bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of the ALDH2 genetic polymorphism effect in alcohol-related glymphatic dysfunction using DTI-ALPS
Authors: Morita Yuichi , Kamagata Koji , Takabayashi Kaito , Andica Christina , Kikuta Junko , Fujita Shohei , Tabata Hiroki , Naito Hitoshi , Someya Yuki , Kaga Hideyoshi , Akashi Toshiaki , Wada Akihiko , Tamura Yoshifumi , Kawamori Ryuzo , Watada Hirotaka , Taoka Toshiaki , Naganawa Shinji , Abe Osamu , Aoki Shigeki
Published: August 2024

Excessive alcohol intake seriously damages the brain. Previous animal studies reported that the glymphatic system, which is a brain waste clearance system via the cerebral spinal fluid, is affected by chronic high alcohol consumption. Glymphatic dysfunction is related to cognitive impairment. The changes of diffusivity along the perivascular space (ALPS) indices associated with heavy, moderate, and no‑alcohol intake and executive function with or without aldehyde dehydrogenase 2 (ALDH2) rs671 polymorphism was evaluated. The present study revealed the glymphatic function and executive function decline in heavy drinkers. Furthermore, ALDH2 rs671 variants may increase vulnerability to alcohol-induced glymphatic dysfunction.
Evaluation of reproducibility of diffusion tensor image analysis along the perivascular space index using a reorientation technique
Authors: Tatekawa Hiroyuki , Matsushita Shu , Miki Yukio
Published: August 2024

Diffusion tensor image analysis along the perivascular space (DTI-ALPS) index is expected to reflect the glymphatic function of the brain, however, head rotation may reduce reliability. This study evaluated whether a reorientation technique, which registers image and vector information of DTI data, improves the reproducibility of the calculation of the ALPS index. A total of 234 cognitively normal subjects were selected from the OASIS-3 dataset. In the evaluation of the intra- and inter-reliability, the reorientation technique enabled to show good to excellent reproducibility (intraclass correlation coefficients > 0.85) in calculating ALPS index even when head rotation existed.
Three-dimensional flow velocity of cerebrospinal fluid (CSF) in human brain during sleep via simultaneous EEG and dynamic sodium MRI
Authors: Lin Ying-Chia , Chen Xingye , Henin Simon , Kumbella Nahbila-Malikha , Aguilera Liz , Rockowitz Zena , Clayton Ashley , Babb James , Ge Yulin , Masurkar Arjun , Liu Anli , Lui Yvonne , Boada Fernando , Qian Yongxian
Published: August 2024

Cerebrospinal fluid (CSF) flow plays a key role in clearance of waste proteins from the brain. Current proton (1H) MRI is limited to measurement of CSF flow in specific regions such as the aqueduct, due to the lack of capability distinguishing CSF from water. Sodium (23Na) MRI is uniquely sensitive to CSF, instead of water, and has the potential to measure CSF flow in entire brain. Here, we use a recently-developed dynamic sodium MRI to measure CSF flow velocity in the brain and to understand how it changes with sleep state monitored by MRI-compatible EEG.
Measurement of changes in cerebrospinal fluid pulsation after traumatic brain injury using EPI-based functional MRI
Authors: Kim Jun-Hee , Park Sung-Hong
Published: August 2024

A recently-proposed method of simultaneous CSF pulsation and BOLD activity imaging was applied to the TBI-fMRI dataset. The CSF pulsation was significantly lower in the TBI group compared to that of healthy control group. The CSF pulsation decreased significantly in the first 6 months after TBI and then no significant changes in the later stage, which was consistent with previous studies, where CSF pulsation from TBI patients was lower than that of control subjects and starts to slowly recover thereafter. This study can be expanded to post-TBI fMRI datasets in general to examine functional activity and CSF pulsation simultaneously.
A novel atlas of the superficial white matter connectivity based on the whole HCP cohort - an inter-individual variability study.
Authors: Herlin Bastien , Uszynski Ivy , Chauvel Maëlig , Dupont Sophie , Poupon Cyril
Published: August 2024

Superficial white matter (SWM) tracts exhibit a high cross-subject variability, which makes them difficult to study. We used the whole HCP cohort, which included 1065 subjects, to build a comprehensive atlas of the short-range cortico-cortical connections using an advanced diffusion analysis and tractography pipeline, followed by an individual and a group-level fiber clustering. Furthermore, we measured the percentage of occurrence of each cluster within the population. In addition to enabling the automatic labeling of any new subject’s SWM tracts, our atlas paves the way for a thorough cross-subject variability study of superficial connectivity.
Patients with sickle cell disease have altered brain fractional anisotropy, axial, mean and radial diffusivity quantified by 7T MRI.
Authors: Meinert-Spyker Elizabeth , Santini Tales , Bharadwaj Sharadhi Umesh , Novelli Enrico , Ibrahim Tamer , Wood Sossena
Published: August 2024

This abstract compares diffusion tensor imaging parameters between healthy controls and sickle cell disease (SCD) patients. Various softwares were utilized to obtain diffusion metrics and conduct voxelwise comparison was conducted. Fractional anisotropy (FA) and axial diffusivity (AD) values were significantly decreased in patients with SCD compared to controls, while mean diffusivity (MD) and radial diffusivity (RD) were primarily increased in patients compared to controls. Our FA and MD findings are consistent with other studies comparing diffusion metrics of individuals with SCD at a lower magnet field. We also present novel findings comparing AD and RD values for the SCD population.
Cortical thickness related to future score on the Dementia Questionnaire for People with Learning Disabilities in adults with Down syndrome
Authors: Koenig Katherine , Ruedrich Stephen , Oh Se-Hong , Lowe Mark , Leverenz James
Published: August 2024

Down syndrome (DS) is a genetic condition that is associated with early onset Alzheimer’s disease (AD). Individuals with DS show changes in neuroanatomy, including regional increases in cortical thickness. Here, we assess cortical thickness in ten non-demented adults with DS. We focus on regions that show cortical thinning in AD and relate cortical thickness to scores on a measure of dementia. We find that regional thickness measures are related to the 4.6 year change in a measure of dementia, suggesting that the magnitude of early DS-related neuroanatomical differences may relate to aspects of dementia onset.
Prediction of amnestic mild cognitive impairment using radiomics-clinical model based on 3D-T1WI imaging
Authors: Zheng Wei , Mu Ronghua , Qin Xiaoyan , Li Xin , Liu Fuzhen , Zhuang Zeyu , Yang Peng , Lv Jian , Zhu Xiqi , Deng Kan
Published: August 2024

Mild cognitive impairment (MCI) is a transitional state between normal aging and dementia disorders, especially Alzheimer's disease (AD). In this study, we aimed to develop a radiomics model based on 3D-T1W imaging to distinguish amnestic mild cognitive impairment (aMCI) patients from the normal elderly population by measuring changes in the frontal lobe. And the result shows that a quantitative nomogram based on clinical feature and radiomic features of MRI imaging can be used to distinguish aMCI and CN with excellent predictive ability, which can be served as a potential decision support tool to assist clinicians in Screening community aMCI population.
Treatment response prediction of major depressive disorder using brain magnetic resonance imaging
Authors: Long Fenghua , Zhang Qian , Wang Yaxuan , Li Qian , Zhao Youjin , Li Fei
Published: August 2024

We performed a meta-analysis by including published studies using machine learning for unrestricted modalities and interventions on magnetic resonance imaging (MRI) data to predict the effectiveness of treatment for patients with major depressive disorder (MDD). The results showed that the resting-state functional MRI (rs-fMRI) had higher predictive performance in the modality subgroups, suggesting brain rs-fMRI may have an advantage in prediction performance. Using machine-learning analysis to predict treatment effectiveness is promising, but should not yet be implemented into clinical practice.
Disrupted subsystem interactions of default mode network in mild cognitive impairment: A Resting-State Functional Connectivity MRI Study
Authors: Piao Sirong , Chen Keliang , Wang Na , Zhang Yong , Li Yuxin
Published: August 2024

The default mode network (DMN) could be further divided into three subsystems, and each subsystem of DMN serves different cognitive functions. In this study, we revealed that cognitive decline is driven by weakened functional connectivity within the core subsystems, but enhanced functional connectivity between the core and MTL subsystems as well as the core and DMPFC subsystems. This dissociation may reflect abnormal core-centered connection abnormalities, along with the disruption of the MTL subsystem and the DMPFC subsystem to some degree. Our findings provided a promising imaging biomarker for the early diagnosis of AD.
A python-based post-processing toolkit for rodent perfusion MRI
Authors: Zhang Jinyuan , Yang Yishuang , Xue Rong , Zhuo Yan , Zhang Zihao
Published: August 2024

We developed a python-based post-processing toolkit for rodent perfusion MRI with an easy-to-use graphical user interface (GUI). Until now, this toolkit provides interfaces for the post-processing of dynamic susceptibility contrast (DSC) MRI and flow-sensitive alternating inversion recovery (FAIR) pulsed arterial spin labeling (pASL). For each modality, the toolkit has function modules including image viewer, display of time series data, ROI tools, and visualization of quantitative parameter maps. This toolkit is open source and welcomes added features. It will benefit preclinical studies using perfusion MRI.
Automated modeling and morphologic analysis of deep medullary veins at 7T MRI in patients with cognitive impairment
Authors: Li Zhixin , Zhang Jingyuan , Liang Li , An Jing , Qian Hairong , Xue Rong , Zhuo Yan , Zhang Zihao
Published: August 2024

Deep medullary veins (DMVs) support cerebral venous drainage. They may display abnormal changes in patients with cognitive impairment. They can be visualized by multi-echo gradient echo imaging at 7T. This study proposed a segmentation and tracking method based on deep learning and shortest-path optimization. It automatically quantified the morphologic parameters of DMVs from the vascular model. These characteristics of DMVs correlated with the patients’ cognitive scores, and might reflect the pathology of vascular lesions in cognitive impairment.
CNN-based Estimation of Spatio-Temporal Regularization Parameter-Maps for TV-Reconstruction in Dynamic Cardiac MRI
Authors: Kofler Andreas , Sirotenko Clemens , Zimmermann Felix , Schote David , Kolbitsch Christoph , Ba Fatima , Altekrüger Fabian , Papoutsellis Evangelos , Papafitsoros Kostas
Published: August 2024

We propose a method for estimating spatio-temporal regularization parameter-maps to be used for dynamic cardiac MR image reconstruction using total variation (TV)-minimization. Based on recent developments in algorithmic unrolling using Neural Networks (NNs), our approach uses two sub-networks. The first one predicts a spatio-temporal regularization parameter-map from an input image. Then, a second sub-network approximately solves a TV-reconstruction problem which is formulated with the estimated regularization parameter-map. We show that the proposed method can be used to further improve the TV-reconstructions compared to using only one single scalar regularization parameter or two regularization parameters for space and time.
Accelerated 3D dynamic upper-airway MRI in naturally sleeping obstructive sleep apnea patients.
Authors: Alam Wahidul , Liu Junjie , Lingala Sajan
Published: August 2024

Obstructive sleep apnea (OSA) is characterized by breathing-related obstructions of the upper airway during sleep. In this work, we develop a motion resolved extra-dimension sparsity-based approach to resolve the kinematics of upper-airway in OSA during natural sleep. This approach is demonstrated on two adult OSA patients: one undergoing a Bi-directional positive airway pressure therapy during MRI scanning, and one without therapy
Accelerated whole-heart MRI for congenital heart disease patients using a motion-corrected deep learning reconstruction network
Authors: Phair Andrew , Fotaki Anastasia , Felsner Lina , Qi Haikun , Botnar René , Prieto Claudia
Published: August 2024

A deep learning reconstruction framework, trained in an end-to-end fashion and incorporating both a non-rigid respiratory motion estimation network and a motion-informed model-based reconstruction network, has been previously demonstrated to enable good quality images from seven-fold undersampled acquisitions for coronary magnetic resonance angiography applications. Herein, we apply the framework to whole-heart MRI scans of patients with congenital heart disease, enabling fast reconstruction of 7×-accelerated acquisitions and achieving image quality comparable to that of state-of-the-art patch-based low-rank iterative techniques.
Convergent and Interpretable Dynamic Cardiac MR Image Reconstruction with Neural Networks-based Convolutional Dictionary Learning
Authors: Kofler Andreas , Wald Christian , Schaeffter Tobias , Haltmeier Markus , Kolbitsch Christoph
Published: August 2024

In this work we consider three different variants physics-informed Neural Networks (PINNs) which use the convolutional dictionary learning framework for image reconsruction in dynamic cardiac MRI. Although all three NNs share the same mechanism for regularization, the iterative schemes differ because they are derived from different problem formulations. We compare the methdos in terms of reconstruction performance as well as stability with respect to the number of iterations. All three methods yield similarly accurate reconstructions. However, by construction, only one of the three methods defines a convergent reconstruction algorithm and is therefore stable w.r.t. to the number of iterations.
Two-Stage Kalman Filtering as a Framework for Accelerated Cardiac MRI
Authors: Curtis Aaron , Cheng Hai-Ling Margaret
Published: August 2024

Robust, real-time dynamic cardiac MRI (CMR) would provide information on the temporal signatures of disease that we currently cannot assess. We present a novel Kalman filtering framework that uses a priori statistics derived from a single cardiac cycle to adaptively predict temporal cardiac dynamics. Kalman filtering is ideal, as it ameliorates noise introduced from our maximum acceleration factor of 60, guarantees reconstruction fidelity, and enables flexible undersampling. Furthermore, reconstruction may be performed at an even higher temporal resolution than the training data. As such, our algorithm can be a foundation for true real-time dynamic CMR.
Implementation of Hyperpolarized 129Xe Accelerated MRI in Phantom and Human Lungs: Preliminary Study and Troubleshooting
Authors: Perron Samuel , Fox Matthew , Ouriadov Alexei
Published: August 2024

Accelerated MRI could significantly improve image quality of lung imaging without increasing costs, especially for low field strengths. The signal decay of a series of undersampled xenon-129 images is fitted to the Stretched-Exponential-Model to yield higher SNR. The proposed method was implemented in undersampled phantom images at low field (0.074T) and human lung images at high field (3T) using the FGRE pulse sequence with hyperpolarized 129Xe; SNR was significantly improved within the same scan duration compared to a fully-sampled image. Potential issues with the compressed-sensing reconstruction are identified and possible solutions presented to promote robustness of method.
Deep Magnetic Resonance Fingerprinting Based on local and global vision transformer
Authors: Li Peng , Li Xiaodi , Lu Xin , Hu Yue
Published: August 2024

Magnetic resonance fingerprinting (MRF) can achieve simultaneous imaging of multiple tissue parameters. However, the size of the tissue fingerprint dictionary used in MRF grows exponentially as the number of tissue parameters increases, which may result in prohibitively large dictionaries that require extensive computational resources. Existing CNN-based methods obtain parameter reconstruction patch-wisely, using only local information and resulting in limited reconstruction speed. In this paper, we propose a novel end-to-end local and global vision transformer (LG-VIT) for MRF parameter reconstruction. The proposed method enables significantly fast and accurate end-to-end parameter reconstruction while avoiding the high computational cost of high-dimensional data.
Motion-mitigated reconstruction of accelerated MRI by using an unfolded variational network
Authors: Zhou Zijian , Qi Haikun , Hu Peng
Published: August 2024

Motion-mitigated reconstruction of highly undersampled MRI was achieved by adding a motion estimation module to the data consistency part of the model-based unfolded variation network. The motion estimation module consisted of a pair of convolutional blocks with residual inputs and added only limited number of trainable parameters to the network. The network was trained and tested on synthesized motion-corrupted images from a publicly available knee dataset. The reconstructed images with the proposed motion estimation module were sharper, and details were better recovered, with the structural similarity and peak signal-to-noise ratio significantly improved.
Does CS-SENSE acceleration influence the performance of an AI based synthetic CT algorithm? A volunteer study in the lumbar spine.
Authors: Shcherbakova Yulia , van der Velden Tijl , Seevinck Peter
Published: August 2024

In this work, we investigated the performance of an AI based algorithm - synthetic CT generation - when subjected to compressed sensing-sensitivity encoding (CS-SENSE) accelerated gradient echo images. We performed MR experiments in five volunteers, using different CS-SENSE acceleration factors for the MR acquisitions. Our results showed that using CS-SENSE factors of 1.45 and 2 increased noise in the MR source images but did not compromise the sCT reconstruction on visual inspection, which was confirmed by quantitative metrics. However, CS-SENSE with a factor of 3 caused artifacts in the sCT images which may affect the safety and diagnostic performance of the product.
Parallel non-Cartesian Spatial-Temporal Dictionary Learning Neural Networks (stDLNN) for Accelerating Dynamic MRI
Authors: Wang Zhijun , She Huajun , Du Yiping
Published: August 2024

Dynamic MRI shows promising clinical values and several applications have been investigated such as cardiac, pulmonary, and hepatic imaging. However, a successful application of dynamic MRI is hampered by its time-consuming acquisition. To improve the performance and interpretability for the accelerating reconstruction methods, we proposed the parallel non-Cartesian Spatial-Temporal Dictionary Learning Neural Networks (stDLNN), which combines the traditional spatial-temporal dictionary learning methods with the deep neural networks for accelerating dynamic MRI. It has favorable interpretability and provides better image quality than the state-of-the-art CS methods (L+S, BCS) and deep learning methods (DCCNN, PNCRNN), especially at high acceleration rate at R=25.
Improving the accuracy of Multipool-Lorentzian fitting in CEST MRI by use of a Pseudo-Voigt lineshape for direct water saturation
Authors: Huemer Markus , Stilianu Clemens , Stollberger Rudolf
Published: August 2024

In Chemical Exchange Saturation Transfer (CEST) MRI one common analysis technique is Multipool-Lorentzian fitting of the resulting Z-Spectrum. Multiple Lorentzian lineshapes are fitted to the measured data. The lineshape of the direct water saturation (DS) can deviate substantially from a Lorentzian depending on the saturation scheme and $$$B_1^+$$$. To prevent a cross-influence of the DS on the CEST and increase the fit accuracy we propose the use of a Pseudo-Voigt lineshape for the water line.
Deformable Groupwise Registration Using a Locally Low-Rank Dissimilarity for Myocardial Strain Estimation from Cine MRI Images
Authors: Chen Haiyang , Hu Chenxi
Published: August 2024

We propose a deformable groupwise registration method using a locally low-rank (LLR) dissimilarity to estimate myocardial strain from cine MRI images. The proposed method eliminates the drift effect commonly observed in the optical flow and sequentially pairwise registration, facilitating more accurate strain estimation in the diastolic phase. Compared to the globally low-rank dissimilarity, LLR dissimilarity shows slightly better tracking accuracy by imposing the low-rank property in local image regions rather than the whole image. Experiments on a large public cine MRI dataset demonstrates the accuracy of the proposed method on tracking and strain estimation.
Habitats Analysis in Hepatocellular Carcinoma to Predict Microvascular Invasion by Intravoxel Incoherent Motion: A Pilot Study
Authors: Li Chenhui , Xie Jinhuan , Long Liling , Zhang Huiting , Song Yang
Published: August 2024

The method of delineating the ROI of whole lesions on quantitative parameter images and then averaging them for comparison did not accurately quantify heterogeneity. In this study, we adopted a habitats analysis method combined with tissue cellularity and blood flow information from IVIM model to segment whole tumor to four subregions to predict microvascular invasion (MVI) in hepatocellular carcinoma. The results show that habitats analysis predicts MVI positivity with an accuracy of 70.19%, and the averaged value of each parameter in whole tumor was not predictive for MVI. This provides a good starting point for further application of this method.
Arterial phase detection when utilizing stack-of-stars dynamic Data Set with various pseudo contrast enhancement
Authors: Hoshiyama Yutaka , Wang Chunqi , Yang Hong , Ota Hideki , Masuda Atsuro , Kawabata Masahiro , Kutsuna Hideaki , Shinoda Kensuke , Kassai Yoshimori
Published: August 2024

We propose an automated method to present candidates of the arterial phase as the optimal time points from the liver contrast-enhanced MRI images based on the time intensity curve (TIC) analysis of the several ROIs. In clinical situation, there may be some differences of TIC due to a speed of uptake and washout and a quality of the image. In this study, the robustness of our proposed automated method was investigated by utilizing stack-of-stars dynamic images with various pseudo contrast enhancement effects. The results showed that our proposed automated method was applicable for such effects.
Head-to-head Comparison of Free Water Elimination Methods in Fornix
Authors: Sakaie Ken , Koenig Katherine , Lowe Mark
Published: August 2024

Diffusion Tensor Imaging measures in fornix may serve as a biomarker in Alzheimer’s disease. However, partial volume averaging between the fornix and surrounding cerebrospinal fluid imposes systematic bias that can conflate tissue microstructure with atrophy. Free Water Elimination methods have been proposed as a solution, but comparison between these methods is limited. We perform direct comparison between the approaches in terms of repeatability and bias.
Translation of a non-contrast quantitative MRI protocol for portal pressure prediction
Authors: Bradley Chris , Cox Eleanor , Francis Susan
Published: August 2024

Most complications in liver cirrhosis arise from portal hypertension. Using a vendor-specific fat suppressed spin-echo echo planar imaging T1 mapping method along with measures of flow within the superior mesenteric artery, we previously validated MRI as a surrogate measure of portal pressure at 1.5 and 3T. Here we translate this work to three MR vendors (GE, Philips and Siemens) using commercially available sequences allowing multi-site studies of assessment of portal pressure. Importantly, this could provide a non-invasive measure of portal pressure for clinical use to replace current invasive gold standard measures.
A statistical analysis of ROI weighting by area for MRE derived liver stiffness measurements
Authors: Yu Justin , Silva Alvin , Silva Annelise , Doan Matthew , Panda Anshuman
Published: August 2024

MR elastography (MRE) derived liver stiffness measurements (LSMs) require manual drawing of ROIs on elastogram images. These ROIs may differ in size, and some clinicians suggest that reporting mean stiffness weighted by ROI area is more accurate than the unweighted mean. In this study the unweighted and weighted mean liver stiffness were calculated for 161 patients undergoing liver MRE exams using various scanning hardware/field strengths, and the statistical significance of the difference between the two sets of LSMs was tested using a paired two-tailed t-test. No statistically significant differences were found between weighted and unweighted LSMs.
Assessment of association between body composition contents and liver fibrosis in the patients with sarcopenic obesity
Authors: Kim Tae-Hoon , Jeong Chang-Won , Lee ChungSub , Noh SiHyeong , Lim DongWook , Kim Youe Ree , Lee Young Hwan
Published: August 2024

Sarcopenic obesity is a disease which associates both sarcopenia and obesity and may trigger worse clinical outcomes including hepatic manifestation of fat accumulation and musculoskeletal disabilities. It is likely that sarcopenia and obesity share common physiological pathways and are interconnected through the muscle-liver-adipose tissue axis. Assessment of muscle mass is a key for the whole-body insulin-mediated glucose metabolism and energy homeostasis. However, it is little known the interconnection between hepatic fibrosis and sarcopenic obesity. This study compared body composition contents in non-obese and sarcopenic obese patients using abdominal MRIs and investigated the relationship between hepatic fibrosis and sarcopenic obesity factors.
The feasibility of fat quantification by MRI-PDFF maps for assessing grading of NAFLD
Authors: Qi Hongyan , Lian Jianxiu , Nan Jiang , Wang Xuan , Lei Junqiang
Published: August 2024

Non-alcoholic fatty liver disease (NAFLD) is a serious threat to human health, and the investigation for non-invasive biomarkers to quantify hepatic fat content appears to be crucial. In the study, PDFF was used to quantify liver fat content, assess the grade and degree of hepatic steatosis. PDFF was found to be effective in assessing fat content in NAFLD, which is expected to be used as a biomarker to assess the grading of steatosis in patients with NAFLD.
Influence of Different uCS Acceleration Factors on Three-dimensional Magnetic Resonance Cholangiopancreatography Image Quality
Authors: Lihua Chen , Qingwei Song , Wang Nan , Dai Yongming , Yu Dan , Li Guobin , Liu Ailian
Published: August 2024

To investigate the effects of different united compressed sensing (uCS) acceleration factors (AFs) on three-dimensional magnetic resonance cholangiopancreatography (3D-MRCP) image quality and to compare the quality with that using conventional parallel imaging (PI).
Adjustment of Saturation and Rotation Effects (AROSE) for CEST Imaging
Authors: Jin Tao , Chung Julius
Published: August 2024

Endogenous CEST signal usually has low specificity due to contamination from the magnetization transfer (MT) effect and from other labile protons with close Larmor frequencies. We propose to improve CEST signal specificity with AROSE which measures the difference between CEST signals acquired with similar average saturation power but largely different duty cycles (DC), e.g., a continuous wave or a high DC pulse train versus a low DC one. Simulation and creatine phantom studies showed that AROSE can improve the specificity of slow to intermediate exchanging CEST signals with relatively limited loss of sensitivity.
Development of in vivo quantitative gluCEST fitting using quantitative 1H-MRS as a reference in the mouse brain
Authors: Maguin Cécile , Mougel Eloïse , Valette Julien , Flament Julien
Published: August 2024

In this work, we propose to quantify glutamate with CEST imaging. We use quantitative magnetic resonance spectroscopy as a standard method to measure glutamate concentration in the mouse striatum, and build a CEST model optimized for high saturation power to properly fit glutamate concentration. The CEST estimator developed in this way allowed us to recover glutamate concentration with an average error of 0.7 mM.
SNR-boosted whole-brain chemical exchange saturation transfer imaging by optimized variable flip angles
Authors: Yong Xingwang , Hsu Yi-Cheng , Sun Yi , Zhang Yi
Published: August 2024

It is well-known that the refocusing flip angles (FAs) of the SPACE sequence can be optimized to generate different image contrasts, such as T1-weighted or T2-weighted. However, the existing SPACE variable FA scheme is unsuitable for CEST imaging whose utmost aim is to increase the SNR during signal readout instead of enforcing contrast. Here, we derived a model to describe the signal-to-noise ratio (SNR) of the SPACE sequence, and maximized SNR by varying refocusing flip angles. Compared to the original constant FA protocol, the optimized variable flip angles yielded both SNR and resolution improvement.
No denoising, no diamonds? - In silico analysis of denoising methods for CEST MR imaging
Authors: Radke Karl Ludger , Adriaenssens Vibhu , Kamp Benedikt , Gallinnis Patrik Jan , Bechler Eric , Wittsack Hans-Jörg , Antoch Gerald , Müller-Lutz Anja
Published: August 2024

CEST imaging requires a high SNR to detect low metabolite concentrations, especially at clinical used magnetic field strength (3 Tesla). In recent years, various approaches have been used to denoise CEST data. Our study investigated the performance of different denoising algorithms using 1000 synthetic CEST MR data. Our results showed that PCA produced the best denoising results for CEST MR imaging in a simulation study.
Probing metabolites in antiretroviral and nicotine treated mouse brains using MRS and CEST-MRI
Authors: Gauthier Gabriel , Bade Aditya , Liu Yutong
Published: August 2024

To better understand synergistic effects of antiretroviral drugs (ARV) and nicotine on neuroimmune functions, we observed drug-associated metabolites in mice utilizing CEST MRI and MRS. Increased CEST signal was found at 3.5 ppm suggesting increased glutamate in mice treated with nicotine. MRS results showed increased myo-inositol in both ARV and nicotine treated mice. glutamate is an excitatory neurotransmitter and myo-inositol is a biomarker of glial activation. The imaging results suggested elevated neuronal activation and neuroimmune dysfunction.
Alterations of brain motion in idiopathic intracranial hypertension (IIH) based on amplified MRI (aMRI)
Authors: Kumar Haribalan , Mcdonald Matthew , Sharifzadeh Alireza , Wright Jet , Kwon Eryn , Potter Leigh , Condron Paul , Emsden Taylor , Cornfeld Daniel , Wilson Graham , Freschini David , Dubowitz David , Scadeng Miriam , Danesh-Meyer Helen , Holdsworth Samantha , Guild Sarah-Jane , Safaei Soroush , Tolou Gonzalo
Published: August 2024

Heartbeat-driven brain motion has historically remained limited to the domain of research. Such motion may provide a window to characterise parenchymal and CSF pressures where direct, invasive measurements are disruptive and difficult to justify. Amplified MRI (aMRI) is a recently developed method which amplifies subtle brain motion. We show preliminary data that aMRI can be used to detect changes in brain motion associated with increased intracranial pressure in idiopathic intracranial hypertension (IIH), suggesting a potential non-invasive method for evaluating pressure levels of the subarachnoid space in patients with altered intracranial pressure.
CO2 as an engine for neuro-fluid flow
Authors: Bhogal Alex , Tong Yunjie , van Grinsven Eva , Zwanenburg Jaco , Philippens Marielle
Published: August 2024

We use Blood Oxygen Level Dependent BOLD in combination with controlled hypercapnic stimulus to investigate the relationship between presumed cerebral blood volume changes and CSF flow in the brain. In a group of 11 subjects, we observe strong CSF inflow to the brain as a result of contracting cerebro-vasculature conforming to the Monro-Kellie Doctrine. Our results suggest that changes in arterial blood gases may provide an ‘engine’ through which to potentially enhance the clearance of waste from the brain.
Concurrent measurement of perfusion parameters related to small blood and lymphatic vessels in the human brain
Authors: Cao Di , Sun Yuanqi , Pan Su , Pillai Jay , Qiao Ye , Lu Hanzhang , Van Zijl Peter , Knutsson Linda , Hua Jun
Published: August 2024

Accumulating evidence has indicated the importance of studying the interaction between the microvascular and lymphatic systems in the brain. To date, most imaging methods can only measure blood or lymphatic vessels separately. This study proposes an MRI approach for concurrent measurement of perfusion parameters related to small blood and lymphatic vessels within one single scan. A dual-echo TSE sequence was optimized for the measurement of gadolinium(Gd)-induced blood and CSF signal changes. The proposed method showed consistent results in human brains as previous studies using separate methods. Signal changes from small blood vessels occurred faster than lymphatic vessels after intravenous Gd-injection.
CSF oxygenation imaging using long TE heavily T2-weighted Fluid-Attenuated Inversion Recovery
Authors: Taso Manuel , Alsop David
Published: August 2024

The cerebrospinal fluid plays an essential role in cerebral homeostasis, contributing to the delivery of oxygen and nutrients to brain tissue as well as clearing waste products. However, the mechanisms and functions of CSF oxygenation and their potential disturbance in pathology remain unknown. Dissolved O2 shortens T1 of water due to its paramagnetic properties. Because of its extremely long T2, selective CSF imaging can be achieved by using extremely long TE (>500ms) Spin-Echo based acquisitions. Therefore, we report here a study using ultra long TE Fluid-Attenuated Inversion Recovery to image baseline CSF oxygenation with minimal tissue contribution.
Altered Hippocampal Subregions Volumes Is Associated With Emotional Impairment of Parkinson’s Disease
Authors: Qu Mingrui , Gao Bingbing , Jiang Yuhan , Li Yuan , Xie Lizhi , Miao Yanwei
Published: August 2024

Depression is the main emotional manifestation associated with Parkinson's disease. The hippocampus is a core region in the limbic system, critical in regulating emotion. This study explored the subregional atrophy pattern of the hippocampus in Parkinson's disease with depression (DPD) patients and its correlation with the severity of depressive symptoms. The results of this study suggest that DPD patients exhibit a left asymmetric atrophy pattern in the hippocampus and its subregions. Partial correlation analysis showed that the left dentate gyrus, left molecular layer, left CA4 and left hippocampal volumes were negatively correlated with Hamilton depression scale scores in DPD patients.
The evaluation of relationship between motor cortex GABA levels and Gyrification Pattern in Patients With early-onset Parkinson Disease
Authors: Tian yuan , Liu pengfei , Lian Jianxiu
Published: August 2024

Stimulation of the motor cortex (MC) signiﬁcantly reduce akinesia and bradykinesia in Parkinson Disease (PD), indicating a key role of motor cortex abnormalities in the pathogenesis of PD. Early-onset Parkinson disease (EOPD), varying between 40 and 55 years of age, it carries additional societal and personal consequences and psychosocial disruption. Thus we aim to explore the cortical gyriﬁcation changes as well as their relationships with r-aminobutyric acid (GABA) in the motor cortex(MC) of patients with early-onset Parkinson disease (EOPD). Results showed that decreased in LGI and GABA+/Cr ratios in the motor cortex were found to be slightly coupled.
Glymphatic system impairment in Parkinson’s disease with rapid movement sleep behavior disorder
Authors: Chen Amei , Huang Junxiang , Huang Xiaofei , Cheng Xiaofang , Xu Yongzhou , Wei Xinhua
Published: August 2024

To assess the activity of the glymphatic system in PD patients with probably rapid movement sleep behavior disorder (PD-pRBD) using diffusion tensor image analysis along the perivascular space( DTI-ALPS) index. 61 PD-pRBD, 92 PD patients with no probable RBD(PD-npRBD) and 59 healthy control (HC) were included in the study. The results showed that the ALPS index in PD-pRBD group was lower than that in PD-npRBD group. The index of ALPS in PD-pRBD was negatively correlated with REM sleep behavior disorder screening questionnaire(RBDSQ) score. We concluded that the glymphatic system function of PD with RBD is impaired.
Sex differences in brain structure in de novo Parkinson’s disease: A cross-sectional and longitudinal neuroimaging study
Authors: Li Hui , Zhang Chen , Jia Xiuqin , Yang Qi
Published: August 2024

The aim of this study was to investigate sex differences in brain structure at baseline and sex differences in longitudinal changes at follow-up between female and male PD patients after excluding the expected effects of age and sex. At baseline, male PD patients exhibited significantly lower brain volume and decreased cortical thickness than age-matched female PD patients. At follow-up, these sex differences remained stable and analogous progressive brain atrophy with no sex interaction were found in male and female PD patients, suggesting similar trend in disease progression between sexes over time.
Amplitude of low-frequency fluctuation-based regional radiomics similarity network: biomarker for Parkinson’s disease
Authors: Shi Dafa , Zhang Haoran , Wang Guangsong , Ren Ke
Published: August 2024

Development of more clinically effective and quantifiable biomarkers to detect PD is urgently needed. It confirmed that regional radiomics similarity network (R2SN) had high reproducibility and a biological basis and provided a new perspective for understanding the human brain. Our study showed that R2SN constructed based on ALFF had good reproducibility and stability, and is biological plausibility. We found PD-related brain regions mainly located in the default-mode, sensorimotor, executive control, visual, frontoparietal network, as well as cerebellum, and striatum. ALFF-based R2SN is a novel, robust potential neuroimaging biomarker for PD and could provide new insights into connectome reorganization in PD.
Advanced intraoperative image quality using multiple surface coils.
Authors: Jellema Pien , Visser Fredy , Blanken Niels , de Luca Alberto , Hoving Eelco , van Baarsen Kirsten , Lequin Maarten , Wijnen Jannie
Published: August 2024

Advanced intraoperative MRI (io-MRI) could provide additional guidance during pediatric neurosurgery. Currently, io-MRI sequences are acquired with two surface coils when using the DORO head-frame. We investigated if the addition of two surface coils and higher SENSE-factors would increase signal- and contrast-to-noise ratios (SNR & CNR), image quality, and decrease artefacts. The four coils set-up resulted in higher T1w SNR and CNR that was more homogeneously distributed. Image quality of T1w, T2w, and fiber-tracks did improve with four coils. Higher SENSE factors with four coils of most ASL and diffusion MRI images did not reduce EPI artefacts or improve image quality.
Magnetic Resonance Spectroscopic Correlates of Survival in IDH-wt, TERTp-mut Gliomas
Authors: Sacli-Bilmez Banu , Danyeli Ayça Erşen , Yakicier Cengiz , Pamir M.Necmettin , Özduman Koray , Dinçer Alp , Ozturk-Isik Esin
Published: August 2024

The 2021 central nervous system tumor classification has suggested that isocitrate dehydrogenase wildtype (IDH-wt) WHO grade-2/3 astrocytomas with molecular features of glioblastoma should be designated as “Glioblastoma, IDH-wildtype, WHO grade-4”. In this study, we explored metabolic correlates of patient survival in tumors fulfilling the criteria for “Glioblastoma, IDH-wildtype, WHO grade-4” using short echo time (TE) single voxel 1H-MRS. The results of this study suggest that higher ratios of glutamine and glutamate complex (Glx) to total creatine (tCr) and glutathione (GSH) to tCr were associated with a shorter survival.
Differentiation of atypical high-grade glioma from primary central nervous system lymphoma with mean apparent propagator-MRI
Authors: Gao Eryuan , Zhao Guohua , Zhang Huiting , Ma Xiaoyue , Wang Peipei , Bai Jie , Yan Xu , Yang Guang , Cheng Jingliang
Published: August 2024

Atypical high-grade glioma (HGG) (with no or little necrosis) and primary central nervous system lymphoma (PCNSL) are difficult to distinguish in routine MR images but their treatment strategies are totally different. Therefore, it’s important to distinguish between them before treatment. This study aimed to investigate the diagnostic efficiency of quantitative analysis based on mean apparent propagator-MRI in discriminating atypical HGG from PCNSL. Through quantitative analysis of MAP parameters, we found that MAP-MRI performed well in differentiating between atypical HGG and PCNSL.
Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction
Authors: Jung Woojin , Mun Seongjae , Ko Jingyu , Kang Koung Mi
Published: August 2024

We validated the brain volumetric results with 3D T1 weighted images with accelerated scans reconstructed by FDA-cleared deep learning-based software (SwiftMR, AIRS Medical). Acceleration scans with three different acceleration levels were simulated using k-space undersampling, and the image quality and brain volume measures were evaluated. In addition, we acquired conventional and accelerated scans from each participant to evaluate the reliability between conventional and accelerated scans reconstructed by SwiftMR and inter-method reliability between different brain segmentation software. As a result, brain volume measures with accelerated scans with deep learning-based reconstruction were in good agreement with those of the corresponding conventional scan.
Reliable and repeatable fully automated bolus arrival times and arterial inputs using 2 Hz whole brain multiband DSC-MRI at 7T
Authors: Schwartz Daniel , Li Xin , Lesage Fred , Linninger Andreas , Jamshidi Mohammad , Stone Becky , Rooney William
Published: August 2024

Dynamic susceptibility contrast imaging has used bolus arrival time (BAT) in tissue, relative to an arterial input function (AIF), as a nuisance variable when deriving perfusion metrics (e.g. blood flow). However, BAT reflects physiological changes in both fluid dynamics of feeding vasculature and capillary inflow. This work presents a reproducible approach for reliable and repeatable quantification of an AIF and whole brain BAT, which itself may be germane to chronic and acute cerebrovascular disease (CVD), such as white matter hyperintensities, age-associated CVD, and stroke.
Diagnostic ability of APT in differentiating ovarian high-grade serous carcinomas from borderline serous tumors
Authors: Song Jiacheng , Zhang Aining , Zhao Xiance , Wang Yishi , Shen Zhiwei , Chen Ting
Published: August 2024

The precise assessment of ovarian tumor, which is complex in presentation and classification, is important for clinical decision making. The value of amide proton transfer weighted (APTw) imaging in the assessment of ovarian lesion has not been comprehensively researched. In this study, we investigated the value of APTw imaging in differentiating ovarian high-grade serous carcinomas from borderline serous tumors. It was found that APT value of high-grade tumor was significantly lower than that of borderline tumor. Our finding indicates the potential of using APTw imaging as a novel method for the differentiation diagnosis of ovarian cancers.
Multiparametric MRI-based Radiomics for Preoperative Prediction of Multiple Biological Characteristics in Endometrial Cancer
Authors: Changjun Ma , Qingling Song , Shifeng Tia , Lihua Chen , Nan Wang , Liangjie Lin , Jiazheng Wang , Ailian Liu
Published: August 2024

Different biological characteristics of endometrial cancer (EC) may lead to different treatment efficacies and prognoses, so stratification of biological characteristics in EC is important for treatment planning.
Quantitative assessment of HIF-1a expression in endometrial cancer by DCE-MRI combined ESWAN multiparameter imaging
Authors: Zongyuan Xie , Shifeng Tian , Ailian Liu
Published: August 2024

Hypoxia -inducible factor (HIF-1α) is a major transcriptional factor regulating gene expression under hypoxic conditions. High expression of HIF-1α contributes to high aggressiveness or poor prognosis of cervical carcinoma. Multimodal MRI techniques DCE-MRI and ESWAN are new tools to determine the expression of HIF-1α. Its quantitative parameters Ktrans, Kep R2 * and T2* values were correlated with HIF-1a expression. Therefore,both DCE-MRI and ESWAN techniques can effectively evaluate HIF-1a expression in endometrial cance.
Amide Proton Transfer Weighted Combined with Diffusion Kurtosis Imaging for Predicting Lymph Node Metastasis in Cervical Cancer
Authors: Wang Yue , Tian Shifeng , Liu Ailian
Published: August 2024

Cervical cancer (CC) is one of the most common gynecological malignancies worldwide, and its incidence is gradually increasing. Acurate identification of lymph node metastases (LNM) is crucial for predicting prognosis and choosing the best available treatment. Amide proton transfer weighted (APTw) imaging can detect the chemical exchange rate of between water and endogenous mobile proteins, peptides or polypeptides[1]. Diffusion kurtosis imaging (DKI) can reflect the limited diffusion movement of water molecules in tissue and the complexity of tissue microstructure [2]. This study is aimed to investigate the quantitative prediction of LNM in CC by APTw combined with DKI.
Saturation Transfer MR Fingerprinting (ST-MRF): free bulk water, semisolid macromolecule, and amide proton parameter quantification
Authors: Singh Munendra , van Zijl Peter , Jiang Shanshan , Zhou Jinyuan , Heo Hye-Young
Published: August 2024

Conventional saturation transfer MRI approaches, such as magnetization transfer contrast (MTC) and chemical exchange saturation transfer (CEST) MRI, acquire qualitative contrast weighted images, without specific information on the quantitative parameters affecting contrast, namely proton exchange rate and concentration. In addition, the contrast weighted images are highly dependent on scan parameters and data acquisition strategies. Here, we developed a fast, quantitative saturation transfer (ST) imaging technique based on MR fingerprinting principles to simultaneously estimate free bulk water, semisolid macromolecule, and amide proton-related parameters. The approach was evaluated with Bloch simulation and synthetic MRI analysis using in vivo human brains.
Maximization of cucurbit[6]uril hyperpolarized chemical exchange saturation transfer (HyperCEST) in bovine blood at 3.0 T
Authors: Grynko Vira , Batarchuk Viktoriia , Shepelytskyi Yurii , Aalto Hannah , Deschamps Joseph , Russet Iulian , Albert Mitchell
Published: August 2024

Cucurbit[6]uril is a well-studied contrast agent for hyperpolarized 129Xe (HP 129Xe) MRI. Although the in vivobiodistribution of CB6 was measured with hyperpolarized chemical exchange saturation transfer (HyperCEST), there were no previous studies reported for maximization of the HyperCEST effect by optimization of depolarization pre-pulse trains. In the present work, we maximized the CB6 HyperCEST effect in bovine blood, and found for the first time, a HyperCEST depletion of the RBC resonance. In addition, the minimum detectable concentration was found to be four times lower than previously reported.
Increasing sampling efficiency using Yarnball sampling in 3D fast spin echo with long echo trains – TurboYarn
Authors: Snyder Jeff , Wilman Alan , Stobbe Rob
Published: August 2024

An efficient k-space sampling strategy using 3D Yarnball was used in long echo train FSE (TurboYarn). As TurboYarn samples many lines worth of k-space in each readout, fully sampled isotropic 1 mm brain scans were acquired in 40 s. TurboYarn was compared to a time-equivalent, 4x under-sampled 3D FSE sequence in brain of three healthy subjects. Resulting images showed excellent GM/WM contrast for TurboYarn, with CNRs higher than 3D FSE. As each readout samples k-space centre, further work will investigate TurboYarn motion robustness, with additional SNR improvements via trajectory and flip angle train optimizations.