High-field Imaging Research Articles

Analysis of wood anatomy via high-resolution micro-MRI and micro-CT: first approaches and results from Pozzo di Bellafonte (Montaione, Florence, Italy)

Several artefacts were found during the excavation performed at “Pozzo di Bellafonte”, located in an archaeological area in the province of Florence (Italy). The material found in the archaeological site included a large amount of wood samples; therefore, a method for understanding the positioning, the shape and the orientation of the wood sample vessels was necessary for identification of botanical taxa. In recent years, the study of ancient remains has benefited greatly from the use of imaging techniques commonly used for medical diagnosis and biomedical research, such as the micro-Computed Tomography (micro-CT) and high-field micro-Magnetic Resonance Imaging (micro-MRI). In this paper such imaging methodologies were employed for assessing the internal structure of representative wood samples extracted from the above mentioned. The complementarity of micro-CT and micro-MRI for the investigation of wood specimen anatomy is also discussed, by underlining what micro-MRI provides as compared with micro-CT and by proposing a tool constituted by the combination of micro-CT/micro-MRI for the study of such wood samples in a multimodal approach.

Recovering MRI magnetic field strength properties using machine learning based on image compression quality scores

AbstractOver the years, significant hardware advancements have led to higher magnetic field MRI (Magnetic Resonance Imaging) acquisitions, providing improved diagnostic image quality at a higher cost. While higher image quality is desired, the investment required for high-field MRI imaging systems remains a significant consideration. Furthermore, historical patient records may still contain low-field magnetic strength MRI data. In this work, we present how image compression quality scores of MRI images could be used to recover their magnetic field strength properties. This work presents an interesting inverse problem scenario where output properties are used to recover an input property of an image. We implemented supervised machine learning models that utilize compressed image quality scores - based on Mean Squared Error (MSE), Structural Similarity Index (SSIM), Visual Information Fidelity (VIF), and Earth Movers Distance (EM) metrics - as inputs. These models classify images into specific classes of magnetic field strength at which they were acquired (Low, Medium, and High) based solely on the quality scores of their compressed copies. The trained machine learning models (Support Vector Machine (SVM), Logistic Regression, K-nearest Neighbours (KNN), Decision Tree and Random Forest) achieved nearly 100% performance efficiency based on accuracy and F-1 score for all considered quality measures. This comprehensive evaluation offers insights into how compression techniques and quality factors impact image fidelity across various MRI magnetic field strengths. The findings of this study may prove valuable in recovering missing meta-tag information in historical image DICOM records and Context-Based Retrieval Systems (CBRS). The approach of using quality scores as features in training machine learning models, as demonstrated in this work, can be extended to other image groups where input parameters create statistically significant distinctions or are challenging to extract from images.

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression.

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders. In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects. Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively. To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Initial findings using high-resolution magnetic resonance imaging for visualisation of the sural nerve and surrounding anatomy in healthy volunteers at 7 Tesla.

Histopathological diagnosis is the gold standard in many acquired inflammatory, infiltrative and amyloid based peripheral nerve diseases and a sensory nerve biopsy of sural or superficial peroneal nerve is favoured where a biopsy is deemed necessary. The ability to determine nerve pathology by high-resolution imaging techniques resolving anatomy and imaging characteristics might improve diagnosis and obviate the need for biopsy in some. The sural nerve is anatomically variable and occasionally adjacent vessels can be sent for analysis in error. Knowing the exact position and relationships of the nerve prior to surgery could be clinically useful and thus reliably resolving nerve position has some utility. 7T images of eight healthy volunteers' (HV) right ankle were acquired in a pilot study using a double-echo in steady-state sequence for high-resolution anatomy images. Magnetic Transfer Ratio images were acquired of the same area. Systematic scoring of the sural, tibial and deep peroneal nerve around the surgical landmark 7 cm from the lateral malleolus was performed (number of fascicles, area in voxels and mm2, diameter and location relative to nearby vessels and muscles). The sural and tibial nerves were visualised in the high-resolution double-echo in steady-state (DESS) image in all HV. The deep peroneal nerve was not always visualised at level of interest. The MTR values were tightly grouped except in the sural nerve where the nerve was not visualised in two HV. The sural nerve location was found to be variable (e.g., lateral or medial to, or crossing behind, or found positioned directly posterior to the saphenous vein). High-resolution high-field images have excellent visualisation of the sural nerve and would give surgeons prior knowledge of the position before surgery. Basic imaging characteristics of the sural nerve can be acquired, but more detailed imaging characteristics are not easily evaluable in the very small sural and further developments and specific studies are required for any diagnostic utility at 7T.

Grain boundary junction disclinations in nanoparticles

Grain boundary junction (GBJ) disclinations are ubiquitous at the nanoscale in icosahedra and decahedra. These structural motifs consist of several tetrahedra sharing a twin grain boundary. According to the coincident site lattice (CSL) theory this twin grain boundary is referred to as Σ3<110>{111} grain boundary. In the present work, GBJ disclinations involving a low energy grain boundary Σ11<110>{113} are reported. Σ3−Σ3−Σ11 triple junction disclination is energetically preferred at the nanoscale as opposed to the ideal (without any misorientation mismatch) Σ3−Σ3−Σ9 triple junction. Molecular dynamics simulations are employed to study the disclinations in three dynamical processes key for nanoparticle synthesis − growth, coalescence, and solidification; across three metal systems Ag, Cu, and Pt which cover a range of stacking fault energies. Results indicate that Pt has a higher preference for disclinations while they are almost non-existent in Cu and to a lesser degree in Ag. Several types of disclinations have been identified and catalogued. Gaussian images (used as a proxy for simulating scanning transmission electron microscopy high angle annular dark field images) reveal that some of the disclinations induce artifacts which makes it non-trivial to identify them even when they are present in experimental particles. A key characteristic of the GBJ disclinations is the rapid change in misorientation angle around Σ11 grain boundary with distance away from the disclination. In this scenario, there is a need to reassess the methodology currently in use for identification of grain boundary type at the nanoscale.

High-field downfield MR spectroscopic imaging in the human brain.

To investigate the feasibility of downfield MR spectroscopic imaging (DF-MRSI) in the human brain at 7T. A 7T DF-MRSI pulse sequence was implemented based on the previously described methodology at 3T, with 3D phase-encoding, spectral-spatial excitation, and frequency selective refocusing. Data were pre-processed followed by analysis using the "LCModel" software package, and metabolite maps created from the LCModel results. Total scan time, including brain MRI and a water-reference MRSI, was 24 min. The sequence was tested in 10 normal volunteers. Estimated metabolite levels and uncertainty values (Cramer Rao lower bounds, CRLBs) for nine downfield peaks were compared between seven different brain regions, anterior cingulate cortex (ACC), centrum semiovale (CSO), corpus callosum (CC), cerebellar vermis (CV), dorsolateral prefrontal cortex (DLPFC), posterior cingulate cortex (PCC), and thalamus (Thal). DF peaks were relatively uniformly distributed throughout the brain, with only a small number of peaks showing any significant regional variations. Most DF peaks had average CRLB<25% in most brain regions. Average SNR values were higher for the brain regions ACC and DLPFC (˜7 ± 0.95, mean ± SD) while in a range of 3.4-6.0 for other brain regions. Average linewidth (FWHM) values were greater than 35 Hz in the ACC, CV, and Thal, and 22 Hz in CC, CSO, DLPFC, and PCC. High-field DF-MRSI is able to spatially map exchangeable protons in the human brain at high resolution and with near whole-brain coverage in acceptable scan times, and in the future may be used to study metabolism of brain tumors or other neuropathological disorders.

Reliable Off-Resonance Correction in High-Field Cardiac MRI Using Autonomous Cardiac B0 Segmentation with Dual-Modality Deep Neural Networks.

B0 field inhomogeneity is a long-lasting issue for Cardiac MRI (CMR) in high-field (3T and above) scanners. The inhomogeneous B0 fields can lead to corrupted image quality, prolonged scan time, and false diagnosis. B0 shimming is the most straightforward way to improve the B0 homogeneity. However, today's standard cardiac shimming protocol requires manual selection of a shim volume, which often falsely includes regions with large B0 deviation (e.g., liver, fat, and chest wall). The flawed shim field compromises the reliability of high-field CMR protocols, which significantly reduces the scan efficiency and hinders its wider clinical adoption. This study aims to develop a dual-channel deep learning model that can reliably contour the cardiac region for B0 shim without human interaction and under variable imaging protocols. By utilizing both the magnitude and phase information, the model achieved a high segmentation accuracy in the B0 field maps compared to the conventional single-channel methods (Dice score: 2D-mag = 0.866, 3D-mag = 0.907, and 3D-mag-phase = 0.938, all p < 0.05). Furthermore, it shows better generalizability against the common variations in MRI imaging parameters and enables significantly improved B0 shim compared to the standard method (SD(B0Shim): Proposed = 15 ± 11% vs. Standard = 6 ± 12%, p < 0.05). The proposed autonomous model can boost the reliability of cardiac shimming at 3T and serve as the foundation for more reliable and efficient high-field CMR imaging in clinical routines.

Thermochemical interactions between Ca2Sm8(SiO4)6O2 apatite and molten calcium–magnesium-aluminosilicate (CMAS)

Thermochemical interactions between Ca2Sm8(SiO4)6O2 (CSmS) apatite and molten calcium-magnesium-aluminosilicate (CMAS) glass having CaO/SiO2 mole ratio 0.37 have been evaluated. CSmS apatite-CMAS diffusion couples were annealed at 1200, 1300, and 1400 °C for 1–50 h. X-ray diffraction, scanning electron microscopy, transmission electron microscopy, high angle annular dark field imaging, selected area electron diffraction and energy dispersive x-ray spectroscopy were used to characterize the phases formed during the reaction. Formation of a distinct cyclosilicate [Ca3Sm2(Si3O9)2] layer was observed at apatite-CMAS interface in couples heat treated at 1200 °C but not at higher temperatures. The cyclosilicate layer nucleated at the apatite-CMAS reaction front, continued to grow into the residual melt and eventually detached from the apatite substrate. Residual CMAS melt became Ca-lean when cyclosilicate was present. Formation of MgCaSi2O6 diopside and dendrites of CaSiO3 wollastonite was also observed within the residual CMAS at 1200 °C. At 1300 and 1400 °C molten CMAS, due to its much lower viscosity, infiltrated the apatite substrate through open pores and along the grain boundaries. Ca2Sm8(SiO4)6O2 apatite thermal/environmental barrier coating has the potential to provide protection against CMAS attack up to about 1200 °C but not at higher temperatures.

Abstract 128: Multi-Direction Diffusion Weighted Imaging on Portable, Low-Field Magnetic Resonance Imaging

Background and aims: Portable, low-field (LF) MRI has the potential to improve access to expeditious, definitive brain imaging and facilitate diagnosis of acute stroke. Currently available diffusion-weighted imaging (DWI) protocols at LF are limited to a single diffusion direction due to acquisition duration. However, single-direction diffusion has reduced sensitivity for detecting acute ischemic infarcts, particularly small lesions residing in white matter tracts. The purpose of this study was to establish the feasibility of acquiring multi-direction DWI compared with single-direction counterparts on LF-MRI. Methods: Patients presenting with a diagnosis of acute ischemic stroke between July and September 2023 were eligible. Consented patients underwent DWI acquisition on a 0.064T LF-MRI (Mk1.9; Hyperfine Research Inc). Three diffusion directions (x, y, and z) were acquired with a b weighting of 900 s/mm 2 and a single acquisition with a b 0 s/mm 2 . The b 900 images were co-registered to the b 0, trace and apparent diffusion coefficient (ADC) maps calculated, and the final images interpolated at 1 mm 3 . Results: Ten patients presenting to the Massachusetts General Hospital with acute ischemic stroke were consented and imaged within 72 hours of last known well. The total acquisition time was 14 minutes, with all subjects able to tolerate the scan duration. Ischemic lesions as small as 0.1 mL were detectable on the LF-MRI (17.5 +/- 18.2 mL). An example of each diffusion direction individually, the combined trace, and corresponding ADC maps are shown in Figure 1, compared with conventional high-field (HF) diffusion images acquired within 30 minutes of the LF acquisition. Conclusion: Multi-direction DWI imaging is feasible on a 0.064T LF-MRI scanner. Our experience suggests further modifications to the pulse sequence and scanner configuration may facilitate a reduction in acquisition time, improve resolution, or both.

High resolution magnetic field imaging probe with two rows of TMR sensors for small defects inspection

It is still a challenging problem to detect small defects for eddy current array probes, which requires the probes to possess excellent sensitivity, as well as high spatial resolution. This paper presents a novel high-resolution magnetic field imaging probe with two rows of tunneling magnetoresistance (TMR) array sensors. The bare die sensors are integrated on a printed circuit board by golden wire bonding technology. The two rows of sensors are placed staggered with each other. The data of the two arrays are merged into a matrix, in which way the image pixel pitch is increased to 0.25 mm. The probe employs a differential scheme to suppress the noise, so as to detect the weak signal of small defects. To highlight the weak defect indications, feature extraction and segmentation algorithms are developed. The experimental results confirm that the proposed method can inspect a small defect with dimensions 1 mm (length) × 0.1 mm (width) × 0.1 mm (depth) on a stainless-steel sample.

Sodium lanthanide tungstate-based nanoparticles as bimodal contrast agents for in vivo high-field MRI and CT imaging.

Research on high-field magnetic resonance imaging (HF-MRI) has been increased in recent years, aiming to improve diagnosis accuracy by increasing the signal-to-noise ratio and hence image quality. Conventional contrast agents (CAs) have important limitations for HF-MRI, with the consequent need for the development of new CAs. Among them, the most promising alternatives are those based on Dy3+ or Ho3+ compounds. Notably, the high atomic number of lanthanide cations would bestow a high capability for X-ray attenuation to such Dy or Ho-based compounds, which would also allow them to be employed as CAs for X-ray computed tomography (CT). In this work, we have prepared uniform NaDy(WO4)2 and NaHo(WO4)2 nanoparticles (NPs), which were dispersible under conditions that mimic the physiological media and were nontoxic for cells, meeting the main requirements for their use in vivo. Both NPs exhibited satisfactory magnetic relaxivities at 9.4 T, thus making them a promising alternative to clinical CAs for HF-MRI. Furthermore, after their intravenous administration in tumor-bearing mice, both NPs exhibited significant accumulation inside the tumor at 24 h, attributable to passive targeting by the enhanced permeability and retention (EPR) effect. Therefore, our NPs are suitable for the detection of tumors through HF-MRI. Finally, NaDy(WO4)2 NPs showed a superior X-ray attenuation capability than iohexol (commercial CT CA), which, along with their high r2 value, makes them suitable as the dual-probe for both HF-MRI and CT imaging, as demonstrated by in vivo experiments conducted using healthy mice.

Beyond Macrostructure: Is There a Role for Radiomics Analysis in Neuroimaging ?

The most commonly used neuroimaging biomarkers of brain structure, particularly in neurodegenerative diseases, have traditionally been summary measurements from ROIs derived from structural MRI, such as volume and thickness. Advances in MR acquisition techniques, including high-field imaging, and emergence of learning-based methods have opened up opportunities to interrogate brain structure in finer detail, allowing investigators to move beyond macrostructural measurements. On the one hand, superior signal contrast has the potential to make appearance-based metrics that directly analyze intensity patterns, such as texture analysis and radiomics features, more reliable. Quantitative MRI, particularly at high-field, can also provide a richer set of measures with greater interpretability. On the other hand, use of neural networks-based techniques has the potential to exploit subtle patterns in images that can now be mined with advanced imaging. Finally, there are opportunities for integration of multimodal data at different spatial scales that is enabled by developments in many of the above techniques-for example, by combining digital histopathology with high-resolution ex-vivo and in-vivo MRI. Some of these approaches are at early stages of development and present their own set of challenges. Nonetheless, they hold promise to drive the next generation of validation and biomarker studies. This article will survey recent developments in this area, with a particular focus on Alzheimer's disease and related disorders. However, most of the discussion is equally relevant to imaging of other neurological disorders, and even to other organ systems of interest. It is not meant to be an exhaustive review of the available literature, but rather presented as a summary of recent trends through the discussion of a collection of representative studies with an eye towards what the future may hold.

Microstructural analysis does not support altered interhemispheric wiring of the human anterior commissure in corpus callosum dysgenesis

BackgroundIndividuals with corpus callosum dysgenesis (CCD) lack the clear disconnection syndrome that is characteristic of individuals in whom the corpus callosum has been surgically severed. One potential explanation for this paradox is that the anterior commissure undergoes neuroplastic remodeling in CCD to improve interhemispheric communication between the brain hemispheres. MethodsA cohort of sixteen individuals with CCD (and sixteen sex and age-matched neurotypical controls) underwent multi-shell diffusion magnetic resonance high-field imaging (dMRI) at 7-Tesla to assess the anatomy of the anterior commissure for evidence of neuroplasticity. ResultsNo significant group-wise differences in midsagittal anterior commissure volumes were detected between the CCD and control cohorts, although there were CCD individuals within the cohort who exhibited volumes that were either substantially larger or smaller than their neurotypical counterparts. Axonal intracellular volume fractions were reduced across the CCD white matter, including regions of the anterior commissure, and tractographic analyses were unable to identify any novel connections projecting through the anterior commissure that were unique to CCD individuals. Finally, variances in the neuroanatomy of the anterior commissure in the CCD cohort did not correlate with performance on neuropsychological tasks that are highly dependent upon interhemispheric communication. ConclusionsThe results of this study indicate that there are individuals within the CCD population in whom it is unlikely that the anterior commissure is the primary substrate for interhemispheric communication. Consequently, other, presently unknown, compensatory mechanisms are likely involved in supporting this function.

Improving portable low-field MRI image quality through image-to-image translation using paired low- and high-field images

Low-field portable magnetic resonance imaging (MRI) scanners are more accessible, cost-effective, sustainable with lower carbon emissions than superconducting high-field MRI scanners. However, the images produced have relatively poor image quality, lower signal-to-noise ratio, and limited spatial resolution. This study develops and investigates an image-to-image translation deep learning model, LoHiResGAN, to enhance the quality of low-field (64mT) MRI scans and generate synthetic high-field (3T) MRI scans. We employed a paired dataset comprising T1- and T2-weighted MRI sequences from the 64mT and 3T and compared the performance of the LoHiResGAN model with other state-of-the-art models, including GANs, CycleGAN, U-Net, and cGAN. Our proposed method demonstrates superior performance in terms of image quality metrics, such as normalized root-mean-squared error, structural similarity index measure, peak signal-to-noise ratio, and perception-based image quality evaluator. Additionally, we evaluated the accuracy of brain morphometry measurements for 33 brain regions across the original 3T, 64mT, and synthetic 3T images. The results indicate that the synthetic 3T images created using our proposed LoHiResGAN model significantly improve the image quality of low-field MRI data compared to other methods (GANs, CycleGAN, U-Net, cGAN) and provide more consistent brain morphometry measurements across various brain regions in reference to 3T. Synthetic images generated by our method demonstrated high quality both quantitatively and qualitatively. However, additional research, involving diverse datasets and clinical validation, is necessary to fully understand its applicability for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.

Rim lesions in MS at 3T: clinical correlation and possible radiological alternatives for daily practice at lower field strength

Background and purposeParamagnetic rim lesions (PRLs) have been described as an imaging feature specific to multiple sclerosis (MS) using high-field strength phase-sensitive MR imaging. These lesions are suggested to reflect chronic active inflammation associated with greater disease severity and a more rapid disability progression. The aim of our study is to investigate the relationship between PRLs, clinical parameters, other radiological findings and disease progression. Material and methodsThis cross-sectional study included MS patients treated with teriflunomide, fingolimod, natalizumab or ocrelizumab for at least 2 years. PRLs seen at 3T MRI were analysed and correlated with clinical data and radiological progression, defined as an increase of the T2/FLAIR-lesion load during therapy. In the search for alternatives for these PRLs, we defined two additional radiological markers: ‘FLAIR-bullet lesions’, and on post-contrast black-blood (BB) images, ‘BB-bullet lesions’. ResultsWe included 84 MS patients of whom 27 (32 %) had at least 1 PRL. PRLs were associated with radiological progression under therapy (p=0.039) and higher clinical disability scores, although only significant for 9-Hole Peg Test (p=0.023). Patients with FLAIR-bullet or BB-bullet lesions at 3T MRI had a higher chance of PRL (p<0.001) with a likelihood ratio of 13.2 for FLAIR-bullets and 12.6 for BB-bullet lesions, thanks to the high negative predictive value of respectively 83 % and 90 %. ConclusionPRLs are associated with an increase of T2/FLAIR-lesion load under therapy and unfavourable clinical outcome. Our newly defined ‘bullet lesions’ are associated with PRLs and might be an interesting MRI marker for centres without access to high-field SWI images.

Research on a portable shielding-free ultra-low field magnetic resonance imaging system

The portable light-weight magnetic resonance imaging system can be deployed in special occasions such as Intensive Care Unit (ICU) and ambulances, making it possible to implement bedside monitoring imaging systems, mobile stroke units and magnetic resonance platforms in remote areas. Compared with medium and high field imaging systems, ultra-low-field magnetic resonance imaging equipment utilizes light-weight permanent magnets, which are compact and easy to move. However, the image quality is highly susceptible to external electromagnetic interference without a shielded room and there are still many key technical problems in hardware design to be solved. In this paper, the system hardware design and environmental electromagnetic interference elimination algorithm were studied. Consequently, some research results were obtained and a prototype of portable shielding-free 50 mT magnetic resonance imaging system was built. The light-weight magnet and its uniformity, coil system and noise elimination algorithm and human brain imaging were verified. Finally, high-quality images of the healthy human brain were obtained. The results of this study would provide reference for the development and application of ultra-low-field magnetic resonance imaging technology.

Correlation study and clinical value analysis between cerebral microbleeds and white matter hyperintensity with high-field susceptibility-weighted imaging.

This study aimed to investigate the relationship between white matter hyperintensity (WMH) and cerebral microbleeds (CMBs) using susceptibility-weighted imaging (SWI) with high resolution. Additionally, it sought to analyze the clinical significance of SWI with high resolution and its potential to guide intravenous thrombolysis in stroke patients. In this retrospective analysis, we examined 96 patients with hypertension after acute stroke in our hospital using SWI. Demographic and medical data of these 96 patients were collected. Spearman correlation analysis was performed to investigate the relationship between CMBs and the grading of WMH. A significant positive correlation was observed between CMBs and the grade of WMH (R = 0.593, P < .05). The data also revealed a superior ROC area under the curve for the modified Fazekas grading of WMH, which was 0.814 (P < .05). There is a positive correlation between CMBs and the grading of leukoaraiosis in patients with acute stroke and hypertension. The higher the degree of WMH, the more severe the microvascular lesions, increasing the likelihood of intracranial hemorrhage. SWI can provide valuable guidance for administering intravenous thrombolysis in patients with acute stroke.

The impact of variations in subject geometry, respiration and coil repositioning on the specific absorption rate in parallel transmit abdominal imaging at 7 T.

Parallel transmit MRI at 7 T has increasingly been adopted in research projects and provides increased signal-to-noise ratios and novel contrasts. However, the interactions of fields in the body need to be carefully considered to ensure safe scanning. Recent advances in physically flexible body coils have allowed for high-field abdominal imaging, but the effects of increased variability on energy deposition need further exploration. The aim of this study was to assess the impact of subject geometry, respiration phase and coil positioning on the specific absorption rate (SAR). Ten healthy subjects (body mass index[BMI] = 25 ± 5 kg m-2 ) were scanned (at 3 T) during exhale breath-hold and images used to generate body models. Seven of these subjects were also scanned during inhale. Simplifications of the coil and body models were first explored, and then finite-difference time-domain simulations were run with a typical eight-channel parallel transmit coil positioned over the abdomen. Simulations were used to generate 10 g averaged SAR (SAR10g ) maps across 100,000 phase settings, and the worst-case scenario 10 g averaged SAR (wocSAR10g ) was identified using trigonometric maximisation. The average maximum SAR10g across the 10 subjects with 1 W input power per channel was 1.77 W kg-1 . Hotspots were always close to the body surface near the muscle wall boundary. The wocSAR10g across the 10 subjects ranged from 2.3 to 3.2 W kg-1 and was inversely correlated to fat volume percentage (R = 8) and BMI (R = 0.6). The coefficient of variation values in SAR10g due to variations in subject geometry, respiration phase and realistic coil repositioning were 12%, 4% and 12%, respectively. This study found that the variability due to realistic coil repositioning was similar to the variability due to differing healthy subject geometries for abdominal imaging. This is important as it suggests that population-based modelling is likely to be more useful than individual modelling in setting safe thresholds for abdominal imaging.

Low-field magnetic resonance image enhancement via stochastic image quality transfer.

Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher income countries e.g. for small child patients with obesity, claustrophobia, implants, or tattoos. However, low-field MR images commonly have lower resolution and poorer contrast than images from high field (1.5T, 3T, and above). Here, we present Image Quality Transfer (IQT) to enhance low-field structural MRI by estimating from a low-field image the image we would have obtained from the same subject at high field. Our approach uses (i) a stochastic low-field image simulator as the forward model to capture uncertainty and variation in the contrast of low-field images corresponding to a particular high-field image, and (ii) an anisotropic U-Net variant specifically designed for the IQT inverse problem. We evaluate the proposed algorithm both in simulation and using multi-contrast (T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR)) clinical low-field MRI data from an LMIC hospital. We show the efficacy of IQT in improving contrast and resolution of low-field MR images. We demonstrate that IQT-enhanced images have potential for enhancing visualisation of anatomical structures and pathological lesions of clinical relevance from the perspective of radiologists. IQT is proved to have capability of boosting the diagnostic value of low-field MRI, especially in low-resource settings.