Magnetic Resonance Fingerprinting-An Overview

Advanced MRI Techniques: Diagnosis and Follow-Up of Multiple Sclerosis

Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing-remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.

Quantifying microglial morphology: an insight into function

Microglia are specialized immune cells unique to the central nervous system (CNS). Microglia have a highly plastic morphology that changes rapidly in response to injury or infection. Qualitative and quantitative measurements of ever-changing microglial morphology are considered a cornerstone of many microglia-centric research studies. The distinctive morphological variations seen in microglia are a useful marker of inflammation and severity of tissue damage. Although a wide array of damage-associated microglial morphologies has been documented, the exact functions of these distinct morphologies are not fully understood. In this review, we discuss how microglia morphology is not synonymous with microglia function, however, morphological outcomes can be used to make inferences about microglial function. For a comprehensive examination of the reactive status of a microglial cell, both histological and genetic approaches should be combined. However, the importance of quality immunohistochemistry-based analyses should not be overlooked as they can succinctly answer many research questions.

Characterization of Age-Related and Sex-Related Differences of Relaxation Parameters in the Intervertebral Disc Using MR-Fingerprinting

BACKGROUND

Multiparameter characterization using MR fingerprinting (MRF) can quantify multiple relaxation parameters of intervertebral disc (IVD) simultaneously. These parameters may vary by age and sex.

PURPOSE

To investigate age- and sex-related differences in the relaxation parameters of the IVD of the lumbar spine using a multiparameter MRF technique.

STUDY TYPE

Prospective.

SUBJECTS

17 healthy subjects (8 male; mean age = 34 ± 10 years, range 20-60 years).

FIELD STRENGTH/SEQUENCE

3D-MRF sequence for simultaneous acquisition of proton density, T1 , T2 , and T1ρ maps at 3.0T.

ASSESSMENT

Global mean T1 , T2 , and T1ρ of all lumbar IVDs and mean T1 , T2 , and T1ρ of each individual IVD (L1-L5) were measured. Gray level co-occurrence matrix was used to quantify textural features (median, contrast, correlation, energy, and homogeneity) from T1 , T2 , and T1ρ maps.

STATISTICAL TESTS

Spearman rank correlations (R) evaluated the association between age and T1 , T2 , and T1ρ of IVD. Mann-Whitney U-tests evaluated differences between males and females in T1 , T2 , and T1ρ of IVD. Statistical significance was defined as P-value <0.05.

RESULTS

There was a significant negative correlation between age and global mean values of all IVDs for T1 (R = -0.637), T2 (R = -0.509), and T1ρ (R = -0.726). For individual IVDs, there was a significant negative correlation between age and mean T1 at all IVD segments (R range = -0.530 to -0.708), between age and mean T2 at L2-L3, L3-L4, and L4-L5 (R range = -0.493 to 0.640), and between age and mean T1ρ at all segments except L1-L2 (R range = -0.632 to -0.763). There were no significant differences between sexes in global mean T1 , T2, and T1ρ (P-value = 0.23-0.76) The texture features with the highest significant correlations with age for all IVDs were global T1ρ mean (R = -0.726), T1 energy (R = -0.681), and T1 contrast (R = 0.709).

CONCLUSION

This study showed that the 3D-MRF technique has potential to characterize age-related differences in T1 , T2, or T1ρ of IVD in healthy subjects.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Using imaging modalities to predict nanoparticle distribution and treatment efficacy in solid tumors: The growing role of ultrasound

Nanomedicine in oncology has not had the success in clinical impact that was anticipated in the early stages of the field's development. Ideally, nanomedicines selectively accumulate in tumor tissue and reduce systemic side effects compared to traditional chemotherapeutics. However, this has been more successful in preclinical animal models than in humans. The causes of this failure to translate may be related to the intra- and inter-patient heterogeneity of the tumor microenvironment. Predicting whether a patient will respond positively to treatment prior to its initiation, through evaluation of characteristics like nanoparticle extravasation and retention potential in the tumor, may be a way to improve nanomedicine success rate. While there are many potential strategies to accomplish this, prediction and patient stratification via noninvasive medical imaging may be the most efficient and specific strategy. There have been some preclinical and clinical advances in this area using MRI, CT, PET, and other modalities. An alternative approach that has not been studied as extensively is biomedical ultrasound, including techniques such as multiparametric contrast-enhanced ultrasound (mpCEUS), doppler, elastography, and super-resolution processing. Ultrasound is safe, inexpensive, noninvasive, and capable of imaging the entire tumor with high temporal and spatial resolution. In this work, we summarize the in vivo imaging tools that have been used to predict nanoparticle distribution and treatment efficacy in oncology. We emphasize ultrasound imaging and the recent developments in the field concerning CEUS. The successful implementation of an imaging strategy for prediction of nanoparticle accumulation in tumors could lead to increased clinical translation of nanomedicines, and subsequently, improved patient outcomes. This article is categorized under: Diagnostic Tools In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery Emerging Technologies.

Navigating Neural Landscapes: A Comprehensive Review of Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) Applications in Epilepsy

This review comprehensively explores the evolving role of neuroimaging, specifically magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS), in epilepsy research and clinical practice. Beginning with a concise overview of epilepsy, the discussion emphasizes the crucial importance of neuroimaging in diagnosing and managing this complex neurological disorder. The review delves into the applications of advanced MRI techniques, including high-field MRI, resting-state fMRI, and connectomics, highlighting their impact on refining our understanding of epilepsy's structural and functional dimensions. Additionally, it examines the integration of machine learning in the analysis of intricate neuroimaging data. Moving to the clinical domain, the review outlines the utility of neuroimaging in pre-surgical evaluations and the monitoring of treatment responses and disease progression. Despite significant strides, challenges and limitations are discussed in the routine clinical incorporation of neuroimaging. The review explores promising developments in MRI and MRS technology, potential advancements in imaging biomarkers, and the implications for personalized medicine in epilepsy management. The conclusion underscores the transformative potential of neuroimaging and advocates for continued exploration, collaboration, and technological innovation to propel the field toward a future where tailored, effective interventions improve outcomes for individuals with epilepsy.

Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting

We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T1 and T2 maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex vivo rat brain phantoms using a 7-T preclinical scanner. Subsequently, the DL model was trained using experimental data, completely excluding the use of any theoretical MRI signal simulator. The best combination of the DL parameters was implemented by an automatic hyperparameter optimization strategy, whose key aspect is to include all the parameters to the fit, allowing the simultaneous optimization of the neural network architecture, the structure of the DL model, and the supervised learning algorithm. By comparing the reconstruction performances of the DL technique with those achieved from the traditional dictionary-based method on an independent dataset, the DL approach was shown to reduce the mean percentage relative error by a factor of 3 for T1 and by a factor of 2 for T2 , and to improve the computational time by at least a factor of 37. Furthermore, the proposed DL method enables maintaining comparable reconstruction performance, even with a lower number of MRF images and a reduced k-space sampling percentage, with respect to the dictionary-based method. Our results suggest that the proposed DL methodology may offer an improvement in reconstruction accuracy, as well as speeding up MRF for preclinical, and in prospective clinical, investigations.

Simultaneous Arterial and Venous Imaging Using 3D Quantitative Parameter Mapping

PURPOSE

To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution.

METHODS

The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed. Arterial images are obtained by adding images using optimized weights to emphasize the arteries. A morphology filter is used to obtain venous images from the magnetic susceptibility maps. For evaluation, images obtained from four out of five healthy volunteers were used to optimize the weights used in the arterial-image calculation, and the optimized weights were applied to the images from the fifth volunteer to obtain an arterial image. Arterial images of the five volunteers were calculated using the leave-one-out method, and the contrast between the arterial and background regions defined using the reference time-of-flight (TOF) method was evaluated using the area under the receiver operation characteristic curve (AUC). The contrast between venous and background regions defined by a reference quantitative susceptibility mapping (QSM) method was also evaluated for the venous image.

RESULTS

The AUC to discriminate blood vessels and background using the proposed method was 0.905 for the arterial image and 0.920 for the venous image.

CONCLUSION

The results indicate that the arterial images and venous images have high signal intensity at the same region as determined from the reference TOF and QSM methods, demonstrating the possibility of acquiring vasculature images with quantitative parameter mapping through calculation in an integrated manner.

Multiparametric MR Evaluation of the Photoperiodic Regulation of Hypothalamic Structures in Sheep

Most organisms on earth, humans included, have developed strategies to cope with environmental day-night and seasonal cycles to survive. For most of them, their physiological and behavioral functions, including the reproductive function, are synchronized with the annual changes of day length, to ensure winter survival and subsequent reproductive success in the following spring. Sheep are sensitive to photoperiod, which also regulates natural adult neurogenesis in their hypothalamus. We postulate that the ovine model represents a good alternative to study the functional and metabolic changes occurring in response to photoperiodic changes in hypothalamic structures of the brain. Here, the impact of the photoperiod on the neurovascular coupling and the metabolism of the hypothalamic structures was investigated at 3T using BOLD fMRI, perfusion-MRI and proton magnetic resonance spectroscopy (1H-MRS). A longitudinal study involving 8 ewes was conducted during long days (LD) and short days (SD) revealing significant BOLD, rCBV and metabolic changes in hypothalamic structures of the ewe brain between LD and SD. More specifically, the transition between LD and SD revealed negative BOLD responses to hypercapnia at the beginning of SD period followed by significant increases in BOLD, rCBV, Glx and tNAA concentrations towards the end of the SD period. These observations suggest longitudinal mechanisms promoting the proliferation and differentiation of neural stem cells within the hypothalamic niche of breeding ewes. We conclude that multiparametric MRI studies including 1H-MRS could be promising non-invasive translational techniques to investigate the existence of natural adult neurogenesis in-vivo in gyrencephalic brains.

Phenotyping heart failure by cardiac magnetic resonance imaging of cardiac macro- and microscopic structure: state of the art review

Heart failure demographics have evolved in past decades with the development of improved diagnostics, therapies, and prevention. Cardiac magnetic resonance (CMR) has developed in a similar timeframe to become the gold-standard non-invasive imaging modality for characterizing diseases causing heart failure. CMR techniques to assess cardiac morphology and function have progressed since their first use in the 1980s. Increasingly efficient acquisition protocols generate high spatial and temporal resolution images in less time. This has enabled new methods of characterizing cardiac systolic and diastolic function such as strain analysis, exercise real-time cine imaging and four-dimensional flow. A key strength of CMR is its ability to non-invasively interrogate the myocardial tissue composition. Gadolinium contrast agents revolutionized non-invasive cardiac imaging with the late gadolinium enhancement technique. Further advances enabled quantitative parametric mapping to increase sensitivity at detecting diffuse pathology. Novel methods such as diffusion tensor imaging and artificial intelligence-enhanced image generation are on the horizon. Magnetic resonance spectroscopy (MRS) provides a window into the molecular environment of the myocardium. Phosphorus (31P) spectroscopy can inform the status of cardiac energetics in health and disease. Proton (1H) spectroscopy complements this by measuring creatine and intramyocardial lipids. Hyperpolarized carbon (13C) spectroscopy is a novel method that could further our understanding of dynamic cardiac metabolism. CMR of other organs such as the lungs may add further depth into phenotypes of heart failure. The vast capabilities of CMR should be deployed and interpreted in context of current heart failure challenges.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

White Matter Cerebrovascular Reactivity: Effects of Microangiopathy and Proximal Occlusions on the Dynamic BOLD Response

Introduction

Cerebral microangiopathy often manifests as white matter hyperintensities (WMH) on T2-weighted MR images and is associated with elevated stroke risk. Large vessel steno-occlusive disease (SOD) is also independently associated with stroke risk, however, the interaction of microangiopathy and SOD is not well understood. Cerebrovascular reactivity (CVR) describes the capacity of cerebral circulation to adapt to changes in perfusion pressure and neurovascular demand, and its impairment portends future infarctions. CVR can be measured with blood oxygen level dependent (BOLD) imaging following acetazolamide stimulus (ACZ-BOLD). We studied CVR differences between WMH and normal-appearing white matter (NAWM) in patients with chronic SOD, hypothesizing additive influences upon CVR measured by novel, fully dynamic CVR maxima ( CVR _max ).

Methods

A cross sectional study was conducted to measure per-voxel, per-TR maximal CVR ( CVR _max ) using a custom computational pipeline in 23 subjects with angiographically-proven unilateral SOD. WMH and NAWM masks were applied to CVR _max maps. White matter was subclassified with respect to the SOD-affected hemisphere, including: i. contralateral NAWM; ii. contralateral WMH iii. ipsilateral NAWM; iv. ipsilateral WMH. CVR _max was compared between these groups with a Kruskal-Wallis test followed by a Dunn-Sidak post-hoc test for multiple comparisons.

Results

19 subjects (age 50±12 years, 53% female) undergoing 25 examinations met criteria. WMH volume was asymmetric in 16/19 subjects with 13/16 exhibiting higher volumes ipsilateral to SOD. Pairwise comparisons of CVR _max between groups was significant with ipsilateral WMH CVR _max lower than contralateral NAWM (p=0.015) and contralateral WMH (p=0.003) when comparing in-subject medians and lower than all groups when comparing pooled voxelwise values across all subjects (p<0.0001). No significant relationship between WMH lesion size and CVR _max was detected.

Conclusion

Our results suggest additive effects of microvascular and macrovascular disease upon white matter CVR, but with greater overall effects relating to macrovascular SOD than to apparent microangiopathy. Dynamic ACZ-BOLD presents a promising path towards a quantitative stroke risk imaging biomarker.

BACKGROUND

Cerebral white matter (WM) microangiopathy manifests as sporadic or sometimes confluent high intensity lesions in MR imaging with T2-weighting, and bears known associations with stroke, cognitive disability, depression and other neurological disorders ^1-5 . Deep white matter is particularly susceptible to ischemic injury owing to the deprivation of collateral flow between penetrating arterial territories, and hence deep white matter hyperintensities (WMH) may portend future infarctions ^6-8 . The pathophysiology of WMH is variable but commonly includes a cascade of microvascular lipohyalinosis and atherosclerosis together with impaired vascular endothelial and neurogliovascular integrity, leading to blood brain barrier dysfunction, interstitial fluid accumulation, and eventually tissue damage ^9-14 . Independent of the microcirculation, cervical and intracranial large vessel steno-occlusive disease (SOD) often results from atheromatous disease and is associated with increased risk of stroke owing to thromboembolic phenomena, hypoperfusion, or combinations thereof ^15-17 . White matter disease is more common in the affected hemisphere of patients with asymmetric or unilateral SOD, producing both macroscopic WMH detectable by routine structural MRI, as well as microstructural changes and altered structural connectivity detected by advanced diffusion microstructural imaging ^{18, 19} . An improved understanding of the interaction of microvascular disease (i.e., WMH) and macrovascular steno-occlusion could better inform stroke risk stratification and guide treatment strategies when coexistent. Cerebrovascular reactivity (CVR) is an autoregulatory adaptation characterized by the capacity of the cerebral circulation to respond to physiological or pharmacological vasodilatory stimuli ^20-22 . CVR may be heterogeneous and varies across tissue type and pathological states ^{1, 16} . Alterations in CVR are associated with elevated stroke risk in SOD patients, although white matter CVR, and in particular the CVR profiles of WMH, are only sparsely studied and not fully understood ^{1, 23-26} . We have previously employed blood oxygen level dependent (BOLD) imaging following a hemodynamic stimulus with acetazolamide (ACZ) in order to measure CVR (i.e. ACZ-BOLD) ^{21, 27, 28} . Despite the emergence of ACZ-BOLD as a technique for clinical and experimental use, poor signal-to-noise characteristics of the BOLD effect have generally limited its interpretation to coarse, time-averaged assessment of the terminal ACZ response at arbitrarily prescribed delays following ACZ administration (e.g. 10-20 minutes) ²⁹ . More recently, we have introduced a dedicated computational pipeline to overcome historically intractable signal-to-noise ratio (SNR) limitations of BOLD, enabling fully dynamic characterization of the cerebrovascular response, including identification of previously unreported, unsustained or transient CVR maxima ( CVR _max ) following hemodynamic provocation ^{27, 30} . In this study, we compared such dynamic interrogation of true CVR maxima between WMH and normal appearing white matter (NAWM) among patients with chronic, unilateral SOD in order to quantify their interaction and to assess the hypothesized additive effects of angiographically-evident macrovascular stenoses when intersecting microangiopathic WMH.

Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging

Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.

Focused Abbreviated Survey MRI Protocols for Brain and Spine Imaging

There has been extensive growth in both the technical development and the clinical applications of MRI, establishing this modality as one of the most powerful diagnostic imaging tools. However, long examination and image interpretation times still limit the application of MRI, especially in emergent clinical settings. Rapid and abbreviated MRI protocols have been developed as alternatives to standard MRI, with reduced imaging times, and in some cases limited numbers of sequences, to more efficiently answer specific clinical questions. A group of rapid MRI protocols used at the authors' institution, referred to as FAST (focused abbreviated survey techniques), are designed to include or exclude emergent or urgent conditions or screen for specific entities. These FAST protocols provide adequate diagnostic image quality with use of accelerated approaches to produce imaging studies faster than traditional methods. FAST protocols have become critical diagnostic screening tools at the authors' institution, allowing confident and efficient confirmation or exclusion of actionable findings. The techniques commonly used to reduce imaging times, the imaging protocols used at the authors' institution, and future directions in FAST imaging are reviewed to provide a practical and comprehensive overview of FAST MRI for practicing neuroradiologists. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Adaptive model-based Magnetic Resonance

PURPOSE

Conventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach-termed adaptive MR-in which incoming subject data is used to update and fine-tune the pulse sequence parameters in real time.

METHODS

We implemented an adaptive, real-time multi-echo (MTE) experiment for estimating T₂ s. Our approach combined a Bayesian framework with model-based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T₂ , which was used to guide the selection of sequence parameters in real time.

RESULTS

Computer simulations predicted accelerations between 1.7- and 3.3-fold for adaptive multi-echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T₂ for n-acetyl-aspartate by a factor of 2.5.

CONCLUSION

Adaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model-based approaches to MRI and MRS.

Quantitative MRI in leukodystrophies

Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies.

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

MRI-LINAC: A transformative technology in radiation oncology

Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.

Microstructural parameters from DW-MRI for tumour characterization and local recurrence prediction in particle therapy of skull-base chordoma

BACKGROUND

Quantitative imaging such as Diffusion-Weighted MRI (DW-MRI) can be exploited to non-invasively derive patient-specific tumor microstructure information for tumor characterization and local recurrence risk prediction in radiotherapy.

PURPOSE

To characterize tumor microstructure according to proliferative capacity and predict local recurrence through microstructural markers derived from pre-treatment conventional DW-MRI, in skull-base chordoma (SBC) patients treated with proton (PT) and carbon ion (CIRT) radiotherapy.

METHODS

Forty-eight patients affected by SBC, who underwent conventional DW-MRI before treatment and were enrolled for CIRT (n = 25) or PT (n = 23), were retrospectively selected. Clinically verified local recurrence information (LR) and histological information (Ki-67, proliferation index) were collected. Apparent diffusion coefficient (ADC) maps were calculated from pre-treatment DW-MRI and, from these, a set of microstructural parameters (cellular radius R, volume fraction vf, diffusion D) were derived by applying a fine-tuning procedure to a framework employing Monte Carlo simulations on synthetic cell substrates. In addition, apparent cellularity (ρ_app ) was estimated from vf and R for an easier clinical interpretation. Histogram-based metrics (mean, median, variance, entropy) from estimated parameters were considered to investigate differences (Mann-Whitney U-test, α = 0.05) in estimated tumor microstructure in SBCs characterized by low or high cell proliferation (Ki-67). Recurrence-free survival analyses were also performed to assess the ability of the microstructural parameters to stratify patients according to the risk of local recurrence (Kaplan-Meier curves, log-rank test α = 0.05).

RESULTS

Refined microstructural markers revealed optimal capabilities in discriminating patients according to cell proliferation, achieving best results with mean values (p-values were 0.0383, 0.0284, 0.0284, 0.0468, and 0.0088 for ADC, R, vf, D, and ρ_app, respectively). Recurrence-free survival analyses showed significant differences between populations at high and low risk of local recurrence as stratified by entropy values of estimated microstructural parameters (p = 0.0110).

CONCLUSION

Patient-specific microstructural information was non-invasively derived providing potentially useful tools for SBC treatment personalization and optimization in particle therapy.

SuperMAP: Deep ultrafast MR relaxometry with joint spatiotemporal undersampling

PURPOSE

To develop an ultrafast and robust MR parameter mapping network using deep learning.

THEORY AND METHODS

We design a deep learning framework called SuperMAP that directly converts a series of undersampled (both in k-space and parameter-space) parameter-weighted images into several quantitative maps, bypassing the conventional exponential fitting procedure. We also present a novel technique to simultaneously reconstruct T1rho and T2 relaxation maps within a single scan. Full data were acquired and retrospectively undersampled for training and testing using traditional and state-of-the-art techniques for comparison. Prospective data were also collected to evaluate the trained network. The performance of all methods is evaluated using the parameter qualification errors and other metrics in the segmented regions of interest.

RESULTS

SuperMAP achieved accurate T1rho and T2 mapping with high acceleration factors (R = 24 and R = 32). It exploited both spatial and temporal information and yielded low error (normalized mean square error of 2.7% at R = 24 and 2.8% at R = 32) and high resemblance (structural similarity of 97% at R = 24 and 96% at R = 32) to the gold standard. The network trained with retrospectively undersampled data also works well for the prospective data (with a slightly lower acceleration factor). SuperMAP is also superior to conventional methods.

CONCLUSION

Our results demonstrate the feasibility of generating superfast MR parameter maps through very few undersampled parameter-weighted images. SuperMAP can simultaneously generate T1rho and T2 relaxation maps in a short scan time.

Structural and functional imaging of brains

Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.

Recent Technical Developments in ASL: A Review of the State of the Art

This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

Application of a novel T1 retrospective quantification using internal references (T1-REQUIRE) algorithm to derive quantitative T1 relaxation maps of the brain

Most MRI sequences used clinically are qualitative or weighted. While such images provide useful information for clinicians to diagnose and monitor disease progression, they lack the ability to quantify tissue damage for more objective assessment. In this study, an algorithm referred to as the T1-REQUIRE is presented as a proof-of-concept which uses nonlinear transformations to retrospectively estimate T1 relaxation times in the brain using T1-weighted MRIs, the appropriate signal equation, and internal, healthy tissues as references. T1-REQUIRE was applied to two T1-weighted MR sequences, a spin-echo and a MPRAGE, and validated with a reference standard T1 mapping algorithm in vivo. In addition, a multiscanner study was run using MPRAGE images to determine the effectiveness of T1-REQUIRE in conforming the data from different scanners into a more uniform way of analyzing T1-relaxation maps. The T1-REQUIRE algorithm shows good agreement with the reference standard (Lin's concordance correlation coefficients of 0.884 for the spin-echo and 0.838 for the MPRAGE) and with each other (Lin's concordance correlation coefficient of 0.887). The interscanner studies showed improved alignment of cumulative distribution functions after T1-REQUIRE was performed. T1-REQUIRE was validated with a reference standard and shown to be an effective estimate of T1 over a clinically relevant range of T1 values. In addition, T1-REQUIRE showed excellent data conformity across different scanners, providing evidence that T1-REQUIRE could be a useful addition to big data pipelines.

Modified MRI Anonymization (De-Facing) for Improved MEG Coregistration

Localising the sources of MEG/EEG signals often requires a structural MRI to create a head model, while ensuring reproducible scientific results requires sharing data and code. However, sharing structural MRI data often requires the face go be hidden to help protect the identity of the individuals concerned. While automated de-facing methods exist, they tend to remove the whole face, which can impair methods for coregistering the MRI data with the EEG/MEG data. We show that a new, automated de-facing method that retains the nose maintains good MRI-MEG/EEG coregistration. Importantly, behavioural data show that this "face-trimming" method does not increase levels of identification relative to a standard de-facing approach and has less effect on the automated segmentation and surface extraction sometimes used to create head models for MEG/EEG localisation. We suggest that this trimming approach could be employed for future sharing of structural MRI data, at least for those to be used in forward modelling (source reconstruction) of EEG/MEG data.

Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue

PURPOSE

To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues.

METHODS

MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis.

RESULTS

The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2  > 0.840).

CONCLUSION

Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.

Synthetic MRI with Magnetic Resonance Spin TomogrAphy in Time-Domain (MR-STAT): Results from a Prospective Cross-Sectional Clinical Trial

BACKGROUND

Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) can reconstruct whole-brain multi-parametric quantitative maps (eg, T₁ , T₂ ) from a 5-minute MR acquisition. These quantitative maps can be leveraged for synthetization of clinical image contrasts.

PURPOSE

The objective was to assess image quality and overall diagnostic accuracy of synthetic MR-STAT contrasts compared to conventional contrast-weighted images.

STUDY TYPE

Prospective cross-sectional clinical trial.

POPULATION

Fifty participants with a median age of 45 years (range: 21-79 years) consisting of 10 healthy participants and 40 patients with neurological diseases (brain tumor, epilepsy, multiple sclerosis or stroke).

FIELD STRENGTH/SEQUENCE

3T/Conventional contrast-weighted imaging (T₁ /T₂ weighted, proton density [PD] weighted, and fluid-attenuated inversion recovery [FLAIR]) and a MR-STAT acquisition (2D Cartesian spoiled gradient echo with varying flip angle preceded by a non-selective inversion pulse).

ASSESSMENT

Quantitative T₁ , T₂ , and PD maps were computed from the MR-STAT acquisition, from which synthetic contrasts were generated. Three neuroradiologists blinded for image type and disease randomly and independently evaluated synthetic and conventional datasets for image quality and diagnostic accuracy, which was assessed by comparison with the clinically confirmed diagnosis.

STATISTICAL TESTS

Image quality and consequent acceptability for diagnostic use was assessed with a McNemar's test (one-sided α = 0.025). Wilcoxon signed rank test with a one-sided α = 0.025 and a margin of Δ = 0.5 on the 5-level Likert scale was used to assess non-inferiority.

RESULTS

All data sets were similar in acceptability for diagnostic use (≥3 Likert-scale) between techniques (T₁ w:P = 0.105, PDw:P = 1.000, FLAIR:P = 0.564). However, only the synthetic MR-STAT T₂ weighted images were significantly non-inferior to their conventional counterpart; all other synthetic datasets were inferior (T₁ w:P = 0.260, PDw:P = 1.000, FLAIR:P = 1.000). Moreover, true positive/negative rates were similar between techniques (conventional: 88%, MR-STAT: 84%).

DATA CONCLUSION

MR-STAT is a quantitative technique that may provide radiologists with clinically useful synthetic contrast images within substantially reduced scan time.

EVIDENCE LEVEL

1 Technical Efficacy: Stage 2.

Learning-based optimization of acquisition schedule for magnetization transfer contrast MR fingerprinting

Magnetization transfer contrast MR fingerprinting (MTC-MRF) is a novel quantitative imaging method that simultaneously quantifies free bulk water and semisolid macromolecule parameters using pseudo-randomized scan parameters. To improve acquisition efficiency and reconstruction accuracy, the optimization of MRF sequence design has been of recent interest in the MRF field, but has been challenging due to the large number of degrees of freedom to be optimized in the sequence. Herein, we propose a framework for learning-based optimization of the acquisition schedule (LOAS), which optimizes RF saturation-encoded MRF acquisitions with a minimal number of scan parameters for tissue parameter determination. In a supervised learning framework, scan parameters were subsequently updated to minimize a predefined loss function that can directly represent tissue quantification errors. We evaluated the performance of the proposed approach with a numerical phantom and in in vivo experiments. For validation, MRF images were synthesized using the tissue parameters estimated from a fully connected neural network framework and compared with references. Our results showed that LOAS outperformed existing indirect optimization methods with regard to quantification accuracy and acquisition efficiency. The proposed LOAS method could be a powerful optimization tool in the design of MRF pulse sequences.

Low‐rank inversion reconstruction for through‐plane accelerated radial MR fingerprinting applied to relaxometry at 0. 35 T

Purpose

To reduce scan time, methods to accelerate phase‐encoded/non‐Cartesian MR fingerprinting (MRF) acquisitions for variable density spiral acquisitions have recently been developed. These methods are not applicable to MRF acquisitions, wherein a single k‐space spoke is acquired per frame. Therefore, we propose a low‐rank inversion method to resolve MRF contrast dynamics from through‐plane accelerated Cartesian/radial measurements applied to quantitative relaxation‐time mapping on a 0.35T system.

Methods

An algorithm was implemented to reconstruct through‐plane aliased low‐rank images describing the contrast dynamics occurring because of the transient‐state MRF acquisition. T₁ and T₂ times from accelerated acquisitions were compared with those from unaccelerated linear reconstructions in a standardized system phantom and within in vivo brain and prostate experiments on a hybrid 0.35T MRI/linear accelerator.

Results

No significant differences between T₁ and T₂ times for the accelerated reconstructions were observed compared to fully sampled acquisitions (p = 0.41 and p = 0.36, respectively). The mean absolute errors in T₁ and T₂ were 5.6% and 2.9%, respectively, between the full and accelerated acquisitions. The SDs in T₁ and T₂ decreased with the advanced accelerated reconstruction compared with the unaccelerated reconstruction (p = 0.02 and p = 0.03, respectively). The quality of the T₁ and T₂ maps generated with the proposed approach are comparable to those obtained using the unaccelerated data sets.

Conclusions

Through‐plane accelerated MRF with radial k‐space coverage was demonstrated at a low field strength of 0.35 T. This method enabled 3D T₁ and T₂ mapping at 0.35 T with a 3‐min scan.

Accelerating MR Parameter Mapping Using Nonlinear Compressive Manifold Learning and Regularized Pre-Imaging

In this study, we presented a novel method to reconstruct the MR parametric maps from highly undersampled k-space data. Specifically, we utilized a nonlinear model to sparsely represent the unknown MR parameter-weighted images in high-dimensional feature space. Each image at a specific time point is assumed to belong to a low-dimensional manifold which is learned from training images created based on the parametric model. The final reconstruction is carried out by venturing the sparse representation of the images in the feature space back to the input space, using the pre-imaging technique. Particularly, among an infinite number of solutions that satisfy the data consistency, the one that is closest to the manifold is selected as the desired solution. The underlying optimization problem is solved using kernel trick, sparse coding, and split Bregman iteration algorithm. In addition, both spatial and temporal regularizations were utilized to further improve the reconstruction quality. The proposed method was validated on both phantom and in vivo human brain T2 mapping data. Results showed the proposed method was superior to the conventional linear model-based reconstruction methods, in terms of artifact removal and quantitative estimate accuracy. The proposed method could be potentially beneficial for quantitative MR applications.

MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification

Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms have been developed to further boost the performance and speed of CEST and semi-solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.

Screening Breast MRI and Gadolinium Deposition: Cause for Concern?

Gadolinium-based contrast agents (GBCAs) have been used worldwide for over 30 years and have enabled lifesaving diagnoses. Contrast-enhanced breast MRI is frequently used as supplemental screening for women with an elevated lifetime risk of breast cancer. Data have emerged that indicate a fractional amount of administered gadolinium is retained in the bone, skin, solid organs, and brain tissues of patients with normal renal function, although there are currently no reliable data regarding the clinical or biological significance of this retention. Linear GBCAs are associated with a higher risk of gadolinium retention than macrocyclic agents. Over the course of their lives, screened women may receive high cumulative doses of GBCA. Therefore, as breast MRI screening utilization increases, thoughtful use of GBCA is indicated in this patient population.

Current approaches and advances in the imaging of stroke

A stroke occurs when the blood flow to the brain is suddenly interrupted, depriving brain cells of oxygen and glucose and leading to further cell death. Neuroimaging techniques, such as computed tomography and magnetic resonance imaging, have greatly improved our ability to visualise brain structures and are routinely used to diagnose the affected vascular region of a stroke patient's brain and to inform decisions about clinical care. Currently, these multimodal imaging techniques are the backbone of the clinical management of stroke patients and have immensely improved our ability to visualise brain structures. Here, we review recent developments in the field of neuroimaging and discuss how different imaging techniques are used in the diagnosis, prognosis and treatment of stroke.

Summary: Stroke imaging has undergone seismic shifts in the past decade. Although magnetic resonance imaging (MRI) is superior to computed tomography in providing vital information, further research on MRI is still required to bring its full potential into clinical practice.

Temperature dependence, accuracy, and repeatability of T1 and T2 relaxation times for the ISMRM/NIST system phantom measured using MR fingerprinting

PURPOSE

Before MR fingerprinting (MRF) can be adopted clinically, the derived quantitative values must be proven accurate and repeatable over a range of T₁ and T₂ values and temperatures. Correct assessment of accuracy and precision as well as comparison between measurements can only be performed when temperature is either controlled or corrected for. The purpose of this study was to investigate the temperature dependence of T₁ and T₂ MRF values and evaluate the accuracy and repeatability of temperature-corrected relaxation values derived from a B₁ -corrected MRF-fast imaging with steady-state precession implementation using 2 different dictionary sizes.

METHODS

The International Society of MR in Medicine/National Institute of Standards and Technology phantom was scanned using an MRF sequence of 2 different lengths, a variable flip angle T₁ , and a multi-echo spin echo T₂ at 14 temperatures ranging from 15°C to 28°C and investigated with a linear regression model. Temperature-corrected accuracy was evaluated by correlating T₁ and T₂ times from each MRF dictionary with reference values. Repeatability was assessed using the coefficient of variation, with measurements taken over 30 separate sessions.

RESULTS

There was a statistically significant fit of the model for MRF-derived T₁ and T₂ and temperature (p < 0.05) for all the spheres with a T₁ > 500 ms. Both MRF methods showed a strong linear correlation with reference values for T₁ (R² = 0.996) and T₂ (R² = 0.982). MRF repeatability for T₁ values was ≤1.4% and for T₂ values was ≤3.4%.

CONCLUSION

MRF demonstrated relaxation times with a temperature dependence similar to that of conventional mapping methods. Temperature-corrected T₁ and T₂ values from both dictionaries showed adequate accuracy and excellent repeatability in this phantom study.

Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer

Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.

Review of Quantitative Knee Articular Cartilage MR Imaging

Osteoarthritis (OA) is one of the most prevalent disorders in today’s society, resulting in significant socio-economic costs and morbidity. MRI is widely used as a non-invasive imaging tool for OA of the knee. However, conventional knee MRI has limitations to detect subtle early cartilage degeneration before morphological changes are visually apparent. Novel MRI pulse sequences for cartilage assessment have recently received increased attention due to newly developed compositional MRI techniques, including: T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), sodium MRI, diffusion-weighted imaging (DWI)/ diffusion tensor imaging (DTI), ultrashort TE (uTE), and glycosaminoglycan specific chemical exchange saturation transfer (gagCEST) imaging. In this article, we will first review these quantitative assessments. Then, we will discuss the variations of quantitative values of knee articular cartilage with cartilage layer (depth)- and angle (regional)-dependent approaches. Multiple MRI sequence techniques can discern qualitative differences in knee cartilage. Normal articular hyaline cartilage has a zonal variation in T2 relaxation times with increasing T2 values from the subchondral bone to the articular surface. T1rho values were also higher in the superficial layer than in the deep layer in most locations in the medial and lateral femoral condyles, including the weight-bearing portion. Magic angle effect on T2 mapping is clearly observed in the both medial and lateral femoral condyles, especially within the deep layers. One of the limitations for clinical use of these compositional assessments is a long scan time. Recent new approaches with compressed sensing (CS) and MR fingerprinting (MRF) have potential to provide accurate and fast quantitative cartilage assessments.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Lesion probability mapping in MS patients using a regression network on MR fingerprinting

BACKGROUND

To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula: see text], [Formula: see text], NAWM, and GM- probability maps.

METHODS

We performed MRF-EPI measurements in 42 patients with multiple sclerosis and 6 healthy volunteers along two sites. A U-net was trained to reconstruct the denoised and distortion corrected [Formula: see text] and [Formula: see text] maps, and to additionally generate NAWM-, GM-, and WM lesion probability maps.

RESULTS

WM lesions were predicted with a dice coefficient of [Formula: see text] and a lesion detection rate of [Formula: see text] for a threshold of 33%. The network jointly enabled accurate [Formula: see text] and [Formula: see text] times with relative deviations of 5.2% and 5.1% and average dice coefficients of [Formula: see text] and [Formula: see text] for NAWM and GM after binarizing with a threshold of 80%.

CONCLUSION

DL is a promising tool for the prediction of lesion probability maps in a fraction of time. These might be of clinical interest for the WM lesion analysis in MS patients.

Feasibility of MR fingerprinting using a high-performance 0.55 T MRI system

BACKGROUND

MR fingerprinting (MRF) is a versatile method for rapid multi-parametric quantification. The application of MRF for lower MRI field could enable multi-contrast imaging and improve exam efficiency on these systems. The purpose of this work is to demonstrate the feasibility of 3D whole-brain T1 and T2 mapping using MR fingerprinting on a contemporary 0.55 T MRI system.

MATERIALS AND METHODS

A 3D whole brain stack-of-spirals FISP MRF sequence was implemented for 0.55 T. Quantification was validated using the NIST/ISMRM Quantitative MRI phantom, and T1 and T2 values of white matter, gray matter, and cerebrospinal fluid were measured in 19 healthy subjects. To assess MRF performance in the lower SNR regime of 0.55 T, measurement precision was calculated from 100 simulated pseudo-replicas of in vivo data and within-session measurement repeatability was evaluated.

RESULTS

T1 and T2 values calculated by MRF were strongly correlated to standard measurements in the ISMRM/NIST MRI system phantom (R² > 0.99), with a small constant bias of approximately 5 ms in T2 values. 3D stack-of-spirals MRF was successfully applied for whole brain quantitative T1 and T2 at 0.55 T, with spatial resolution of 1.2 mm × 1.2 mm × 5 mm, and acquisition time of 8.5 min. Moreover, the T1 and T2 quantifications had precision <5%, despite the lower SNR of 0.55 T.

CONCLUSION

A 3D whole-brain stack-of-spirals FISP MRF sequence is feasible for T1 and T2 mapping at 0.55 T.

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Purpose

MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma.

Materials and methods

A whole-brain 3D isotropic 1mm³ acquisition under a 3.0T field strength was used to obtain MRF T₁ and T₂-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T₁ and T₂ estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test.

Results

MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T₁ (r² = 0.99) and T₂ (r² = 0.97). MRF T₁ relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T₂ relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001)

Conclusions

Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

Application of magnetic resonance fingerprinting to differentiate grade I transitional and fibrous meningiomas from meningothelial meningiomas

Background

The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas.

Methods

Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T₁-weighted imaging (T1WI) and T₂-weighted imaging (T2WI). To investigate the difference in quantitative T1 and T2 values derived from MRF and apparent diffusion coefficient (ADC) values between the three groups using the Kruskal-Wallis test, regions of interest (ROIs) were manually drawn on the parenchymal portion of the tumors; P<0.017 was considered statistically significant after Bonferroni correction for multiple comparison. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performances of the different parameters.

Results

Meningothelial meningiomas had significantly higher T1 and T2 values than transitional and fibrous meningiomas (all P<0.017). ROC analysis results revealed that the combination of T1 and T2 values had the largest area under the curve (AUC). The AUC for the combination of T1 and T2 values was 0.826 between meningothelial and transitional meningiomas, and the AUC for the combination of T1 and T2 values between meningothelial and fibrous meningiomas was 0.903. No significant differences were found in the T1 and T2 values between transitional and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05).

Conclusions

MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

Advances in translational imaging of the microcirculation

The past few decades have seen an explosion in the development and use of methods for imaging the human microcirculation during health and disease. The confluence of innovative imaging technologies, affordable computing power, and economies of scale have ushered in a new era of "translational" imaging that permit us to peer into blood vessels of various organs in the human body. These imaging techniques include near-infrared spectroscopy (NIRS), positron emission tomography (PET), and magnetic resonance imaging (MRI) that are sensitive to microvascular-derived signals, as well as computed tomography (CT), optical imaging, and ultrasound (US) imaging that are capable of directly acquiring images at, or close to microvascular spatial resolution. Collectively, these imaging modalities enable us to characterize the morphological and functional changes in a tissue's microcirculation that are known to accompany the initiation and progression of numerous pathologies. Although there have been significant advances for imaging the microcirculation in preclinical models, this review focuses on developments in the assessment of the microcirculation in patients with optical imaging, NIRS, PET, US, MRI, and CT, to name a few. The goal of this review is to serve as a springboard for exploring the burgeoning role of translational imaging technologies for interrogating the structural and functional status of the microcirculation in humans, and highlight the breadth of current clinical applications. Making the human microcirculation "visible" in vivo to clinicians and researchers alike will facilitate bench-to-bedside discoveries and enhance the diagnosis and management of disease.

Emerging Trends in Neuroimaging of Epilepsy

Neuroimaging techniques, particularly magnetic resonance imaging, yield increasingly sophisticated markers of brain structure and function. Combined with ongoing developments in machine learning, these methods refine our abilities to detect subtle epileptogenic lesions and develop reliable prognostics.

Accelerated white matter lesion analysis based on simultaneous T 1 and T 2 ∗ quantification using magnetic resonance fingerprinting and deep learning

PURPOSE

To develop an accelerated postprocessing pipeline for reproducible and efficient assessment of white matter lesions using quantitative magnetic resonance fingerprinting (MRF) and deep learning.

METHODS

MRF using echo-planar imaging (EPI) scans with varying repetition and echo times were acquired for whole brain quantification of T 1 and T 2 ∗ in 50 subjects with multiple sclerosis (MS) and 10 healthy volunteers along 2 centers. MRF T 1 and T 2 ∗ parametric maps were distortion corrected and denoised. A CNN was trained to reconstruct the T 1 and T 2 ∗ parametric maps, and the WM and GM probability maps.

RESULTS

Deep learning-based postprocessing reduced reconstruction and image processing times from hours to a few seconds while maintaining high accuracy, reliability, and precision. Mean absolute error performed the best for T 1 (deviations 5.6%) and the logarithmic hyperbolic cosinus loss the best for T 2 ∗ (deviations 6.0%).

CONCLUSIONS

MRF is a fast and robust tool for quantitative T 1 and T 2 ∗ mapping. Its long reconstruction and several postprocessing steps can be facilitated and accelerated using deep learning.

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

Introduction

Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging.

Methods

A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020.

Results

A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive.

Conclusions

aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.

Sensitive detection of extremely small iron oxide nanoparticles in living mice using MP2RAGE with advanced image co-registration

Magnetic resonance imaging (MRI) is a widely used non-invasive methodology for both preclinical and clinical studies. However, MRI lacks molecular specificity. Molecular contrast agents for MRI would be highly beneficial for detecting specific pathological lesions and quantitatively evaluating therapeutic efficacy in vivo. In this study, an optimized Magnetization Prepared—RApid Gradient Echo (MP-RAGE) with 2 inversion times called MP2RAGE combined with advanced image co-registration is presented as an effective non-invasive methodology to quantitatively detect T1 MR contrast agents. The optimized MP2RAGE produced high quality in vivo mouse brain T1 (or R1 = 1/T1) map with high spatial resolution, 160 × 160 × 160 µm³ voxel at 9.4 T. Test–retest signal to noise was > 20 for most voxels. Extremely small iron oxide nanoparticles (ESIONPs) having 3 nm core size and 11 nm hydrodynamic radius after polyethylene glycol (PEG) coating were intracranially injected into mouse brain and detected as a proof-of-concept. Two independent MP2RAGE MR scans were performed pre- and post-injection of ESIONPs followed by advanced image co-registration. The comparison of two T1 (or R1) maps after image co-registration provided precise and quantitative assessment of the effects of the injected ESIONPs at each voxel. The proposed MR protocol has potential for future use in the detection of T1 molecular contrast agents.

Magnetic resonance fingerprinting: from evolution to clinical applications

In 2013, Magnetic Resonance Fingerprinting (MRF) emerged as a method for fast, quantitative Magnetic Resonance Imaging. This paper reviews the current status of MRF up to early 2020 and aims to highlight the advantages MRF can offer medical imaging professionals. By acquiring scan data as pseudorandom samples, MRF elicits a unique signal evolution, or 'fingerprint', from each tissue type. It matches 'randomised' free induction decay acquisitions against pre-computed simulated tissue responses to generate a set of quantitative images of T1 , T2 and proton density (PD) with co-registered voxels, rather than as traditional relative T1 - and T2 -weighted images. MRF numeric pixel values retain accuracy and reproducibility between 2% and 8%. MRF acquisition is robust to strong undersampling of k-space. Scan sequences have been optimised to suppress sub-sampling artefacts, while artificial intelligence and machine learning techniques have been employed to increase matching speed and precision. MRF promises improved patient comfort with reduced scan times and fewer image artefacts. Quantitative MRF data could be used to define population-wide numeric biomarkers that classify normal versus diseased tissue. Certification of clinical centres for MRF scan repeatability would permit numeric comparison of sequential images for any individual patient and the pooling of multiple patient images across large, cross-site imaging studies. MRF has to date shown promising results in early clinical trials, demonstrating reliable differentiation between malignant and benign prostate conditions, and normal and sclerotic hippocampal tissue. MRF is now undergoing small-scale trials at several sites across the world; moving it closer to routine clinical application.

Calgary Normative Study: design of a prospective longitudinal study to characterise potential quantitative MR biomarkers of neurodegeneration over the adult lifespan

INTRODUCTION

A number of MRI methods have been proposed to be useful, quantitative biomarkers of neurodegeneration in ageing. The Calgary Normative Study (CNS) is an ongoing single-centre, prospective, longitudinal study that seeks to develop, test and assess quantitative magnetic resonance (MR) methods as potential biomarkers of neurodegeneration. The CNS has three objectives: first and foremost, to evaluate and characterise the dependence of the selected quantitative neuroimaging biomarkers on age over the adult lifespan; second, to evaluate the precision, variability and repeatability of quantitative neuroimaging biomarkers as part of biomarker validation providing proof-of-concept and proof-of-principle; and third, provide a shared repository of normative data for comparison to various disease cohorts.

METHODS AND ANALYSIS

Quantitative MR mapping of the brain including longitudinal relaxation time (T1), transverse relaxation time (T2), T2*, magnetic susceptibility (QSM), diffusion and perfusion measurements, as well as morphological assessments are performed. The Montreal Cognitive Assessment (MoCA) and a brief, self-report medical history will be collected. Mixed regression models will be used to characterise changes in quantitative MR biomarker measures over the adult lifespan. In this report, we describe the study design, strategies to recruit and perform changes to the acquisition protocol from inception to 31 December 2018, planned statistical approach and data sharing procedures for the study.

ETHICS AND DISSEMINATION

Participants provide signed informed consent. Changes in quantitative MR biomarkers measured over the adult lifespan as well as estimates of measurement variance and repeatability will be disseminated through peer-reviewed scientific publication.

Correlations of amide proton transfer-weighted MRI of cerebral infarction with clinico-radiological findings

Objective

To clarify the relationship between amide proton transfer-weighted (APTW) signal, which reflects intracellular pH, and clinico-radiological findings in patients with hyperacute to subacute cerebral infarction.

Materials and methods

Twenty-nine patients (median age, 70 years [IQR, 54 to 74]; 15 men) were retrospectively examined. The 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal (APT₁₀, APT₂₅, APT₅₀, APT₇₅ and APT₉₀, respectively) were measured within the infarction region-of-interest (ROI), and compared between poor prognosis and good prognosis groups (modified Rankin Scale [mRS] score ≥2 and mRS score <2, respectively). Correlations between APTW signal and time after onset, lesion size, National Institutes of Health Stroke Scale (NIHSS) score, mRS score, and mean apparent diffusion coefficient (ADC) were evaluated.

Results

The poor prognosis group had lower APT₅₀, APT₇₅, and APT₉₀ than the good prognosis group (–0.66 [–1.19 to –0.27] vs. –0.09 [–0.62 to –0.21]; –0.27 [–0.63 to –0.01] vs. 0.31 [–0.15 to 1.06]; 0.06 [–0.21 to 0.34] vs. 0.93 [0.36 to 1.50] %; p <0.05, respectively). APT₅₀ was positively correlated with time after onset (r = 0.37, p = 0.0471) and negatively with lesion size (r = –0.39, p = 0.0388). APT₇₅ and APT₉₀ were negatively correlated with NIHSS (r = –0.41 and –0.43; p <0.05, respectively). APT₅₀, APT₇₅ and APT₉₀ were negatively correlated with mRS (r = –0.37, –0.52 and –0.57; p <0.05, respectively). APT₁₀ and APT₂₅ were positively correlated with mean ADC (r = 0.37 and 0.38; p <0.05, respectively).

Conclusion

We demonstrated correlations between APTW signals of infarctions and clinico-radiological findings in patients with hyperacute to subacute infarctions. The poor prognosis group had a lower APTW signal than the good prognosis group. APTW signal was reduced in large infarctions, infarctions with low ADC, and in patients with high NIHSS and mRS scores.

A Perspective on MR Fingerprinting

This article reviews the basic concept of MR fingerprinting (MRF) with the goal of highlighting MRF's key contributions, putting them in the context of other quantitative MRI literature, and refining MRF's terminology. The article discusses the robustness and flexibility of MRF's signature dictionary-matching reconstruction along with more advanced MRF reconstructions. A key feature of MRF is the lack of assumptions about the signal evolution, which gives scientists the flexibility to tailor sequences for their needs. The article argues that the concept of unique fingerprints does not capture the requirements for successful parameter mapping and that an analysis of the signal's derivatives with respect to biophysical parameters, such as relaxation times, is more informative, as it allows one to evaluate the efficiency of a pulse sequence. The article points at the source of MRF's efficiency, namely, flip angle variations at the time scale of the relaxation times, and reveals that MRF's advantages are strongest at long scan times, as required for 3D imaging. Further, it outlines how MRF's flexibility can be used to design mutually tailored pulse sequences and biophysical models with the goal of improving the reproducibility of parameter mapping biological tissue. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Acceleration of 2D-MR fingerprinting by reducing the number of echoes with increased in-plane resolution: a volunteer study

Objective

To compare the absolute values and repeatability of magnetic resonance fingerprinting (MRF) with 3000 and 1500 echoes/slice acquired in 41 s and 20 s (MRF3k and MRF1.5k, respectively).

Materials and methods

MRF3k and MRF1.5k scans based on fast imaging with steady precession (FISP) were conducted using a 3 T scanner. Inter-scan agreement and intra-scan repeatability were investigated in 41 and 28 subjects, respectively. Region-of-interest (ROI) analysis was conducted on T1 values of MRF3k by two raters, and their agreement was evaluated using intraclass correlation coefficients (ICCs). Between MRF3k and MRF1.5k, differences in T1 and T2 values and inter-measurement correlation coefficients (CCs) were investigated. Intra-measurement repeatability was evaluated using coefficients of variation (CVs). A p value < 0.05 was considered statistically significant.

Results

The ICCs of ROI measurements were 0.77–0.96. Differences were observed between the two MRF scans, but the CCs of the overall ROIs were 0.99 and 0.97 for the T1 and T2 values, respectively. The mean and median CVs of repeatability were equal to or less than 1.58% and 3.13% in each of the ROIs for T1 and T2, respectively; there were some significant differences between MRF3k and MRF1.5k, but they were small, measuring less than 1%.

Discussion

Both MRF3k and MRF1.5k had high repeatability, and a strong to very strong correlation was observed, with a trend toward slightly higher values in MRF1.5k.

Electronic supplementary material

The online version of this article (10.1007/s10334-020-00842-8) contains supplementary material, which is available to authorized users.