bluuebunny/crossref_metadata_2025 huggingface dataset:
Free Water Imaging in a Pig Model of Traumatic Brain Injury
Authors: Parker Drew , Johnson Victoria , Chen H. , Wolf John , Verma Ragini
Published: August 2023

The way brain injury can evolve has different manifestations on imaging in multiple MRI modalities, pointing to different pathological etiologies. The true picture can be seen only by correcting for free water, as it biases all the diffusion measurements, especially the longitudinal outcome. While this has been observed in humans, it is for the first time free water analysis has been carried out in a gyrencephalic pig model of TBI. In the future, co-registration with histopathological outcomes will be undertaken to verify the specificity of the diffusion measurements, which will lay the foundation for interpretation of unbiased diffusion measurements.
Elucidating dynamic anaerobic metabolism in obligate anaerobes with living cells
Authors: Cheng Leo , Pavao Aidan , Girinathan Brintha , Peltier Johann , Silva Pamela , Dupuy Bruno , Muti Isabella , Malloy Craig , Bry Lynn
Published: August 2023

Anaerobic microbial metabolism drives critical functions within global ecosystems, host-microbiota interactions, and industrial applications, yet remains ill-defined. We resolved dynamic metabolism in living cells of the anaerobic pathogen Clostridioides difficile using High-Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy to inform genome-scale predictions of cellular metabolism. Analyses leveraged the sensitivity of 13C NMR spectroscopy to simultaneously track cellular carbon and nitrogen flow from fermentable 13C and 15N-labeled substrates. We illustrate a versatile approach to elaborate complex anaerobic metabolism for clinical, scientific, and industrial applications.
Design and fabrication of portable, low-field MR relaxometer for clinical measurement of volemic status
Authors: Sherman Sydney , Cima Michael
Published: August 2023

A low-field portable MR-based sensor was fabricated for the acquisition of clinical T2 relaxometry measurements in skeletal muscle. We have previously reported methods for designing low-field permanent magnet array configurations with varying sensitive region profiles. The newly constructed array has a sensitive region 15-20mm from the surface of the magnet; field maps from the constructed magnet show good alignment with simulated fields. The exclusion of subcutaneous fat tissue in the sensitive region will improve sensitivity to fluid shifts within the skeletal muscle.
Open-source model-based reconstruction in Julia: A pipeline for spiral diffusion imaging
Authors: Jaffray Alexander , Wu Zhe (Tim) , Uludag Kamil , Kasper Lars
Published: August 2023

We investigated the use of physically-motivated corrections for non-Cartesian imaging within a fast, open-source MR reconstruction framework written in the Julia programming language. Building on existing Julia libraries for MR image reconstruction, we developed a comprehensive, open-source pipeline for non-Cartesian image reconstruction including B0 inhomogeneity correction, gradient system characterization and eddy current correction. We demonstrated that spiral images can be reconstructed using this pipeline with high geometric accuracy in a fast, accessible and efficient manner on modest hardware.
Comparison between GRAPPA and automatic compressed sensing-based reconstruction up to 16-fold acceleration
Authors: Varela-Mattatall Gabriel , Haast Roy , Oran Omer , Khan Ali , Menon Ravi
Published: August 2023

With the recent development of an automatic compressed sensing (CS)-based reconstruction method, we investigated its allowance to recover T2* maps from prospectively undersampled multi-echo, gradient echo-based acquisitions at 7T. We compared our CS method with the more conventional GRAPPA-based reconstruction using up to 16-fold acceleration. In contrast to GRAPPA, our CS-based method allows recovery of T2* maps up to 16-fold acceleration, which demonstrates its promise for ultra-fast acquisitions. However, current results also show some caveats that need to be addressed as future work.
Coil Selective Golden Angle DCE-MR Image Reconstruction using Mutual Dependence
Authors: Kocanaogullari Aziz , Ariyurek Cemre , Afacan Onur , Kurugol Sila
Published: August 2023

MRI literature shows that it is possible to increase image reconstruction quality by removing coils that cause majority of the streaking artifacts. We introduce to measure the coil quality based on mutual information between a reference and each coil image. Specifically we apply this technique to DCE-MRI reconstruction from under-sampled radial stack of stars trajectory for kidney imaging and calculate mutual dependence between a dynamic image from each coil and a reference image to assess coil contribution to reconstruction. Experiments show mutual dependence based coil selection reduces artifacts and increases reconstructed image SNR by $$$16.84\%$$$ using $$$1/3$$$ of the coils.
Reconstruction for Simultaneous Multi-Slab Spatiotemporal Encoding (SMS SPEN) Using Split Slice-GRAPPA combined with CAIPIRINHA
Authors: Yu Jaeyong , Kim Sugil , Park Jang-Yeon
Published: August 2023

To reduce acquisition time, acceleration techniques such as simultaneous multi-slice and parallel imaging techniques have been applied to various sequences. In this work, we proposed a reconstruction method for simultaneous multi-slab spatiotemporal-encoding (SMS SPEN) using split slice-GRAPPA combined with CAIPIRINHA. The proposed method was applied to the recently developed ultrafast 3D SPEN imaging sequence called ERASE (Equal-TE Rapid Acquisition with Sequential Excitation) and a case of multiband factor of 3 was demonstrated with human brain imaging at 3T.
Prospects of non-Cartesian 3D-SPARKLING encoding for functional MRI: A preliminary case study for retinotopic mapping
Authors: Amor Zaineb , G.R. Chaithya , Daval-Frérot Guillaume , Thirion Bertrand , Mauconduit Franck , Ciuciu Philippe , Vignaud Alexandre
Published: August 2023

For the first time, non-Cartesian 3D-SPARKLING (Spreading Projection Algorithm for Rapid K-space sampLING) encoding scheme was used for task-based fMRI (retinotopic mapping) at 7T. Additionally, this new acquisition technique was compared with 3D-EPI, considered as one of the reference acquisition schemes in high-resolution fMRI. The experiment was performed on a single participant at 1mm isotropic and for a temporal resolution of 2.4s. We found that both techniques yield similar statistically significant activation patterns in the visual cortex.
A Comparison of Background Field Removal and “Single-Step” Algorithms in Realistic Phantoms: Towards QSM Challenge 3.0?
Authors: Milovic Carlos , Langkammer Christian , Marques José Pedro , Shmueli Karin
Published: August 2023

The 2019 QSM Reconstruction Challenge compared how different algorithms reconstructed QSM from true local field maps. However, this neglects the importance of residual background fields, and how they degrade the solutions. Here, we used a realistic “total field” simulation to compare three different background field removal methods, and to estimate the susceptibility maps resulting from three state-of-the-art QSM algorithms. We also compared the performance of two single-step algorithms, that use the total field map as an input. Our results showed that the two-step Weak-Harmonic QSM method is robust against residual fields and achieved the lowest error scores, outperforming single-step methods.
On the water–fat in-phase assumption for quantitative susceptibility mapping (QSM)
Authors: Boehm Christof , Meineke Jakob , Weiss Kilian , Makowski Marcus , Karampinos Dimitrios
Published: August 2023

Gradient echo imaging using in-phase echoes has been proposed to reduce the field-map estimation in water–fat regions to a convex nonlinear least squares problem. Conventionally, the in-phase assumption is based on a single-peak fat-model. However, fat is known to have a complex spectrum rendering the definition of in-phase echo times problematic. In this work, the single-fat-peak in-phase assumption is replaced by a multi-peak effective in-phase assumption. QSM based on multi-peak in-phase echo times is shown to yield similar results to water–fat imaging based field- and susceptibility-mapping in a simulation and in vivo in the spine and the breast.
Quiet quantitative susceptibility mapping with Looping Star
Authors: Damestani Nikou , Solana Ana , Wiesinger Florian , Fernandez Brice , Williams Steven , Lythgoe David
Published: August 2023

Looping Star is an acoustically quiet T2*-weighted acquisition technique, which has primarily been used to demonstrate functional sensitivity. We present the application of Looping Star to quantitative susceptibility mapping in a small cohort, directly comparing its outcomes with a conventional susceptibility-weighted imaging technique. We found that Looping Star produced comparable quantitative values in subcortical regions in comparison with conventional susceptibility-weighted imaging.
Large-Scale Functional Network Connectivity Mediates the Associations of Serum Lipids and Cognitive Function in Patients with Type 2 Diabetes
Authors: Zhang Wen , Zhang Jilei , Zhang Bing
Published: August 2023

Patients with type 2 diabetes mellitus (T2DM) often have pathologically altered lipid metabolism. Evidence has confirmed that dyslipidemia is linked to cognitive decline. We explored the large-scale functional network connectivity alterations and their potential relationships with serum lipids and cognitive performance in T2DM patients. Our results suggested lower inter and intra-network functional connectivity in T2DM patients and the possibility of improving cognitive function through lipids management.
Towards Mapping the Resting-State Connectome of the Limbic System in Real-Time with Connectome-based Neurofeedback
Authors: Sharpe Jeff , de la Rocque Guimaraes Bruno Sa , Posse Stefan
Published: August 2023

In the present study we develop a real-time seed-based correlation analysis (SBC) pipeline with online regression to compute a connectome fingerprint matrix and characterize the performance of this methodology for quantifying intra- and inter-network connectivity dynamics across major resting state networks (RSNs) in healthy subjects. We assess the association between connectivity in the limbic system and intensity of self-induced mood states with neurofeedback based on the connectome matrix.
Relationship between resting-state fMRI functional connectivity and intracranial EEG band-limited power coupling
Authors: Sabaroedin Kristina , Wilson Will , Pittman Daniel , Federico Paolo , LeVan Pierre
Published: August 2023

Functional connectivity (FC) of resting-state fMRI (rs-fMRI) is a popular method for characterizing brain connectivity. rs-fMRI indirectly measures neuronal fluctuations through blood-oxygenation-level dependent (BOLD) signal and is susceptible to various physiological noise which lead to spurious correlations. We investigated the relationship between rs-fMRI FC and band-limited power (BLP) coupling measured using intracranial EEG (icEEG). Both static and dynamic connectivity analyses revealed a relationship between BOLD FC and icEEG BLP coupling across multiple frequency bands. However, this relationship depends on distance and electrode type. BOLD FC is distinct in fluctuations and spatial variability, suggesting non-neural signal sources in rs-fMRI connectivity.
Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting improves IVIM analysis in the human kidney
Authors: Stabinska Julia , Zöllner Helge , Wittsack Hans-Jörg , Ljimani Alexandra
Published: August 2023

Recent studies have shown that a three-compartment model is preferable when analyzing renal DWI signal, as the conventional bi-exponential IVIM fitting does not differentiate between pure water diffusion and incoherent intra-tubular fluid motion. However, triexponential IVIM modelling in the kidney is challenging due to suboptimal SNR of diffusion-weighted images. In the present study, we applied Image Downsampling Expedited Adaptive Least-squared (IDEAL) fitting, which utilizes image downsampling to generate high SNR images to iteratively update the initial model parameters until the final image resolution is reached, and achieved more reliable estimates of the IVIM-related parameters compared with the conventional fitting methods.
Mapping spatially heterogeneous single nephron function in the kidney using MRI.
Authors: Baldelomar Edwin , Charlton Jennifer , Bennett Kevin
Published: August 2023

Nephrons are the functional units of the kidney, coordinated with surrounding nephrons through the vasculature to filter blood plasma. We used in vitro CFE-MRI combined with Gd-DTPA contrast enhanced MRI to dynamically map single nephron physiology throughout the isolated, perfused rat kidney. We were able to map the heterogeneity and spatial variability of macromolecular binding and single nephron filtration. MRI appears to measure similar dynamics in single nephron filtration as intra-vital optical microscopy, with the advantage of measuring all nephrons in the kidney.
Synthetic arterial spin labelling datasets of the kidneys for pipeline evaluation and comparison
Authors: Brumer Irène , Bauer Dominik , Schad Lothar , Zöllner Frank
Published: August 2023

Synthetic kidney ASL data with respiratory motion was generated using models from the XCAT phantom and matching recommendations for in-vivo acquisitions. Both pCASL and PASL datasets with 1 M0 and 25 control-label pairs were created and analysed using an in-house developed processing pipeline including registration, manual segmentation, calculation of mean perfusion-weighted image and perfusion map. The registration performed well on the synthetic data and the perfusion maps yielded good cortex/medulla contrast. The presented method allows a wide range of parameter choices for creating synthetic ASL datasets valuable for testing processing pipelines and comparing them across research and clinical imaging centres.
Parametric T1 MR Microscopy Detects Gadolinium Residuals in Ex Vivo Rat Kidneys
Authors: Tasbihi Ehsan , Hummel Luis , Gladytz Thomas , Starke Ludger , Millward Jason , Seeliger Erdmann , Niendorf Thoralf
Published: August 2023

Accumulation of gadolinium (Gd) following use of Gd-based contrast agents (GBCA) is a concern. To study the potential of T1 microscopy for assessing Gd residues in the kidney, rats were administered 8 intravenous doses of various GBCAs over a period of two weeks. Five days following the last administration, the kidneys were collected and fixed in formalin. High resolution T1 maps obtained from ex vivo scans showed significantly reduced T1 levels for both linear and macrocyclic GBCAs. This demonstrates to potential for quantitative T1 mapping to detect Gd residues non-invasively in renal tissue.
Relative cerebral blood volume of tumor habitats can differentiate presurgical IDH-wildtype glioblastoma from IDH-mutant astrocytoma grade 4.
Authors: Álvarez-Torres María del Mar , Fuster-Garcia Elies , Balaña Carmen , Puig Josep , Reynes Gaspar , Emblem Kyrre , Mollà-Olmos Enrique , Pineda Jose , García-Gómez Juan M
Published: August 2023

IDH-wildtype glioblastoma and IDH-mutant astrocytoma are classified as different gliomas according to WHO 2021. IDH mutations are key at clinical level, since they are associated with patient prognosis and seem to be critical for treatment selection. Despite these evidences, current protocols do not include the full sequencing for all tumors. In this sense, non-invasive and automatically calculated MRI-based biomarkers can be helpful for the clinical practice.

Our results show that perfusion markers obtained in an automated, repeatable, and non-invasive manner may be candidates for being surrogate predictive markers of IDH mutation status in astrocytomas grade 4.
Inhomogeneous MT (ihMT) MRI in a glioblastoma mouse model
Authors: Varma Gopal , Yeo Alan , Callahan Cody , Alsop David , Grant Aaron , Charest Alain
Published: August 2023

Inhomogeneous MT (ihMT) MRI was applied in a genetic mouse model of glioblastoma to assess its potential to provide useful complementary information regarding the true extent of tumor infiltration. Data were acquired to produce maps of MT and ihMT ratios, which were analyzed based on regions of interest relative to brain tissue contralateral to the tumor and progression with time. The tumor was characterized by significantly lower MT and ihMT. Reduction in peripheral white matter ihMT was taken to indicate demyelinating processes associated with glioblastoma. Thus, ihMT might be used to inform on disease progression in tumor adjacent brain tissue.
Cost-Effectiveness Analysis of Diagnosis of Necrosis from Recurrent Tumor after RT with MRS, MRP and Combined Imaging Method for Low-Grade Glioma
Authors: Liao Huijun , Huang Raymond , Kang Stella , Lin Alexander
Published: August 2023

Our decision-analytic model examined the cost-effectiveness of MR Spectroscopy (MRS), MR perfusion (MRP), and the combination of MRS, MRP and DWI for differentiating brain radiation necrosis from tumor progression in high-risk low-grade glioma. Our results suggested that performing combined imaging method had good diagnostic accuracy for a 3-year time horizon but not a cost-effective in the long run. In contrast, MRS and especially MRP alone were more cost-effective over all time horizons. MRS is the most cost-effective method in lifetime when its negative predictive value≥88% at the Willingness-to-Pay threshold of $100,000.
Application of APTw imaging in clear cell renal cell carcinoma
Authors: Wang Xia , Bu# Chaoqun , Tian# Gang , Du Zeliu , Jiang Yu , Zhao Na , Yu Chanjuan , Han* Yuedong , He Jianguang , Yue Xiuzheng , Shen Zhiwei
Published: August 2023

The application of amide proton transfer (APT) weighted imaging in molecular imaging of craniocerebral tumors has been relatively mature, but rarely reports on renal tumors. This study conducted a preliminary comparative analysis of clear cell renal cell carcinoma (ccRCC) and healthy adult renal APT imaging. The APTw values 6.40(6.26~7.75)% of tumor foci in the ccRCC group was significantly higher than that of healthy adult renal (2.05±0.24) %The preliminary results indicate that APT technology has potential clinical application value in the diagnosis of ccRCC.
Feasibility of Quantifying Cerebral Blood Volume and Blood-Brain Barrier Water Exchange using Non-Contrast MR Fingerprinting
Authors: Thomson Emma , Powell Elizabeth , Wheeler-Kingshott Claudia Gandini , Parker Geoff
Published: August 2023

We propose the use of magnetic resonance fingerprinting (MRF), applied using a spoiled gradient echo sequence, to quantify cerebral blood volume ($$$\nu_b$$$) and inter-vascular water exchange (1/$$$\tau_b$$$), without the need for contrast agents. Through a simulation study we optimise a simulated acquisition protocol and test the sensitivity of the measurement, and its accuracy in the presence of variations in blood T1, tissue T1, and B1. We demonstrate that voxel-wise simultaneous quantification of $$$\nu_b ,\tau_b , T_{1,b}, T_{1,e}$$$ and $$$B_1^+$$$ is likely feasible with an optimised acquisition.
Application of Deep Learning techniques to Magnetic Resonance Fingerprinting
Authors: Cabini Raffaella Fiamma , Barzaghi Leonardo , Cicolari Davide , Pichiecchio Anna , Figini Silvia , Arosio Paolo , Filibian Marta , Lascialfari Alessandro , Carrazza Stefano
Published: August 2023

We developed a Neural Network (NN) for the reconstruction of T1 and T2 parametric maps obtained with the Magnetic Resonance Fingerprinting (MRF) technique. The training phase was realized on experimental inputs, eliminating the use of simulated datasets and theoretical models. The set of optimal hyperparameters of the NN and the supervised training algorithm were established through an optimization procedure. The model achieved similar performances to the traditional reconstruction method, but the number of MRF images required was lower with respect to the dictionary-based method. If translated to the clinic, our results envisage a significant time shortening of MRI investigation.
Fast and High-Resolution T2* weighted and susceptibility-based MRI using 3D-EPI with Deep Learning Reconstruction
Authors: Fernandez Brice , Lebel R. Marc , Wang Xinzeng , Guidon Arnaud , Banerjee Suchandrima , Skare Stefan , Sprenger Tim
Published: August 2023

Fast and high-resolution T2*w and susceptibility-weighted imaging is an essential part of brain MR assessment for many neurological conditions. Very high spatial resolution can be helpful for visualization of microvascular details as well as the central vein sign in white matter Multiple Sclerosis lesions, but such scans have a long acquisition time. In this abstract, we demonstrate high-quality whole-brain T2*w and susceptibility-based MRI at 0.5 mm isotropic resolution in less than 4 minutes using a 3D-echo-planar acquisition and a deep learning reconstruction. Finally, straightforward improvements are discussed for further reduction of the scan time.
Prior-knowledge MRS Metabolite Quantification using Deep Learning Frameworks: A proof-of-concept
Authors: Turco Federico , Slotboom Johannes
Published: August 2023

We implemented a mathematical representation of a prior-knowledge model in a Neural Network using a Tensorflow. The trainables tensors are directly the free parameters of the model and we do metabolite quantification by overfitting the output to the signal that we want to replicate. We found that this way of fitting has a relatively low performance in time domain but similar to the state-of-the-art (TDFDFit) when using frequency domain. In addition we have a faster method and it can be used in future works as a component of a more complex network.
Quantitative MRI parameter estimation with supervised deep learning: MLE-derived labels outperform groundtruth labels
Authors: Epstein Sean , Bray Timothy , Hall-Craggs Margaret , Zhang Hui
Published: August 2023

We propose a novel deep learning technique for quantitative MRI parameter estimation. Our method is trained to map noisy qMRI signals to conventional best-fit parameter labels, which act as proxies for the groundtruth parameters we wish to estimate. We show that this training leads to more accurate predictions of groundtruth model parameters than traditional approaches which train on these groundtruths directly. Furthermore, we show that our proposed method is both conceptually and empirically equivalent to existing unsupervisedapproaches, with the advantage of being formulated as supervised training.
Measuring the macromolecular baseline in the neonatal brain
Authors: Lopez Maria Yanez , Oeltzschner Georg , Price Anthony N , Puts Nicolaas AJ , Hughes Emer J , McAlonan Grainne M , Arichi Tomoki , Edden Richard AE , De Vita Enrico
Published: August 2023

The doublet nature of the 3 ppm peak previously reported in neonates indicates that a lower macromolecular contribution to the GABA+ 3 ppm signal is likely to be present in this population. Detailed characterisation of age‐related MM contribution rates is required to improve the MRS fitting process, and therefore, to further increase the accuracy of metabolic measurements in neonates. As a first step, we here measure the macromolecular baseline using metabolite-nulling MRS in healthy term neonatal participants.
GABA and Glutamate response to social processing; a functional MRS study
Authors: Pasanta Duanghathai , White David , He Jason , Puts Nicolaas , Ford Talitha
Published: August 2023

We performed functional magnetic resonance spectroscopy (fMRS) to measure the dynamic response of GABA and Glutamate in the superior temporal sulcus (STS) and visual cortex (V1) while viewing social stimuli. MEGA-PRESS fMRS spectra were analyzed in both block and event-related design. Sliding window analyses were used to investigate GABA and Glutamate dynamics at higher temporal resolution. A small decrease in GABA level was observed during stimulus presentation in V1, but no change was observed in STS. We highlight the feasibility of using fMRS to assess changes in metabolite response during social processing in health and disease.
Denoising MR spectra by deep learning: miracle or mirage?
Authors: Dziadosz Martyna , Rizzo Rudy , Kyathanahally Sreenath P , Kreis Roland
Published: August 2023

The main limitation of MRS is low SNR. Several approaches for denoising have been proposed. However, it is debatable, whether denoising can reduce estimate uncertainties. In this work, we investigate denoising using deep learning (DL) in time-frequency representations. The results were assessed using two methods: first, an adjusted noise score was used and second, the outcome of traditional fitting was evaluated. We found that time-frequency domain denoising through DL produces a visually appealing spectrum but mean residuals for the relevant spectral regions and variance in fit results remained as high as without denoising.
Versatile Open source B0 shimtool
Authors: Jani Mahrshi , Su Shengyue , Sarma Manoj Kumar , Fillmer Ariane , Henning Anke
Published: August 2023

In this work, we compare the spectroscopy results and metabolite maps for different shimming routine. We use vendor default shimming technique and our own shimming technique. We tried to do shimming in different regions of brain (i.e. prefrontal cortex, occipital, and insula), also we tried to do multivoxel shimming. We compared the frequency shift maps between vendor’s implemented shim routine and our own shim algorithm. Also, we compared metabolite maps we got from different shimmed region after shimming using vendors and our own shimming routine.
Detection of Samples Out of Training Distribution: Rejection of Potential Erroneous Local SAR Predictions
Authors: Meliado Ettore Flavio , Raaijmakers Alexander , Luijten P.R. , van den Berg C.A.T.
Published: August 2023

Recognize potential hazardous situations far from the modeled MR examination scenarios is crucial for RF safety applications and especially for deep-learning-based approaches. Last year we presented a Bayesian deep-learning approach for local SAR assessment. This approach allowed accurate local SAR estimations and returned reliable feedbacks on the error/uncertainty of the estimates for the MR examination scenario observed during training. However, it also showed the dangers of using the predicted uncertainty to identify out-of-training MR examination scenarios. In this study, we propose a simple approach to detect/reject potential erroneous local SAR predictions due to out-of-training transmit array and/or anatomical variations.
Numerical Simulation of Tissue Damage Due to Magnetically Induced Force for Multi-Configuration Passive Medical Devices
Authors: Ihsan Zainul , Schwarz Michael , Husain Mubashir , Schaefers Gregor
Published: August 2023

Numerical simulation was performed to evaluate tissue damage due to magnetically induced (MI) force in 3T Magnetic Resonance (MR) environment for multi-configuration passive medical devices. Static magnetic and mechanical simulations were employed to determine the impact of MI force on the tissue surrounding the implant. The simulation results were used to select the worst-case for passive medical devices and for quantitative assessment of the tissue damage.
Local SAR management strategies for RF shimming in fetal MRI at 3T
Authors: Yetisir Filiz , Turk Esra , Adalsteinsson Elfar , Grant Patricia , Wald Lawrence
Published: August 2023

RF shimming (RFS) improves the transmit field for fetal MRI, however, fetal safety is understudied. Previous simulations studied the SARlocal of the standard imaging mode (CP mode) of each subject to inform the safety of RFS. We evaluated two local SAR management strategies which utilize subject-specific models and use either the individual’s CP mode SARlocal as a limit for RFS or the maximum CP mode SARlocal value across 7 subjects. We evaluated the B1+ performance inside the fetus for each strategy. Using the maximum CP mode SARlocal across the population as the SAR limit greatly improves RFS performance.
Investigation of the Ability of Slot Element Metallization to Reduce SAR and RF Heating due to Associated Components
Authors: Alkandari Dheyaa , Wright Steven
Published: August 2023

Evidence indicates that excess RF power from coil’s associated circuitry could cause injuries to patients. Slot elements have been investigated earlier and demonstrated good potential when used for multi-channel RF coils. Here we investigate the potential of using the extended metallization of slot elements to shield stray electric field generated from RF coil associated circuitry. RF heating experiment was designed to compare the temperature of the phantom with and without using the slot’s extended metallization to shield the associated circuitry. Experimental results demonstrated an observable reduction in the phantom temperature resulting from extending the slots metallization.
Comparison of 2D vs 3D Deep Learning Algorithms to Estimate Temperature Throughout the Human Body
Authors: Carluccio Giuseppe , Montin Eros , Lattanzi Riccardo , Collins Christopher
Published: August 2023

We developed and compared two different Deep-Learning (DL) based approaches to approximating temperature in subject-specific body models. The first involved use of a 2D U-net to predict temperature throughout the body on a slice-by-slice basis, and the second involved use of a 3D U-net to predict temperature in the 3D body. The 3D approach greatly outperformed the 2D approach, and was very fast.
Altered Brain Activity and Functional Connectivity between Thalamus and Cortex in Vestibular Migraine: A Resting-State fMRI Study
Authors: Zhe Xia , Huang Yang , Tang Min , Ai Kai , Lei Xiaoyan , Zhang Xiaoling
Published: August 2023

To investigate the abnormal whole brain functional connectivity patterns in patients with VM by a fully data-driven resting-state functional connectivity methods without any hypothesis. Our findings indicated that whole brain amplitude of low-frequency fluctuation (ALFF) and connectivity abnormalities of these regions may be associated with functional impairments in pain information processing and modulation, transmitting and multisensory integration in patients with VM.
Impact of capillary transit time heterogeneity on resting-state BOLD-FC in patients with unilateral asymptomatic carotid artery stenosis
Authors: Schneider Sebastian , Archila-Meléndez Mario , Göttler Jens , Kaczmarz Stephan , Kufer Jan , Zott Benedikt , Priller Josef , Kallmayer Michael , Zimmer Claus , Sorg Christian , Preibisch Christine
Published: August 2023

Blood oxygenation level dependent functional connectivity (BOLD-FC) is commonly used as a proxy for neuronal connectivity. Therefore, aberrant BOLD-FC in brain disorders is typically interpreted as aberrant neuronal connectivity. However, beyond changes in neuronal connectivity, impairments in neurovascular coupling (NVC) may also impact on BOLD-FC. This study investigates how impaired local NVC, under conditions of preserved neural functioning, influences BOLD-FC in a sample of unilateral asymptomatic internal carotid artery stenosis patients and healthy age-matched controls. We show that timing aspects of local NVC, namely increased capillary transit time heterogeneity, reduces BOLD-FC, without changes in neuronal functioning.
Non-invasive measures of resting perfusion and hemodynamic compromise in patients with large vessel steno-occlusive disease
Authors: Sayin Ece Su , Duffin James , Poublanc Julien , Mikulis David , Fisher Joseph , Sobczyk Olivia
Published: August 2023

Dynamic susceptibility contrast perfusion measures using hypoxia-induced deoxyhemoglobin (dOHb) and BOLD-MRI-CO2 CVR reveals that patients with steno-occlusive disease can have the degree of hymodynamic compromise classified into two severities by the differences in hemodynamic measures at rest and in response to stress.
Graph theory demonstrates functional reorganization dynamics related to tumor grade and location in glioma
Authors: Pasquini Luca , Jenabi Mehrnaz , Peck Kyung , Holodny Andrei
Published: August 2023

Brain tumors lead to modifications of brain networks known as functional reorganization or plasticity, which may be compensatory in nature and lead to valuable clinical applications. However, the determinants of plasticity are unclear. We evaluated functional networks of 30 low-grade (LGG) and 30 high-grade (HGG) left-hemispheric gliomas versus 20 healthy controls (HC) through rs-fMRI and graph-theory. We hypothesized that tumor grade and location impact brain connectivity. Our results show that both LGG and HGG develop ipsilateral and contralateral functional network changes. Additionally, tumor location is crucial: frontal and temporal tumors show bilateral modifications; parietal and insular tumors only local effects.
Dynamic alterations of functional connectivity density in amyotrophic lateral sclerosis: a resting-state fMRI study
Authors: Shi Jia , Chen Hua
Published: August 2023

In this study, we made the first investigation on abnormal pattern of dynamic functional connection density (dFCD) in ALS. We gathered resting state functional magnetic resonance imaging (fMRI) data from 50 patients with ALS and 55 healthy controls (HC). dFCD was analyzed by sliding window correlation method; and the standard deviation of dFCD across the sliding window was calculated voxel-wisely to quantify dFCD variability. Our study has found abnormal dFCD variability in ALS. The indices of dFCD variability showed moderate discrimination power between two groups, suggesting its potential serving as the diagnostic biomarker for ALS.
Abnormal stability of dynamic functional architecture in amyotrophic lateral sclerosis: a preliminary resting-state fMRI study
Authors: Shi Jia , Chen Hua
Published: August 2023

Static and dynamic analyses for identifying functional connectivity(FC)have demonstrated brain dysfunctions in amyotrophic lateral sclerosis(ALS).We are to make the first attempt to perform studies about the stability of dynamic FC analysis based on resting-state fMRI data, in order to provide the new insight into the mechanism in ALS and investigate its correlation with disease severity. Our observation revealed that the abnormal pattern of FC stability involved sensorimotor regions(i.e.left precentral and postcentral gyrus)and non-sensorimotor areas(i.e.right temporal pole and middle/inferior frontal gyrus)in ALS patients, suggesting the potential of functional stability serving as the biomarker for monitoring disease progression in ALS.
Quantitative susceptibility mapping in the dynamic evaluation of renal ischemia-reperfusion injury in rabbits: a feasibility study
Authors: Luo Kai , Chen Jie , Zhang Jinggang , Dou Weiqiang
Published: August 2023

The purpose was to explore whether quantitative susceptibility mapping (QSM) can assess the dynamic process of renal ischemia-reperfusion injury (IRI) in rabbits. We found that the magnetic susceptibility values of the outer medulla were statistically significant among the IRI group. Additionally, the magnetic susceptibility values of the outer medulla was highly correlated with the pathological score of renal injury. With these findings, QSM could serve as a quantitative biomarker to assess the dynamic changes of the outer medulla in the early stage of renal IRI.
Real-Time Magnetic Resonance Imaging-Based Computational Modelling To Simulate Urine Flow In Urethra
Authors: Shahid Labib , Gonzalez-Pereira Juan Pablo , Johnson Cody , Roldán-Alzate Alejandro
Published: August 2023

Studying common urinary conditions such as BPH/LUTS require measuring urine flow in the urethra by invasive techniques. We present a method that uses real-time MR images of the bladder and urethra to quantify urine flow dynamics. Images of the urethra define the anatomical geometry, while images of the bladder inform the flow rate inside the urethra. Coupling MRI with CFD allows the urinary flow simulation inside the urethra providing information about urine velocity, pressure, and wall shear stress non-invasively.
Can we evaluate the progression from acute kidney injury to chronic kidney disease with sodium MRI and disease biomarkers?
Authors: Rasmussen Camilla , Bøgh Nikolaj , Thorsen Thomas , Bertelsen Lotte , Hansen Esben , Laustsen Christoffer
Published: August 2023

This study evaluates 23Na-MRI and renal injury disease biomarkers in a porcine model of unilateral renal ischemia-reperfusion injury. Pigs were distributed into groups of healthy controls, 2 ischemia times, and three survival times (n = 25). We found a significant difference between thecorticomedullary sodium gradients in pigs exposed to long ischemia. Neutrophil gelatinase-associated lipocalin (NGAL) was increased immediately after the ischemia-reperfusion injury regardless of the length of ischemia, but only remained elevated in the long-time ischemia group. Our results suggest a kidney injury model with the ability to differentiate between reversible and progressive acute kidney injury.
Tumor stiffness based on 3D MR Elastography as a marker for predicting the aggressiveness in cervical cancer
Authors: Xiao Yuanqiang , Chen Wenying , Li Mengsi , Chen Jun , Yin Meng , Ehman Richard , Wang Jin
Published: August 2023

Preoperative prediction of aggressiveness (histologic subtype, grade of differentiation, Federation International of Gynecology and Obstetrics (FIGO) stage) in cervical cancer (CC) using a noninvasive method remains a challenge. 3D MR Elastography (MRE) is a novel functional MRI technique which can quantitatively characterize the mechanical properties of tumors. We retrospectively analyzed 24 CC patients undergoing 3D MRE examinations and found that tumor stiffness (TS) in adenocarcinoma and FIGO stage III/IV was significantly higher than that in squamous cell carcinoma and FIGO stage I/II. TS based on 3D MRE could serve as a potential noninvasive marker to assess the aggressiveness in CC.
Quantifying confidence in the OE-MRI biomarker pOxy-R using bootstrap analysis
Authors: Little Ross , Parker Geoff , O'Connor James
Published: August 2023

OE-MRI is an emerging technique for identifying, mapping and quantifying tumour hypoxia. Current analysis is based on combining data with a perfusion map and categorising each voxel absolutely as hypoxic, normoxic or necrotic. In this study we use bootstrap analysis to map the uncertainty on the biomarker pOxy-R. We investigate how this performs in synthetic tumour data before applying the method to data from 9 patients with rectal cancer undergoing chemoradiotherapy. Bootstrapping enabled estimates of confidence intervals for change, thus identifying those patients who exhibited hypoxia modification on therapy.
3D Cartesian T1rho Magnetic Resonance Fingerprinting Sequence Design for Evaluation of Cartilage and Skeletal Muscle in the Knee
Authors: Eck Brendan , Kim Jeehun , Yang Mingrui , Ma Dan , Griswold Mark , Li Xiaojuan
Published: August 2023

Magnetic resonance fingerprinting offers a promising framework by which to rapidly quantify T1rho relaxation alongside other tissue properties such as T1 and T2. However, T1rho-MRF has only recently been reported and sequence optimization remains under-explored, particularly for 3D sequences. Using a digital phantom constructed from real knee tissue property maps, we investigate sequence parameters for a 3D Cartesian T1rho-MRF sequence including preparation pulse scheduling and timing, flip angles, number of readouts, and acceleration factor. T1, T2, and T1rho quantification errors in cartilage and skeletal muscle were evaluated.
Using 3D realistic blood vessel structures and machine learning for MR vascular Fingerprinting
Authors: Delphin Aurélien , Boux Fabien , Brossard Clément , Warnking Jan , Lemasson Benjamin , Barbier Emmanuel , Christen Thomas
Published: August 2023

MR vascular fingerprinting aims at mapping cerebral vascular properties such as blood volume and blood oxygenation. We propose to improve the technique by generating dictionaries based on 3D vascular networks segmented from whole brain high-resolution (3 µm isotropic) microscopy datasets. In order to compensate for the limited number of available data and long computing times, we used a machine-learning reconstruction process to generalize our results and tested our approach in healthy, stroke and tumor animal models. Our results show high quality maps with expected contrast and baseline values in healthy animals as well as expected trends in pathological tissues.
Fast distortionless T1-T2 mapping in the prostate using MR fingerprinting with radial acquisition and subspace reconstruction
Authors: Yu Victoria , Cohen Ouri , Wu Can , Subashi Ergys , Baumann Manuel , Koken Peter , Doneva Mariya , Zelefsky Michael , Cervino Laura , Otazo Ricardo
Published: August 2023

The application of MR fingerprinting in the prostate is challenging due to the presence of image distortions produced by B0 inhomogeneities. This works presents the combination of radial sampling to minimize the effects of B0 inhomogeneity and temporal subspace reconstruction to accelerate the acquisition for fast distortionless T1 and T2 mapping in the prostate in less than 4 minutes.
Reliable Quantification of Phosphocreatine and total Creatine during Deep Hypothermic Circulatory Arrest in Neonatal Pig Brain using LCModel
Authors: Gu Meng , Hurd Ralph , Spielman Daniel
Published: August 2023

Reliable in-vivo measurement of phosphocreatine using 1H MRS offers valuable information for understanding brain energy metabolism. At 3T, separate quantification of phosphocreatine and creatine has been challenging using LCModel. This problem exacerbates in studies of deep hypothermic circulatory arrest (DHCA), a technique used in many cardiac surgeries, due to temperature-dependent chemical shifts. Furthermore, total creatine quantification is hampered using a 37°C-only basis set as it fails to account for the increased polarization at lower temperatures. By using a semi-laser sequence with temperature dependent LCModel basis sets, reliable quantification of phosphocreatine and total creatine was achieved for the DHCA studies.
Monitoring the complexification of cerebellar and thalamic cells during early development with diffusion-weighted MR spectroscopy
Authors: Qiu Lily , Palombo Marco , Lerch Jason , Ligneul Clémence
Published: August 2023

Monitoring non-invasively the development of brain cells in the neonate and infant brain could be of interest for neurodevelopmental disorders. In this work, we assess whether diffusion-weighted MR spectroscopy (DWMRS) has the potential to follow cerebellar and thalamic cells development in the healthy rat brain from P5 to P30. Results show that DWMRS is sensitive to microstructural changes in the developing brain. The modeling of the data shows a cell growth and complexification (from P15 to P30), and underlies the need of different modeling hypotheses at earlier time points.
Comparison of Gradient Induced Peak E-fields on Simplified and Realistic Body Models
Authors: Ertan Koray , Decuzzi Paolo , Roemer Peter , Rutt Brian
Published: August 2023

Either peak E-fields on simple geometries with uniform interior properties as suggested by IEC or coupled E-field and neurodynamic simulations on realistic body models can be employed in PNS optimal gradient coil design. Magneto quasi-static simulations were performed to compare the magnitude and location of the peak E-fields in uniform interior body models with smoothed or realistic surface features to fully heterogeneous Virtual Family models. Although peak E-fields are higher on the heterogeneous body models due to complex tissue interfaces, simplified and/or homogeneous models represent a more practical and robust approach predicting population-wide PNS performance.
Excitation vector optimization for safe parallel transmission MRI of passively conducting implants in the presence of motion
Authors: Berangi Mostafa , Kuehne Andre , Waiczies Helmar , Niendorf Thoralf
Published: August 2023

MRI aided monitoring of (biodegradable) passively conducting implants is challenged by transmission field inhomogeneities and potential elevation of RF power deposition (SAR) in the vicinity of an implant. Small movements of an implant with respect to the RF transceiver constitute another potential risk factor for clinical MRI. Recognizing this challenge and the opportunities, this work uses a multi-objective genetic algorithm (GA) to examine the feasibility of excitation vector optimized parallel transmission in the presence of small variations in implant position/orientation. The GA approach provided excitation vectors that meet the safety guidelines for SAR in close vicinity of a (biodegradable) passively conducting implant and that are immune to small changes in the relative position between the implant and the RF transceiver. Our findings are not limited to the specific implant configurations and experimental setups used in this study but provide the technical foundation to derive a generalized transfer function.
When they go high, go low? (Maybe, but not so fast): Comparing RF heating of active implantable medical devices in 0.55 T vs. 1.5 T horizontal scanners
Authors: Sanpitak Pia , Bhusal Bhumi , Nguyen Bach , Jiang Fuchang , Kazemivalipour Ehsan , Bonmassar Giorgio , Pilitsis Julie , Rosenow Joshua , Webster Gregory , Popescu Andrada , Kim Daniel , Golestanirad Laleh
Published: August 2023

Low-field Magnetic Resonance Imaging (MRI) systems are gaining traction, but their impact on radiofrequency (RF) heating of elongated implants is unclear. The RF heating of conductive lead models with realistic trajectories was examined inside a 1.5 T MRI coil and a 0.55 T Wide Bore MRI coil. 0.1g-SAR was recorded at the tips of conductive implanted leads in adult patients with deep brain stimulation (DBS) systems and pediatric patients with cardiac implants, at both chest and head landmarks. In some instances, heating was higher in the 0.55 T coil, so caution must be exercised before promoting low-field coils as "implant-friendly".
MR Safety of Inductively-coupled and Conventional Intra-oral Coils
Authors: Tesfai Agazi , Reiss Simon , Lottner Thomas , Vollmer Andreas , Bock Michael , Özen Ali
Published: August 2023

Intraoral coils (IOCs) increase the signal-to-noise ratio in dental MRI exams several times over external coils. However, the intraoral coil placement might be associated with safety hazards such as RF heating. This study evaluates the safety of different IOCs using temperature and E-field measurements to detect temperature hotspots. An inductively-coupled and a wired IOC were constructed, E-field hotspots were detected and the temperature increase was measured showing that it remains below 1K over 6min RF exposure.
Microstructural changes in the grey matter of patients with visual snow syndrome: an ultra-high field morphological and quantitative MRI study
Authors: Strik Myrte , Clough Meaghan , Solly Emma , White Owen , Kolbe Scott , Fielding Joanne
Published: August 2023

Visual snow syndrome (VSS) is a neurological disorder characterized by continuous visual disturbances, and accompanied by a range of non-visual symptoms, including tinnitus and migraine. Little is known about the pathological mechanisms underlying VSS. In this study we assessed brain morphometry and microstructure in VSS patients using high-resolution structural (MP2RAGE, 0.75 mm iso) and quantitative (T1 mapping) 7T MRI. In VSS patients, we observed similar morphometry, but widespread changes in the grey matter microstructure (lower T1 values), which followed a caudal-rostral pattern affecting the occipital cortices most profoundly. Migraine did not appear to independently affect these changes.