bluuebunny/crossref_metadata_2025 huggingface dataset:
Особенности функционирования наименований предметов одежды в английских фразеологизмах
Authors: Е.А. Курочкина
Published: November 2024

в данной статье рассматриваются особенности функционирования наименований предметов одежды в составе английских фразеологических единиц. Актуальность исследования определяется интересом к специфике использования наименований предметов одежды и их символизации в составе фразеологизмов, поскольку дает возможность для более глубокого понимания материального и духовной наследия народа. Автор использовал такие методы исследования как аналитико-описательный метод, интерпретационный метод, метод количественных подсчетов, статистический метод, метод сплошной выборки. Объектом исследования являются различные типы фразеологических единиц, в том числе пословицы и поговорки, с названиями одежды. Анализ показал, что наиболее частотными лексическими единицами являются clothes (одежда), hаt (шляпа), shoes (обувь) и shirt (рубашка). Самым часто встречающимся наименованием аксессуара стали glоvеs (перчатки). Реже всего можно встретить в структуре фразеологизмов такие наименования деталей одежды как shoestring (шнурок), stitch (шов), hооd (капюшон). Необходимо отметит, что наименования предметов одежды в составе пословиц и поговорок могут служить как для описания ситуации, так и для характеристики человека. Кроме того, основной части лексических единиц присуща стилистическая и гендерная индифферентность.

this article examines the features оf the functioning оf clothing item nаmеs in English phraseological units. The rеlеvаnсе оf the study is determined bу the interest in the specifics оf using clothing item nаmеs and their symbolization in phraseological units, since it provides аn opportunity fоr а dееpеr understanding оf the material and spiritual heritage оf the реорlе. The author used such rеsеаrсh methods аs the analytical and descriptive method, the interpretative method, the method оf quantitative calculations, the statistical method, and the method оf continuous sampling. The object оf the study is various tуpеs оf phraseological units, including proverbs and sayings with clothing nаmеs. The analysis showed that the most frequent lexical units аrе clothes, hаt, shоes and shirt. The most common nаm fоr аn accessory is glоves. The least common nаmеs fоr clothing items in the structure оf phraseological units аrе shoestring, stitch, hооd. It should bе nоtеd that the nаmеs оf clothing items in proverbs and sayings cаn serve both tо describe а situation and tо characterize а pеrsоn. In addition, the main part оf the lехiсаl units is characterized bу stylistic and gender indifference.
AI in policing and security
Authors:   Parliamentary Office of Science and Technology, Christie Lorna
Published: November 2024

Artificial intelligence could change policing. But the efficacy of such technologies is not well established. What are the governance and privacy concerns?
Meaningful environmental and social governance reporting for net zero
Authors:   Parliamentary Office of Science and Technology, Wentworth Jonathan
Published: November 2024

The reporting of environmental, social and governance (ESG) risks could encourage investments that address climate change targets, but a lack of standards raises reliability concerns.
Responding to the challenge of antimicrobial resistance
Authors:   Parliamentary Office of Science and Technology, Vagnoni Cristiana
Published: November 2024

Antimicrobial resistance is a global emergency. The Government has set out a series of strategies to tackle it. What progress has been made?
The future of UK research: structure and funding
Authors:   Parliamentary Office of Science and Technology, Vagnoni Cristiana
Published: November 2024

In its 2017 Industrial Strategy, the UK Government set out a target of investing 2.4% of GDP on R&D by 2027. How is it planning to reach this target? What are the uncertainties emerging from COVID-19 and the withdrawal from the European Union?
Research evidence and policy-making: increasing demand, publication speed and public scrutiny
Authors:   Parliamentary Office of Science and Technology, Vagnoni Cristiana
Published: November 2024

COVID-19 has increased demand for research evidence. In response the research and publication processes have sped up. What does this mean for scrutiny?
Cross-Vendor Multiparametric Mapping of the Human Brain Using 3D-QALAS: A Multicenter & Multivendor Study
Authors: Fujita Shohei , Gagoski Borjan , Hwang Ken-Pin , Hagiwara Akifumi , Warntjes Marcel , Fukunaga Issei , Uchida Wataru , Saito Yuya , Sekine Towa , Tachibana Rina , Muroi Tomoya , Akatsu Toshiya , Kasahara Akihiro , Sato Ryo , Ueyama Tsuyoshi , Andica Christina , Kamagata Koji , Amemiya Shiori , Takao Hidemasa , Hoshino Yasunobu , Tomizawa Yuji , Yokoyama Kazumasa , Bilgic Berkin , Hattori Nobutaka , Abe Osamu , Aoki Shigeki
Published: November 2024

Motivation: To address the unmet need for a cross-vendor, multiparametric technique to facilitate data pooling across sites. Goal(s): To evaluate a vendor-standardized multiparametric mapping scheme based on 3D-QALAS for whole-brain T1, T2, and proton density (PD) mapping. Approach: Intra-scanner repeatability and inter-vendor reproducibility were evaluated in vivo on five different 3T systems from four vendors (GE, Philips, Siemens, and Canon). Patients with multiple sclerosis were scanned on systems from different vendors to assess the feasibility of the scheme in real-world clinical settings. Results: 3D-QALAS provided T1, T2, and PD with coefficient of variations <4.0% using 3T scanners from different manufacturers. Impact: The four major vendors used in this study constitute a considerable portion of the global installation base, demonstrating the value of cross-vendor quantitative technique 3D-QALAS for imaging in clinical sites with multiple vendors, as well as in multicenter research settings.
Dynamic lung water magnetic resonance imaging during exercise stress
Authors: Seemann Felicia , Javed Ahsan , Khan Jaffar , Bruce Christopher , Chae Rachel , Yildirim Korel , Potersnak Amanda , Wang Haiyan , Baute Scott , Ramasawmy Rajiv , Lederman Robert , Campbell-Washburn Adrienne
Published: November 2024

Motivation: Quantification of lung water during exercise is of interest for early diagnosis of heart failure. Goal(s): To develop a time-resolved 3D MRI method to quantify lung water in transitions between rest and exercise. Approach: We derive quantitative time-resolved lung water density (LWD) maps using a motion corrected sliding-window image reconstruction. We included 12 healthy controls and 2 patients with heart failure, and a porcine model of mitral regurgitation (n=5). Results: We measured a peak exercise ΔLWD=16±6.8% in controls, but detected no changes during rest (ΔLWD=-1.4±3.5%, p=0.18). Accumulation rates were slower in patients (2.0±0.1%/min) vs controls (2.6±0.9%/min). Animals developed ΔLWD=3.3±1.5%. Impact: Exercise-induced changes in lung water can be dynamically quantified using a continuous 3D MRI acquisition with a sliding-window and motion corrected image reconstruction, which may have clinical utility in unmasking latent heart failure at early stages of disease.
Accelerated 2D Cartesian MRI with an 8-channel local B0 coil array combined with parallel imaging
Authors: Tian Rui , Uecker Martin , Davids Mathias , Thielscher Axel , Buckenmaier Kai , Holder Oliver , Steffen Theodor , Scheffler Klaus
Published: November 2024

Motivation: The inherently slow MRI scans can be accelerated through rapid modulation of nonlinear gradient fields; however, its fundamental mechanisms and limits remain incompletely understood and validated. Goal(s): We investigate accelerated MRI with flexible modulations of nonlinear B0 fields using a custom-built local B0 array. Approach: The sampling theory is extended to rigorously compare nonlinear field modulation schemes in a quantitative k-space. A novel field calibration technique is proposed to enhance reconstruction. With safety evaluations, we perform in-vivo accelerated scans. Results: Our in-vivo 2D FLASH scans make significant steps to speed up MRI with local B0 array, achieving eight-fold joint acceleration with parallel imaging. Impact: For the first time, the sampling efficiency of nonlinear gradients in the entire k-space is quantitatively visualized, allowing rigorous comparison of distinct B0 modulations. Furthermore, the field estimation technique enables fast and robust in-vivo scans accelerated by flexible nonlinear fields.
DE-NIK: Leveraging Dual-Echo Data for Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit k-Space Representations
Authors: Spieker Veronika , Stelter Jonathan , Huang Wenqi , Eichhorn Hannah , Weiss Kilian , Braren Rickmer , Zimmer Veronika , Hammernik Kerstin , Prieto Claudia , Karampinos Dimitrios , Schnabel Julia
Published: November 2024

Motivation: Neural implicit k-space representations (NIK) enable binning-free respiratory-resolved MR reconstructions in a data-driven manner. The multi-dimensionality of MR, i.e., provided in dual-echo acquisitions, is expected to improve reconstruction performance and allows for further echo-processing. Goal(s): A Dual-Echo-NIK that takes advantage of the redundant data present in two echoes and enables subsequent water-fat-separation. Approach: We propose three Dual-Echo-NIK variants trained (1) individually, (2) jointly and (3) in an echo-modulated way. Motion-resolved echo and water-fat reconstructions are evaluated on a free-breathing phantom simulation and in-vivo. Results: Quantitative simulations demonstrate improved performance for the modulated Dual-Echo-NIK. In-vivo reconstructions reveal sharper reconstructions when both echoes are utilized. Impact: The Dual-Echo Neural Implicit k-space Representations indicate how echo information can lead to improved motion-resolved reconstructions, including subsequent water-fat separations. Echo-modulation can further enhance reconstruction performance and offers the potential to reduce acquisition times for training data.
HD-Movienet: High-definition 4D MRI using 3D radial kooshball acquisition and deep learning reconstruction
Authors: Murray Victor , Wu Can , Otazo Ricardo
Published: November 2024

Motivation: State-of-the-art motion-resolved 4D MRI techniques lack sufficient spatial resolution and efficient acquisition and reconstruction for application in clinical practice. Goal(s): To develop HD-Movienet, a deep learning-based method to efficiently acquire and reconstruct 4D MRI with approximately 1mm isotropic resolution using 3D radial acquisitions. Approach: HD-Movienet uses accelerated half-spoke (UTE) and full-spoke (T1-weighted) 3D radial kooshball acquisition and image-time-coil deep learning 4D reconstruction without k-space data consistency. Results: HD-Movienet can enable 4D MRI with isotropic 1.1mm resolution, 4 minutes of scan time, and reconstruction of less than 7 seconds to image patients with lung tumors. Impact: Deep learning-based HD-Movienet reconstruction enables motion-resolved 4D MRI technique with isotropic 1.1mm resolution, 4 minutes of scan time, and reconstruction of less than 7 seconds for robust radiation-free imaging of patients with mobile tumors.
Automatic Infiltration Risk Prior Generation with Modified Triplet Loss for Pre-Operative Glioblastoma Infiltration Prediction
Authors: Zhao Walter , Gongala Sree , Goñi Eunate Alzaga , Wang Xiaofeng , Deng Shengwen , Tippareddy Charit , Akbari Hamed , Kazerooni Anahita , Davatzikos Christos , Couce Marta , Sloan Andrew , Badve Chaitra , Ma Dan
Published: November 2024

Motivation: Pre-operative glioblastoma (GBM) infiltration prediction models rely on manual infiltration risk (IR) prior segmentation which is tedious, requires expert input, and is highly variable. Goal(s): Automation is needed for fast segmentation. A data-driven method would account for GBM heterogeneity and be independent of specific MRI input for applicability to clinical protocols. Approach: IR priors are grown using modified triplet loss with inter-prior and intra-prior terms to ensure priors are distinct from each other and maintain similarity within individual priors. Results: TripleSeq generated more consistent IR priors compared to manual segmentation. TripleSeq-trained models showed good classification (> 85% mean accuracy) of ground truth infiltration. Impact: Glioblastoma (GBM) infiltration inevitably leads to tumor recurrence and progression. We introduce an automatic method to generate infiltration risk priors for improved GBM infiltration machine learning prediction, which applied pre-operatively can identify at-risk peritumoral regions for targeted neurosurgery and radiotherapy.
Predicting Brain Age of Healthy Adults Based on Morphological MRI Parcellation Using Radiomics
Authors: Montin Eros , Muccio Marco , Li Chenyang , Sun Zhe , Ge Yulin , Lattanzi Riccardo
Published: November 2024

Motivation: A machine learning model capable of accurately estimating brain age could have a large clinical impact. Goal(s): To apply radiomics analysis to morphological MR images and train a machine learning model capable of accurately estimating subjects’ age from radiomics features. Approach: T1- and T2-weighted brain images of 725 healthy adults were used to extract 18324 radiomics features from bilateral caudate, putamen, and hippocampus, and used to train a stacking regressor machine learning model. Results: Our machine learning model accurately estimated the subjects’ age with a mean absolute error of 4.77±0.35 years using radiomics features from T1-(45%) and T2-weighted(55%). Impact: Investigating advanced machine learning methods to accurately estimate brain aging based on commonly used clinical MR images provides vital insights to further improve our understanding of brain changes in both healthy aging and neurodegeneration.
Fast and motion robust brain examination using simultaneous multi-slice turbo gradient spin echo BLADE Sequence
Authors: Zhou Kun , Yang Li , Xiao Nan
Published: November 2024

Motivation: PROPELLER/BLADE is robust to motion in brain imaging but comes at the cost of longer acquisition time. Goal(s): Our goal was to reduce the acquisition time of commercial sequences (BLADE and EPI) based brain motion-insensitive workflow by a factor of 2. Approach: The SMS-TGSE-BLADE sequence was developed with acceleration techniques, including in-plane GRAPPA, SMS, and EPI readout. Results: Comparable image quality was obtained with the SMS-TGSE-BLADE sequence with more than 2-fold decrease in acquisition time. Impact: The improvement in acquisition speed in the motion-insensitive brain examination (including T1-FLAIR, T2W, T2-FLAIR and DWI) through SMS-TGSE-BLADE sequence may increase patient comfort. It can also increase patient throughput and cost efficiency of healthcare providers.
Deep Learning Reconstruction for Free-Breathing Radial Cine Imaging
Authors: Yurt Mahmut , Ryu Kanghyun , Li Zhitao , Zhu Xucheng , Mao Xianglun , Setsompop Kawin , Janich Martin , Pauly John , Syed Ali , Vasanawala Shreyas
Published: November 2024

Motivation: We aim to introduce a cardiac cine imaging protocol to address the issues of motion susceptibility and robustness in the previous techniques. Goal(s): Our objective is to demonstrate an accelerated acquisition and high-quality reconstruction framework based on free-breathing radial cardiac cine imaging that shows enhanced patient comfort and robustness against respiratory motion. Approach: We synergistically leverage a raw k-space preprocessing module, region optimized coil compression, and deep learning reconstruction based on memory efficient unrolled neural networks. Results: Our experiments indicate that the proposed framework achieves high reconstruction quality at large acceleration factors (e.g., 8x), in terms of spatial and temporal accuracy. Impact: Conventional cardiac protocols use Cartesian k-space sampling and are susceptible to motion artifacts. We provide an acquisition and reconstruction framework based on a free-breathing protocol and deep learning reconstruction for enhanced patient comfort and robustness against motion artifacts.
Distortion-Free Fat/Water Separated Body Diffusion-Weighted Imaging using Spatio-Temporal Joint Reconstruction
Authors: Zhou Xuetong , Hargreaves Brian , Lee Philip
Published: November 2024

Motivation: DWI is effective for cancer imaging, but conventional EPI suffers from geometric distortion and chemical shift artifacts. Conventional fat suppression techniques are sensitive to the large B0 and B1+ inhomogeneities in the body. Residual fat causes artifacts and is a confounding factor in using DWI for cancer diagnosis. Goal(s): Perform robust fat/water separation in distortion-free DWI. Approach: A diffusion-weighted EPTI acquisition and joint reconstruction method is used. Separation is performed using chemical shift encoding along the temporal dimension. A distortion-less FSE-based phase navigator is used to resolve shot-to-shot phase. Results: The proposed method is validated in vivo in the brain, head&neck, and breast. Impact: Using the proposed navigated EPTI sequence, we demonstrated fat/water separated DWI that is robust to B0 variation in the body. This will enable more reliable use of DWI to assess cancer and other abnormalities, complementing or replacing contrast-enhanced imaging.
Image recovery using deep end-to-end posterior networks
Authors: Chand Jyothi Rikhab , Jacob Mathews
Published: November 2024

Motivation: End-to-End (E2E) trained unrolled algorithms recover MR images with high quality. However, they have large memory demands during training. In addition, these maximum a posteriori methods cannot provide uncertainty estimates. Goal(s): To develop a memory-efficient framework for E2E learning of the posterior probability distribution. Approach: We model the posterior distribution as a combination of the data-consistent-determined likelihood term and the prior, represented using a Convolutional Neural Network whose weights are learned in an E2E fashion using maximum likelihood optimization. Results: The proposed E2E training strategy requires significantly less memory than unrolling. In addition, the model facilitates sampling and provides uncertainty estimates. Impact: The higher memory efficiency of the proposed E2E scheme makes it an attractive option for image reconstruction problems of large dimensions. The learned posterior model provides a minimum mean square estimate and uncertainty maps, which unrolled approaches cannot offer.
Impact of Gender on Alzheimer’s disease: a Behavioral and Metabolic Analysis in AβPP-PS1 Mouse Model
Authors: Ramesh Akila , Patel Anant
Published: November 2024

Motivation: Sex specific status of neurometabolic activity in Alzheimer’s disease is poorly understood. Goal(s): To assess glutamatergic and GABAergic neurometabolism in different brain regions of male and female AβPP-PS1 mouse model of AD. Approach: Tracer approach involving infusion of [1,6-13C2]glucose in AβPP-PS1 mouse model of AD together with 1H-[13C]-NMR spectroscopy was used to estimate rate of neuronal Glucose oxidation (CMRGlc(Ox)) in AD mice. Results: The neuronal metabolic activity reduced in the cerebral cortex, hippocampus and cerebellum of female AβPP-PS1 mice. However, only hippocampal neurometabolic activity was reduced in the male mice. This suggests a differential progression of AD in male and female AβPP-PS1 mice. Impact: The findings of the study suggest differential progression of AD in male and female AβPP-PS1 mice. These factors require attention for future interventions for AD treatment.
An optimised framework for relating microstructural MRI to multi-stain histology metrics in the mouse brain
Authors: Tisca Cristiana , Tachrount Mohamed , Smart Adele , Lange Frederik , Howard Amy , Wang Chaoyue , Tendler Benjamin , Qiu Lily , Bratley Claire , Kor Daniel , Huszar Istvan , Ballarobre-Barreiro Javier , Mayr Manuel , Lerch Jason , Martins-Bach Aurea , Miller Karla
Published: November 2024

Motivation: Voxel-wise MRI-histology comparisons routinely rely on manual segmentations of ROIs and subjective quantitative histological metrics, an error-prone and labour-intensive process. Goal(s): We developed an automated framework for investigating relationships between multiple MRI metrics and immunostains. Approach: We used MRI and histology protocols optimised for ex-vivo mouse brains. We co-registered this data and derived quantitative histological metrics. We conducted voxel-wise correlations in grey and white matter between MRI (diffusion, R2* and susceptibility) and immunohistochemistry (myelin, neurofilament and extracellular matrix proteins). Results: Our framework successfully recapitulated known relationships for myelin and neurofilaments and, interestingly, demonstrated new relationships between MRI metrics and extracellular matrix protein stains. Impact: Our optimised framework combines openly-shared software and MRI-histology protocols, addressing current challenges, such as obtaining high-quality histology data, MRI-to-histology registration and automatic extraction of quantitative histological metrics. This can benefit future MRI-histology studies in mouse brains prepared for ex-vivo MRI.
Combining Cortical Neurometabolic Changes and Structural Disconnection Improves Stroke Severity Prediction: A High-Resolution 1H-MRSI Study
Authors: Meng Ziyu , Wang Tianyao , Zhou Hong , Xu Chang , Bo Bin , Zhao Yibo , Guo Rong , Li Yudu , Jin Wen , Yu Xin , Liang Zhi-Pei , Li Yao
Published: November 2024

Motivation: Understanding distant metabolic changes resulting from stroke injuries can offer valuable prognostic biomarkers for patient recovery but remains underexplored. Goal(s): Our goal was to investigate the relationship between lesional and cortical neurometabolic changes, structural disconnections, and their collective impact on stroke severity using high-resolution 3D 1H-MRSI. Approach: 3D 1H-MRSI scanning using SPICE technology (scan time: 8 minutes, resolution: 2×3×3 mm3, FOV: 240×240×72 mm3) was performed on 105 acute ischemic stroke patients. Results: Cortical neurometabolic changes were associated with lesional metabolic levels and structural disconnections, which can be used jointly to improve symptom severity prediction in stroke patients. Impact: The demonstrated predictive value of combining structural disconnections with distant cortical metabolic disruptions may offer prognostic biomarkers useful for treatment and management of stroke patients.
Prediction of Long-term Motor Function Based on Functional Connectivity in Ischemic Stroke after Intra-arterial Thrombectomy
Authors: Yang Wei , Lin Bing-Fong , Lai Yen-Jun , Tang Chih-Wei , Lu Chia-Feng
Published: November 2024

Motivation: Intra-arterial thrombectomy (IAT) can remove the thrombus to restore cerebral blood flow. However, even if the thrombus is removed, the experienced hypoxia may still damage the brain, resulting in motor deficits. Goal(s): This study demonstrated that early brain network changes after IAT treatment can predict long-term recovery in ischemic stroke patients. Approach: Functional connectivity was correlated with motor recovery after IAT treatment, identifying key functional connectivity features that influence stroke prognosis to unravel the involved mechanisms. Results: Long-term motor functions can be predicted based on the two-week functional connectivity and Fugl-Meyer Assessment scores. Impact: The current clinical challenge is that nearly half of stroke patients who undergo IAT still cannot fully recover after treatment and rehabilitation. Early prediction of post-IAT motor recovery in stroke patients can provide appropriate rehabilitation plans in clinics.
Evaluation of Aortic Hemodynamics Using Four-Dimensional Flow of Magnetic Resonance Imaging in Rabbits with Liver Fibrosis
Authors: Li Jiali , Li Yuansheng , Zhang Xiaoyong , Chen Jing
Published: November 2024

Motivation: Hepatic fibrosis impacts systemic blood flow. Goal(s): In this rabbit study, we tracked aortic hemodynamics during fibrosis development. Approach: Thirty rabbits underwent biweekly 4D cardiac magnetic resonance (CMR) scans for 14 weeks post-bile duct ligation (BDL). Results: Results revealed significant increases in wall shear stress, energy loss, and most aortic parameters at each plane by the 2nd week after bile duct ligation (BDL), peaking at the 6th week (p < 0.05). Liver fibrosis appeared at the 2nd, 4th, and 6th weeks post-BDL, corresponding to grades F2, F3, and F4. Plane 2's relative pressure difference strongly correlated with fibrosis severity (R=0.86). Impact: The occurrence of liver fibrosis could increase WSS, EL, RPD and other hemodynamic parameters of aorta as early as the second week following BDL, which can be detected by 4D flow MRI.
Referenceless 4D Flow MR for cardiac imaging
Authors: Trenti Chiara , Ylipää Erik , Ebbers Tino , Engvall Jan , Dyverfeldt Petter
Published: November 2024

Motivation: Scan times for clinical 4D Flow MRI are still around 5-10 mins, which is too long for ideal integration in clinical practice. Goal(s): To investigate the possibility to reduce scan time by reconstructing three-directional velocity without the acquisition of reference scan in cardiac applications. Approach: Training a conditional generative adversarial network (cGAN) to estimate the reference scan from the three-velocity encoded scan segments. Results: Correlation coefficients for the pulmonary and systemic flow volumes and for maximum velocities were higher than 0.99, showing an excellent agreement between the cGAN-enabled referenceless 4D Flow MRI and conventional 4D flow MRI, thus potentially reducing scan time. Impact: By reconstructing the three-directional velocity without the reference scan it is possible reduce scan time of 4D Flow MRI, alleviating costs and patient discomfort, which especially is important for elderly and impaired subjects.
3D non-enhanced coronary MRA combined with wall imaging in the diagnosis of coronary artery stenosis
Authors: hu qiuju , zhao yane , TIAN DI , CHEN WEIBO , WANG BAIJUN , CHEN TONG , JIN DONGSHENG , lu guangming
Published: November 2024

Motivation: Advancements in coronary MR angiography (CMRA) have optimized the visualization of coronary anatomical structures, subsequently enhancing coronary artery stenosis, dilation, and certain anatomical variations【1-3】.Current meta-analysis shows that coronary MRA has a 79% accuracy rate for detecting obstructive CAD compared with gold-standard ICAGoal(s): Thus,the combining wall imaging may potentially enhances the diagnosis performance of coronary artery stenosisApproach: compare diagnostic performance of 3D -non enheanced CMRA with combined wall imagingResults: Our study suggest that combining these two techniques may improve the accuracy of coronary stenosis. Impact: CMRA has unique diagnostic in detecting coronary artery stenosis, and the improvement of diagnostic accuracywill further promote its clinical application.
Association between Aortic Morphology and Aortic Wall Properties
Authors: Venkatesh Bharath Ambale , Kachenoura Nadjia , Bollache Emilie , Dietenbeck Thomas , Redheuil Alban , Mousseaux Elie , Lima Joao
Published: November 2024

Motivation: To understand how closely aortic morphology is associated with aortic wall properties. Goal(s): (1) To correlate aortic shape using morphometrics to aortic stiffness indexed by pulse wave velocity (2) To correlate shape to regional aortic wall shear stressApproach: We use atlas-based shape analysis (morphometrics) to generate principal modes of shape variation, and then correlate modes of shape variation with pulse wave velocity to check their association. We also generate deep-learning based WSS using aortic shapes defined as point clouds forming the input to the neural network. Results: Aortic shapes were moderately associated with aortic stiffness as well as regional wall shear stress. Impact: Studying aortic morphological remodeling patterns may provide key insight into underlying disease processes that involve changes in aortic material wall properties and regional flow characteristics.
Quantifying Cervical Spinal Cord Pathology of Multiple Sclerosis Using Oscillating Gradient Spin-echo DWI
Authors: Li Sisi , Liu Fan , Xiao Yi , Shi Diwei , Zhao Mangsuo , Zhang Yuqi , Zhang Xianchang , Wang Yishi , Xu Junzhong , Guo Hua
Published: November 2024

Motivation: Spinal cord MRI has both diagnostic and prognostic value for multiple sclerosis (MS) patients. Several quantitative MRI biomarkers show high sensitivity to characterize MS lesions but lack pathological specificity. Time-dependent DWI may reveal microstructural features and pathological variations in MS. Goal(s): To explore diffusion time-dependence in the cervical spinal cord and its potential to quantify pathology of MSApproach: Optimized oscillating gradient spin-echo (OGSE) DTI were performed for healthy volunteers (N=18) and MS patients (N=17). Results: Diffusivities show time-dependence in the dorsal-columns and lateral-funiculis of healthy controls. The increase of RD in MS lesions is larger than healthy WM when diffusion time decreases. Impact: The time-dependence of diffusivities in the cervical spinal cord of healthy volunteers and MS patients are observed using optimized OGSE DWI sequences on a clinical scanner. This may reveal further insight into the microstructural differences and pathological variations in MS.
Low-intensity focused ultrasound Reverses Cisplatin-Induced Cognitive Impairment in Rats: Behavioral and DTI Evidence
Authors: Han Xiaowei , Liu Jiahuan , Zhu Xisong , Zhang Jiangong
Published: November 2024

Motivation: Cisplatin-Induced cognitive impairment, resulting from chemotherapeutic agents, is typically addressed through pharmacological treatments absent of effective rehabilitation therapy. Goal(s): Aim to investigate the therapeutic efficacy of Low-Intensity Focused Ultrasound (LIFUS), with a specific emphasis on the hippocampus, using an established animal model. Approach: We scrutinized the behavioral and cerebral alterations in rats with cisplatin chemotherapy, utilizing pre- and post-treatment behavioral phenotypes and diffusion weighted imaging (DTI) with a 9.4T MRI scanner. Results: Our findings revealed significant differences in indicators of biological behavior and DTI across specific brain regions in the LIFUS-treated group, suggesting that LIFUS holds potential in reversing brain damage. Impact: Our research helps to understand brain plasticity changes after LIFUS treatment with cisplatin chemotherapy, providing the theoretical support for future clinical intervention in chemotherapy related cognitive impairment.
Microstructural Characterization of Network-Based Neurodegeneration in Multiple Sclerosis Using High Gradient Diffusion MRI.
Authors: Chiang Florence , Krijnen Eva , Eskandarian Laleh , Lee Hong-Hsi , Lee Hansol , Klawiter Eric , Huang Susie
Published: November 2024

Motivation: Findings of this study help clarify the microstructural substrate of network-based gray matter (GM) atrophy and improve current understanding of network concepts in multiple sclerosis (MS). Goal(s): The goal of this study was to assess network behavior of microstructural alterations in atrophy-prone GM. Approach: We leveraged high gradient diffusion MRI to probe GM at the mesoscopic scale by using the SANDI (Soma and Neurite Density Imaging) method. Results: Our results demonstrated decreased cell body density in atrophy-prone GM of MS, which correlates with clinical disability. Further, covariance of localized GM microstructural alteration suggests that neuronal loss may relate in part to network-based effects. Impact: Decreased cell body density in atrophy-prone gray matter in multiple sclerosis is correlated with clinical disability and exhibits network behavior. Findings may support future development of quantitative non-invasive methods for sensitive monitoring of disease progression to enable prompt clinical intervention.
Brain White Matter Microstructural Abnormalities in Children with Global Developmental Delay: A Tract-Based Spatial Statistics Analysis
Authors: Zhang Xiaoxue , Zhao Xin , Guo Jinxia , Zhang Xiaoan , Shen Yanyong , Wang Changhao
Published: November 2024

Motivation: The diagnosis of global developmental delay (GDD) heavily relies on clinical scale assessments, which are highly subjective and present challenges for early diagnosis and intervention. Goal(s): The purpose of this study was to investigate the changes in white matter microstructure in children with GDD.Approach: We used a diffusional kurtosis imaging (DKI)-based TBSS approach to analyze the whole brain. Results: Our findings indicate abnormalities in multiple white matter brain regions among children with GDD. Additionally, DKI parameters were found to be correlated with clinical developmental levels. Impact: The DKI can offer quantitative parameter values for assessing microstructural changes in the brain of GDD, making it a promising diagnostic tool.
Characterization of liver inflammation in non-alcoholic steatohepatitis using MRI cytometry
Authors: jiang xiaoyu , Izzy Manhal , Washington Mary , Xu Junzhong , Gore John
Published: November 2024

Motivation: Addressing the unmet need for non-invasive non-alcoholic steatohepatitis (NASH) diagnosis. Goal(s): Assessing MRI cytometry’s potential for quantifying alterations in cell sizes and cell densities linked to inflammation, a critical factor in NASH diagnosis. Approach: Histology-based simulations were used to assess MRI cytometry's performance across various SNR levels in normal and NASH liver tissues. Additionally, used MRI cytometry to distinguish healthy liver from NASH with a clinical 3T scanner. Results: Both simulations and in vivo data revealed increased cell density and reduced cell sizes in inflammatory areas compared to steatosis and healthy liver tissues. Impact: Findings of this study establish a strong foundation for future investigations into the role of non-invasive assessment of liver cellular characteristics in diagnosing NASH, with the ultimate goal of reducing the necessity for liver biopsy.
Direct Neuronal Activity-related (DIANA) fMRI in Awake Mice
Authors: Meng Wanru , Guan Yufei , Qiu Yifan , Zuo Sicheng , Liang Mingyao , Yang Ganghan , Li Ye , He Yi
Published: November 2024

Motivation: Toi et al. reported a revolutionary approach of direct imaging of neuronal activity (DIANA) by fMRI in anesthetized mice at 9.4 T. However, anesthesia has a profound impact on the central nervous system, leading to modifications in physiological parameters. Goal(s): Our goal is to investigate Direct Neuronal Activity-related (DIANA) fMRI in awake mice. Approach: We performed the event-related cerebral functional magnetic resonance imaging and DIANA experiment in habit-trained awake mice. Results: In response to the electrical stimulation, a statistically significant increase in the DIANA signal was observed in the contralateral S1FL compared with the prestimulus signal (p < 0.005, n = 6 mice). Impact: Direct detection of neural activity allows us to better understand the rapid dynamics of neural activity, which will help improve the understanding and diagnosis of neurological diseases.
Quantum-Sensing MRI: Neuronal Firings in Human Brains under Finger-Tapping in a Wide Range of Ages
Authors: Qian Yongxian , Chen Xingye , Lin Ying-Chia , Henin Simon , Kumbella Nahbila-Malikha , Rockowitz Zena , Babb James , Ge Yulin , Masurkar Arjun , Liu Anli , Lui Yvonne
Published: November 2024

Motivation: The qsMRI has the potential for non-invasive detection of neuronal electrical activities (action potentials or firings) in the human brain. This emerging technique, however, is still in infant stage and needs more studies to show its potentials. Goal(s): This study explores whether qsMRI detects the change in neuronal firings during a finger-tapping task in a wide range of ages. Approach: A group of healthy subjects (27–84 years old) were studied on a 3T MRI scanner, using three tasks: finger-tapping, no tapping, and resting state. Results: Firing rate varied with age, and older people showed higher firing rate during tapping than resting. Impact: These positive results further demonstrated the potential of qsMRI to detect neuronal firings in humans, and will encourage researchers to use the technique in a wide range of studies on brain functions and neurological disorders including aging and Alzheimer’s disease.
Connectomics at 64 mT
Authors: Planchuelo-Gómez Álvaro , Gholam James , Ametepe Joshua , Padormo Francesco , Beltrachini Leandro , Cercignani Mara , Jones Derek
Published: November 2024

Motivation: Neuroscience MRI research, including assessment of structural connectomics, has been largely limited to high-resource settings. Goal(s): To democratise assessment of brain connectivity by demonstrating the first ever diffusion-weighted imaging (DWI)-based connectomics at 64 mT. Approach: 15-direction DWI data were acquired at 64 mT. Whole-brain tractograms were recovered after deep learning based denoising and constrained spherical deconvolution. Whole-brain adjacency matrices and graph-theory parameters were extracted, and their test-retest agreement and variability assessed. For one subject, results were compared to high-field MRI. Results: Global graph-theory parameters (e.g., small-worldness) showed high test-retest agreement. However, inter-hemispheric connectivity was overestimated at 64 mT compared to high-field results. Impact: Our unique combinations of low-field (64 mT) diffusion-weighted imaging, denoising, spherical deconvolution and connectomics opens up new research opportunities, allowing the assessment of structural connectivity and network neuroscience studies of under-served populations where this has never previously been possible.
Longitudinal study tracking physiological changes through multiparametric MRI during repeated MRgFUS-induced BBB opening
Authors: Rigollet Sébastien , Ador Thomas , Dumont Erik , Pichon Chantal , Barbier Emmanuel , Delalande Anthony , Stupar Vasile
Published: November 2024

Motivation: Long-term delivery of therapeutic agents via repeated MRgFUS is an innovative approach for enhancing glioblastoma treatment but underlying mechanisms are not well documented. Goal(s): Find the best strategy for long-term drug delivery after multiple MRgFUS mediated BBB opening. Approach: Repeated MRgFUS treatments were delivered up to 8 sessions over one month along with a multi-parametric MRI protocol follow-up to measure physiological, hemodynamic and oxygenation parameters in order to assess the safety and effectiveness of the procedure. Results: Intensive, repeated treatments, may lead to tissue modifications that require attention and limit the frequency of ultrasound mediated drug delivery to once a week. Impact: Long-term delivery of therapeutics through a FUS-induced permeabilized BBB redefines therapeutic strategies as it improves patient outcomes. To ensure the best translation towards clinical treatment, evaluation of hemodynamics and oxygenation modifications in the CNS is necessary to refine treatment parameters.
Artifact free Projection onto Dipole Fields via a Generalized Frequency-domain Discrete Dipole Kernel
Authors: Milovic Carlos , Lambert Mathias , Fuchs Patrick , Kiersnowski Oliver , Wang Chaoyue , Wang Zheng , Tejos Cristian
Published: November 2024

Motivation: Overcoming striping artifacts in the background removal step is a common challenge, especially in non-orthogonal (oblique) B0 field orientations. Goal(s): Develop a robust solution to eliminate striping artifacts while improving the accuracy of QSM images. Approach: We introduce a novel approach, employing a generalized discrete kernel to suppress striping artifacts generated by the Projection onto Dipole Fields method. Results: Our approach successfully addresses striping artifacts and enhances the accuracy of PDF solutions, even at non-orthogonal B0 field angles, promising artifact-free results. Impact: Our work promises to benefit the EMTP community by providing a more robust solution for addressing striping artifacts. This can lead to improved diagnostic accuracy and higher-quality imaging, ultimately enhancing patient care and advancing MRI technology.
A human brain atlas of χ-separation (chi-separation) for normative iron and myelin distributions
Authors: Min Kyeongseon , Sohn Beomseok , Kim Woo Jung , Park Chae Jung , Song Soohwa , Shin Dong Hoon , Chang Kyung Won , Shin Na-Young , Kim Minjun , Shin Hyeong-Geol , Lee Phil Hyu , Lee Jongho
Published: November 2024

Motivation: Abnormal iron and myelin distributions are associated with neurodegenerative diseases. An advanced susceptibility mapping technique, χ-separation, can disentangle paramagnetic iron and diamagnetic myelin contributions in quantitative susceptibility mapping. Goal(s): In this study, a normative χ-separation atlas is created from 106 healthy volunteers. Approach: To this end, individual χ-separation maps were registered to a common space and averaged across subjects. Results: The resulting χ-separation atlas reflects well-known iron and myelin-rich structures in the brain. The analysis based on regions of interest revealed distinct characteristics of normative para- and diamagnetic susceptibility profiles throughout subcortical nuclei, thalamic nuclei, and white matter fibers. Impact: Our χ-separation atlas would be utilized as a reference for imaging susceptibility in the brain and may assist in accurate localization of targets for intervention such as deep brain stimulation or high-intensity focused ultrasound.
Three-dimensional MR Elastography Identifies Portal Hypertension in Cirrhosis: A Prospective Multicenter Study
Authors: Wang Zhiying , Zhou Minghui , Pan Chen , Luo Baihe , Li Jialin , Liu Qiang , Shi Yu
Published: November 2024

Motivation: Hepatic venous pressure gradient (HVPG) is the gold standard for diagnosing portal hypertension, but it is invasiveness, cost, and feasibility. Goal(s): To develop a non-invasive model based on Three-dimensional (3D) MR elastography (3D-MRE) to detect portal hypertension. Approach: Spearman correlation analysis between 3D-MRE parameters and HVPG; Multivariable linear regression analysis between mechanical parameters and HVPG; Logistic regression analysis and establish a model to diagnose portal hypertension. Results: 3D-MRE is a non-invasive, rapid, and highly accurate tool for predicting portal hypertension. Especially Spleen stiffness at 60Hz was the independent parameters associating HVPG. Impact: This indicates that the use of 3D-MRE can provide more personalized evaluation and better medical experience for patients with cirrhosis and provides a new method for non-invasive diagnosis of portal hypertension.
Abdominal Foundation Model: Bootstrapping artificial intelligence for MRI organ volume biomarker analysis in ADPKD
Authors: Zhu Chenglin , He Xinzi , Hu Zhongxiu , Dev Hreedi , Romano Dominick , Sharbatdaran Arman , Prince Anna , Figueroa Andrea , Wang Sophie , He Hui Yi Ng , Blumenfeld Jon , Prince Martin
Published: November 2024

Motivation: Abdominal organ volumes are critical MRI biomarkers in many diseases including autosomal dominant polycystic kidney disease. Goal(s): We aim to develop a segmentation model with an enhanced ability to generalize across various abdominal organs and MR pulse sequences. Approach: We construct a multi-modality abdominal foundation model expanding upon our existing ADPKD kidney model which adapts to diverse organs and tissues with minimal new training data. Results: The model was trained using a model-in-loop methodology and evaluated against radiologist benchmarks, yielding an impressive Dice score of 0.94 for in-distribution sequences and 0.73 for organ segmentations on out-of-distribution sequences. Impact: This foundational model can seamlessly integrate into clinical workflows, utilizing routine cases to enhance its performance and extending its application to additional organs and tissues. This advance also marks a significant step toward the automation of MRI reporting.
Perfluorinated Iridium Catalyst for Signal Amplification by Reversible Exchange Provides Metal-Free Aqueous Hyperpolarized [13C1]-Pyruvate
Authors: Ettedgui Jessica , Blackman Burchelle , Raju Natarajan , Kotler Samuel , Chekmenev Eduard , Goodson Boyd , LeClair Christopher , Krishna Murali , Swenson Rolf
Published: November 2024

Motivation: Signal Amplification by Reversible Exchange (SABRE) recent progresses include hyperpolarizing [1-13C]pyruvate in aqueous solutions. However, overcoming the challenge of iridium toxicity in hyperpolarized mixtures is essential for broader biocompatible SABRE applications. Goal(s): The removal of Ir metal from hyperpolarized SABRE mixtures is an unmet need with substantial clinical significance. Approach: A perfluorinated SABRE catalyst was developed to counter iridium contamination in hyperpolarized aqueous solutions by exploiting its high hydrophobicity for straightforward separation. Results: The residual Ir was found to be only 177 ppb, representing a 8130-fold reduction in Ir concentration and the lowest and safest level reported to date for a SABRE-hyperpolarized solution. Impact: Hyperpolarizing [1-13C]pyruvate using a perfluorinated SABRE catalyst reduced the residual iridium levels to safe levels for human injection. Future development along with solvent removal could make SABRE-SHEATH a faster and cost-effective alternative for biocompatible hyperpolarized agents in next-generation molecular imaging.
First-in-Human Whole-Abdomen Metabolic Imaging with Hyperpolarized [1-13C]Pyruvate in D2O and Initial Application in Human Pancreatic Cancer
Authors: Zhang Guannan , Deh Kofi , Park Hijin , Cunningham Charles , Bragagnolo Nadia , Lyashchenko Serge , Ahmmed Shake , Leftin Avigdor , Coffee Elizabeth , Hricak Hedvig , Miloushev Vesselin , Mayerhoefer Marius , Keshari Kayvan
Published: November 2024

Motivation: Whole-abdomen imaging with hyperpolarized [1-13C]pyruvate holds promise to diagnose metabolic diseases. D2O solvation could extend the 13C T1 lifetime, resulting in enhanced image SNR. Goal(s): Establish the safety and feasibility of utilizing D2O to administer hyperpolarized [1-13C]pyruvate in whole-abdomen imaging, and present the first application of whole-abdomen hyperpolarized [1-13C]pyruvate MRI in a PDAC patient. Approach: We quantified the metabolic characteristics of organs in healthy and diseased subjects. Results: The use of D2O is safe and feasible. It has no significant impact on organ metabolism and delivery of the pyruvate bolus. This technique demonstrates potential for application in cancer patients. Impact: The safety and feasibility of employing D2O for hyperpolarized 13C whole-abdomen MRI sets the stage for translational studies. The first application of hyperpolarized whole-abdomen [1-13C]pyruvate MRI to a PDAC patient provides essential support for its future exploration in oncology.
Combining multi-echo and phase cycling in bSSFP acquisition to improve whole-brain deuterium metabolic imaging at 9.4 T
Authors: Valsala Praveen Iyyappan , Pohmann Rolf , Heule Rahel , Avdievich Nikolai , Engelmann Jörn , Kuebler Laura , Martins André , Scheffler Klaus
Published: November 2024

Motivation: Deuterium metabolic imaging could significantly impact the field of neuro-oncology by providing clinical quantitative metabolic information. Goal(s): To improve the spatial resolution of human deuterium metabolic imaging at 9.4 T. Approach: We performed phantom and in vivo experiments with oral intake of deuterated glucose using multi-echo phase-cycled bSSFP acquisitions. The results were compared with a standard 3D spectroscopy sequence. Results: We achieved higher spatial resolution compared to a 3D spectroscopy sequence. Phase cycling improved the reliability of the metabolite quantification especially in the large off-resonance and low SNR regimes. Impact: We present an improved whole-brain dynamic deuterium metabolic imaging strategy at 9.4 T using bSSFP with multiple echoes and phase cycling. The efficacy of this method is validated with phantom and in vivo experiments along with standard spectroscopy measurements.