bluuebunny/crossref_metadata_2025 huggingface dataset:
Image- and spectroscopy-based quantitative assessment of renal function using hyperpolarized 13C-labelled Z-OMPD
Authors: Grashei Martin , Wodtke Pascal , Skinner Jason , Sühnel Sandra , Setzer Nadine , Hundshammer Christian , Schilling Franz
Published: August 2024

Fast and accurate assessment of kidney function is crucial for monitoring and detection of kidney disease and failure in various oncological scenarios. Current techniques rely on non‑spatially resolved blood or urine biomarkers and possess time- or safety-related constraints when using MRI or CT. Here, we demonstrate fast 3D bSSFP imaging and slice spectroscopy protocols using hyperpolarized [1,5-13C2]Z-OMPD for assessment of renal perfusion and filtration in comparison with 13C-urea as an established perfusion agent. Measured renal blood flow and glomerular filtration rates agree with literature and between agents and methods, thereby rendering Z-OMPD a versatile agent for assessment of kidney functionality.
Robust Image Reconstruction using Multi-channel Spatial Nulling Maps: An Alternative to ESPIRiT?
Authors: Hu Jiahao , Zheyuan Yi , Zhao Yujiao , Zhang Junhao , Xiao Linfang , Man Christopher , Lau Vick , Leong Alex , Chen Fei , Wu Ed
Published: August 2024

We develop a novel parallel imaging reconstruction method by extracting null-subspace bases of calibration data/matrix to calculate image-domain spatial nulling maps that contain both coil sensitivity and finite image support information. Images are reconstructed by solving a nulling system formed by multi-channel spatial nulling maps without any masking-related procedure (i.e., in existing SENSE/ESPIRiT for minimizing noise propagation). We demonstrate this method with 2D brain, knee and cardiac data under various conditions, yielding results highly comparable to ESPIRiT with optimal manual masking. Our proposed hybrid-domain reconstruction method is efficient, and more robust than existing ESPIRiT for parallel imaging in practice.
Fast MRSI Reconstruction Combining Linear and Nonlinear Manifold Models
Authors: Li Yahang , Wang Zepeng , Anderson Aaron , Zhao Ruiyang , Arnold Paul , Huesmann Graham , Lam Fan
Published: August 2024

A computationally efficient MRSI reconstruction method is presented. The proposed problem formulation integrates a subspace model of the high-dimensional spatiotemporal function (SPICE) and a network-based learned projector on to a low-dimensional manifold of generic spectroscopic signals. The subspace representation allows for more flexible spatiotemporal sampling designs than using nonlinear manifold constraint alone, while the manifold constraint effectively regularizes the subspace fitting, especially at higher orders. An efficient algorithm is designed to solve the optimization problem. The benefits of the proposed synergy have been demonstrated using simulations as well as experimental 31P and 1H-MRSI data.
Improved Reconstruction for High-Resolution QSM from Highly Sparse Unsuppressed Water Signals of 1H-MRSI Scans
Authors: Ke Ziwen , Zhao Yibo , Li Yudu , Guo Rong , Liang Zhi-Pei , Li Yao
Published: August 2024

The SPICE technique has demonstrated a unique capability of simultaneous QSM/MRSI. To achieve fast high-resolution QSM, highly sparse sampling of (k,t)-space is used in SPICE data acquisition, which poses a significant challenge in image reconstruction. In this work, we solved this problem using a subspace-assisted parallel imaging technique with learned image priors. The proposed method has been validated using experimental data, producing high-quality QSM maps from the unsuppressed water signals of 1H-MRSI scans.
Arterial transit artifacts may be easier to identify transient ischemic attack and stroke in intracranial stenosis than High-resolution MRI
Authors: Li Ling , Zhang Xiaoling , Tang Min , Lei Xiaoyan , Zhang Jing , Yan Xuejiao , Wen Yu , Ai Kai
Published: August 2024

High-resolution magnetic resonance imaging (HRMRI) can be used to characterize the differences in plaque characteristics between transient ischemic attack (TIA) and stroke populations, but it is a time consuming and complicated method.. In this study, we compared the diagnostic performance of HRMRI and arterial spin labeling (ASL) with two post labeling delay times (PLD) combined with clinical risk factors to distinguish TIA and stroke in intracranial stenosis. The results showed that there was no statistical difference between the two methods. In addition, combined model has a good diagnostic performance in predicting stroke occurrence in TIA patients.
Quantification of oxygen metabolism in acute ischemic stroke with multi-parametric quantitative BOLD MRI
Authors: Li Hongwei , Chu Ying-Hua , Luo Yu , Wang He
Published: August 2024

Multi-parametric quantitative BOLD (Mq-BOLD), a biophysical model-based technology, has shown promising results for measuring brain oxygenation in healthy subjects. Our purpose is to explore Mq-BOLD in evaluating the changes of oxygen metabolism in early stage of acute ischemic stroke. There is compensatory elevated oxygen extraction fraction (OEF) in the hypoperfused tissue, but decreased cerebral metabolic rate of oxygen (CMRO2) present in the central part of the infarct core. These alternative biomarkers may provide intuitive diagnostic information of ischemic penumbra in stroke. Moreover, Mq-BOLD only depends on standard clinical imaging protocols, which has a great potential for future routine application.
Quantitative evaluation of mannitol induced effects on ischemic rat brains using free water elimination and mapping with explicit T2 attenuation
Authors: Chiang Chia-Wen , Farrher Ezequiel , Cho Kuan-Hung , Huang Sheng-Min , Shah N. , Choi Chang-Hoon , Kuo Li-Wei
Published: August 2024

Cerebral edema occurs after stroke. Mannitol is commonly used dehydrating agent for effectively improving cerebral edema. However, the edema state after mannitol administration and its effectiveness at the post-acute stages remain unclear. Recently, we have demonstrated free-water elimination and mapping (FWET2) can be used to characterize vasogenic edema in stroke animal models. The aim of this study was to quantitatively evaluate mannitol-induced effects on ischemic rat brains at different time points by using FWET2. We attempted to examine if free water fraction change could reflect mannitol-induced effects on infraction and correlate free water fraction change with total infarct volume.
Brownian superparamagnetic iron oxide nanoparticles enable therapeutic cell viability monitoring with Magnetic Particle Imaging
Authors: Kuo Renesmee , Saayujya Chinmoy , Yeo Kim Hwang , Rodrigo Irati , Chandrasekharan Prashant , Huynh Quincy , Fellows Benjamin , Pauly John , Conolly Steven
Published: August 2024

Molecular imaging tools can noninvasively track cells in vivo. However, no techniques today can rapidly monitor cell therapies to allow for nimble treatment optimization for each patient, the epitome of Personalized Medicine. Magnetic Particle Imaging (MPI) is a new tracer imaging technology that could soon provide MDs unequivocal therapy treatment feedback in just three days. MPI with Brownian SPIOs shows promise towards noninvasive sensing of cell viability via viscosity changes in apoptotic cells. This unique ability could greatly improve the efficacy of cell therapies by enabling rapid personalization of the treatment.
Quantification of NOE effect and its application on brain tumor detection
Authors: Yu Jingyi , Wu Jian , Lan Xinli , Yang Yonggui , Wu Zhigang , Cai Congbo , Cai Shuhui
Published: August 2024

Chemical exchange saturation transfer (CEST) quantification is mostly based on pixel-wise fitting of Z-spectra, which is time-consuming and noise-sensitive. Herein, we propose an approach to quantify CEST based on U-Net. The proposed method can simultaneously quantify the concentration and the exchange rate of nuclear Overhauser enhancement (NOE), together with the B0 map. The results of a simulation sample and a rat C6 glioma model suggest that the quantification of NOE effect with U-Net is accurate, precise and fast.
Observing visually evoked responses in human thalamus and cortex at millisecond temporal resolution: Preliminary study at 3 T
Authors: Toi Phan Tan , Oh Sehong , Park Jang-Yeon
Published: August 2024

There has been interested in observing neural activity dynamics in humans at high temporospatial resolution using noninvasive neuroimaging. Here, we report preliminary results of direct imaging of neuronal activity (DIANA) in humans at 3T using checkerboard pattern stimulation. The results show sequential temporospatial dynamics of activities in visual and prefrontal areas evoked by checkerboard pattern stimulation with a signal change of 0.1~0.3%. In contrast, DIANA signals were distinct from control experiments compared with checkerboard pattern stimulation ones. Our preliminary observations suggest that DIANA is feasible for human fMRI studies.
In vivo Detection of Changes in Membrane Potential in Rat Cortex by T2 mapping
Authors: Min Kyeongseon , Chung Sungkwon , Lee Seung‐Kyun , Lee Jongho , Phan Tan Toi , Kim Daehong , Park Jang-Yeon
Published: August 2024

Membrane potential is the crucial element of neuronal activation. We investigated the possibility of using MRI to detect the depolarization of membrane potential in rat cortex. To directly access brain cells, a craniotomy was performed to make a burr hole on the skull. T2 change in the exposed cortex was measured while depolarizing it by directly perfusing artificial cerebrospinal fluid of high potassium concentration. Our findings showed that T2 value of depolarized cortex increased by +2.7% at [K+] = 80 mM. This observation demonstrates that changes in membrane potential are detectable with MRI by T2 contrast in vivo.
Correlation of zero echo time MB-SWIFT fMRI with neuronal activity during sensory stimulation in anesthetized and awake rats
Authors: Valjakka Juha , Paasonen Jaakko , Salo Raimo , Paasonen Ekaterina , Gureviciene Irina , Kettunen Mikko , Idiyatullin Djaudat , Michaeli Shalom , Mangia Silvia , Tanila Heikki , Gröhn Olli
Published: August 2024

Zero echo time (ZTE) fMRI with MB-SWIFT poses an artefact free alternative to traditional EPI-based BOLD fMRI approaches. However, the exact origin of the fMRI signal captured with ZTE is unknown. In this work, we investigated the correlation between electrical brain activity and the ZTE fMRI signal during sensory stimulation in anesthetized and awake rats. It is shown that a linear model explains the relationship between the fMRI signal and electrical activity in anesthetized but not in awake rats. We conclude that MB-SWIFT fMRI provides a good proxy for neuronal activity under conventional experimental conditions.
Investigation of electrical conductivity changes during functional activity of the brain via phase-based MR-EPT: Preliminary observation
Authors: Jung Kyu-Jin , Cui Chuanjiang , Lee Jae-Hun , Kim Jun-Hyeong , Park Kyoung-Jin , Lee SooHyoung , Jung SunYoung , Kim Dong-Hyun
Published: August 2024

BOLD-fMRI is measured from time-series of magnitude information, whereas the phase contrast information, which is related to the electrical properties, is excluded from process. In this study, we focus on the phase information and attempt to expose the relationship between BOLD signal and conductivity activation. In addition, we investigate the potential of functional EPT relative to standard BOLD fMRI.
High-frequency Conductivity Signal Changes Measured with Functional MREPT during Visual Stimulation
Authors: Jahng Geon-Ho , Jeong Jeonin , Lee Mun Bae , Lee Jiyoon , Kwon Oh In
Published: August 2024

To investigate the neuronal response of conductivity during visual stimulation and compare that with BOLD, 30 young healthy volunteers were recruited from the local community. We performed two independent experiments of functional magnetic resonance electrical properties tomography (MREPT) MRI. We found that the conductivity value was increased during visual stimulation to some brain areas, indicating that functional MREPT MRI can be used to measure neuronal activity; therefore, conductivity-based fMRI signals may be helpful for measuring neuronal activation during stimulation.
Estimation of Aortic Pressure Difference in Fontan Patients by 4D Flow MRI
Authors: Hung Hsueh-Ping , Wu Ming-Ting , Weng Ken-Pen , Peng Hsu-Hsia
Published: August 2024

We aimed to evaluate the aortic blood pressure characteristics and cardiac function in patients after the Fontan operation. The Fontan group exhibited significantly increased peak diameter index and decreased peak velocity and peak flow rate in some of planes in the aorta. The Fontan group also presented decreased pressure difference (PD) in aortic arch and descending aorta. The aortic PD might be more sensitive than cardiac index in detection of cardiovascular alteration in Fontan patients. The aortic PD measured by 4D flow MRI can be a noninvasive alternative to characterize aortic remodeling.
Autonomous 5D-flow with Radial k-Space Sampling
Authors: Rodríguez-Soto Ana , Schuchardt Eleanor , Hedge Sanjeet , Witschey Walter , Contijoch Francisco
Published: August 2024

Autonomous acquisition of radial k-space data improves sample uniformity in 2D cardiac MRI. We aim to extend this approach to 5D-flow imaging (4D flow with respiratory gating). We have simulated data acquisition using an autonomous approach (ARKS) and compared it to golden-angle (GA) based spiral phyllotaxis acquisition. Simulations were based on physiologic data recorded from pediatric patients undergoing conventional 4D flow imaging. We found that a 4.5 min ARKS scan achieves a higher degree of sampling uniformity than an 8 min GA scan. Future work will focus on implementing 5D-flow ARKS in vivo and evaluating the impact on flow accuracy.
Deep learning based segmentation of aortic cross sections (2D+t) in multi-vendor 4D PCMRI
Authors: Manini Chiara , Hüllebrand Markus , Pullig Marius , Kühne Titus , Nordmeyer Sarah , Jarmatz Lina , Harloff Andreas , Schulz-Menger Jeanette , Hennemuth Anja
Published: August 2024

Standardized 4D PCMRI postprocessing protocols could enable comparable bloodflow quantification. We propose an automatic segmentation of aortic cross section over time with a residual trained data from different imaging sequences, scanner types, pathologies and position of cross section planes. Dice score, Hausdorff metric as well as flow and velocity curves for the segmented areas show good performance both in the validation and test sets.
Deep learning-based non-rigid motion-corrected reconstruction for whole-heart multi-dimensional joint T1/T2 imaging
Authors: Felsner Lina , Velasco Carlos , Qi Haikun , Kunze Karl , Neji Radhouene , Botnar René , Prieto Claudia
Published: August 2024

Myocardial T1 and T2 mapping play an important role in the assessment of cardiovascular disease. 3D whole-heart joint T1/T2 water/fat mapping approaches have been recently proposed, however they require long reconstruction times. Recently a Machine learning based reconstruction was proposed for joint motion correction and motion corrected image reconstruction of undersampled free-breathing single contrast 3D coronary MR angiography. Here, we extend this approach for non-rigid motion-corrected reconstructions for multi-contrast data for joint T1/T2 mapping. The proposed approach achieves good agreement with reference techniques and comparable image quality to state-of-the-art methods albeit in 1200 times shorter reconstruction times.
Diffusion Tensor Estimation Using Model-Based Deep Learning
Authors: Li Jialong , Lu Qiqi , Feng Yanqiu , Zhang Xinyuan
Published: August 2024

Diffusion tensor imaging (DTI) is widely used in clinical applications and neuroscience. Its practical utility is limited by the need for multiple scans. Here, we integrate deep learning and model-based optimization methods to estimate diffusion tensor using only one non-diffusion-weighted images and six diffusion-weighted images. The data fidelity term is the weighted linear least squares fitting (WLLS) and the regularization term is Regularization by Denoising (RED). The Alternating Direction Method of Multiplier (ADMM) is adopted to iteratively optimize the model. Experiment results demonstrate that the proposed model-based strategy has great potential to improve the accuracy of diffusion tensor estimation.
Tackling the gyral bias and bottleneck problems with hybrid diffusion-microscopy tractography in the BigMac dataset
Authors: Zhu Silei , Huszar Istvan , Eichert Nicole , Cottaar Michiel , Daubney Greg , Khrapitchev Alexandre , Mars Rogier , Mollink Jeroen , Scott Connor , Smart Adele , Sallet Jerome , Jbabdi Saad , Miller* Karla , Howard* Amy
Published: August 2024

We present data fusion combining precisely co-registered dMRI and microscopy to reconstruct 3D fibre orientation with micron-scale spatial resolution. We then perform hybrid dMRI-microscopy tractography to investigate two known challenges in tractography: the gyral bias and bottleneck problems. Our results using hybrid tractography suggest that the gyral bias can be overcome by increased spatial resolution, and that microstructure-informed fibre orientations can overcome the bottleneck problem, irrespective of spatial resolution. These observations can be used to inform tractography analyses in vivo. This approach builds on the complementary strengths of microscopy (high spatial resolution) and dMRI (3D whole-brain coverage).
Age-related regional patterns in cerebral microstructure revealed using mean apparent propagator (MAP) MRI
Authors: Bouhrara Mustapha , Avram Alexandru , Kiely Matthew , Trivedi Aparna , Benjamini Dan
Published: August 2024

The relationship between brain microstructure and aging has been the subject of intense study. We used the mean apparent propagator (MAP) MRI framework, which is suitable to characterize diffusion in complex microstructure, to investigate age-related differences in a cohort of cognitively unimpaired participants, spanning a wide age range. In white matter, we established an opposing pattern of higher non-Gaussianity (NG) alongside lower propagator anisotropy (PA) among older adults. In gray matter, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters. These results suggest that MAP-MRI provides otherwise inaccessible regional microstructural information.
Axon diameter mapping is confounded by glial cells
Authors: Veraart Jelle , Raven Erika , Jones Derek , Palombo Marco
Published: August 2024

The specificity of strongly diffusion-weighted MRI to intra-axonal signal contributions to neuronal processes has always been presumed. Here we demonstrate empirically that strongly diffusion-weighted MRI data is also sensitive to a distinct isotropic compartment that may bias axon diameter estimates. We hypothesize that such a compartment represents isotropically-distributed glial processes. We use in vivo human data and Monte Carlo simulations to support our hypothesis and evaluate a novel strategy to suppress signal arising from glial cell bodies and processes to promote more accurate axon diameter mapping.
Quantifying features of human gray matter microstructure postmortem using Neurite Exchange Imaging (NEXI) at ultra-high field
Authors: Hertanu Andreea , Uhl Quentin , Pavan Tommaso , Lamy Christophe M. , Jelescu Ileana O.
Published: August 2024

In this work, we characterized microstructure properties of cortical gray matter and hippocampus using diffusion MRI, on two samples of postmortem fixed healthy human brain. The weak-to-absent diffusivity time-dependence and marked kurtosis time-dependence supported the suitability of the Neurite Exchange Imaging (NEXI) model to probe postmortem human gray matter microstructure. NEXI parametric estimations revealed region-specific values, calling for further validation using histology and further clarifying the discrepancy between compartment diffusivities estimated here vs. the literature. This study offers an important window on human gray matter microstructure at a spatial resolution unachievable in vivo.
A piecewise-polynomial basis for generalized diffusion encoding gradient waveforms
Authors: Caruyer Emmanuel
Published: August 2024

Diffusion-encoding gradient waveforms are a key parameter of experimental design in diffusion magnetic resonance imaging. Their optimization is important for e.g. maximizing the efficiency in B-tensor encoding, or improving the sensitivity and specificity to microstructure parameters of biophysical models. The main challenge in optimizing gradient waveforms and trajectories is the large dimension of the search space and the constraints associated with physical and physiological limitations. Here we propose an original piecewise polynomial representation, which natively enforces the linear constraints that arise from refocusing and regularity. We illustrate the basis on B-tensor encoding and Monte-Carlo simulation of the diffusion signal.
Intelligent Slice Placement for Oblique Coronal ACL plane prescription for Knee MRI using Deep Learning
Authors: Agarwal Apoorva , Bhushan Chitresh , Yeo Desmond T.B. , Foo Thomas , Gui Dawei , Anand Deepa , Fung Maggie , Kolupar Trevor , Abraham Tisha , NT Sanjay , Padmanabhan Kameswari , Patil Uday , Shanbhag Dattesh
Published: August 2024

In clinical practice, oblique coronal and sagittal scans have been shown to be superior for visualization of ACL and assessment of ACL tears. In this work, we demonstrate a Deep Learning based method to obtain these complex scan planes (Coronal ACL and Coronal Blumensaat) directly from standard 2D tri-planar Localizers. Results on 487 test volumes show <0.6mm mean error for both planes, indicating suitability for clinical usage.
Physics-informed Deep Diffusion MRI Reconstruction: Break the Data Bottleneck in Artificial Intelligence
Authors: Qian Chen , Sun Yiting , Wang Zi , Zhang Xinlin , Cai Qinrui , Kang Taishan , Jiang Boyu , Tao Ran , Wu Zhigang , Guo Di , Qu Xiaobo
Published: August 2024

Deep learning is widely employed in biomedical magnetic resonance image (MRI) reconstructions. However, accurate training data are unavailable in multi-shot interleaved echo planer imaging (Ms-iEPI) diffusion MRI (DWI) due to inter-shot motion. In this work, we propose a Physics-Informed Deep DWI reconstruction method (PIDD). For Ms-iEPI DWI data synthesis, a simplified physical motion model for motion-induced phase synthesis is proposed. Then, lots of synthetic phases are combined with a few real data to generate efficient training data. Extensive results show that, PIDD trained on synthetic data enables sub-second, ultra-fast, high-quality, and robust reconstruction with different b-values and undersampling patterns.
Model-Assisted Deep Learning-Based Reconstruction: Does the Model Help?
Authors: Guan Yue , Li Yudu , Liu Ruihao , Meng Ziyu , Li Yao , Du Yiping , Liang Zhi-Pei
Published: August 2024

Deep learning-based image reconstruction has two known practical issues: (a) sensitivity to data perturbations, and (b) poor generalization. An approach to addressing these issues is to use classical signal models to assist/constrain deep learning. This paper performs a systematic analysis of the role of signal models in model-assisted deep learning-based reconstruction. Our results show that signal models (e.g., subspace model or sparse model) can substantially reduce the sensitivity of deep learning-based reconstruction to data perturbations; they can also help improve generalization capability.
Pharmacokinetic Parameters’ Distribution Estimation with Normalizing Flow in Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Authors: Fang Ke , Wang Zejun , Cheng Zhaowei , Wang Bao , Jin Xinyu , Liu Yingchao , Bai Ruiliang
Published: August 2024

The pharmacokinetic (PK) parameters extracted from the DCE-MRI provide valuable information but suffer from many sources of variability. Thus, the efficient and fast estimation of the distributions of these ambiguous PK parameters caused by variabilities could significantly improve the robustness and repeatability of DCE-MRI. The estimation of the PK parameters’ distributions provides a way to quantify the PK parameters’ values and variabilities simultaneously. In this study, we demonstrated the feasibility of the normalizing flow-based distribution estimation network (FPDEN) for PK parameters’ distribution estimation in DCE-MRI.
A novel deep multimodal contrastive network for early prediction of cognitive deficits using multimodal MRI and clinical data
Authors: Li Zhiyuan , Li Hailong , Parikh Nehal , Dillman Jonathan , Ralescu Anca , He Lili
Published: August 2024

Deep learning has shown promising results in early predicting cognitive deficits in very preterm infants using multimodal brain MRI data, acquired soon after birth. Prior methods focus on the feature fusion of different modalities but ignore the latent high-order feature similarity information. In this study, we propose a novel deep multimodal contrastive network using T2-weighted structural MRI (sMRI), diffusion tensor imaging (DTI), resting-state functional MRI (rsfMRI), and clinical data to predict later cognitive deficits. Our proposed model significantly improved predictive power compared to other peer models for early diagnosis of cognitive deficits.
µGUIDE: a framework for microstructure imaging via generalized uncertainty-driven inference using deep learning
Authors: Jallais Maëliss , Palombo Marco
Published: August 2024

This work proposes µGUIDE: a general Bayesian framework to estimate posterior distributions of tissue microstructure parameters from any given biophysical model or MRI signal representation, with exemplar demonstration in diffusion-weighted MRI. Harnessing a new deep learning architecture for automatic signal feature selection combined with simulation-based inference and efficient sampling of the posterior distributions, µGUIDE bypasses the high computational and time cost of conventional Bayesian approaches and does not rely on acquisition constraints to define model-specific summary statistics. The obtained posterior distributions allow to highlight degeneracies present in the model definition and quantify the uncertainty and ambiguity of the estimated parameters.
MRI reconstruction via Data-Driven Markov Chains with Joint Uncertainty Estimation: Extended Analysis
Authors: Luo Guanxiong , Heide Martin , Blumenthal Moritz , Uecker Martin
Published: August 2024

The application of generative models in MRI reconstruction is shifting researchers’ attention from the unrolled reconstruction networks to the probabilistically tractable iterations and permits an unsupervised fashion for medical image reconstruction.
Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia.
Authors: Villaseñor Paulina , Aquiles Ana , Cortes-Servín David , Perez-Moriel Aylin , Luna-Munguía Hiram , Ramirez-Manzanares Alonso , Larriva-Sahd Jorge , Concha Luis
Published: August 2024

Focal cortical dysplasias are characterized by abnormal cyto- and myelo- architecture and represent a frequent cause of epilepsy. In some cases these lesions are macroscopically subtle, often going undetected by several conventional imaging techniques, thus warranting the development of alternative imaging methods for their diagnosis. Novel methods for the analysis of diffusion-weighted imaging permit the investigation of the complex architecture of the cortex. Through spatial analysis of diffusion metrics using a multi-tensor approach we demonstrate abnormalities in an animal model of cortical dysplasia that reflect myeloarchitecture disarrangement as seen by histology.
A 15-minute 860um whole-brain MR-Fingerprinting and DTI epilepsy protocol demonstrated on 51 medial temporal lobe epilepsy patients.
Authors: Wang Kang , Cao Xiaozhi , Chen Quan , Zhou Zihan , Wu Dengchang , Liu Yunsong , He Hongjian , Zhong Jianhui , Setsompop Kawin , Liao Congyu
Published: August 2024

In this work, we combined a 5-minute whole-brain 0.86mm-iso 3D-MR fingerprinting (MRF) with a 10-minute whole-brain 0.86mm-iso diffusion MRI protocol, to achieve high-fidelity whole-brain T1/T2/PD and diffusivity maps at sub-millimeter isotropic resolution. This protocol was applied to medial temporal lobe epilepsy (MTLE) patients to enable accurate detection of the hippocampal sclerosis. A multi-parametric analysis was implemented with whole-brain subcortical segmentation. A multi-component 2D-relaxometry spectra was estimated with non-negative joint sparsity for robust suspicious lesion detection.
Direct visualization and automatic segmentation of the centromedian nucleus for epilepsy deep brain stimulation
Authors: Saranathan Manojkumar , Ganne Chaitanya , Pati Sandipan
Published: August 2024

We present a patient-specific segmentation method for targeting the centromedian nucleus for epilepsy deep brain stimulation and compare it to an atlas-based indirect targeting method in 8 patients.
Quantitative Susceptibility of Subcortical Grey-Matter Regions in Early versus Refractory Focal Epilepsy
Authors: Vaughan David , Pierre Eric , Bryant Marty , Abbott David , Pardoe Heath , Syeda Warda , Tahayori Bahman , Tailby Chris , Jackson Graeme
Published: August 2024

Magnetic susceptibility of subcortical grey matter regions was assessed in participants of the Australian Epilepsy Project pilot study. Adults with medication-resistant focal epilepsy were compared to those with newly-diagnosed focal epilepsy, and to people with a single seizure but no epilepsy diagnosis. Basal ganglia, thalamus, hippocampi and amygdala showed susceptibility values consistent with published values, with a positive correlation to age seen at the basal ganglia. There was no significant difference in subcortical susceptibility between the groups. Although other brain network changes may progress with refractory seizures, mineralisation of subcortical regions appears generally stable over the course of focal epilepsy.
Free-breathing renal R2*/QSM using 3D multi-echo UTE cones acquisition and motion-resolved reconstruction with image-based self-navigator
Authors: Kang MungSoo , Behr Gerald , Glezerman Ilya , Otazo Ricardo , Kee Youngwook
Published: August 2024

Respiratory motion is a significant challenge for the acquisition of reliable renal R2*/QSM. The combination of 3D multi-echo UTE cones MRI and respiratory motion-resolved image reconstruction with an image-based self-navigator was developed to enable motion-robust renal R2*/QSM. Motion-resolved reconstruction with an image-based self-navigator showed better image quality compared to conventional gridding reconstruction and higher apparent SNR and CNR compared to motion-resolved reconstruction using the center of the k-space as navigator. 3D multi-echo UTE cones MRI and motion-resolved image reconstruction with image-based self-navigator demonstrated the feasibility of motion-robust, free-breathing, and high isotropic resolution of renal R2*/QSM.
Motion Correction for Interleaved EPI Diffusion Imaging using a Markerless Optical Tracking System
Authors: Xiao Yi , Wang Chunyao , Li Sisi , Chen Huijun , Guo Hua
Published: August 2024

Multi-shot interleaved EPI can achieve high-resolution diffusion imaging and effectively reduce geometric distortions. However, multi-shot acquisitions are susceptible to bulk motion which causes artifacts. Optical tracking-based motion correction is an effective method to reduce motion artifacts in DWI. Based on a self-developed Structured Light Optical MOtion tracking (SLOMO) system, a retrospective motion correction method was developed for multi-shot interleaved EPI DWI. The performance was evaluated by in-vivo experiments and compared with software-based correction.
Real-time correction of rigid motion and 1st-order shims using rapid 3D orbital navigators
Authors: Riedel Malte , Ulrich Thomas , Pruessmann Klaas
Published: August 2024

Rigid head motion, which is a challenging problem in itself, is further accompanied by field variations as the object moves in an inhomogeneous background field, and because pose changes lead to varying susceptibility-induced fields. In contrast to external sensors like optical cameras, navigators are naturally sensitive to field variations. We propose a fast, scan-integrated calibration method to sensitize the 3D orbital navigators to rigid motion and 1st order shim fields. The obtained motion and field parameters are used to correct the scan geometry and shim settings in real-time. The performance is evaluated in phantom and in-vivo studies.
Real-time automatic field-of-view adjustment in fetal MR scans using Gadgetron
Authors: Silva Sara Neves , Verdera Jordina Aviles , Tomi-Tricot Raphaël , Neji Radhouene , Wilkinson Thomas , Ozenne Valéry , Lewin Alexander , Story Lisa , De Vita Enrico , Rutherford Mary , Pushparajah Kuberan , Hajnal Jo , Hutter Jana
Published: August 2024

MRI provides an ideal tool for characterising fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion. To address this challenge, we are developing an intrinsically motion-robust deep-learning-based fetal MRI method to achieve real-time fetal head tracking and update the acquisition geometry prospectively. Our method uses Gadgetron for real-time reconstruction of the scans and a 3D UNet for fetal head position location and motion estimation. Real-time tracking and correction for functional fetal MRI was demonstrated both in controlled phantom setups and in fetal MRI cases.
The cerebellum modulates non-linear behavior of motor planning areas in variable grip-force visuomotor task
Authors: Lorenzi Roberta , Korkmaz Gokce , Alahmadi Adnan , Casiraghi Letizia , Monteverdi Anita , D'Angelo Egidio , Palesi Fulvia , Kingshott Claudia Gandini Wheeler
Published: August 2024

The hemodynamic response to neuronal stimuli can be both linear and nonlinear with the applied grip-force of a “squeeze-ball” task, controlled by a visual cue. Dynamic Causal Modelling was applied here to understand the causal effective between-region connectivity shaping the hemodynamic response recorded by functional-MRI. Effective connectivity resulted non-symmetric, with strong excitation from visual to motor areas. Results indicated primary visual cortex linear modulation of the cerebellar response, which exerted nonlinear influence on cortical motor planning, suggesting activation hierarchy in the motor circuit with prominent cerebellar role. This result may have important implications for understanding pathological changes affecting neural mechanisms.
Superconducting Quantum Interference Device (SQUID-) Based Susceptometry as a Reference Measurement for Quantitative Susceptibility Mapping
Authors: Simchick Gregory , Wakai Ronald , Fischer Roland , Baffa Oswaldo , Pratt Kevin , Paulson Doug , Reeder Scott , Hernando Diego
Published: August 2024

Many quantitative susceptibility mapping (QSM) studies lack independent reference measurements of susceptibility (χ) for validation. In this work, superconducting quantum interference device (SQUID-) based susceptometry and QSM data were acquired for phantoms with varying manganese chloride (MnCl2) concentrations. χSQUID demonstrated low uncertainty and excellent agreement with the nominal susceptibility values. χQSM and R2* agreed relatively well with the nominal values and previously published results. However, χQSM demonstrated higher uncertainty in comparison to χSQUID. SQUID susceptometry has the potential to identify sources of bias and variability in QSM methods by serving as an independent reference measurement of susceptibility.
A Deep learning informed Polynomial Fitting Approach for Electrical Properties Tomography
Authors: Jung Kyu-Jin , G.Meerbothe Thierry , Cui Chuanjiang , Park Mina , Yi Jaeuk , van den Berg Cornelis A.T. , Kim Dong-Hyun , Mandija Stefano
Published: August 2024

This work presents a neural network informed fitting approach for conductivity reconstructions in MR-Electrical Properties Tomography. First, an artificial neural network is used to predict weights from T2-weighted images. These weights are used in a weighted fitting approach to calculate polynomial coefficients that parametrize the phase map. The conductivity is finally reconstructed from these coefficients. The reconstruction approach is tested on simulated data and in-vivo data and shows more accurate results than conventional fitting methods.
Histological validation of myelin-sensitive MRI metrics in the common marmoset
Authors: Rowley Christopher , Chitsaz Daryan , Leppert Ilana , Campbell Jennifer , Nuara Stephen , Kennedy Timothy , Pike G. , Tardif Christine
Published: August 2024

Several studies have compared myelin-sensitive MRI maps to myelin staining to demonstrate the degree of correlation of the MRI metric with myelin content. This study in the common marmoset compares six myelin-sensitive MRI metrics acquired in vivo to stains for myelin, cell nuclei, and ferritin. T2*-based myelin water fraction (MWF) and inhomogeneous magnetization transfer saturation (ihMTsat) presented the greatest specificity for myelin content, with ihMTsat having a higher signal in grey matter regions. T1w/T2w had the strongest correlation with the iron-storage protein ferritin, and T2* presented the greatest correlation with the cell nuclei stain.
The FACE: Flexible Array for Cervical & Extraspinal 3T MR Imaging
Authors: Abel Frederik , Tan Ek , Lunenburg Martijn , van Leeuwen Carel , van Hooren Thijs , van Uden Mark , Arteaga Catalina , Vincent Jana , Robb Fraser , Lebl Darren , Sneag Darryl
Published: August 2024

Conventional cervical coils lack the flexibility to closely conform to the inherently curved neck region, particularly at its head/shoulder junctions. High SNR imaging of the c-spine and extraspinal soft tissues (including small peripheral nerves) relies on close proximity of receive elements to these targeted structures. This study evaluates the performance of a novel, conformal, 23-channel Flexible Array for Cervical & Extraspinal (FACE) 3T MR Imaging with increased flexibility to enhance image quality and SNR compared to conventional coils. SNR measurements on phantoms and high resolution 2D and 3D in vivo c-spine and peripheral nerve neck imaging were performed at 3T.
Feasibility Study for Wireless RF Coil: Wireless transfer of 8ch MR received data using body array coil and system clock
Authors: Okamoto Kazuya , Kato Sojuro , Spring Mark , Hamamura Yoshinori , Horio Daisuke , Tanaka Yu , Sugimoto Shun , Watanabe Kazunari
Published: August 2024

We prototyped a new acquisition board (NAB) equipped with wireless signal transmission modules, and connected it to the reception RF coil and the scanner system. The configuration enabled that the transmission of the 8-ch reception signal data from the RF coil and the system clock was carried out between boards wirelessly. Finally, two-dimensional SE images were obtained without deterioration in image quality.
Abbreviated Three Minute 4D Flow MRI of the Portal Circulation: Prospective Evaluation in Obese Subjects
Authors: Oechtering Thekla , Shamim AMK Muntasir , Harris David , Panagiotopoulos Nikolaos , Spahic Alma , Wieben Oliver , Johnson Kevin , Roldán-Alzate Alejandro , Reeder Scott
Published: August 2024

Constant, non-pulsatile flow in the portal venous system offers the possibility of time-averaged reconstruction for shortening the acquisition time. We acquired both a 10min and 3min radial 4D flow MRI (PCVIPR) in 10 subjects in a test-retest paradigm. Time-averaged 10min and 3min exams were compared to the reference standard, i.e., cardiac-phase resolved 10min exam (14 timeframes). All datasets were analyzable with quality rated as “good” for all 3min exams. Small vessels were best visualized in the time-averaged 10min data. Conservation of mass analysis and test-retest repeatability yielded excellent results for all reconstructions. Quantitative results agreed well between reconstructions.
Evaluation of hemodynamic parameters for prediction of aortic growth in patients with chronic Stanford type B aortic dissection using 4D flow MRI.
Authors: Higuchi Satoshi , Ota Hideki , Mori Ryuichi , Ichinoseki Yuki , Kamada Hiroki , Takase Kei
Published: August 2024

Uncomplicated type B aortic dissection (AD) has a poor long-term outcome and further optimization of predictors for aortic expansion is required. Seventeen patients with chronic type B AD who underwent 4D flow MRI were included and divided into two groups based on the aortic growth rate. The morphological and hemodynamic parameters in each group were retrospectively analyzed. The forward flow and volume in true lumen and ratio of these parameters at entry and false lumen to true lumen were significantly higher in the fast growth-rate group than in the slow one; no morphological parameters showed a significant difference.
Improving single-shot multi-parametric mapping via multi-slice information sharing based on multiple overlapping-echo detachment imaging
Authors: Dai Chenyang , Wang Jiechao , Yang Qizhi , Wu Zhigang , Cai Congbo , Cai Shuhui
Published: August 2024

Multi-parametric quantitative magnetic resonance imaging (mqMRI) has important applications in clinic. Multiple overlapping-echo detachment (MOLED) imaging can achieve single-shot mqMRI. However, the existing methods mainly focus on single-slice reconstruction. To improve the reconstruction quality of parametric maps by exploring data redundancy among adjacent slices, we proposed a multi-slice information sharing method via multiple modulation patterns of MOLED k-space and deep neural network. The results show that our method can effectively utilize the correlation information among adjacent slices and improve the reconstruction quality compared to the single-slice reconstruction method.
Validation of Constrained qBOLD-Based 3D CMRO2 Mapping With Repeatability Test and Hypercapnic Challenge
Authors: Lee Hyunyeol , Xu Jing , Wehrli Felix
Published: August 2024

In the original qBOLD, it is challenging to separate deoxyhemoglobin’s contribution to R2' from other sources modulating the voxel signal. Further, extracting DBV and Yv from measured R2' is a nontrivial task. It was recently shown that the constrained qBOLD method was able to properly separate the several confounding factors, yielding the expected contrast for both Yv and DBV maps across the entire brain, and, together with a separate measurement of CBF, leading to whole-brain 3D CMRO2 maps within physiologically plausible ranges. Here, we validated the new 3D qBOLD method with respect to repeatability and hypercapnic gas breathing challenges.
Morphological comparison of deep white matter bundles between the human and chimpanzee brain using a geometrical approach
Authors: Chauvel Maelig , Uszynski Ivy , Pascucci Marco , Herlin Bastien , Leprince Yann , Mangin Jean-François , Hopkins William , Poupon Cyril
Published: August 2024

Humans and chimpanzees are related by a common ancestor that lived around 6 to 7 millions years ago. From then, a cascade of acquired brain features have occurred and the scientific community has tried for years to capture them. Providing measures of the hominin brain divergences or conserved characters can be challenging considering the multitude of variables involved. We propose here a study relying on an intuitive and yet innovative morphological analysis of the deep white matter (DWM) bundles of the human and chimpanzee brain using isomap algorithm.
Noninvasive diagnosis of clinically significant portal hypertension with MR elastography, T1, and T1ρ mapping of the liver and spleen
Authors: Bane Octavia , Ozkaya Efe , Kennedy Paul , Fischman Aaron , Thung Swan , Taouli Bachir
Published: August 2024

In this prospective study, we explored the diagnostic value of MR elastography (MRE) as well as T1-pre and post-gadoxetate contrast at the hepatobiliary phase and T1ρ mapping of the liver and spleen for noninvasive diagnosis of clinically significant portal hypertension (CSPH) in patients with liver disease. 2D MRE liver (r=0.457, p<0.001) and spleen stiffness (r=0.438, p<0.001) showed a strong significant correlation with portal pressure measurement based on hepatic venous pressure gradient (HVPG). 2D MRE spleen stiffness outperformed other imaging parameters for prediction of CSPH [AUC = 0.867 (0.764-0.970)].
Dynamic distortion correction using blip-rewound EPI and joint multi-echo reconstruction
Authors: Wu Wenchuan
Published: August 2024

In this work, we propose a new method for dynamic distortion correction by integrating a tailored EPI trajectory and a joint multi-echo reconstruction, which permits robust dynamic field mapping and distortion correction without compromising spatial resolution. The performance of the proposed method is demonstrated using in vivo experiments.
Segmented 3D GRE-EPI optimized for BOLD fMRI at 9.4T
Authors: Mueller Sebastian , Bause Jonas , Stirnberg Rüdiger , Scheffler Klaus
Published: August 2024

A segmented 3D GRE EPI was adapted and optimized specifically for BOLD fMRI at a 9.4T MR system. While EPI is widely used in fMRI, especially at UHF its application becomes challenging for instance for long echo trains used at high spatial resolution. In this work, investigations on the stability of the system, tSNR, flexible sequence design, different temporal phase correction schemes, and efficient use of the limited SAR budget were performed. Finally, a protocol for BOLD fMRI of the motor cortex at 1.0mm nominal isotropic resolution (FOV=200x215x44mm³) with a volume TR of 3 seconds was set up.
Integrated heart-brain 4D flow MRI evaluation of hemodynamic coupling in healthy aging adults
Authors: Richter Adam , Moore Jackson , Aristova Maria , Ragin Ann , Schnell Susanne , Rogalski Emily , Markl Michael , Jarvis Kelly
Published: August 2024

Age-related changes in cardiovascular hemodynamics may be associated with brain changes. However, this relationship is not clear since blood flow in the heart and brain are usually imaged and analyzed in separate exams and pipelines. We have developed a technique for parameter mapping in both the aorta and intracranial vessels to allow for integrated MRI evaluation of heart-brain hemodynamic coupling. This study demonstrates a single MRI study and analysis pipeline to facilitate more comprehensive, integrated heart-brain hemodynamic analysis in clinical and research settings.
Quantitative Flow Velocity in Cerebral Perforating Arteries with 7T MRI: the EUFIND study.
Authors: Pham Stanley , van Vliet Jari , van Tuijl Rick , Biessels Geert Jan , Costagli Mauro , van Buchem Mark , Kraff Oliver , Villringer Arno , Ladd Mark , Siero Jeroen , de Rochefort Ludovic , Zwanenburg Jaco
Published: August 2024

We analyzed multi-center blood flow velocity measurements in perforating arteries from 7T MRI with the two-dimensional phase-contrast (2D-PC) sequence (eight sites, comprising three MRI vendors). Analysis was performed with the software tool Small vessEL MRI MArkers (SELMA). Inter-rater reliability of SELMA was excellent with overall intra-class coefficients for number of vessels (Ndetected), mean velocity (Vmean) and velocity pulsatility index (vPI) of at least 0.84 for 2D-PC data from all MRI vendors. Inter-vendor differences were larger than the intra-vendor differences (coefficients of variation: 0.62 vs. 0.39, 0.21 vs. 0.12 and 0.39 vs. 0.12 for Ndetected, Vmean and vPI, respectively).
Hybrid multi-delay PCASL of time-encoded and variable-TR schemes for the assessment of cerebral perfusion in Moyamoya disease
Authors: Togao Osamu , Obara Makoto , Yamashita Koji , Kikuchi Kazufumi , Wada Tatsuhiro , Tokunaga Chiaki , Mikayama Ryoji , Ishida Shota , Hamano Hiroshi , Vaclavu Lena , van Osch Matthias J.P. , van de Ven Kim , Van Cauteren Marc , Ishigami Kousei
Published: August 2024

We have developed a multi-delay PCASL acquisition with a hybrid scheme, combining time-encoded and variable-TR schemes. This hybrid scheme combines the advantage of high SNR obtained with the time-encoded scheme with the timing flexibility of the variable-TR scheme. We investigated the abilities for CBF (cerebral blood flow) and ATT (arterial transit time) quantification in Moyamoya disease. The hybrid scheme provided a higher temporal SNR than the other two schemes. Although slight differences in the CBF and ATT measurements were found between the hybrid and the other two schemes, the differences were acceptable, considering the strong correlations and excellent agreements.