dependent, effects in diffusion. These effects signify the gradual coarse-graining of tissue structure, which occurs qualitatively differently in different brain tissue compartments. We show that studying the transient effects has the pot…
Quantitative Magnetic Resonance Imaging (MRI) is based on a two-steps approach: estimation of the magnetic moments distribution inside the body, followed by a voxel-by-voxel quantification of the human tissue properties. This splitting simplifies the computations but poses several constraints on the measurement process, limiting its efficiency. Here, we perform quantitative MRI as a one step process; signal localization and parameter quantification are simultaneously obtained by the solution of a large scale nonlinear inversion problem based on first-principles. As a consequence, the constrain…
SQUID-based MRI (magnetic resonance imaging) at microtesla fields has developed significantly over the past few years. Here we describe application of this method for magnetic relaxation measurements in the living human brain. We report values of the longitudinal relaxation time T1 for brain tissues, measured in vivo for the first time at microtesla fields. The experiments were performed at 46 microtesla field using a seven-channel SQUID system designed for microtesla MRI and MEG. Values of T1, measured for different tissues at this field, are found to be close (within 5%) to the corresponding…
Magnetic resonance imaging (MRI) is the cornerstone technique for diagnostic medicine, biology, and neuroscience. This imaging method is highly innovative, noninvasive and its impact continues to grow. It can be used for measuring changes in the brain after enhanced neural activity, detecting early cancerous cells in tissue, as well as for imaging nanoscale biological structures, and controlling fluid dynamics, and it can be beneficial for cardiovascular imaging. The MRI performance is characterized by a signal-to-noise ratio, however the spatial resolution and image contrast depend strongly o…
Purpose: Quantitative magnetization transfer (qMT) imaging can be used to quantify the proportion of protons in a voxel attached to macromolecules. Here, we show that the original qMT balanced steady-state free precession (bSSFP) model is biased due to over-simplistic assumptions made in its derivation. Theory and Methods: We present an improved model for qMT bSSFP, which incorporates finite radio-frequency (RF) pulse effects as well as simultaneous exchange and relaxation. Further, a correction to finite RF pulse effects for sinc-shaped excitations is derived. The new model is compared to the…
Heart failure is a leading cause of mortality in the Western world. The mouse is a widely used model for a number of diseases, induced by genetic modification or surgical intervention. When performing experiments in mice, in vivo magnetic resonance imaging (MRI) can be used to evaluate heart anatomy and function at multiple levels. Volumetric measurements of ventricle size at each phase of the heart cycle (obtained with cine MRI) can be used as a sensitive measure for heart failure. Cine MRI is applied here to genetic models of heart disease, including stress tests with pharmacological manipul…
University Hospital Tübingen（蒂宾根大学医院）；University of Stuttgart（斯图加特大学）；Max-Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Eberhard Karls University（埃伯哈德·卡尔斯大学）；Helmholtz Zentrum München（慕尼黑亥姆霍兹中心）；German Center for Diabetes Research（德国糖尿病研究中心）；University of Freiburg（弗赖堡大学）
Purpose: To enable fast and reliable assessment of subcutaneous and visceral adipose tissue compartments derived from whole-body MRI. Methods: Quantification and localization of different adipose tissue compartments from whole-body MR images is of high interest to examine metabolic conditions. For correct identification and phenotyping of individuals at increased risk for metabolic diseases, a reliable automatic segmentation of adipose tissue into subcutaneous and visceral adipose tissue is required. In this work we propose a 3D convolutional neural network (DCNet) to provide a robust and obje…
In this article, we present an up-to-date overview of the potential biomedical applications of sodium MRI in vivo. Sodium MRI is a subject of increasing interest in translational research as it can give some direct and quantitative biochemical information on the tissue viability, cell integrity and function, and therefore not only help the diagnosis but also the prognosis of diseases and treatment outcomes. It has already been applied in vivo in most of human tissues, such as brain for stroke or tumor detection and therapeutic response, in breast cancer, in articular cartilage, in muscle and i…
Combining the unmatched soft-tissue imaging capabilities of magnetic resonance imaging (MRI) with high precision robotics has the potential to improve the accuracy, precision, and safety of a wide range of image-guided medical procedures. However, the goal of highly functional MRI-compatible robotic systems has not yet been realized because conventional electromagnetic servomotors used by medical robots can become dangerous projectiles near the strong magnetic field of an MRI scanner. Here we report a novel electromagnetic servomotor design that is constructed from non-magnetic components and …
Although the socket is critical in a prosthetic system for a person with limb amputation, the methods of its design are largely artisanal. A roadblock for a repeatable and quantitative socket design process is the lack of predictive and patient specific biomechanical models of the residuum. This study presents the evaluation of such a model using a combined experimental-numerical approach. The model geometry and tissue boundaries are derived from MRI. The soft tissue non-linear elastic and viscoelastic mechanical behavior was evaluated using inverse finite element analysis (FEA) of in-vivo ind…
Optical pumping of He-3 produces large (hyper) nuclear-spin polarizations independent of the magnetic resonance imaging (MRI) field strength. This allows lung MRI to be performed at reduced fields with many associated benefits, such as lower tissue susceptibility gradients and decreased power absorption rates. Here we present results of 2D imaging as well as accurate 1D gas diffusion mapping of the human lung using He-3 at very low field (3 mT). Furthermore, measurements of transverse relaxation in zero applied gradient are shown to accurately track pulmonary oxygen partial pressure, opening t…
In utero diffusion MRI provides unique opportunities to non-invasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as the growth of white matter tracts in the brain, the maturation of placental villous trees, or the fibres in the fetal heart remain to be studied and understood in detail. Advances in fetal interventions and surgery furthermore increase the need for ever more precise antenatal diagnosis from fetal MRI. However, the specific properties of the in utero environment, such as fetal and maternal motion, increased field-of-…
Massachusetts Eye and Ear（麻省眼耳医院）；Harvard Medical School（哈佛医学院）；Florida International University（佛罗里达国际大学）
Neuroimaging is essential in brain studies for the diagnosis and identification of disease, structure, and function of the brain in its healthy and disease states. Literature shows that there are advantages of multitasking with some deep learning (DL) schemes in challenging neuroimaging applications. This study examines the feasibility of using multitasking in three different applications, including tissue segmentation, cross-modality conversion, and bias-field correction. These applications reflect five different scenarios in which multitasking is explored and 280 training and testing session…
The introduction of neuroendoscopy, microneurosurgery, neuronavigation, and intraoperative imaging for surgical operations has made significant improvements over other traditionally invasive surgical techniques. The integration of magnetic resonance imaging (MRI)-driven surgical devices with intraoperative imaging and endoscopy can enable further advancements in surgical treatments and outcomes. This work proposes the design and development of an MRI-driven endoscope leveraging the high (3-7 T), external magnetic field of an MR scanner for heat-mitigated steering within the ventricular system …
Microscopic Propagator Imaging (MPI) with Diffusion MRI
University of Verona（维罗纳大学）；Technical University of Denmark（丹麦技术大学）；Copenhagen University Hospital - Amager and Hvidovre（哥本哈根大学医院阿马格和维杜夫雷院区）；Danish Research Centre for Magnetic Resonance（丹麦磁共振研究中心）
Solids and rigid tissues such as bone, ligaments, and tendons, typically appear dark in magnetic resonance imaging (MRI), which is due to the extremely short-lived proton nuclear magnetic resonance (NMR) signals. This short lifetime is due to strong dipolar interactions between immobilized proton spins, which render it challenging to detect these signals with sufficient resolution and sensitivity. Here we show the possibility of exciting long-lived signals in cortical bone tissue with a signature consistent with that of bound water signals. Contrary to long-standing belief, it is further shown…
Mathematical models are becoming increasingly important in magnetic resonance imaging (MRI), as they provide a mechanistic approach for making a link between tissue microstructure and signals acquired using the medical imaging instrument. The Bloch equations, which describes spin and relaxation in a magnetic field, is a set of integer order differential equations with a solution exhibiting mono-exponential behaviour in time. Parameters of the model may be estimated using a non-linear solver, or by creating a dictionary of model parameters from which MRI signals are simulated and then matched w…
Magnetic fields associated with currents flowing in tissue can be measured non-invasively by means of zero-field-encoded ultra-low-field magnetic resonance imaging (ULF MRI) enabling current density imaging (CDI) and possibly conductivity mapping of human head tissues. Since currents applied to a human are limited by safety regulations and only a small fraction of the current passes through the relatively high-resistive skull, a sufficient signal-to-noise ratio (SNR) may be difficult to obtain when using this method. In this work, we study the relationship between the image SNR and the SNR of …
