A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities

Person-centered analyses reveal that developmental adversity at moderate levels and neural threat/safety discrimination are associated with lower anxiety in early adulthood

Parsing heterogeneity in the nature of adversity exposure and neurobiological functioning may facilitate better understanding of how adversity shapes individual variation in risk for and resilience against anxiety. One putative mechanism linking adversity exposure with anxiety is disrupted threat and safety learning. Here, we applied a person-centered approach (latent profile analysis) to characterize patterns of adversity exposure at specific developmental stages and threat/safety discrimination in corticolimbic circuitry in 120 young adults. We then compared how the resultant profiles differed in anxiety symptoms. Three latent profiles emerged: (1) a group with lower lifetime adversity, higher neural activation to threat, and lower neural activation to safety; (2) a group with moderate adversity during middle childhood and adolescence, lower neural activation to threat, and higher neural activation to safety; and (3) a group with higher lifetime adversity exposure and minimal neural activation to both threat and safety. Individuals in the second profile had lower anxiety than the other profiles. These findings demonstrate how variability in within-person combinations of adversity exposure and neural threat/safety discrimination can differentially relate to anxiety, and suggest that for some individuals, moderate adversity exposure during middle childhood and adolescence could be associated with processes that foster resilience to future anxiety.

A General Framework for Characterizing Inaccuracy in Stereotactic Systems

BACKGROUND AND OBJECTIVES

Identifying and characterizing sources of targeting error in stereotactic procedures is essential to maximizing accuracy, potentially improving surgical outcomes. We aim to describe a generic framework which characterizes sources of stereotactic inaccuracy.

METHODS

We assembled a list of stereotactic systems: ROSA, Neuromate, Mazor Renaissance, ExcelsiusGPS, Cirq, STarFix (FHC), Nexframe, ClearPoint, CRW, and Leksell. We searched the literature for qualitative and quantitative work identifying and quantifying potential sources of inaccuracy and describing each system's implementation using Standards for Reporting Qualitative Research guidelines. Our literature search spanned 1969 to 2024, and various studies were included, with formats ranging from phantom studies to systematic reviews. Keyword searches were conducted, and the details about each system were used to create a framework for identifying and describing the unique targeting error profile of each system.

RESULTS

We describe and illustrate the details of various sources of stereotactic inaccuracies and generate a framework to unify these sources into a single framework. This framework entails 5 domains: imaging, registration, mechanical accuracy, target planning and adjustment, and trajectory planning and adjustment. This framework was applied to 10 stereotactic systems.

CONCLUSION

This framework provides a rubric to analyze the sources of error for any stereotactic system. Illustrations allow the reader to understand sources of error conceptually so that they may apply them to their practice.

Structural Development of Speech Networks in Young Children

Characterizing the structural development of the neural speech network in early childhood is important to understand speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). In order to increase sample size and performance variability, we included children who were diagnosed with attention-deficit hyperactivity disorder (ADHD) from a larger ongoing study. Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus, pars opercularis , right pre-supplementary and supplementary motor area, and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automated fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT, in bilateral SLFIII, and in the cerebellar peduncles. These findings suggest that individual differences in speech performance are reflected in structural grey and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.

AutoCorNN: An Unsupervised Physics-Aware Deep Learning Model for Geometric Distortion Correction of Brain MRI Images Towards MR-Only Stereotactic Radiosurgery

Geometric distortions in brain MRI images arising from susceptibility artifacts at air-tissue interfaces pose a significant challenge for high-precision radiation therapy modalities like stereotactic radiosurgery, necessitating sub-millimeter accuracy. To achieve this goal, we developed AutoCorNN, an unsupervised physics-aware deep-learning model for correcting geometric distortions. Two publicly available datasets, the MPI-Leipzig Mind-Brain-Body with 318 subjects, and the Vestibular Schwannoma-SEG dataset, encompassing 242 patients were utilized. AutoCorNN integrates two 2D convolutional encoder-decoder neural networks with the forward physical model of MRI signal generation to predict undistorted MR and field map images from distorted MR input. The network is trained in an unsupervised manner by minimizing the mean absolute error between the measured and estimated k-space data, without requiring ground truth images during training or deployment. The model was evaluated on vestibular schwannoma cases. AutoCorNN achieved a peak signal-to-noise ratio (PSNR) of 41.35 ± 0.02 dB, a root mean square error (RMSE) of 0.02 ± 0.003, and a structural similarity index (SSIM) of 0.99 ± 0.02 outperforming uncorrected and B0-mapping correction methods. Geometric distortions of about 1.6 mm were observed at the air-tissue interfaces at the air canal and nasal cavity borders. Geometrically, distortion correction increased the target volume from 3.12 ± 0.52 cc to 3.84 ± 0.54 cc. Dosimetrically, AutoCorNN improved target coverage (0.96 ± 0.01 to 0.97 ± 0.02), conformity index (0.92 ± 0.03 to 0.94 ± 0.03), and reduced dose gradients outside the target. AutoCorNN achieves accurate geometric distortion correction comparable to conventional iterative methods while offering substantial computational acceleration, enabling precise target delineation and conformal dose delivery for improved radiation therapy outcomes.

Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC)

PURPOSE

To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers.

METHODS

This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63-83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant.

RESULTS

In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177).

CONCLUSION

In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.

Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction

PURPOSE

BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of more complex reconstruction that is computationally prohibitive. In this work we develop rapid reconstruction pipeline for BUDA-cEPI to pave the way for its deployment in routine clinical and neuroscientific applications. The proposed reconstruction includes the development of ML-based unrolled reconstruction as well as rapid ML-based B0 and eddy current estimations that are needed. The architecture of the unroll network was designed so that it can mimic S-LORAKS regularization well, with the addition of virtual coil channels.

METHODS

BUDA-cEPI RUN-UP - a model-based framework that incorporates off-resonance and eddy current effects was unrolled through an artificial neural network with only six gradient updates. The unrolled network alternates between data consistency (i.e., forward BUDA-cEPI and its adjoint) and regularization steps where U-Net plays a role as the regularizer. To handle the partial Fourier effect, the virtual coil concept was also introduced into the reconstruction to effectively take advantage of the smooth phase prior and trained to predict the ground-truth images obtained by BUDA-cEPI with S-LORAKS.

RESULTS

The introduction of the Virtual Coil concept into the unrolled network was shown to be key to achieving high-quality reconstruction for BUDA-cEPI. With the inclusion of an additional non-diffusion image (b-value = 0 s/mm2), a slight improvement was observed, with the normalized root mean square error further reduced by approximately 5 %. The reconstruction times for S-LORAKS and the proposed unrolled networks were approximately 225 and 3 s per slice, respectively.

CONCLUSION

BUDA-cEPI RUN-UP was shown to reduce the reconstruction time by ∼88× when compared to the state-of-the-art technique, while preserving imaging details as demonstrated through DTI application.

Processing, evaluating, and understanding FMRI data with afni_proc.py

FMRI data are noisy, complicated to acquire, and typically go through many steps of processing before they are used in a study or clinical practice. Being able to visualize and understand the data from the start through the completion of processing, while being confident that each intermediate step was successful, is challenging. AFNI's afni_proc.py is a tool to create and run a processing pipeline for FMRI data. With its flexible features, afni_proc.py allows users to both control and evaluate their processing at a detailed level. It has been designed to keep users informed about all processing steps: it does not just process the data, but also first outputs a fully commented processing script that the users can read, query, interpret, and refer back to. Having this full provenance is important for being able to understand each step of processing; it also promotes transparency and reproducibility by keeping the record of individual-level processing and modeling specifics in a single, shareable place. Additionally, afni_proc.py creates pipelines that contain several automatic self-checks for potential problems during runtime. The output directory contains a dictionary of relevant quantities that can be programmatically queried for potential issues and a systematic, interactive quality control (QC) HTML. All of these features help users evaluate and understand their data and processing in detail. We describe these and other aspects of afni_proc.py here using a set of task-based and resting-state FMRI example commands.

A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth, and interactive QC with afni_proc.py and more

Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically underdiscussed aspect of reproducibility. This includes checking datasets at their very earliest stages (acquisition and conversion) through their processing steps (e.g., alignment and motion correction) to regression modeling (correct stimuli, no collinearity, valid fits, enough degrees of freedom, etc.) for each subject. There are a wide variety of features to verify throughout any single-subject processing pipeline, both quantitatively and qualitatively. We present several FMRI preprocessing QC features available in the AFNI toolbox, many of which are automatically generated by the pipeline-creation tool, afni_proc.py. These items include a modular HTML document that covers full single-subject processing from the raw data through statistical modeling, several review scripts in the results directory of processed data, and command line tools for identifying subjects with one or more quantitative properties across a group (such as triaging warnings, making exclusion criteria, or creating informational tables). The HTML itself contains several buttons that efficiently facilitate interactive investigations into the data, when deeper checks are needed beyond the systematic images. The pages are linkable, so that users can evaluate individual items across a group, for increased sensitivity to differences (e.g., in alignment or regression modeling images). Finally, the QC document contains rating buttons for each "QC block," as well as comment fields for each, to facilitate both saving and sharing the evaluations. This increases the specificity of QC, as well as its shareability, as these files can be shared with others and potentially uploaded into repositories, promoting transparency and open science. We describe the features and applications of these QC tools for FMRI.

PyHySCO: GPU-enabled susceptibility artifact distortion correction in seconds

Over the past decade, reversed gradient polarity (RGP) methods have become a popular approach for correcting susceptibility artifacts in echo-planar imaging (EPI). Although several post-processing tools for RGP are available, their implementations do not fully leverage recent hardware, algorithmic, and computational advances, leading to correction times of several minutes per image volume. To enable 3D RGP correction in seconds, we introduce PyTorch Hyperelastic Susceptibility Correction (PyHySCO), a user-friendly EPI distortion correction tool implemented in PyTorch that enables multi-threading and efficient use of graphics processing units (GPUs). PyHySCO uses a time-tested physical distortion model and mathematical formulation and is, therefore, reliable without training. An algorithmic improvement in PyHySCO is its use of the one-dimensional distortion correction method by Chang and Fitzpatrick to initialize the non-linear optimization. PyHySCO is published under the GNU public license and can be used from the command line or its Python interface. Our extensive numerical validation using 3T and 7T data from the Human Connectome Project suggests that PyHySCO can achieve accuracy comparable to that of leading RGP tools at a fraction of the cost. We also validate the new initialization scheme, compare different optimization algorithms, and test the algorithm on different hardware and arithmetic precisions.

Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

Assessing the impact of distortion correction on Gamma Knife radiosurgery for multiple metastasis: Volumetric and dosimetric analysis

Introduction

Magnetic resonance imaging (MRI) is a robust neuroimaging technique and is the preferred method for stereotactic radiosurgery (SRS) planning. However, MRI data always contain distortions caused by hardware and patient factors.

Research question

Can these distortions potentially compromise the effectiveness and safety of SRS treatments?

Material and methods

Twenty-six MR datasets with multiple metastatic brain tumors (METs) used for Gamma Knife radiosurgery (GKRS) were retrospectively evaluated. A commercially available software was used for distortion correction. Geometrical agreement between corrected and uncorrected tumor volumes was evaluated using MacDonald criteria, Euclidian distance, and Dice similarity coefficient (DSC). SRS plans were generated using uncorrected tumor volumes, which were assessed to determine their coverage of the corrected tumor volumes.

Results

The median target volume was 0.38 cm3 (range,0.01-12.38 cm3). A maximum displacement of METs of up to 2.87 mm and a median displacement of 0.55 mm (range,0.1-2.87 mm) were noted. The median DSC between uncorrected and corrected MRI was 0.92, and the most concerning case had a DSC of 0.46. Although all plans met the optimization criterion of at least 98% of the uncorrected tumor volume (median 99.55%, range 98.1-100%) receiving at least 100% of the prescription dose, the percent of the corrected tumor volume receiving the total prescription dose was a median of 95.45% (range,23.1-99.5%).

Discussion and conclusion

MRI distortion, though visually subtle, has significant implications for SRS planning. Regular utilization of corrected MRI is recommended for SRS planning as distortion is sometimes enough to cause a volumetric miss of SRS targets.

Morphometric Analysis of the Eye by Magnetic Resonance Imaging in MGST2-Gene-Deficient Mice

Strabismus, a neuro-ophthalmological condition characterized by misalignment of the eyes, is a common ophthalmic disorder affecting both children and adults. In our previous study, we identified the microsomal glutathione S-transferase 2 (MGST2) gene as one of the potential candidates for comitant strabismus susceptibility in a Japanese population. The MGST2 gene belongs to the membrane-associated protein involved in the generation of pro-inflammatory mediators, and it is also found in the protection against oxidative stress by decreasing the reactivity of oxidized lipids. To look for the roles of the MGST2 gene in the development, eye alignment, and overall morphology of the eye as the possible background of strabismus, MGST2 gene knockout (KO) mice were generated by CRISPR/Cas9-mediated gene editing with guide RNAs targeting the MGST2 exon 2. The ocular morphology of the KO mice was analyzed through high-resolution images obtained by a magnetic resonance imaging (MRI) machine for small animals. The morphometric analyses showed that the height, width, and volume of the eyeballs in MGST2 KO homozygous mice were significantly greater than those of wild-type mice, indicating that the eyes of MGST2 KO homozygous mice were significantly enlarged. There were no significant differences in the axis length and axis angle. These morphological changes may potentially contribute to the development of a subgroup of strabismus.

FD-Net: An unsupervised deep forward-distortion model for susceptibility artifact correction in EPI

PURPOSE

To introduce an unsupervised deep-learning method for fast and effective correction of susceptibility artifacts in reversed phase-encode (PE) image pairs acquired with echo planar imaging (EPI).

METHODS

Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, neglecting consistency to the acquired EPI images. This work introduces a novel unsupervised deep Forward-Distortion Network (FD-Net) that predicts both the susceptibility-induced displacement field and the underlying anatomically correct image. Unlike previous methods, FD-Net enforces the forward-distortions of the correct image in both PE directions to be consistent with the acquired reversed-PE image pair. FD-Net further leverages a multiresolution architecture to maintain high local and global performance.

RESULTS

FD-Net performs competitively with a gold-standard reference method (TOPUP) in image quality, while enabling a leap in computational efficiency. Furthermore, FD-Net outperforms recent unwarping-based methods for unsupervised correction in terms of both image and field quality.

CONCLUSION

The unsupervised FD-Net method introduces a deep forward-distortion approach to enable fast, high-fidelity correction of susceptibility artifacts in EPI by maintaining consistency to measured data. Therefore, it holds great promise for improving the anatomical accuracy of EPI imaging.

The Quality Assurance of a 1.5 T MR-Linac

The recent introduction of a commercial 1.5 T MR-linac system has considerably improved the image quality of the patient acquired in the treatment unit as well as enabling online adaptive radiation therapy (oART) treatment strategies. Quality Assurance (QA) of this new technology requires new methodology that allows for the high field MR in a linac environment. The presence of the magnetic field requires special attention to the phantoms, detectors, and tools to perform QA. Due to the design of the system, the integrated megavoltage imager (MVI) is essential for radiation beam calibrations and QA. Additionally, the alignment between the MR image system and the radiation isocenter must be checked. The MR-linac system has vendor-supplied phantoms for calibration and QA tests. However, users have developed their own routine QA systems to independently check that the machine is performing as required, as to ensure we are able to deliver the intended dose with sufficient certainty. The aim of this work is therefore to review the MR-linac specific QA procedures reported in the literature.

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Hormonal contraceptive exposure relates to changes in resting state functional connectivity of anterior cingulate cortex and amygdala

Introduction

Hormonal contraceptives (HCs), nowadays one of the most used contraceptive methods, downregulate endogenous ovarian hormones, which have multiple plastic effects in the adult brain. HCs usually contain a synthetic estrogen, ethinyl-estradiol, and a synthetic progestin, which can be classified as androgenic or anti-androgenic, depending on their interaction with androgen receptors. Both the anterior cingulate cortex (ACC) and the amygdala express steroid receptors and have shown differential functionality depending on the hormonal status of the participant and the use of HC. In this work, we investigated for the first time the relationship between ACC and amygdala resting state functional connectivity (rs-FC) and HC use duration, while controlling for progestin androgenicity.

Methods

A total of 231 healthy young women participated in five different magnetic resonance imaging studies and were included in the final analysis. The relation between HC use duration and (i) gray matter volume, (ii) fractional amplitude of low-frequency fluctuations, and (iii) seed-based connectivity during resting state in the amygdalae and ACC was investigated in this large sample of women.

Results

In general, rs-FC of the amygdalae with frontal areas, and between the ACC and temporoparietal areas, decreased the longer the HC exposure and independently of the progestin's androgenicity. The type of HC's progestin did show a differential effect in the gray matter volume of left ACC and the connectivity between bilateral ACC and the right inferior frontal gyrus.

Mixed methodology in human brain research: integrating MRI and histology

Postmortem magnetic resonance imaging (MRI) can provide a bridge between histological observations and the in vivo anatomy of the human brain. Approaches aimed at the co-registration of data derived from the two techniques are gaining interest. Optimal integration of the two research fields requires detailed knowledge of the tissue property requirements for individual research techniques, as well as a detailed understanding of the consequences of tissue fixation steps on the imaging quality outcomes for both MRI and histology. Here, we provide an overview of existing studies that bridge between state-of-the-art imaging modalities, and discuss the background knowledge incorporated into the design, execution and interpretation of postmortem studies. A subset of the discussed challenges transfer to animal studies as well. This insight can contribute to furthering our understanding of the normal and diseased human brain, and to facilitate discussions between researchers from the individual disciplines.

Hormonal contraception & face processing: Examining face gender, androgenicity & treatment duration

Previous cross-sectional studies observed differences between users and non-users of combined oral contraceptives (COCs) in both the structure and function of the fusiform face area (FFA) related to face processing. For the present study 120 female participants performed high-resolution structural, as well as functional scans at rest, during face encoding and face recognition. Participants were either never-users of COCs (26), current first-time users of androgenic (29) or anti-androgenic COCs (23) or previous users of androgenic (21) or anti-androgenic COCs (21). Results suggest that associations between COC-use and face processing are modulated by androgenicity, but do not persist beyond the duration of COC use. The majority of findings concern the connectivity of the left FFA to the left supramarginal gyrus (SMG), which is a key region in cognitive empathy. While connectivity in anti-androgenic COC users differs from never users irrespective of the duration of COC use already at rest, connectivity in androgenic COC users decreases with longer duration of use during face recognition. Furthermore, longer duration of androgenic COC use was related to reduced identification accuracy, as well as increased connectivity of the left FFA to the right orbitofrontal cortex. Accordingly, the FFA and SMG emerge as promising ROIs for future randomized controlled trials on the effects of COC use on face processing.

Unsupervised cycle-consistent network using restricted subspace field map for removing susceptibility artifacts in EPI

PURPOSE

To design an unsupervised deep neural model for correcting susceptibility artifacts in single-shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications.

METHODS

This work proposes an unsupervised cycle-consistent model based on the restricted subspace field map to take advantage of both the deep learning (DL) and the reverse polarity-gradient (RPG) method for single-shot EPI. The proposed model consists of three main components: (1) DLRPG neural network (DLRPG-net) to obtain field maps based on a pair of images acquired with reversed phase encoding; (2) spin physical model-based modules to obtain the corrected undistorted images based on the learned field map; and (3) cycle-consistency loss between the input images and back-calculated images from each cycle is explored for network training. In addition, the field maps generated by DLRPG-net belong to a restricted subspace, which is a span of predefined cubic splines to ensure the smoothness of the field maps and avoid blurring in the corrected images. This new method is trained and validated on both preclinical and clinical datasets for diffusion MRI.

RESULTS

The proposed network could effectively generate smooth field maps and correct susceptibility artifacts in single-shot EPI. Simulated and in vivo preclinical/clinical experiments demonstrated that our method outperforms the state-of-the-art susceptibility artifact correction methods. Furthermore, the ablation experiments of the cycle-consistent network and the restricted subspace in generating field maps did show the advantages of DLRPG-net.

CONCLUSION

The proposed method (DLRPG-net) can effectively correct susceptibility artifacts for preclinical and clinical single-shot EPI sequences.

Superconducting magnet designs and MRI accessibility: A review

Presently, magnetic resonance imaging (MRI) magnets must deliver excellent magnetic field (B₀ ) uniformity to achieve optimum image quality. Long magnets can satisfy the homogeneity requirements but require considerable superconducting material. These designs result in large, heavy, and costly systems that aggravate as field strength increases. Furthermore, the tight temperature tolerance of niobium titanium magnets adds instability to the system and requires operation at liquid helium temperature. These issues are crucial factors in the disparity of MR density and field strength use across the globe. Low-income settings show reduced access to MRI, especially to high field strengths. This article summarizes the proposed modifications to MRI superconducting magnet design and their impact on accessibility, including compact, reduced liquid helium, and specialty systems. Reducing the amount of superconductor inevitably entails shrinking the magnet size, resulting in higher field inhomogeneity. This work also reviews the state-of-the-art imaging and reconstruction methods to overcome this issue. Finally, we summarize the current and future challenges and opportunities in the design of accessible MRI.

A Detailed Review on Synthesis, Functionalization, Application, Challenges, and Current Status of Magnetic Nanoparticles in the Field of Drug Delivery and Gene Delivery System

For progression of health care system, it has always been a challenge to the researchers for formulation to a type of advanced drug delivery system which will have less toxicity, targeted delivery and will be highly biodegradable. Nano science or nanotechnology has been validated to be a successful method as of targeting the drug to its active site be due to its special physicochemical properties and size thereby reducing the dose of administration, increasing bioavailability, and also reducing toxicity. Magnetic nanoparticles recently in few decades have proved as an effective advanced drug delivery system for its elevated magnetic responsiveness, biocompatibility, elevated targeted drug delivery effectiveness, etc. The drug can be easily targeted to active site by application of external magnetic field. Among the various elements, nanoparticles prepared with magnetically active iron oxide or other iron-based spinel oxide nanoparticles are widely used due to its high electrical resistivity, mechanical hardness, chemical stability, etc. Owing to their easy execution towards drug delivery application, extensive research has been carried out in this area. This review paper has summarized all recent modifications of iron-based magnetically active nanoparticle based drug delivery system along with their synthesis, characterization, and applications.

Slice-direction geometric distortion evaluation and correction with reversed slice-select gradient acquisitions

Accurate spatial alignment of MRI data acquired across multiple contrasts in the same subject is often crucial for data analysis and interpretation, but can be challenging in the presence of geometric distortions that differ between acquisitions. It is well known that single-shot echo-planar imaging (EPI) acquisitions suffer from distortion in the phase-encoding direction due to B₀ field inhomogeneities arising from tissue magnetic susceptibility differences and other sources, however there can be distortion in other encoding directions as well in the presence of strong field inhomogeneities. High-resolution ultrahigh-field MRI typically uses low bandwidth in the slice-encoding direction to acquire thin slices and, when combined with the pronounced B₀ inhomogeneities, is prone to an additional geometric distortion in the slice direction as well. Here we demonstrate the presence of this slice distortion in high-resolution 7T EPI acquired with a novel pulse sequence allowing for the reversal of the slice-encoding gradient polarity that enables the acquisition of pairs of images with equal magnitudes of distortion in the slice direction but with opposing polarities. We also show that the slice-direction distortion can be corrected using gradient reversal-based method applying the same software used for conventional corrections of phase-encoding direction distortion.

Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging

Multi-parametric quantitative magnetic resonance imaging (mqMRI) allows the characterization of multiple tissue properties non-invasively and has shown great potential to enhance the sensitivity of MRI measurements. However, real-time mqMRI during dynamic physiological processes or general motions remains challenging. To overcome this bottleneck, we propose a novel mqMRI technique based on multiple overlapping-echo detachment (MOLED) imaging, termed MQMOLED, to enable mqMRI in a single shot. In the data acquisition of MQMOLED, multiple MR echo signals with different multi-parametric weightings and phase modulations are generated and acquired in the same k-space. The k-space data is Fourier transformed and fed into a well-trained neural network for the reconstruction of multi-parametric maps. We demonstrated the accuracy and repeatability of MQMOLED in simultaneous mapping apparent proton density (APD) and any two parameters among T₂, T₂*, and apparent diffusion coefficient (ADC) in 130-170 ms. The abundant information delivered by the multiple overlapping-echo signals in MQMOLED makes the technique potentially robust to system imperfections, such as inhomogeneity of static magnetic field or radiofrequency field. Benefitting from the single-shot feature, MQMOLED exhibits a strong motion tolerance to the continuous movements of subjects. For the first time, it captured the synchronous changes of ADC, T₂, and T₁-weighted APD in contrast-enhanced perfusion imaging on patients with brain tumors, providing additional information about vascular density to the hemodynamic parametric maps. We expect that MQMOLED would promote the development of mqMRI technology and greatly benefit the applications of mqMRI, including therapeutics and analysis of metabolic/functional processes.

Associations between MRI-assessed locus coeruleus integrity and cortical gray matter microstructure

The locus coeruleus (LC) is one of the earliest sites of tau pathology, making it a key structure in early Alzheimer's disease (AD) progression. As the primary source of norepinephrine for the brain, reduced LC integrity may have negative consequences for brain health, yet macrostructural brain measures (e.g. cortical thickness) may not be sensitive to early stages of neurodegeneration. We therefore examined whether LC integrity was associated with differences in cortical gray matter microstructure among 435 men (mean age = 67.5; range = 62-71.7). LC structural integrity was indexed by contrast-to-noise ratio (LCCNR) from a neuromelanin-sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi-shell diffusion technique, was used to characterize cortical microstructure, modeling total diffusion in restricted, hindered, and free water compartments. Higher LCCNR (greater integrity) was associated with higher hindered and lower free water diffusion in multiple cortical regions. In contrast, no associations between LCCNR and cortical thickness survived correction. Results suggest lower LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cytoarchitectural barriers due to broader neurodegenerative processes. These findings highlight the potential utility for LC imaging and advanced diffusion measures of cortical microstructure in assessing brain health and early identification of neurodegenerative processes.

Geometric distortion assessment in 3T MR images used for treatment planning in cranial Stereotactic Radiosurgery and Radiotherapy

Magnetic Resonance images (MRIs) are employed in brain Stereotactic Radiosurgery and Radiotherapy (SRS/SRT) for target and/or critical organ localization and delineation. However, MRIs are inherently distorted, which also impacts the accuracy of the Magnetic Resonance Imaging/Computed Tomography (MRI/CT) co-registration process. In this phantom-based study, geometric distortion is assessed in 3T T2-weighted images (T2WIs), while the efficacy of an MRI distortion correction technique is also evaluated. A homogeneous polymer gel-filled phantom was CT-imaged before being irradiated with 26 4-mm Gamma Knife shots at predefined locations (reference control points). The irradiated phantom was MRI-scanned at 3T, implementing a T2-weighted protocol suitable for SRS/SRT treatment planning. The centers of mass of all shots were identified in the 3D image space by implementing an iterative localization algorithm and served as the evaluated control points for MRI distortion detection. MRIs and CT images were spatially co-registered using a mutual information algorithm. The inverse transformation matrix was applied to the reference control points and compared with the corresponding MRI-identified ones to evaluate the overall spatial accuracy of the MRI/CT dataset. The mean image distortion correction technique was implemented, and resulting MRI-corrected control points were compared against the corresponding reference ones. For the scanning parameters used, increased MRI distortion (>1mm) was detected at areas distant from the MRI isocenter (>5cm), while median radial distortion was 0.76mm. Detected offsets were slightly higher for the MRI/CT dataset (0.92mm median distortion). The mean image distortion correction improves geometric accuracy, but residual distortion cannot be considered negligible (0.51mm median distortion). For all three datasets studied, a statistically significant positive correlation between detected spatial offsets and their distance from the MRI isocenter was revealed. This work contributes towards the wider adoption of 3T imaging in SRS/SRT treatment planning. The presented methodology can be employed in commissioning and quality assurance programmes of corresponding treatment workflows.

Improvement of diffusion weighted MRI by practical B0 homogenization for head & neck cancer patients undergoing radiation therapy

BACKGROUND

MRI is a frequently used tool in radiation therapy planning. For MR-based tumor segmentation, diffusion weighted imaging plays a major role, which can fail due to excessive image artifacts for head and neck cancer imaging. Here, an easy-to-use setup is presented for imaging of head and neck cancer patients in a radiotherapy thermoplastic fixation mask.

METHODS

In a prospective head and neck cancer study, MRI data of 29 patients has been acquired at 3 different time points during radiation treatment. The data was analyzed with respect to Nyquist ghosting artifacts in the diffusion images in conventional single shot and readout segmented EPI sequences. For 9 patients, an improved setup with water bags for B₀ homogenization was used, and the impact on artifact frequency was analyzed. Additionally, volunteer measurements with B₀ fieldmaps are presented.

RESULTS

The placement of water bags to the sides of the head during MRI measurements significantly reduces artefacts in diffusion MRI. The number of artifact-free images in readout segmented EPI increased from 74% to 95% of the cases. Volunteer measurements showed a significant increase in B₀ homogeneity across slices (head foot direction) as well as within each slice.

CONCLUSIONS

The placement of water bags for B₀ homogenization is easy to implement, cost-efficient and does not impact patient comfort. Therefore, if very sophisticated soft- or hardware solutions are not present at a given site, or cannot be implemented due to restrictions from the thermoplastic mask, this is an excellent alternative to reduce artifacts in diffusion weighted imaging.

Patient specific distortion detection and mitigation in MR images used for stereotactic radiosurgery

Objective. In MRI-based radiation therapy planning, mitigating patient-specific distortion with standard high bandwidth scans can result in unnecessary sacrifices of signal to noise ratio. This study investigates a technique for distortion detection and mitigation on a patient specific basis. Approach. Fast B0 mapping was performed using a previously developed technique for high-resolution, large dynamic range field mapping without the need for phase unwrapping algorithms. A phantom study was performed to validate the method. Distortion mitigation was validated by reducing geometric distortion with increased acquisition bandwidth and confirmed by both the B0 mapping technique and manual measurements. Images and contours from 25 brain stereotactic radiosurgery patients and 95 targets were analyzed to estimate the range of geometric distortions expected in the brain and to estimate bandwidth required to keep all treatment targets within the ±0.5 mm iso-distortion contour. Main Results. The phantom study showed, at 3 T, the technique can measure distortions with a mean absolute error of 0.12 mm (0.18 ppm), and a maximum error of 0.37 mm (0.6 ppm). For image acquisition at 3 T and 1.0 mm resolution, mean absolute distortion under 0.5 mm in patients required bandwidths from 109 to 200 Hz px−1 for patients with the least and most distortion, respectively. Maximum absolute distortion under 0.5 mm required bandwidths from 120 to 390 Hz px−1. Significance. The method for B0 mapping was shown to be valid and may be applied to assess distortion clinically. Future work will adapt the readout bandwidth to prospectively mitigate distortion with the goal to improve radiosurgery treatment outcomes by reducing healthy tissue exposure.

Target localization accuracy in frame‐based stereotactic radiosurgery: Comparison between MR‐only and MR/CT co‐registration approaches

Purpose

In frame‐based Gamma Knife (GK) stereotactic radiosurgery two treatment planning workflows are commonly employed; one based solely on magnetic resonance (MR) images and the other based on magnetic resonance/computed tomography (MR/CT) co‐registered images. In both workflows, target localization accuracy (TLA) can be deteriorated due to MR‐related geometric distortions and/or MR/CT co‐registration uncertainties. In this study, the overall TLA following both clinical workflows is evaluated for cases of multiple brain metastases.

Methods

A polymer gel‐filled head phantom, having the Leksell stereotactic headframe attached, was CT‐imaged and irradiated by a GK Perfexion unit. A total of 26 4‐mm shots were delivered at 26 locations directly defined in the Leksell stereotactic space (LSS), inducing adequate contrast in corresponding T2‐weighted (T2w) MR images. Prescribed shot coordinates served as reference locations. An additional MR scan was acquired to implement the “mean image” distortion correction technique. The TLA for each workflow was assessed by comparing the radiation‐induced target locations, identified in MR images, with corresponding reference locations. Using T1w MR and CT images of 15 patients (totaling 81 lesions), TLA in clinical cases was similarly assessed, considering MR‐corrected data as reference. For the MR/CT workflow, both global and region of interest (ROI)‐based MR/CT registration approaches were studied.

Results

In phantom measurements, the MR‐corrected workflow demonstrated unsurpassed TLA (median offset of 0.2 mm) which deteriorated for MR‐only and MR/CT workflows (median offsets of 0.8 and 0.6 mm, respectively). In real‐patient cases, the MR‐only workflow resulted in offsets that exhibit a significant positive correlation with the distance from the MR isocenter, reaching 1.1 mm (median 0.6 mm). Comparable results were obtained for the MR/CT‐global workflow, although a maximum offset of 1.4 mm was detected. TLA was improved with the MR/CT‐ROI workflow resulting in median/maximum offsets of 0.4 mm/1.1 mm.

Conclusions

Subpixel TLA is achievable in all workflows. For the MR/CT workflow, a ROI‐based MR/CT co‐registration approach could considerably increase TLA and should be preferred instead of a global registration.

Dual k-space and image-space post-processing for field-cycling MRI under low magnetic field stability and homogeneity conditions

We present a method to correct artifacts typically present in images acquired in field-cycled MRI experiments under poor magnetic field spatial-homogeneity and time-stability conditions. The proposed method was tested in both simulated and experimental data. The experiments were performed using a fast field-cycling MRI relaxometer of own design, based on a current-driven variable-geometry electromagnet. Current instability-induced artifacts in the images were mitigated through a phase correction array resulted from entropy and background minimization. Image distortions due to magnetic field inhomogeneity were compensated through two different approaches, involving a previous determination of the magnetic field homogeneity-map, or an experimental protocol where two images are acquired with inverted readout gradient polarity. Results show that images acquired at extreme conditions can be successfully improved, thus strengthening the possibilities for both low-cost MRI devices and faster field-switched MRI systems.

Manifold-based respiratory phase estimation enables motion and distortion correction of free-breathing cardiac diffusion tensor MRI

PURPOSE

For in vivo cardiac DTI, breathing motion and B₀ field inhomogeneities produce misalignment and geometric distortion in diffusion-weighted (DW) images acquired with conventional single-shot EPI. We propose using a dimensionality reduction method to retrospectively estimate the respiratory phase of DW images and facilitate both distortion correction (DisCo) and motion compensation.

METHODS

Free-breathing electrocardiogram-triggered whole left-ventricular cardiac DTI using a second-order motion-compensated spin echo EPI sequence and alternating directionality of phase encoding blips was performed on 11 healthy volunteers. The respiratory phase of each DW image was estimated after projecting the DW images into a 2D space with Laplacian eigenmaps. DisCo and motion compensation were applied to the respiratory sorted DW images. The results were compared against conventional breath-held T₂ half-Fourier single shot turbo spin echo. Cardiac DTI parameters including fractional anisotropy, mean diffusivity, and helix angle transmurality were compared with and without DisCo.

RESULTS

The left-ventricular geometries after DisCo and motion compensation resulted in significantly improved alignment of DW images with T₂ reference. DisCo reduced the distance between the left-ventricular contours by 13.2% ± 19.2%, P < .05 (2.0 ± 0.4 for DisCo and 2.4 ± 0.5 mm for uncorrected). DisCo DTI parameter maps yielded no significant differences (mean diffusivity: 1.55 ± 0.13 × 10^-3 mm² /s and 1.53 ± 0.13 × 10^-3 mm² /s, P = .09; fractional anisotropy: 0.375 ± 0.041 and 0.379 ± 0.045, P = .11; helix angle transmurality: 1.00% ± 0.10°/% and 0.99% ± 0.12°/%, P = .44), although the orientation of individual tensors differed.

CONCLUSION

Retrospective respiratory phase estimation with LE-based DisCo and motion compensation in free-breathing cardiac DTI resulting in significantly reduced geometric distortion and improved alignment within and across slices.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Functional Activities Detected in the Olfactory Bulb and Associated Olfactory Regions in the Human Brain Using T2-Prepared BOLD Functional MRI at 7T

Olfaction is a fundamental sense that plays a vital role in daily life in humans, and can be altered in neuropsychiatric and neurodegenerative diseases. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) using conventional echo-planar-imaging (EPI) based sequences can be challenging in brain regions important for olfactory processing, such as the olfactory bulb (OB) and orbitofrontal cortex, mainly due to the signal dropout and distortion artifacts caused by large susceptibility effects from the sinonasal cavity and temporal bone. To date, few studies have demonstrated successful fMRI in the OB in humans. T2-prepared (T2prep) BOLD fMRI is an alternative approach developed especially for performing fMRI in regions affected by large susceptibility artifacts. The purpose of this technical study is to evaluate T2prep BOLD fMRI for olfactory functional experiments in humans. Olfactory fMRI scans were performed on 7T in 14 healthy participants. T2prep BOLD showed greater sensitivity than GRE EPI BOLD in the OB, orbitofrontal cortex and the temporal pole. Functional activation was detected using T2prep BOLD in the OB and associated olfactory regions. Habituation effects and a bi-phasic pattern of fMRI signal changes during olfactory stimulation were observed in all regions. Both positively and negatively activated regions were observed during olfactory stimulation. These signal characteristics are generally consistent with literature and showed a good intra-subject reproducibility comparable to previous human BOLD fMRI studies. In conclusion, the methodology demonstrated in this study holds promise for future olfactory fMRI studies in the OB and other brain regions that suffer from large susceptibility artifacts.

Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data

Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.

12-year prediction of mild cognitive impairment aided by Alzheimer's brain signatures at mean age 56

Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer's disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Towards that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: (i) a validated MRI-derived Alzheimer's disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and (ii) a novel grey matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246-367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51-60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer's disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61-71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply ageing-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P = 0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step towards improving very early identification of Alzheimer's disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.

Improving distortion correction for isotropic high-resolution 3D diffusion MRI by optimizing Jacobian modulation

PURPOSE

To improve distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI when in a time-saving acquisition scenario.

THEORY AND METHODS

Data were acquired using simultaneous multi-slab (SMSlab) acquisitions, with a b = 0 image pair encoded by reversed polarity gradients (RPG) for phase encoding (PE) and diffusion weighted images encoded by a single PE direction. Eddy current-induced distortions were corrected first. During the following susceptibility distortion correction, image deformation was first corrected by the field map estimated from the b = 0 image pair. Intensity variation was subsequently corrected by Jacobian modulation. Two Jacobian modulation methods were compared. They calculated the Jacobian modulation map from the field map, or from the deformation corrected b = 0 image pair, termed as J_Field and J_RPG , respectively. A modified version of the J_RPG method, with proper smoothing, was further proposed for improved correction performance, termed as J_RPG-smooth .

RESULTS

Compared to J_Field modulation, less remaining distortions are observed when using the J_RPG and J_RPG-smooth methods, especially in areas with large B0 field inhomogeneity. The original J_RPG method causes signal-to-noise ratio (SNR) deficiency problem, which manifests as degraded SNR of the diffusion weighted images, while the J_RPG-smooth method maintains the original image SNR. Less estimation errors of diffusion metrics are observed when using the J_RPG-smooth method.

CONCLUSION

This study improves the distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI by optimizing Jacobian modulation. The optimized method outperforms the conventional J_Field method regarding intensity variation correction and accuracy of diffusion metrics estimation, and outperforms the original J_RPG method regarding SNR performance.

Improved reproducibility of diffusion MRI of the human brain with a four-way blip-up and down phase-encoding acquisition approach

PURPOSE

To assess the effects of blip-up and -down echo planar imaging (EPI) acquisition designs, with different choices of phase-encoding directions (PEDs) on the reproducibility of diffusion MRI (dMRI)-derived metrics in the human brain.

METHODS

Diffusion MRI data in seven subjects were acquired five times, each with five different protocols. The base design included 64 diffusion directions acquired with anterior-posterior (AP) PED, the first and second protocols added reverse phase-encoded b = 0 s / mm 2 posterior-anterior (PA) PED images. The third one included 32 directions all with PED acquisitions with opposite polarity (AP and PA). The fourth protocol, also with 32 unique directions used four PEDs (AP, PA, right-left (RL), and left-right (LR)). The scan time was virtually identical for all protocols. The variability of diffusion MRI metrics for each subject and each protocol was computed across the different sessions.

RESULTS

The highest reproducibility for all dMRI metrics was obtained with protocol four (AP/PA-RL/LR, ie, four-way PED). Protocols that used only b = 0 s / mm 2 for distortion correction, which are the most widely used designs, had the lowest reproducibility.

CONCLUSIONS

An acquisition design with four PEDs, including all DWIs in addition to b = 0 s / mm 2 images should be used to achieve high reproducibility in diffusion MRI studies.

Dual polarity encoded MRI using high bandwidth radiofrequency pulses for robust imaging with large field inhomogeneity

PURPOSE

The ability to use dual polarity encoded MRI with the missing pulse steady-state free precession (MP-SSFP) sequence is demonstrated to perform robust MRI with low radiofrequency (RF) amplitude, where the field is distorted by embedding metallic screws in an agar phantom. Image-based estimation of the 3D ΔB₀ map and image distortion correction is shown to require ~1 minute to perform.

THEORY AND METHODS

Dual polarity encoded MP-SSFP was implemented at 1.5T and used to image agar phantoms with one stainless steel and one titanium screw embedded inside. A multispectral fast spin-echo acquisition was performed for comparison. Self-consistent ΔB₀ estimation is performed iteratively using a 3D B-spline basis, which is compared to the ΔB₀ estimate generated by the multispectral sequence.

RESULTS

Dual polarity encoded MP-SSFP yields image quality similar to the multispectral sequence used with substantially less imaging time, provided the MP-SSFP experimental parameters are chosen well. The multispectral sequence appears to visualize modestly closer in proximity to the metallic screws used, despite the spectral bins covering the same bandwidth as the pulses used in MP-SSFP. However, MP-SSFP avoids ripple artifacts characteristic of the multispectral sequence. The ΔB₀ estimate generated by MP-SSFP is qualitatively similar to that generated by the multispectral sequence but larger in magnitude.

CONCLUSION

Despite longer processing time compared to multispectral imaging, MP-SSFP yields similar image quality with significantly lower acquisition times in the absence of parallel imaging. The work herein demonstrates the ability to perform 3D ΔB₀ estimation and image correction within a reasonable amount of time, ~1 minute.

Correcting Susceptibility Artifacts of MRI Sensors in Brain Scanning: A 3D Anatomy-Guided Deep Learning Approach

Echo planar imaging (EPI), a fast magnetic resonance imaging technique, is a powerful tool in functional neuroimaging studies. However, susceptibility artifacts, which cause misinterpretations of brain functions, are unavoidable distortions in EPI. This paper proposes an end-to-end deep learning framework, named TS-Net, for susceptibility artifact correction (SAC) in a pair of 3D EPI images with reversed phase-encoding directions. The proposed TS-Net comprises a deep convolutional network to predict a displacement field in three dimensions to overcome the limitation of existing methods, which only estimate the displacement field along the dominant-distortion direction. In the training phase, anatomical T1-weighted images are leveraged to regularize the correction, but they are not required during the inference phase to make TS-Net more flexible for general use. The experimental results show that TS-Net achieves favorable accuracy and speed trade-off when compared with the state-of-the-art SAC methods, i.e., TOPUP, TISAC, and S-Net. The fast inference speed (less than a second) of TS-Net makes real-time SAC during EPI image acquisition feasible and accelerates the medical image-processing pipelines.

IPEM topical report: guidance on the use of MRI for external beam radiotherapy treatment planning. Phys Med Biol 2021;66:055025. [PMID: 33450742 DOI: 10.1088/1361-6560/abdc30]

This document gives guidance for multidisciplinary teams within institutions setting up and using an MRI-guided radiotherapy (RT) treatment planning service. It has been written by a multidisciplinary working group from the Institute of Physics and Engineering in Medicine (IPEM). Guidance has come from the experience of the institutions represented in the IPEM working group, in consultation with other institutions, and where appropriate references are given for any relevant legislation, other guidance documentation and information in the literature. Guidance is only given for MRI acquired for external beam RT treatment planning in a CT-based workflow, i.e. when MRI is acquired and registered to CT with the purpose of aiding delineation of target or organ at risk volumes. MRI use for treatment response assessment, MRI-only RT and other RT treatment types such as brachytherapy and gamma radiosurgery are not considered within the scope of this document. The aim was to produce guidance that will be useful for institutions who are setting up and using a dedicated MR scanner for RT (referred to as an MR-sim) and those who will have limited time on an MR scanner potentially managed outside of the RT department, often by radiology. Although not specifically covered in this document, there is an increase in the use of hybrid MRI-linac systems worldwide and brief comments are included to highlight any crossover with the early implementation of this technology. In this document, advice is given on introducing a RT workload onto a non-RT-dedicated MR scanner, as well as planning for installation of an MR scanner dedicated for RT. Next, practical guidance is given on the following, in the context of RT planning: training and education for all staff working in and around an MR scanner; RT patient set-up on an MR scanner; MRI sequence optimisation for RT purposes; commissioning and quality assurance (QA) to be performed on an MR scanner; and MRI to CT registration, including commissioning and QA.

Registration of magnetic resonance and computed tomography images in patients with oral squamous cell carcinoma for three-dimensional virtual planning of mandibular resection and reconstruction

The aim of this study was to evaluate and present an automated method for registration of magnetic resonance imaging (MRI) and computed tomography (CT) or cone beam CT (CBCT) images of the mandibular region for patients with oral squamous cell carcinoma (OSCC). Registered MRI and (CB)CT could facilitate the three-dimensional virtual planning of surgical guides employed for resection and reconstruction in patients with OSCC with mandibular invasion. MRI and (CB)CT images were collected retrospectively from 19 patients. MRI images were aligned with (CB)CT images employing a rigid registration approach (stage 1), a rigid registration approach using a mandibular mask (stage 2), and two non-rigid registration approaches (stage 3). Registration accuracy was quantified by the mean target registration error (mTRE), calculated over a set of landmarks annotated by two observers. Stage 2 achieved the best registration result, with an mTRE of 2.5±0.7mm, which was comparable to the inter- and intra-observer variabilities of landmark placement in MRI. Stage 2 was significantly better aligned compared to all approaches in stage 3. In conclusion, this study demonstrated that rigid registration with the use of a mask is an appropriate image registration method for aligning MRI and (CB)CT images of the mandibular region in patients with OSCC.

Evaluation of eddy current distortion and field inhomogeneity distortion corrections in MR diffusion imaging using log-demons DIR method

To investigate the feasibility of the log-demons deformable image registration (DIR) method to correct eddy current and field inhomogeneity distortions while preserving diffusion tensor information. Diffusion-weighted images (DWIs) are susceptible to distortions caused by eddy current and echo-planar imaging (EPI) gradients. We propose a post-acquisition correction algorithm using the log-demons DIR technique for eddy current and field inhomogeneity distortions of DWI. The new correction technique was applied to DWI acquired using a diffusion phantom and the multiple acquisitions for standardization of structural imaging validation and evaluation (MASSIVE) brain database. This method is compared to previous methods using cross-correlation, mutual information (MI). In the phantom study, the log-demons algorithm reduced eddy current and field inhomogeneity distortions while preserving diffusion tensor information when compared to affine and demon's registration techniques. Analysis of the tensor metrics using percent difference and the root mean square of the apparent diffusion coefficient and fractional anisotropy found that the log-demons algorithm outperforms the other algorithms in terms of preserving diffusion information. In the MASSIVE study, the average MI of all slices increased for both eddy current and field inhomogeneity distortion correction. The average absolute differences of all slices between corrected images with opposing gradients were also on average decreased. This work indicates that the log-demons DIR algorithm is feasible to reduce eddy current and field inhomogeneity distortions while preserving quantitative diffusion information.

Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery

•

45 data sets (18 on a 1.5 T MR and 27 on a 3 T MR) were evaluated for susceptibility induced distortions.

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Maximum distortions of up to 1.7 mm were found for organs at risk in standard diagnostic settings.

•

Median distortions ranged between 0.1 and 0.2 mm for all organs at risk.

•

Active shimming was estimated to reduce distortions by a factor of 2.3 to 2.9.

•

A safety margin of 1 mm would have encompassed 99.8% of the distortions.

Background and purpose

Magnetic resonance imaging (MRI) is a crucial factor in optimal treatment planning for stereotactic radiosurgery. To further the awareness of possible errors in MRI, this work aimed to investigate the magnitude of susceptibility induced MRI distortions for intracranial organs at risk (OARs) and test the effectiveness of actively shimming these distortions.

Materials and methods

Distortion maps for 45 exams of 42 patients (18 on a 1.5 T MRI scanner, 27 on a 3 T MRI scanner) were calculated based on a high-bandwidth double-echo gradient echo sequence. The investigated OARs were brainstem, chiasm, eyes, and optic nerves. The influence of active shimming was investigated by comparing unshimmed 1.5 T data with shimmed 3 T data and comparing the results to a model based prediction.

Results

The median distortion for the different OARs was found to be between 0.13 and 0.18 mm for 1.5 T and between 0.11 and 0.13 mm for 3 T. The maximum distortion was found to be between 1.3 and 1.7 mm for 1.5 T and between 1.1 and 1.4 mm for 3 T. The variation of values was much higher for 1.5 T than for 3 T across all investigated OARs. Active shimming was found to reduce distortions by a factor of 2.3 to 2.9 compared to the expected values.

Conclusions

Using a safety margin for OARs of 1 mm would have encompassed 99.8% of the distortions. Since distortions are inversely proportional to the readout bandwidth, they can be further reduced by increasing the bandwidth. Additional error sources like gradient nonlinearities need to be addressed separately.

Whole brain dynamics during optogenetic self-stimulation of the medial prefrontal cortex in mice

Intracranial self-stimulation, in which an animal performs an operant response to receive regional brain electrical stimulation, is a widely used procedure to study motivated behavior. While local neuronal activity has long been measured immediately before or after the operant, imaging the whole brain in real-time remains a challenge. Herein we report a method that permits functional MRI (fMRI) of brain dynamics while mice are cued to perform an operant task: licking a spout to receive optogenetic stimulation to the medial prefrontal cortex (MPFC) during a cue ON, but not cue OFF. Licking during cue ON results in activation of a widely distributed network consistent with underlying MPFC projections, while licking during cue OFF (without optogenetic stimulation) leads to negative fMRI signal in brain regions involved in acute extinction. Noninvasive whole brain readout combined with circuit-specific neuromodulation opens an avenue for investigating adaptive behavior in both healthy and disease models.

A phantom based laser marking workflow to visually assess geometric image distortion in magnetic resonance guided radiotherapy

Magnetic resonance (MR)-only workflows require quality assurance due to potential dosimetric impacts of using geometry distorted MR images in radiotherapy planning. MR-visible silicone-based fiducials were arranged in regular 3D structures to cover extended imaging volumes. The scanner’s patient marking workflow with a 2-axes movable laser bridge allowed to visually check geometric distortions of each MR reconstructed fiducial against its true position in 3D space. A measurement resolution and uncertainty of the order of 0.5 mm in sagittal and coronal, and 1 mm in transversal direction was found. The proposed workflow required 1 min of evaluation time per fiducial position, and a 9 min 3D MR volume acquisition.

Retrospective Distortion and Motion Correction for Free-Breathing DW-MRI of the Kidneys Using Dual-Echo EPI and Slice-to-Volume Registration

BACKGROUND

Diffusion-weighted MRI (DW-MRI) of the kidneys is a technique that provides information about the microstructure of renal tissue without requiring exogenous contrasts such as gadolinium, and it can be used for diagnosis in cases of renal disease and assessing response-to-therapy. However, physiological motion and large geometric distortions due to main B₀ field inhomogeneities degrade the image quality, reduce the accuracy of quantitative imaging markers, and impede their subsequent clinical applicability.

PURPOSE

To retrospectively correct for geometric distortion for free-breathing DW-MRI of the kidneys at 3T, in the presence of a nonstatic distortion field due to breathing and bulk motion.

STUDY TYPE

Prospective.

SUBJECTS

Ten healthy volunteers (ages 29-38, four females).

FIELD STRENGTH/SEQUENCE

3T; DW-MR dual-echo echo-planar imaging (EPI) sequence (10 b-values and 17 directions) and a T₂ volume.

ASSESSMENT

The distortion correction was evaluated subjectively (Likert scale 0-5) and numerically with cross-correlation between the DW images at b = 0 s/mm² and a T₂ volume. The intravoxel incoherent motion (IVIM) and diffusion tensor (DTI) model-fitting performance was evaluated using the root-mean-squared error (nRMSE) and the coefficient of variation (CV%) of their parameters.

STATISTICAL TESTS

Statistical comparisons were done using Wilcoxon tests.

RESULTS

The proposed method improved the Likert scores by 1.1 ± 0.8 (P < 0.05), the cross-correlation with the T₂ reference image by 0.13 ± 0.05 (P < 0.05), and reduced the nRMSE by 0.13 ± 0.03 (P < 0.05) and 0.23 ± 0.06 (P < 0.05) for IVIM and DTI, respectively. The CV% of the IVIM parameters (slow and fast diffusion, and diffusion fraction for IVIM and mean diffusivity, and fractional anisotropy for DTI) was reduced by 2.26 ± 3.98% (P = 6.971 × 10^-2 ), 11.24 ± 26.26% (P = 6.971 × 10^-2 ), 4.12 ± 12.91% (P = 0.101), 3.22 ± 0.55% (P < 0.05), and 2.42 ± 1.15% (P < 0.05).

DATA CONCLUSION

The results indicate that the proposed Di + MoCo method can effectively correct for time-varying geometric distortions and for misalignments due to breathing motion. Consequently, the image quality and precision of the DW-MRI model parameters improved.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 1.

Comparison and evaluation of distortion correction techniques on an MR-guided radiotherapy system

PURPOSE

To evaluate two distortion correction techniques for diffusion-weighted single-shot echo-planar imaging (DW-ssEPI) on a 0.35 T magnetic resonance-guided radiotherapy (MRgRT) system.

METHODS

The effects of sequence optimization through enabling parallel imaging (PI) and selecting appropriate bandwidth on spatial distortion were first evaluated on the 0.35 T MRgRT system using a spatial integrity phantom. Field map (FM) and reversed gradient (RG) corrections were then performed on the optimized protocol to further reduce distortion. An open-source toolbox was used to quantify the spatial displacement before and after distortion correction. To evaluate ADC accuracy and repeatability of the optimized protocol, as well as impacts of distortion correction on ADC values, the optimized protocol was scanned twice on a diffusion phantom. The calculated ADC values were compared with reference ADCs using paired t-test. Intraclass correlation coefficient (ICC) between the two repetitions, as well as between before and after FM/RG correction was calculated to evaluate ADC repeatability and effects of distortion correction. Six patients were recruited to assess the in-vivo performance. The optimal distortion correction technique was identified by visual assessment. To quantify distortion reduction, tumor and critical structures were contoured on the turbo spin echo (TSE) image (reference image), the DW-ssEPI image, and the distortion corrected images independently by two radiation oncologists. Mean distance to agreement (MDA) and DICE coefficient between contours on the reference images and the diffusion images were calculated. Tumor apparent diffusion coefficient (ADC) values from the original DW-ssEPI images and the distortion corrected images were compared using Bland-Altman analysis.

RESULTS

Sequence optimization played a vital role in improving the spatial integrity, and spatial distortion was proportional to the total readout time. Before the correction, distortion of the optimized protocol (PI and high bandwidth) was 1.50 ± 0.89 mm in a 100 mm radius and 2.21 ± 1.39 mm in a 175 mm radius for the central plane. FM corrections reduced the distortions to 0.42 ± 0.27 mm and 0.67 ± 0.49 mm respectively, and RG reduced distortion to 0.40 ± 0.22 mm and 0.64 ± 0.47 mm, respectively. The optimized protocol provided accurate and repeatable ADC quantification on the diffusion phantom. The calculated ADC values were consistent before and after FM/RG correction. For the patient study, the FM correction was unable to reduce chemical shift artifacts whereas the RG method successfully mitigated the chemical shift. MDA reduced from 2.52 ± 1.29 mm to 1.11 ± 0.72 mm after the RG correction. The DICE coefficient increased from 0.80 ± 0.13 to 0.91 ± 0.06. A Bland-Altman plot showed that there was a good agreement between ADC measurements before and after application of the RG correction.

CONCLUSION

Two distortion correction techniques were evaluated on a commercial low-field MRgRT system. Overall, the RG correction was able to drastically improve spatial distortion and preserve ADC accuracy.

Evaluation of patient-specific MR distortion correction schemes for improved target localization accuracy in SRS

PURPOSE

This work aims at promoting target localization accuracy in cranial stereotactic radiosurgery (SRS) applications by focusing on the correction of sequence-dependent (also patient induced) magnetic resonance (MR) distortions at the lesion locations. A phantom-based quality assurance (QA) methodology was developed and implemented for the evaluation of three distortion correction techniques. The same approach was also adapted to cranial MR images used for SRS treatment planning purposes in single or multiple brain metastases cases.

METHODS

A three-dimensional (3D)-printed head phantom was filled with a 3D polymer gel dosimeter. Following treatment planning and dose delivery, volumes of radiation-induced polymerization served as hypothetical lesions, offering adequate MR contrast with respect to the surrounding unirradiated areas. T1-weighted (T1w) MR imaging was performed at 1.5 T using the clinical scanning protocol for SRS. Additional images were acquired to implement three distortion correction methods; the field mapping (FM), mean image (MI) and signal integration (SI) techniques. Reference lesion locations were calculated as the averaged centroid positions of each target identified in the forward and reverse read gradient polarity MRI scans. The same techniques and workflows were implemented for the correction of contrast-enhanced T1w MR images of 10 patients with a total of 27 brain metastases.

RESULTS

All methods employed in the phantom study diminished spatial distortion. Median and maximum distortion magnitude decreased from 0.7 mm (2.10 ppm) and 0.8 mm (2.36 ppm), respectively, to <0.2 mm (0.61 ppm) at all target locations, using any of the three techniques. Image quality of the corrected images was acceptable, while contrast-to-noise ratio slightly increased. Results of the patient study were in accordance with the findings of the phantom study. Residual distortion in corrected patient images was found to be <0.3 mm in the vast majority of targets. Overall, the MI approach appears to be the most efficient correction method from the three investigated.

CONCLUSIONS

In cranial SRS applications, patient-specific distortion correction at the target location(s) is feasible and effective, despite the expense of longer imaging time since additional MRI scan(s) need to be performed. A phantom-based QA methodology was developed and presented to reassure efficient implementation of correction techniques for sequence-dependent spatial distortion.

Deconvolution-based distortion correction of EPI using analytic single-voxel point-spread functions

PURPOSE

To develop a postprocessing algorithm that corrects geometric distortions due to spatial variations of the static magnetic field amplitude, B₀ , and effects from relaxation during signal acquisition in EPI.

THEORY AND METHODS

An analytic, complex point-spread function is deduced for k-space trajectories of EPI variants and applied to corresponding acquisitions in a resolution phantom and in human volunteers at 3 T. With the analytic point-spread function and experimental maps of B₀ (and, optionally, the effective transverse relaxation time, T 2 * ) as input, a point-spread function matrix operator is devised for distortion correction by a Thikonov-regularized deconvolution in image space. The point-spread function operator provides additional information for an appropriate correction of the signal intensity distribution. A previous image combination algorithm for acquisitions with opposite phase blip polarities is adapted to the proposed method to recover destructively interfering signal contributions.

RESULTS

Applications of the proposed deconvolution-based distortion correction ("DecoDisCo") algorithm demonstrate excellent distortion corrections and superior performance regarding the recovery of an undistorted intensity distribution in comparison to a multifrequency reconstruction. Examples include full and partial Fourier standard EPI scans as well as double-shot center-out trajectories. Compared with other distortion-correction approaches, DecoDisCo permits additional deblurring to obtain sharper images in cases of significant T 2 * effects.

CONCLUSION

Robust distortion corrections in EPI acquisitions are feasible with high quality by regularized deconvolution with an analytic point-spread function. The general algorithm, which is publicly released on GitHub, can be straightforwardly adapted for specific EPI variants or other acquisition schemes.

Contemporary approaches to high-field magnetic resonance imaging with large field inhomogeneity

Despite its importance as a clinical imaging modality, magnetic resonance imaging remains inaccessible to most of the world's population due to its high cost and infrastructure requirements. Substantial effort is underway to develop portable, low-cost systems able to address MRI access inequality and to enable new uses of MRI such as bedside imaging. A key barrier to development of portable MRI systems is increased magnetic field inhomogeneity when using small polarizing magnets, which degrades image quality through distortions and signal dropout. Many approaches address field inhomogeneity by using a low polarizing field, approximately ten to hundreds of milli-Tesla. At low-field, even a large relative field inhomogeneity of several thousand parts-per-million (ppm) results in resonance frequency dispersion of only 1-2 kHz. Under these conditions, with necessarily wide pulse bandwidths, fast spin-echo sequences may be used at low field with negligible subject heating, and a broad range of other available imaging sequences can be implemented. However, high-field MRI, 1.5 T or greater, can provide substantially improved signal-to-noise ratio and image contrast, so that higher spatial resolution, clinical quality images may be acquired in significantly less time than is necessary at low-field. The challenge posed by small, high-field systems is that the relative field inhomogeneity, still thousands of ppm, becomes tens of kilohertz over the imaging volume. This article describes the physical consequences of field inhomogeneity on established gradient- and spin-echo MRI sequences, and suggests ways to reduce signal dropout and image distortion from field inhomogeneity. Finally, the practicality of currently available image contrasts is reviewed when imaging with a high magnetic field with large inhomogeneity.

Development and validation of 3D MP-SSFP to enable MRI in inhomogeneous magnetic fields

PURPOSE

We demonstrate the feasibility of MRI with missing-pulse steady-state free precession (MP-SSFP) in a 4T magnet with artificially degraded homogeneity.

METHODS

T₁ , T₂ , and diffusion contrast of MP-SSFP was simulated with constant and alternate radiofrequency (RF) phase using an extended phase graph. To validate MP-SSFP performance in human brain imaging, MP-SSFP was tested with two types of artificially introduced inhomogeneous magnetic fields: (1) a pure linear gradient field, and (2) a pseudo-linear gradient field introduced by mounting a head-gradient set at 36 cm from the magnet isocenter. Image distortion induced by the nonlinear inhomogeneous field was corrected using B₀ mapping measured with MP-SSFP.

RESULTS

The maximum flip angle in MP-SSFP was limited to ≤10° because of the large range of resonance frequencies in the inhomogeneous magnetic fields tested in this study. Under this flip-angle limitation, MP-SSFP with constant RF phase provided advantages of higher signal-to-noise ratio and insensitivity to B₁ ⁺ field inhomogeneity as compared with an alternate RF phase. In diffusion simulation, the steady-state magnetization in constant RF phase MP-SSFP increased with an increase of static field gradient up to 8 to 21 mT/m depending on simulation parameters. Experimental results at 4T validated these findings. In human brain imaging, MP-SSFP preserved sufficient signal intensities, but images showed severe image distortion from the pseudo-linear inhomogeneous field. However, following distortion correction, good-quality brain images were achieved.

CONCLUSION

MP-SSFP appears to be a feasible MRI technique for brain imaging in an inhomogeneous magnetic field.