bluuebunny/crossref_metadata_2025 huggingface dataset:
Resting-state single-vessel cerebral blood velocity by phase contrast fMRI
Authors: Jiang Yuanyuan , Hike David , Yu Xin
Published: August 2023

This research utilizes a novel high-resolution phase-contrast (PC) MRI method to measure resting-state fluctuation of cerebral blood flow-related velocity (CBFv) from penetrating vessels in the rat parietal cortex. This novel PC-based mapping scheme has identified vessel-specific correlation and anti-correlation patterns between venules and arterioles with the low-frequency oscillatory features less than 0.05Hz in anesthetized rat brains. By combining PC-based CBFv fMRI and single-vessel cerebral blood volume (CBV)-fMRI, we will further study the vasodynamic changes in diseased animal models.
Qualitative assessment of Ex-vivo Manganese-Enhanced MRI of gyrencephalic brains
Authors: Just Nathalie , Batailler Martine , Dubois Jean-Philippe , Migaud Martine
Published: August 2023

In-vivo Manganese-Enhanced MRI (MEMRI) studies have shown important potential in rodents for the delineation of cytoarchitectural brain features and of functional details. Ex-vivo MEMRI on the other hand offers the possibility to investigate brain microstructure and function with improved spatial resolution and no motion artefacts. Here, ex-vivo lamb brains were immersed in a highly concentrated MnCl2 solution for a month and revealed interesting cytoarchitectural features already 24 hours after immersion and up to 3 months after the end of immersion on MPRAGE images at 3T. A novel ex-vivo MEMRI approach is proposed, which could benefit MEMRI translation to human studies.
Selective galactose culture condition reveals distinct metabolic signatures in complex I and V deficient human skin fibroblasts by 1H HR-MAS NMR
Authors: Meyer Christoph , Hertig Damian , Urzi Christian , Arnold Janine , Nuoffer Jean-Marc , Vermathen Peter
Published: August 2023

Mitochondrial respiratory chain defects present as highly heterogeneous disorders which cannot be unambiguously diagnosed using standard laboratory methods. In this study we observed the biochemical consequences of complex I and complex V deficient human skin fibroblasts when cultivated under galactose stress condition compared to glucose based cell culture condition. We investigated extracellular flux using Seahorse XFe96 cell analyzer and assessed the metabolome fingerprints using High Resolution Magic Angle Spinning NMR. The selective culture method reveals CI and CV defect-specific changes in metabolites associated with the TCA cycle, malate aspartate shuttle and choline metabolism.
Cross-Linked Protoporphyrin IX polymer as Efficient, Tunable CEST MRI NanoPlatform for molecular Imaging
Authors: Zhang Xiaoxiao , Wu Zhigang , Sun Peng , Shen Zhiwei , Lin Liangjie , Hu Geli , Huang Haoyu , Wang Jiazheng
Published: August 2023

CEST MRI is an novel molecular imaging technique in which the contrast is generated by the dynamic exchange between the exchangeable proton and water. Porphyrin and its analogues are a promising class of highly sensitive, diamagnetic CEST agents with highly upfield shifted protons. We synthesized a water-soluble polymeric CEST MRI agent grafted with protoporphyrin IX(PpIX). The PpIX polymeric agent resonated at -13.5 ppm from water and showed excellent CEST MRI properties.
Hyperpolarising 13C-glucose with an endogenous labile photoinduced radical
Authors: Lewis Jennifer , Gaunt Adam , Marco-Rius Irene , Comment Arnaud
Published: August 2023

The use of the endogenous molecule alpha-ketoglutarate (α-KG) as a non-persistent radical is examined to hyperpolarise 13C-glucose. A radical build-up curve was obtained and the maximum radical concentration was calculated to be 29 ± 3 mM. The microwave irradiation frequency was then examined to optimise the polarisation transfer between the electron on α-KG and glucose. A dissolution was successfully carried out and a hyperpolarised 13C spectrum of 13C-glucose was obtained.
Recurrent Variational Inference for fast and robust reconstruction of accelerated FLAIR MRI in Multiple Sclerosis
Authors: Karkalousos D. , Liebrand L. , Noteboom S. , Hulst H. , Vos F. , Caan M.
Published: August 2023

Robustness when applying Deep Learning methods to clinical data is crucial for accurate high-resolution reconstructions while having fast inference times. We propose the Cascades of Independently Recurrent Variational Inference Machine (CIRVIM), targeting deep unrolled optimization and enforcing data consistency for further robustness. We quantify contrast resolution of seven and half times prospectively undersampled FLAIR MRI without fully-sampled center containing Multiple Sclerosis lesions. The proposed scheme reduces inference times by a factor of 6 compared to Compressed Sensing. Lesion contrast resolution improves by approximately 13% while preserving spatial detail with enhanced sharpness compared to more blurred results of other presented methods.
Abdominal 3D-T1-weighted imaging with the radial MP2RAGE sequence.
Authors: MAINGAULT François , CORBIN Nadège , LEFRANÇOIS William , TROTIER Aurélien , MIRAUX Sylvain , RIBOT Emeline
Published: August 2023

The Magnetization Prepared Two RApid Gradient Echo (MP2RAGE) sequence with a cartesian sampling is performed to obtain 3D-T1 weighted images of the brain. A radial encoding giving a better robustness to respiratory motion has been implemented in order to use the MP2RAGE sequence for abdominal imaging.
Optimal Parameter Selection for 3D Radial Density Adapted Trajectories
Authors: Bydder Mark , Ali Fadil , Saucedo Andres , Wang Chencai , Hagiwara Akifumi , Pham Alex , Yao Jingwen , Ellingson Ben
Published: August 2023

The present article develops an understanding of how to choose optimal (or at least reasonable) parameter values for 3D radial density adapted sampling. This has a practical role in designing clinical protocols for short TE non-Cartesian imaging.
Diffusion metrics in human white matter depend on fiber orientation
Authors: Bartels Lara , Doucette Jonathan , Birkl Christoph , Weber Alexander , Rauscher Alexander
Published: August 2023

In this work we studied the orientation dependence of diffusivities measured in DTI of healthy human white matter in vivo. The observed orientation dependence of the mean diffusivity can be explained by the effects of diffusion-mediated dephasing in the presence of diamagnetic myelin. Orientation dependence was markedly different for the radial and axial components of the diffusivity and suggests the presence of residual dipole-dipole interaction between water molecules.
The impact of head orientation with respect to B0: An unexplored source of variance in diffusion MRI
Authors: Kleban Elena , Jones Derek , Tax Chantal
Published: August 2023

Recently observed anisotropy of compartmental white matter T2-values as a function of tissue orientation w.r.t. B0 in combination with echo-time-dependence of diffusion MRI signals suggest that similar tissue-orientational effects could be expected in standard diffusion tensor measures. In this work we show the change of up to 20-30% in diffusion tensor measures as a function of fibre orientation w.r.t. B0 from in vivo experiments and support these observations by simplified two-compartment white matter signal simulations.
Multi-Spectral Susceptibility-Weighted Imaging in the Presence of Metallic Hardware
Authors: Koch Kevin , Swearningen Brad , Nencka Andrew
Published: August 2023

To address the unmet need for metal artifact suppressed susceptibility-weighted imaging (SWI) in neuroradiology, here we introduce a novel approach to the generation of SWI contrasts using conventional (currently available) 3D-multi-spectral imaging (MSI) metal-artifact-suppression sequences. This approach leverages basic spin-echo based 3D-MSI sequences, and then utilizes the inherent spectral information within MSI to develop "phase-contrast" maps that can then used to generate SWI-like contrasts. This new metal-suppressed SWI approach has potential applications in patients with high susceptibility intra-cranial hardware, such as aneurysm clips, vascular shunts, cochlear implants, and fixed dental/orthodontic hardware.
Nonlinear multi-echo dipole inversion
Authors: Kames Christian , Doucette Jonathan , Rauscher Alexander
Published: August 2023

We propose a two-pass multi-echo nonlinear dipole inversion method. In the first pass an initial susceptibility map is obtained. The susceptibility map is then further processed by deconvolving the residual of the forward computed phase and the input phase to recover remnant low frequency susceptibility sources. The proposed method attains a NRMSE of 18.8 on the QSM Reconstruction Challenge 2.0 calcification dataset (Sim2Snr1), decisively outperforming the best scoring submissions of the challenge (NRMSE 26.3, 28.3, 28.5).
Longitudinal changes in fMRI brain fingerprints of asymptomatic high school American football athletes
Authors: Fitzgerald Bradley , Bari Sumra , Vike Nicole , Lycke Roy , Auger Joshua , Nauman Eric , Goni Joaquin , Talavage Thomas
Published: August 2023

We used resting state functional MRI data to investigate whether asymptomatic high school American football athletes undergo functional connectome (FC) changes during exposure to head acceleration events (HAEs). FCs of asymptomatic high school football athletes were shown to undergo significant changes during the season and then return to their pre-season state after the conclusion of collision activities, with changes reflected most profoundly in the somatomotor network. Late-season changes appear to affect all athletes without association with the magnitude of HAEs experienced. These observations demonstrate that participation in American football can cause significant changes in brain functionality without manifesting symptoms.
Topological organization effects of different theta burst stimulation protocols over precuneus in healthy adults
Authors: Li Xue , Xu Xin , Xi Jiang , Huang Xiaoqi , Xing Haoyang
Published: August 2023

This study explored the seed-based functional connectivity (FC) and topological organization alteration applied different TBS protocols over precuneus in healthy adults. Increased FC were found in sensorimotor network and insula after application of iTBS or cTBS, decreased FC in left thalamus was found after cTBS. Only cTBS induced significant topological alterations in whole-brain network characterized by small-worldness on FC and functional topology organization, The findings suggested distal effects were complicated and could not been simply summarized as inhibition/facilitation like as proximal rTMS effects. This study may help to elucidate the underlying mechanisms of information transmission through brain function connectivity.
Structural and resting-state functional connectivity changes due to chronic noise exposure
Authors: Kumaran S Senthil , Ankeeta A , Singh Himanshu , Chauhan Nisha
Published: August 2023

The effects of cumulative lifetime noise exposure on ascending auditory pathway function in audio metrically normal individuals is explored by sustained and transient fMRI responses and related auditory brainstem response (ABR). The experiment included continuous (scanner noise) and deviant noise (additional pink noise) levels that affected mental workload and auditory/visual attention. Our results exhibited reduced attention and mental workload in central auditory regions in people exposed to higher noise (>85dBA) in comparison with those exposed to lesser noise (<85dBA).
Static and dynamic connectivity are differentially affected by head motion: a healthy control and Parkinson’s disease study
Authors: Saviola Francesca , Tambalo Stefano , Cabalo Donna , Novello Lisa , Pierotti Enrica , Dodich Alessandra , Papagno Costanza , Turella Luca , Van De Ville Dimitri , Jovicich Jorge
Published: August 2023

An open discussion in functional connectivity (FC) studies is the mitigation of motion-related artifacts. Data-driven denoising such as Independent Component Analysis (ICA) could help in improving the reproducibility of results, however, the definition of pipelines to deal with mild to high motion cases is still controversial. We estimate the effect of different workflows optimized for best-controlling head motion both in healthy and Parkinson’s Disease cohorts. Regardless of baseline head motion level, ICA-based control of motion confounds affects functional connectivity metrics, with non-negligible impact on static connectivity and most severe effects on temporal and spatial features of dynamic functional connectivity measures.
Abnormal static and dynamic functional network connectivity in patients with capsular stroke based on the triple-network model.
Authors: Wang Yingying , Wang Caihong , Miao Peifang , Wei Ying , Wu Luobing , Cheng Jingliang , Guo Jingxia
Published: August 2023

To explore the mechanisms of cognitive impairment and reorganization in patients with left- and right-sided capsular stroke (CS_L, CS_R), we collected resting-state fMRI data from 62 CS_L, 56 CS_R patients and 57 normal controls (NC). Based on the triple-network model [involving the default mode, central executive and salience networks], static (SFNC) and dynamic functional network connectivities (DFNC) were performed to calculate inter-network functional connectivities and estimate temporal features in each state among the three groups. We found more significant SFNC and DFNC changes in CS_R group, suggesting more extensive cognitive impairment and reorganization in CS_R patients than those with CS_L.
Renal T2-mapping with a T2-preparation sequence: comparison of signal models
Authors: Periquito Joao , Sharma Kanishka , Alhummiany Bashair , Sousa Joao , Sourbron Steven
Published: August 2023

A recent consensus paper recommends a mono-exponential signal model to determine T2-values from a T2-preparation sequence. However, this assumes complete signal recovery after each readout, and therefore necessitates long acquisition times. In this study, we compare the mono-exponential model against a forward modelling approach which is also accurate with incomplete recovery. Simulations, phantom data and repeatability data in healthy volunteers show the forward model is significantly more accurate and allows for a 7-fold reduction in acquisition time with a negligible cost in T2 precision.
Evaluating renal fibrosis in a nephrotoxic nephritis model using DTI-MRI
Authors: Avraham Shimrit , Virgincar Rohan , Webster Joshua , Shaw Andrey , Xie Luke
Published: August 2023

Accurate estimation of kidney function is crucial to the detection, evaluation, and treatment of chronic kidney disease (CKD). The traditional methods are inaccurate or invasive. Here, we used DTI-MRI to evaluate kidney function with disease progression in nephrotoxic serum- induced CKD model (NTN). We detect changes associated with renal inflammation and fibrosis prior to functional decline. Moreover, AD and ADC of the cortex-outer medulla border were highly correlated with histologic evidence of fibrosis. These results suggest that DTI-MRI can detect early stages of CKD non-invasively in-vivo and can be used for fibrosis mapping in a variety of renal diseases.
Spatial Heterogeneity in Quantitative Renal ADC, ASL perfusion and R2* Maps Using Texture Analysis
Authors: Li Lu-Ping , Wilt Emily , Mikheev Artem , Rusinek Henry , Sprague Stuart , Kohn Orly , Prasad Pottumarthi
Published: August 2023

While regions of interest analysis is widely used in quantitative MRI, emphasis usually is placed only on the spatial average and information of spatial heterogeneity is ignored. Texture analysis has gained increasing interest in the context of applying artificial intelligence. These Radiomic tools are now readily available in image analysis tool boxes for more widespread adoption. We illustrate an application of such analysis on quantitative renal MRI, including ADC, ASL and R2* maps. Our results show that several measures of heterogeneity of cortical voxel-wise maps discriminate between healthy and individuals with chronic kidney disease.
Velocity-compensated optimized diffusion encoding in respiratory-triggered renal ADC mapping
Authors: McTavish Sean , Van Anh , Peeters Johannes , Weiss Kilian , Makowski Marcus , Braren Rickmer , Karampinos Dimitrios
Published: August 2023

Diffusion-weighted imaging (DWI) and ADC mapping remains a potential biomarker for the assessment of renal fibrosis in chronic kidney disease and characterization of renal carcinoma. However, for body DWI applications including renal DWI, motion effects can confound the robustness of abdominal DWI. Motion-compensated diffusion encoding designs have been proposed as alternatives in overcoming the effect motion in other organs such as the liver and the pancreas. The purpose of this work is to assess the effect of respiratory motion and to apply motion compensated diffusion encoding waveforms in the context of coronal respiratory-triggered ADC mapping in the kidney.
Stiffening of renal transplants after donation assessed by MR elastography – physiological adaption from donor to recipient
Authors: Garcia Stephan Marticorena , Friederdorff Frank , Mang Josef , Webster Alexandra , Hamm Bernd , Braun Jürgen , Sack Ingolf
Published: August 2023

Renal stiffness was investigated by using magnetic resonance elastography (MRE) with tomoelastography-postprocessing in 24 participants (12 renal donor-recipient couples) to explore the influence of kidney transplantation on renal viscoelasticity for the first time. Renal stiffness increases immediately after transplantation. These early changes could be due to changes in renal perfusion and increase in renal metabolism, which is also reflected by increase in renal volume. Cold ischemia time was found in being a contributor to changes of solid renal structures. Inccrease in renal stiffness after transplantation could be a novel predictive biomarker for better renal outcome.
Quantitative evaluation of renal injury in the early chronic kidney disease with quantitative susceptibility mapping
Authors: Jiayuan Shan , Jinggang Zhang , Jie Chen , Wei Xing , Yishi Wang , Jilei Zhang
Published: August 2023

To explore the value of quantitative susceptibility mapping (QSM) in evaluating renal injury in patients with chronic kidney disease (CKD). 40 CKD patients were included in the study to evaluate the potential clinical value of QSM. We found that with the progress of CKD staging, renal medulla susceptibility values decreased significantly. Susceptibility value of the medulla was highly correlated with estimated glomerular filtration rate (eGFR). QSM could serve as a quantitative biomarker to assess the renal injury of early CKD.
Tumor infiltration beyond contrast enhancement and FLAIR hyperintensity at autopsy predicts survival in glioblastoma patients
Authors: Bobholz Samuel , Lowman Allison , Brehler Michael , Duenweg Savannah , Sherman John , Kyereme Fitzgerald , Cochran Elizabeth , Coss Dylan , Connelly Jennifer , Mueller Wade , Agarwal Mohit , Banerjee Anjishnu , LaViolette Peter
Published: August 2023

This study compared autopsy tissue samples to clinical MRI from glioblastoma (GBM) patients to assess the effects of tumor outside of T1-contrast enhancement and FLAIR hyperintensity on clinical characteristics and outcomes. Non-enhancing tumors were more frequent amongst patients who had a history of bevacizumab treatment and no history of Tumor Treating Fields treatment. Additionally, non-enhancing tumors were associated with shorter overall survival times. These results suggest that non-enhancing tumors have clinically significant correlates and may result in worse survival outcomes for GBM patients.
A multi-task generative network for simultaneous post-contrast MR image synthesis and tumor segmentation: application to brainstem glioma
Authors: Zhang Yajing , Xiong Xiangyu , Liu Yaou
Published: August 2023

To reduce the exposure of Gadolinium-based Contrast Agents (GBCAs) in brainstem glioma detection and provide high-resolution contrast information, we propose a novel multi-task generative network for contrast-enhanced T1-weight MR synthesis on brainstem glioma images. The proposed network can simultaneously synthesize the high-resolution contrast-enhanced image and the segmentation mask of brainstem glioma lesions.
Value of diffusion and intravoxel incoherent motion virtual MR elastography in differentiating benign and malignant focal liver lesions
Authors: Zhang Yuelang , Li Xiang , Li Chenxia , Cui Ting , Wang Jinhan , Xing Shuo , Li Xianjun , Yang Jian
Published: August 2023

Diffusion and IVIM virtual MR elastography (dMRE) provides quantitative estimates of tissue stiffness without using mechanical vibrations. It rarely applied to identify focal liver lesions (FLL). This retrospective study included 21 subjects (11 malignant lesions and 10 benign lesions). DWI were obtained to calculating dMRE. The kPa values of malignant FLLs (7.93 ± 2.37) was significantly higher than that of benign FLLs (-0.28±5.37) (P < 0.01). ROC showed an AUC of 0.93 for dMRE in differentiating maglinant FLLs and benign FLLs. The sensitivity and specificity were 91% and 90%, respectively. Malignant lesions could be distinguished from benign FLLs by dMRE.
Tailored MR fingerprinting of pediatric brain tumor patients
Authors: Poojar Pavan , Qian Enlin , Maddocks Alexis , Geethanath Sairam
Published: August 2023

We demonstrated the utility of tailored MR fingerprinting (TMRF) of pediatric patients with brain tumor to 1) differentiate tumor from healthy tissue using quantitative maps; 2) tailor TMRF sequence to include T2 fluid-attenuated inversion recovery (FLAIR) contrast that could potentially substitute T2 FLAIR sequence used in routine pediatric tumor protocol. The mean土SD difference in T1 and T2 values between tumor and normal tissues for 3 patients were 1.05土0.09 and 0.05土0.02 seconds respectively. The TR and flip angle trains were tailored to include T2 FLAIR contrast for adult imaging. Current and future work includes optimizing T2 FLAIR for the pediatric population.
Combining Region-optimized virtual coils with low rank reconstructions for accelerated cardiac MR Fingerprinting
Authors: Cruz Gastao , Phair Andrew , Velasco Carlos , Botnar René , Prieto Claudia
Published: August 2023

Cardiac Magnetic Resonance Fingerprinting (MRF) produces co-registered, multi-parametric maps from highly accelerated acquisitions. Low rank methods leveraging temporal information have enabled highly undersampled MRF reconstructions. However, residual aliasing from these reconstructions can potentially propagate through the MRF framework into the parametric maps. Region-Optimized Virtual coils have recently been proposed for undersampled reconstructions in conventional imaging, by suppressing unwanted sources of aliasing signal. Here we combine both methods and investigate its performance in Cardiac Magnetic Resonance Fingerprinting.
Joint sparsity multi-component MRF reconstruction - directly from k-space to component maps
Authors: Nagtegaal Martijn , Hartsema Emiel , Koolstra Kirsten , Vos Frans
Published: August 2023

The use of high undersampling factors and short flip angle trains leads to shorter acquisition times in MR Fingerprinting acquisitions. To obtain accurate multi-component estimates from this data advanced reconstructions are required. We study a low-rank ADMM based reconstruction method that adds a multi-component constraint to the inverse reconstruction problem (MC-ADMM). This method is combined with a joint-sparsity constraint yielding higher quality multi-component estimates with k-SPIJN than with previous methods. In simulations we observed increased stability to sequence truncation and in vivo multi-component estimates contained less noise-like effects.
3D magnetic resonance fingerprinting at 50 mT with integrated estimation and correction of image distortions due to B0 inhomogeneities
Authors: O'Reilly Thomas , Börnert Peter , Webb Andrew , Koolstra Kirsten
Published: August 2023

Strong B0 inhomogeneities in compact point-of-care low field permanent magnet systems can cause image distortions and reduced signal for large field-of-view images. MRF, as a flexible acquisition framework, can encode these effects into the acquisition process, to incorporate them into the reconstruction process. In this work, we use an alternating TE in the MRF sequence that supports ΔB0 estimation and image distortion correction of the MRF data. This method reduces distortions in the relaxation time maps without needing to acquire an additional ΔB0 map.
Learning-based prediction of encoding capability for acquisition schedule of Magnetization Transfer Contrast MR fingerprinting
Authors: Kang Beomgu , Heo Hye-Young , Park Hyunwook
Published: August 2023

Magnetization transfer contrast MR fingerprinting (MTC-MRF) is used to quantify multiple tissue parameters of free bulk water and semisolid macromolecule using pseudo-randomized MRF schedules. An optimal design of the MRF schedule is important to improve the quantification accuracy and reduce the scan time. However, lack of the objective function that represents the encoding capability of MRF schedule hinders the reliable optimization. In this study, we propose a novel metric that represents the encoding capability of MRF schedule based on recurrent neural network. Unlike the conventional metrics based on indirect measurements, the proposed learning-based metric directly measures the tissue quantification errors.
Predicting PDFF and R2* from Magnitude-Only Two-Point Dixon MRI Using Generative Adversarial Networks
Authors: Basty Nicolas , Thanaj Marjola , Cule Madeleine , Sorokin Elena , Thomas E. , Bell Jimmy , Whitcher Brandon
Published: August 2023

We implement generative adversarial network (GAN) models to predict fully quantitative parameters from a complex-valued multiecho MRI sequence using only data from the magnitude-only two-point Dixon acquisition in the UK Biobank abdominal protocol. The training data consists of in- and opposed-phase channels from the Dixon sequence as inputs and the proton density fat fraction (PDFF) and R2* parameter maps estimated from the IDEAL acquisition as outputs. We compare conditional and cycle GANs, where the conditional GAN models outperformed the cycleGAN models in SSIM, PSNR and MSE. PDFF predictions were better than R2* predictions for all models.
Macromolecular background signals for gray and white matter regions in the human brain as defined from strong diffusion-weighted MR spectroscopy
Authors: Simsek Kadir , Döring André , Pampel André , Möller Harald , Kreis Roland
Published: August 2023

Diffusion-weighted MRS was successfully implemented at short TE, reaching ultra-high b values >20 ms/μm2 on a 3T Siemens Connectom system. With simultaneous fitting for different b-value spectra, macromolecular background patterns are estimated using different approaches to model metabolite diffusion and different macromolecular signal parameterization in gray matter and white matter.
An extended version of the restricted SAR protocol allowing safe in vivo testing of RF coils in an unconditional and flexible way
Authors: Dudysheva Natalia , Amadon Alexis , Vignaud Alexandre , Abdeddaim Redha , Mauconduit Franck
Published: August 2023

This work promotes the RF coil elaboration facilitating its in-vivo testing phase. To exclude patient risk, in-vivo studies with each new coil configuration require prior SAR verifications and commission approval lengthening the design process. The so-called “Restricted SAR” (rS) protocol offers a solution to safely use homemade coils in vivo at any development stage without prior validation. This protocol constrains transmitted RF power and automatically respects the SAR safety limits, whatever the SAR distribution. Here, we propose the extended rS protocol with flexible sequence parametrization. This adjustability offers better B0 mapping coverage, optimal B1+-map estimation, and higher spatial image resolutions.
Variability of the specific absorption rate in the child’s head using a transmit array head coil at 7T: a simulation study
Authors: Delbany Maya , Luong Michel , Morel Laurent , Adam Jean-Pierre , Joly Jean-Christophe , Gras Vincent
Published: August 2023

In this study, a 3T MRI database is used to create numerical children’s head models in order to study the variability of the specific absorption rate in the head of children at 7T using a transmit array head coil. These numerical models are integrated in a homemade multi-transmit RF coil model and then used to simulate SAR maps in the head using a finite difference time domain solver called GORF.
Frequency, pattern, and associations of renal iron accumulation in sickle/beta-thalassemia
Authors: Meloni Antonella , Barbuto Luigi , Positano Vincenzo , Pistoia Laura , Fina Priscilla , Peritore Giuseppe , Zerbini Michela , Restaino Gennaro , Gerardi Calogera , Tedesco Letizia , Maddaloni Domenico , Cademartiri Filippo , Pepe Alessia
Published: August 2023

Sickle/beta-thalassemia and homozygous sickle cell disease (HbSS) patients were rather similar in respect to hepatic, pancreatic and cardiac iron deposition detected by the T2* MRI technique, but sickle/β-thalassemia patients had significantly less renal iron overload. In sickle/beta-thalassemia renal T2* values were not associated to age, gender, splenectomy, transfusions, serum ferritin levels or iron load in the liver, pancreas and heart, suggesting that performing MRI T2* in other organs is not a reliable approach to predict the exact renal iron state. Renal T2* values were inversely correlated with serum lactate dehydrogenase, confirming that kidney iron results from chronic hemolysis.
MRI-based Assessment of Urethral Biomechanics During Voiding
Authors: Johnson Cody , Kounga Maxwell , Gonzalez-Pereira Juan , Wells Shane , Bushman Wade , Roldán-Alzate Alejandro
Published: August 2023

Non-invasive methods to evaluate voiding dysfunction in men are extremely limited. We report here a non-invasive, MRI-based protocol to characterize urethral biomechanics during voiding. All four subjects were able to void in the scanner with high-fidelity, 3D images of the urethra. These images were successfully analyzed for anatomy, function, and biomechanics. Future work will be aimed at furthering these methods and resulting metrics so that they may be applied clinically.
Automatic 3D bladder segmentation from low-field MR images using 3D U-Net
Authors: Straetemans Lianne , Alblas Dieuwertje , Morsinkhof Lisan , Wolterink Jelmer , Simonis Frank
Published: August 2023

Pelvic organ prolapse (POP) is a common problem in women, but little is known about treatments. Automatic 3D segmentation of pelvic organs would be useful for improving research in this area. This study successfully applies a 3D U-Net for automatic bladder segmentation of upright and supine low-field MRI scans from asymptomatic women. The resulting network will probably also perform well on data from POP patients. Further improvements are expected when the training data is completed. Future work will focus on segmentation of additional pelvic organs.
Combination of IVIM with DCE-MRI in diagnostic and prognostic evaluation of breast cancer
Authors: zheng Yurong , Li Li , Wang Rui , Gan Tiejun , Wang Pengfei , Zhang Jing , Ai Kai
Published: August 2023

Intravoxel incoherent motion (IVIM) combined with Dynamic Contrast Enhanced MRI (DCE-MRI) are meaningful MRI techniques applied to breast cancer. This study uses DCE-derived parameters (voiume translocation constant, Ktrans and rate constant, Kep) and IVIM-derived parameters (diffusion coefficient, D and perfusion fraction, f) to perform correlation analysis with prognosis of breast cancer indexes (ER, PR, her-2, Ki-67). The results show that IVIM and DCE-MRI can distinguish benign and malignant breast lesions. Therefore, there are correlation between Ktrans, Kep, D and prognostic factors of breast cancer. Our research may provide more important clinical evidence for the treatment and prognosis of breast cancer.
Quantifying and mapping hypoxia modification in patients with uterine cervical cancer using oxygen-enhanced MRI
Authors: Datta Anubhav , Dubec Michael , Buckley David , McHugh Damien , Salah Amal , Little Ross , Berks Michael , Cheung Susan , West Catharine , Choudhury Ananya , Barraclough Lisa , Hoskin Peter , O'Connor James
Published: August 2023

Hypoxia is a ubiquitous negative prognostic factor in solid tumours. Oxygen-enhanced MRI can spatially map regions refractory to an oxygen challenge and, when combined with a perfusion measurement, has the potential to quantify hypoxia in vivo. We developed the technique in healthy volunteers before successfully translating into a longitudinal patient study of patients with cervical carcinoma. We present initial data to support OE-MRI quantifying and mapping hypoxia modification following therapy in this clinical dataset.
Quantitative T1 and T2 measurements of metastatic bone lesions in prostate cancer patients: MR fingerprinting versus standard quantitative MRI
Authors: Rata Mihaela , Tunariu Nina , Jiang Yun , Hughes Julie , Hopkinson Georgina , Scurr Erica , Winfield Jessica , Gulani Vikas , Koh Dow-Mu , Orton Matthew
Published: August 2023

Magnetic resonance fingerprinting (MRF) generates fast, co-registered quantitative maps from a single acquisition. This prospective study evaluates MRF-derived measures of treatment-induced T1 and T2 changes in prostate cancer patients with metastatic bone disease, by comparison with existing quantitative T1 and T2 measurements. This study demonstrated a good correlation of MRF-derived T1 and T2 changes with existing quantitative methods, supporting the use of MRF for faster measurements in bone lesions.
Towards A Clinical Prostate MR Fingerprinting Protocol
Authors: Baumann Manuel , Keupp Jochen , Mazurkewitz Peter , Koken Peter , Nehrke Kay , Meineke Jakob , Amthor Thomas , Doneva Mariya
Published: August 2023

We present an efficient MR Fingerprinting (MRF) protocol for prostate imaging at 3T. Full prostate coverage is achieved in 04:20 min with no considerable reconstruction latency. Dixon-MRF has been implemented in the scanner software and combined with a B1+ DREAM scan in a fully-integrated B1-corrected MRF reconstruction. Furthermore, flow compensation is included to suppress artifacts caused by blood flow in large vessels. The proposed prostate MRF protocol has been evaluated in six healthy volunteers.
Incorporating saturation bands into MR Fingerprinting reduces streaking artefacts
Authors: Trimble Christopher , Sørland Kaia , Sandsmark Elise , Elschot Mattijs , Bathen Tone , Cloos Martijn
Published: August 2023

Magnetic Resonance Fingerprinting (MRF) enables fast quantitative MR imaging, which is appealing in prostate cancer diagnostics. In pelvic MR Fingerprinting, blood flow in the femoral vessels causes strong streak-like artefacts when a radial sampling strategy is used. Here we develop a strategy to incorporate saturation bands into MRF sequences. Our phantom study shows quantification of areas outside the saturation band are not significantly affected. Meanwhile, qualitative analysis of in vivo experiments indicates a marked reduction in streak intensity when saturation is applied.
Dictionary variance based optimization of MR Fingerprinting
Authors: Boyacioglu Rasim , Huang Sherry , McGivney Debra , Chen Yong , Griswold Mark
Published: August 2023

This study presents an optimization tool to investigate and validate the effects of MR sequence modules on MR Fingerprinting. Dictionary variance across the tissue property dimension can predict the outcome of a given change in an MRF sequence. An MRF sequence variant is optimized by varying three typical MRF sequence blocks of FA pattern, RF phase and inversion pulses. The observations from the dictionary variance align with in vivo data results.
Using Machine Learning to Identify Metabolite Spectral Patterns that Reflect Outcome after Cardiac Arrest
Authors: Louis Marcia Sahaya , Liao Huijun Vicky , Singh Rohit , Joshi Ajay , Lee Jong Woo , Lin Alexander
Published: August 2023

More than half of patients who undergo targeted temperature management (TTM) after cardiac arrest do not survive hospitalization and 50% of those survivors suffer from long-term cognitive deficits. The goal of this study is to use machine learning methods to characterize the pattern of metabolic changes in patients with good and poor outcomes after cardiac arrest. A machine learning pipeline that incorporates z-scores, decision-tree modeling, principal component analysis, and linear support vector machine was applied to MR spectroscopy data acquired after cardiac arrest. Results confirm that N-acetylaspartate and lactate are important markers but other unexpected findings emerged as well.
Spherical-CNN based diffusion MRI parameter estimation is robust to gradient schemes and equivariant to rotation
Authors: Goodwin-Allcock Tobias , Gray Robert , Nachev Parashkev , McEwan Jason , Zhang Hui
Published: August 2023

We demonstrate the advantages of spherical convolutional neural networks over conventional fully connected networks at estimating rotationally invariant microstructure indices. Fully-connected networks (FCN) have outperformed conventional model fitting for estimating microstructure indices, such as FA. However, these methods are not robust to changes diffusion weighted image sampling scheme nor are they rotationally equivariant. Recently spherical-CNN have been supposed as a solution to this problem. However, the advantages of spherical-CNNs have not been leveraged. We demonstrate both spherical-CNNs robust to new gradient schemes as well as the rotational equivariance. This has potential to decrease the number of training datapoints required.
Isolating cardiac-related pulsatility in blood oxygenation level-dependent MRI with deep learning
Authors: Valsamis Jake , Luciw Nicholas , Haq Nandinee , Atwi Sarah , Duchesne Simon , Cameron William , MacIntosh Bradley
Published: August 2023

Persistent exposure to highly pulsatile blood can damage the brain’s microvasculature. A convenient method for measuring cerebral pulsatility would allow investigation into its relationship with vascular dysfunction and cognitive decline. In this work, we propose a convolutional neural network (CNN) based deep learning solution to estimate cerebral pulsatility using only the frequency content from BOLD MRI scans. Various frequency component inputs were assessed, and echo time dependence was evaluated with a 5-fold cross-validation. Pulsatility was estimated from BOLD MRI data acquired on a different scanner to assess generalizability. The CNN reliably estimated pulsatility and was robust to various scan parameters.
Image enhancement of Quasi-Diffusion Imaging using a fully connected neural network
Authors: Storey Ian , Spilling Catherine , Ye Xujiong , Barrick Thomas , Howe Franklyn
Published: August 2023

A fully connected neural network (FCN) was trained to map a short diffusion weighted image acquisition to high quality Quasi-Diffusion Imaging (QDI) parameter maps. The FCN produced denoised and enhanced QDI parameter maps compared to weighted least squares fitting of data to the QDI model. The FCN shows generalisation to unseen pathology such as grade IV glioma dMRI data and demonstrates the FCN can produce high quality QDI tensor maps from clinically feasible 2 minute data acquisitions. An FCN further enhances the ability of QDI to provide non-Gaussian diffusion imaging within clinically feasible acquisition times.
Hybrid supervised and self-supervised deep learning for quantitative mapping from weighted images using low-resolution labels
Authors: Qiu Shihan , Christodoulou Anthony , Xie Yibin , Li Debiao
Published: August 2023

Deep learning methods have been developed to estimate quantitative maps from conventional weighted images, which has the potential to improve the availability and clinical impact of quantitative MRI. However, high-resolution labels required for network training are not commonly available in practice. In this work, a hybrid supervised and physics-informed self-supervised loss function was proposed to train parameter estimation networks when only limited low-resolution labels are accessible. By taking advantage of high-resolution information from the input weighted images, the proposed method generated sharp quantitative maps and had improved performance over the supervised training method purely relying on the low-resolution labels.
Linear-combination modeling of short-TE PRESS data using parameterized and experimentally derived macromolecule basis functions
Authors: Zöllner Helge , Gong Tao , Hui Steve , Song Yulu , Chen Weibo , Wang Guangbin , Oeltzschner Georg , Edden Richard
Published: August 2023

Recent expert consensus emphasizes the use of measured MM spectra for reliable linear-combination modeling (LCM) of short-TE MRS data. Here we compare the metabolite estimates from short-TE PRESS data modeled with a parameterized and measured MM basis functions in a large dataset.
Harmonisation of multi-site MRS data with ComBat
Authors: Bell Tiffany , Godfrey Kate , Ware Ashley , Yeates Keith , Harris Ashley
Published: August 2023

Multisite magnetic resonance spectroscopy (MRS) studies are becoming increasingly more common, however data collection across multiple sites introduces non-biological variability that can mask true biological effects. Using PRESS and MEGA-PRESS data obtained from the BIG GABA repository and linear modelling, we show that (1) scanner vendor and data collection site is significantly associated with metabolite levels and (2) data harmonisation using ComBat successfully removes non-biological variance to reveal biological effects of interest. We therefore recommend ComBat as an approach to harmonise multi-site MRS data.
Combined RF & Gradient Injection Network for AIMDs with leads
Authors: Hammersen Vincent , Wolff Michael , Rennings Andreas , Schaefers Gregor
Published: August 2023

MR safety of AIMD with leads is assessed test procedures defined in ISO/TS10974. This separates the different electromagnetic field interactions into independent test procedures. E.g., malfunction and rectification testing, with gradient and RF injection networks connected to the lead ports of AIMDs. But this does not correspond to "realistic MRI exposures", where a precise combination of RF and magnetic fields is used for imaging. For this reason, a concept is being proposed in which both injection networks are combined to allow a concerted exposure. This allows the simultaneous exposition of any gradient and RF signal combination.
Continuous monitoring of MRI staff exposure to stray magnetic field at 1.5 T and 3 T
Authors: Galante Angelo , Vito Valentino , Braggio Elia , Milanesi Roberta , Giugno Vincenzo , Alecci Marcello
Published: August 2023

We show how to monitor the MRI staff exposure to the $$$B_0$$$ stray-field. Monitoring is extended to several body districts without interferences with normal hospital operative procedures. The Weighted Peak index is calculated, for different Action Levels limits as from the current EU regulations, to consider the non-sinusoidal nature of exposure. Results show that exposure limits are exceeded even at 1.5 T and their occurrences significantly increase at 3.0 T scanners.
Analytical Evaluation of Radio-Frequency Energy-Induced Heating in a Hot Spot without perfusion
Authors: Kozlov Mikhail , Boulant Nicolas
Published: August 2023

We derived analytical steady-state and transient solutions for a sphere and a SAR source with uniform and the Gaussian distribution located in an infinite medium of homogeneous properties. The results obtained analytically showed that even without taking into account blood perfusion (i) if power deposition is present only in a sphere that encloses 10 gram of human tissue and SAR10g=10W/kg the steady-state temperature rise is below 3°C for power deposition distributions as sharp as Gaussian with σ=R/3=4.33mm, (ii) the sharper the Gaussian distribution of power deposition, the higher Tmax(t=+∞) and the faster it will approach steady-state.
Virtual precision surgery for mri implant safety
Authors: Bottauscio Oriano , Arduino Alessandro , Baruffaldi Fabio , Chiampi Mario , Martinez Jessica , Zanovello Umberto , Zilberti Luca
Published: August 2023

In silico evaluation of heating during an MRI exam for patients with passive implants patients need detailed anatomical models to reproduce in vivo scenarios. A quantification of the influence of the model approximation is fundamental to define the main requirements of the digital model.Here, we analyze the impact of different model approximation in simulating RF and gradient-induced heating caused by orthopedic implants. It was found that, whereas the heating due to switched gradient fields does not strictly require the adoption of advanced virtual surgery, the heating caused by RF is strongly affected by the precision of the digital model.
Bullying is associated with reduced cognitive scores and altered brain morphometry over time in preadolescent children.
Authors: Menken Miriam , Rivera Pedro Rodriguez , Isaiah Amal , Ernst Thomas , Cloak Christine , Chang Linda
Published: August 2023

Few studies identified brain morphometric changes associated with peer-victimization (“being bullied”), and no study examined how these changes can mediate the relationship between bullying and cognition. Using T1-weighted MRI scans and cognitive test scores from the Adolescent Brain Cognitive Development longitudinal dataset, we found that bullying is associated with reduced cognitive performance over time. Bullied children had smaller putamen volumes and right insula surface areas, thinner left precentral and banks of superior temporal sulcus cortices, but larger left entorhinal and right pars orbitalis surface areas. Importantly, these altered brain measures partially mediated the relationship between bullying and cognitive scores.
A very motion-robust pediatric brain MRI protocol for clinical use
Authors: Skare Stefan , van Niekerk Adam , Sprenger Tim , Ramolli Aleksandra , Österman Yords , Svoboda Jan , Norbeck Ola , Rydén Henric , Avventi Enrico , Berglund Johan
Published: August 2023

Selected pediatric patients (3-9Y) scheduled for a clinical brain MRI under general anesthesia are enrolled in this ongoing study to be scanned awake, while watching a movie for entertainment, using a new motion-robust brain MRI protocol. The protocol consists solely of custom-made, inherently motion-robust, sequences, with all necessary MR contrasts for clinical use. All but one sequence uses real-time correction of head motion with an external tracking device. All eight unsedated pediatric patients scanned so far resulted in diagnostic images, despite some patients moving their heads in excess of 30 degrees (peak-peak) during the exam.
Dose-dependent response of cerebral blood flow in healthy volunteers following administration of β2-adrenergic receptor agonist clenbuterol
Authors: Bishop Courtney , Lodeweyckx Thomas , de Hoon Jan , Van Laere Koen , Koole Michel , Vandenberghe Wim , Rizzo Gaia , Rabiner Eugenii , Martin Renee , Ford Anthony , Vargas Gabriel
Published: August 2023

Initial evidence is provided for central effects of the β2-AR agonist clenbuterol on CBF in healthy volunteers. Regions showing particular effect (the hippocampus and thalamus) are associated with cognition and neurodegeneration in Parkinson’s and Alzheimer’s Disease, so similar targeting of β2-AR may prove beneficial in these conditions. Further work is required to determine the extent of central mediation of the effect of β2-AR agonism with clenbuterol in healthy volunteers.
Structural brain imaging with high-resolution 3D MRI on the Next-Generation 7T brain scanner
Authors: Beckett Alexander , Chen Jingjia , Gunamony Shajan , Vu An , Torrisi Salvatore , Liu Chunlei , Stockmann Jason , Feinberg David
Published: August 2023

The 128-channel receive, 16-channel parallel transmit capabilities of the new NexGen 7T system, in conjunction with the high amplitude and slew rate of the novel “Impulse” head gradient coil, provide many potential benefits for high-resolution 3D neuroimaging. High channel array coils allow acceleration on two phase encoded axes for very high total acceleration factors, and faster gradients can reduce image readout time for additional benefits. We demonstrate these benefits in different 3D imaging applications (MP2RAGE, FLAIR, FLASH, SWI) at 7T.