bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond business: Exploring the social engagement of entrepreneurs in Phnom Penh, Cambodia
Authors: Ban Bunheng , You Vithyea , Sario T. Pio
Published: November 2024

The current article aims to shed light on the social engagement practices of businesses in Phnom Penh, Cambodia, and to inform readers about those practices. In particular, the article examines how entrepreneurs engage in social activities, establish communication with their contemporaries, and advocate for entrepreneurship. The data was collected from a representative sample of business owners while employing a quantitative research design to determine how much business owners participate in social activities. The ongoing research has yielded preliminary findings and conclusions. The findings reveal that entrepreneurs have high social engagement through active participation in mentoring programs, knowledge-sharing activities, and networking events. They demonstrated their participation in these activities. The findings shed light on the significance of social capital and the growth of communities within the framework of Phnom Penh's environment for entrepreneurial endeavours. The implications of this study for policy, practice, theory, and future research, emphasizing the need to foster a culture that encourages social activity among entrepreneurs and fosters a supportive environment, were discussed. The study adds to the expanding body of literature on entrepreneurship by highlighting the diverse features of entrepreneurial pursuits and the importance of social engagement that extends beyond corporate objectives. Future studies should be conducted with a bigger sample size and scope.
A Logit Regression Approach to Identifying Predictors of Intimate Partner Violence in Tanzania
Authors: Anasel Mackfallen Giliad , Swai Idda L
Published: November 2024

Introduction
Intimate Partner Violence (IPV) is among the common forms of gender-based violence worldwide. The IPV magnitude in Tanzania is approximated to be 44%, in which 4 in 10 married women experienced spousal violence. The present study zeroed into the uses of logit regression to identify the predictors of IPV in Tanzania.
 
Methods
The data was obtained from the Tanzania Demographic and Health Survey 2022. The unity of analysis was currently married women and men. Logit (logistic) regression analysis was performed to determine the predictors of IPV in Tanzania. IPV was measured into three categories: emotional violence, physical violence, and sexual violence.
 
Results
Women’s age, partners’ education level, partners’ occupation, and frequency of husband/partner being drunk are factors that predict emotional violence significantly (P<0.05). Age of household head, age of women at first birth, partners’ occupation, women’s current age, frequency of husband/partner's drinking habit, women’s education level, and literacy level are factors that predict less and more severe physical violence significantly (P<0.05). In addition, the wealth index, women’s age at first birth, and women’s occupation explain the sexual violence significantly (P<0.05). While residing in Dodoma, Arusha, Tanga, Tabora, Kagera, Mwanza, Mara, Manyara, Kusini Unguja, Tanga, Songwe, Kilimanjaro, and Katavi has a high likelihood of experiencing IPV significantly (P<0.05).
 
Conclusion
The intervention to address IPV should first focus on changing men's and women's attitudes and beliefs. Change of attitude and belief should be to both men and women who believe that wife beating is okay, and that perpetuates the increase of IPV. This study recommends an emphasis on archiving employment, especially for men who reside in regions where IPV has been expected, to reduce the likelihood of men committing violence.
Brain metabolites and regional cerebral blood volume altered in anti-NMDAR encephalitis patients
Authors: Uberti Mariano , Sajja Balasrinivasa , Jayagopal Lakshman Arcot , Mullane Audrina , Zhang Yan , White Matthew , Taraschenko Olga
Published: November 2024

Motivation: The chronic phase of autoimmune encephalitis includes persistent loss of cognitive and adaptive functions leading to long-term disability. MR-based modalities help in longitudinal studies to understand disease progression and response to treatment. Goal(s): To investigate the in vivo MRI-based methods sensitive to detecting the alterations in metabolites and perfusion in encephalitis patients. Approach: 1H-MRS and rCBV were performed on encephalitis patients with memory deficits and healthy controls. Results: Changes in metabolite concentrations in the hippocampus and cortex suggest the long-term effect of neuroinflammation in patients. Reduced hippocampal rCBV in memory deficit patients is consistent with clinical cognitive assessments. Impact: Altered brain metabolite concentrations and regional blood volume were detected with 1H-MRS and rCBV in autoimmune encephalitis and memory deficit patients. This approach can support the investigation of the role of angiogenesis and neurogenesis in memory loss in chronic encephalitis.
Prediction of Lymphovascular Space Invasion in endometrial cancer using MRI-based radiomics models
Authors: Chen Lu , Huang Xiao-li , Qin Lan-hui , Yang Chong-ze , Deng Kan , Liao Jin-yuan
Published: November 2024

Motivation: Predicting LVSI before surgery remains a critical challenge. Goal(s): To predict preoperative LVSI in patients with endometrial cancer in a noninvasive way. Approach: We developed and validated MRI radiomics and clinical-radiomics models based on the features extracted from tumor and peritumoral regions. Results: The clinical-radiomics model based on the features extracted from the tumors with 3mm peritumoral region exhibited the hightest predictive performance in the training cohort and testing cohort with an AUC of 0.86 and 0.86, respectively. The model also displayed clinical validity as depicted in the DCA curve. Impact: Incorporating the radiomics features extracted from tumor with 3mm peritumoral region and clinical significance factors can improve the predictive efficacy of the model for predicting LVSI and increase its applicability in clinical practice.
Attention-Boosted CNN for Improving the Classification of IDH and TERTp Mutation Status in Gliomas Based on Dynamic Susceptibility Contrast MRI
Authors: Buz-Yalug Buse , Turhan Gulce , Cetin Ayse Irem , Danyeli Ayca Ersen , Yakicier Cengiz , Pamir M. Necmettin , Ozduman Koray , Dincer Alp , Ozturk-Isik Esin
Published: November 2024

Motivation: Molecular markers, such as IDH and TERTp, have been reported as significant prognostic factors in gliomas. Goal(s): The aim of this study is to predict IDH and TERTp mutational subtypes in gliomas non-invasively using deep-learning applied to rCBV images derived from DSC-MRI. Approach: We proposed a deep-learning approach with attention gates to classify IDH- and TERTp-mutation subgroups of gliomas using rCBV images along with anatomical-MRI. Additionally, Grad-CAM approach was employed to provide an explanation of which image sections played a role in decision-making. Results: Attention-boosted deep learning-based classification model yielded high accuracy rates. GradCAM approach also highlighted the significance of different tumor components. Impact: The proposed attention-boosted deep learning based method might have the potential to assist clinicians in the noninvasive identification of IDH and TERTp mutations at the pre-surgery point and potentially enhance treatment strategies and patient outcomes.
Enhancing transcranial focused ultrasound treatment planning with synthetic ct from ultra-short echo time (UTE) MRI: a deep learning approach
Authors: Liu Dong , Xin Zhuoyao , Ji Robin , Tsitsos Fotis , Jiménez-Gambín Sergio , Ferrera Vincent , Konofagou Elisa E. , Guo Jia
Published: November 2024

Motivation: There’s a clinical interest in exploring an alternative option using ultrashort-time-echo MRI to replace CT imaging for accurate transcranial FUS treatment planning. Goal(s): To employ a deep learning approach to generate synthetic CT images from a limited UTE-MRI dataset. Approach: A deep learning framework based on 3D Transformer U-net is applied to the paired UTE-CT dataset and acoustic simulation is performed to validate the results. Results: Utilizing UTE MRI can offer synthetic CT as an alternative to traditional CT imaging. The simulations showed a minimal maximum acoustic pressure difference of less than8% and a focus shift of less than1.5mm compared to CT-based simulations. Impact: This study introduces a novel multi-task deep learning approach that enables accurate synthetic CT generation from limited UTE-MRI data. This innovation provides a cost-effective and radiation-free alternative to traditional CT imaging, significantly enhancing transcranial focused ultrasound treatment planning.
300 µm multi-echo bSSFP fMRI at 7 Tesla revealed the IPS-V1 feedback circuit of spatial attention in the human brain
Authors: Wang Yifei , Guo Fanhua , Liang Huilou , An Jing , Xue Rong , Qian Chencan , Zhang Peng
Published: November 2024

Motivation: Layer-specific response in frontoparietal areas and their connectivity with the visual cortex are important to understand the neural circuitry of attention. Goal(s): Investigate the neural circuitry of attention in IPS and V1 with laminar fMRI. Approach: Using ultra-high resolution multi-echo bSSFP fMRI at 7 Tesla, layer-specific functional activity in IPS and V1 were simultaneously recorded in a spatial attention task. Results: Attention demanding task induced significant activations in both superficial and deep layers of IPS, enhanced activity in the deep layers of V1, and increased feedback connectivity from the deep layers of IPS to the deep layers of V1. Impact: This study demonstrates the feasibility of using ultra-high resolution multi-echo bSSFP fMRI at 7 Tesla to simultaneously image multiple brain regions to investigate the neural circuitry of high-level cognition.
Predictive Model for Proliferative HCC Using LI-RADS v2018: Assessing Therapeutic Outcomes in Hepatectomy and Systemic Therapy
Authors: Lu Mengtian , Zhang Xueqin , Zhang Tao , Qu Qi , Yan Zuyi , Zhao Xiance
Published: November 2024

Motivation: Hepatocellular carcinoma (HCC) can be categorized into proliferative and non-proliferative classes, with proliferative HCC exhibiting aggressive characteristics and a poor prognosis. Goal(s): To develop a predictive model for proliferative HCC using Liver Imaging Reporting and Data System (LI-RADS) and to investigate its prognostic value for HCC. Approach: A logistic regression nomogram was constructed based on LI-RADS features to identify proliferative HCC. The implication of model-predicted proliferative HCC for different therapeutic outcomes in HCC was investigated. Results: The predictive model for proliferative HCC performed well and is a risk factor for postoperative recurrence in HCC, associated with favorable outcomes in systemic therapy. Impact: The MR-based model, utilizing LI-RADS v2018, could predict proliferative HCC before treatment. Patients with model-predicted proliferative HCC had more post-hepatectomy recurrences but better responses to systemic therapy, which may facilitate clinical decision-making for more precise and rational therapeutic strategies.
Intertumoral Heterogeneity based on MRI Radiomics Features Predicts prognosis in HCC patients before Hepatectomy
Authors: Dong Mengshi , Xiao Yuanqiang , Li Chao , Zhang Lina , Zhang Tianhui , Zhou Jinhui , Zhang Linqi , Jin Xin , Fang Zebin , Li Mengsi , Han Yu , Wang Jin
Published: November 2024

Motivation: Hepatocellular carcinoma (HCC) exhibits significant intertumoral heterogeneity, which contributes significantly to treatment resistance and failure. Noninvasive imaging and radiomics for preoperative decoding of the subtypes and prognosis may be valuable in clinical management. Goal(s): To preoperatively develop and validate clustering analysis of HCC based on MRI radiomics features for identifying subtypes with discrete prognosis. Approach: We performed clustering analysis of HCC based on MRI radiomics features to detect distinct subtypes, and subsequently clinicopathological parameters and prognosis were compared and evaluated between different subtypes. Results: Based on the radiomics features of MRI, clustering analysis identified two distinct subtypes with discrete prognosis in HCC patients. Impact: Clustering analysis based on the radiomics features of multiparametric MRI is a potential noninvasive decision-making method for the management of patients with HCC in clinical practice.
Interleaved 23Na/1H (pTx) MRI of the human heart at 7 Tesla
Authors: Ruck Laurent , Egger Nico , Nagelstraßer Sophia , Wilferth Tobias , Herrler Jürgen , Kopp Christoph , Wildenberg Saskia , Bitz Andreas , Uder Michael , Nagel Armin
Published: November 2024

Motivation: Interleaved dual-nuclear acquisition enables time-efficient 23Na and 1H cardiac MRI within one measurement. However, at 7T the reduced excitation wavelengths can lead to flip angle (FA) inhomogeneities in 23Na MRI and even to signal dropouts in 1H MRI. Both effects impair a reproducible quantitative evaluation of the myocardial 23Na signal. Goal(s): To reduce FA inhomogeneities for interleaved 23Na/1H MRI. Approach: We included three different pTx pulses in 1H MRI of the interleaved sequence and introduced a fast 23Na FA mapping. Results: All three pTx pulses improved the 1H FA homogeneity and 23Na images showed better signal homogeneity after FA correction. Impact: Interleaved 23Na/1H (pTx) MRI in combination with additional fast 23Na FA mapping is less prone to FA inhomogeneities and by that should enable reliable quantification of myocardial 23Na signal within clinically feasible acquisition times.
Revealing membrane integrity and cell size from diffusion kurtosis time-dependence
Authors: Lee Hong-Hsi , Novikov Dmitry , Fieremans Els , Huang Susie
Published: November 2024

Motivation: The non-monotonic dependence of the diffusion kurtosis on diffusion time has been observed in tissue, yet its relation to membrane integrity and tissue geometry remains unknown. Goal(s): We investigate the relation between the characteristic time tpeak and the tissue parameters, such as cell size, volume fraction and permeability. Approach: We perform Monte Carlo simulations of diffusion and exchange in randomly, densely packed spheres with varying permeability, cell fractions and sizes, and identify the value of tpeak. Results: We obtain an empirical, albeit highly accurate relation of tpeak to tissue parameters in a broad parameter range. Impact: Diffusion-kurtosis time-dependence is sensitive to pathological changes in membrane integrity and cellular structure in diseases, such as ischemic stroke and tumors. Numerical simulations suggest an empirical interpretation of kurtosis time-dependence, offering a novel biomarker for in vivo evaluation of pathology.
Quantification of exchange in the mouse brain using double diffusion encodings with fixed total diffusion-weighting
Authors: Cai Teddy , Williamson Nathan , Basser Peter , Tachrount Mohamed , Miller Karla
Published: November 2024

Motivation: Exchange is an important effect in diffusion MR of the brain but remains difficult to quantify using conventional methods and signal models due to parameter degeneracy. Goal(s): To develop and demonstrate robust measurement of exchange in the mouse brain. Approach: A method based on double diffusion encoding was previously developed to probe exchange isolated from other effects, yielding robust exchange time measurements. We apply this method in vivo for the first time. Results: We report a fast in vivo exchange time of approximately 38 ms as compared to 146 ms in a fixed sample, obtained by averaging through a slice. Impact: Cellular water exchange reflects not only structural characteristics but has also been linked to metabolism. Quantifying exchange may yield rich information, yet methods to do so are not mature. Here, we demonstrate a unique, isolated measurement of exchange in vivo.
Spiral HASTE using variable-flip-angle single-shot spiral-ring TSE for rapid T2-weighted abdominal imaging
Authors: Wang Zhixing , Zhong Xiaodong , Yang Yang , Mugler John , Liu An , Meyer Craig , Qing Kun
Published: November 2024

Motivation: Conventional Cartesian HASTE may be susceptible to image blurring, resolution loss, and artifacts in abdominal imaging. Goal(s): To develop a 2D T2-weighted abdominal spiral HASTE technique to achieve better image sharpness, reduced scan time, and reduced power deposition compared to Cartesian HASTE. Approach: A variable-flip-angle refocusing RF series was designed and employed to maintain high signal-intensity at middle- and late-echoes with a smooth signal-evolution compared to a constant-flip-angle scheme. Variable-density spiral-ring trajectories combined with L1-ESPIRiT reconstruction were performed to accelerate the data acquisition. Results: Whole-abdomen spiral HASTE images were acquired with 1.5×1.5×6 mm3 spatial-resolution and 25 slices in a 7-second acquisition at 3T. Impact: This work highlights the utilization of spiral-ring TSE acquisition along with variable-flip-angle RF pulses and L1-ESPIRiT reconstruction for accelerated single-shot abdominal imaging, providing images with improved image sharpness, shorter scan time, and reduced power deposition over conventional Cartesian HASTE.
Detecting the pathogenic threshold of neuromelanin accumulation in Parkinson’s disease and prodromal Parkinson’s disease patients
Authors: Perot Jean-Baptiste , Gaurav Rahul , Lejeune François-Xavier , Rebbah Sana , Mao Zeqian , Valabregue Romain , Arnulf Isabelle , Vidailhet Marie , Corvol Jean-Christophe , Vila Miquel , Lehéricy Stéphane
Published: November 2024

Motivation: Neuromelanin is a pigment that accumulates specifically in neurons population that are vulnerable in Parkinson's disease. The role of neuromelanin in pathogenesis is still unclear. Goal(s): We tested the hypothesis that there is a pathogenic threshold of neuromelanin accumulation that triggers neurodegeneration in Parkinson's disease patients. Approach: We performed longitudinal neuromelanin-MRI imaging of the substantia nigra of Parkinson's disease, prodromal Parkinson's disease (iRBD) patients, and healthy volunteers. Results: We confirmed accelerated decrease of neuromelanin-MRI signal in patients with Parkinson's disease, which started from the maximum of healthy volunteer, in line with hypothetic pathogenic threshold. iRBD patients showed similar trajectory delayed by 5 years. Impact: Results support the hypothesis of a pathogenic threshold of neuromelanin. Its role in Parkinson's disease pathogenesis needs more investigations. Late reach of this threshold in prodromal patients results in delayed age of Parkinson's disease onset, suggesting different progression pattern.
PRIME: Phase Reversed Interleaved Multi-Echo acquisition enables highly accelerated distortion-free diffusion MRI
Authors: Jun Yohan , Liu Qiang , Cho Jaejin , Yong Xingwang , Fujita Shohei , Huang Susie , Rathi Yogesh , Bilgic Berkin
Published: November 2024

Motivation: Current distortion-free multishot diffusion MRI (dMRI) techniques rely on interim reconstructions to estimate a fieldmap, whose quality deteriorates at high accelerations, thus precluding high-resolution imaging. Goal(s): To develop a distortion-free acquisition that reaches high accelerations with high fidelity. Approach: We propose PRIME, which incorporates a second echo acquired at lower resolution and acceleration, but with matching echo spacing as the first echo. This yields high-fidelity fieldmaps to be used in 10-fold accelerated scans. Results: PRIME enables high-quality distortion-free dMRI at Rinplane×SMS=5×2 and 1mm3 resolution without prolonging the scan thanks to utilizing the dead time in gSlider RF-encoded acquisitions. Impact: We propose a distortion-free dMRI sequence, PRIME, that reaches Rinplane×SMS=5×2 at 1mm3 resolution with high fidelity owing to its ability to estimate a high-quality fieldmap from a second echo inserted without prolonging the TR in gSlider RF-encoded acquisitions.
Towards Genuine Three-dimensional Diffusion Imaging with Second Order Gradient Moment Nulling
Authors: Wang Yishi , Weng Dehe , Zhang Jieying , Qian Tianyi , Liu Wenzhang , Zhou Kun , Wu Yanglei , Zhang Baogui , Li Qing
Published: November 2024

Motivation: While 3D acquisition has the advantages of achieving high resolution and signal-to-noise ratio and has been established for most sequences, diffusion imaging, has predominantly adhered to 2D acquisition or partial 3D such as multi-slab acquisition for over 50 years. Goal(s): We aim to bring diffusion imaging to the next era by implementing a genuine 3D diffusion imaging sequence. Approach: The sequence was implemented using gradient moment nulling and 3D EPI acquisition and basic reconstruction methods. Results: Whole brain 3D diffusion imaging was achieved at isotropic sub-millimeter resolution and a practical scan time. Impact: This work liberates diffusion imaging from 2D or partial 3D acquisition to true 3D acquisition.
A 16-Channel Ankle Conformal Array Coil for Robot Assisted Dynamic Ankle Joint Imaging at 1.5T MRI
Authors: Poniatowski Matthäus , Elias Ilan , Mahmutovic Mirsad , König Alexander , Mahnken Andreas , Keil Boris
Published: November 2024

Motivation: Many musculoskeletal disorders cannot be detected in static MRI, making surgical intervention necessary. Goal(s): Our Goal was to enable motion controlled dynamic MRI to potentially add diagnostic findings and reduce surgical interventions. Approach: We advanced our apparatus for controlled passive movement of the foot (Robotic Motion Device) and implemented an adapted 16-channel Ankle Coil for accelerated imaging. Results: Combining the Robotic Motion Device and the 16-channel Ankle Coil allowed us to perform controlled passive foot movement and acquire high SNR images. Impact: The combination of a Robotic Motion Device and an adapted 16-channel Ankle Coil enables dynamic image acquisition with controlled passive movement of the ankle joint, potentially adding and improving diagnostic findings and reducing surgical interventions.
A correction for modeling of radial, spiral, and PROPELLOR DCE data: time-averaged extended Tofts
Authors: Korobova Natalia , Troelstra Marian , Gurney-Champion Oliver
Published: November 2024

Motivation: Accurate quantification of pharmacokinetic parameters in dynamic contrast-enhanced (DCE) MRI requires high temporal resolution, often reached through non-cartesian sampling patterns that oversample the center of k-space (e.g. radial, spiral, PROPELLOR). In pharmacokinetic models, image contrast is assumed to be formed instantly at discrete time-points. However, in acquisitions oversampling the k-space center, the signal per time-frame becomes an average over acquisition time. Goal(s): To correct for the time-averaged signals. Approach: We proposed a modification to DCE modeling and tested it in simulations and in-vivo. Results: Modern sampling patterns predominantly affect the pharmacokinetic parameter estimates for longer sampling times (>8s) per DCE frame. Impact: We verified that for short acquisitions per frame (<8s) per DCE-frame, conventional Toft's modeling is sufficient. However, for longer sampling times (>8s) per DCE frame, our time-averaged extended Toft's model is needed for accurate estimations of pharmacokinetic parameters.
Personalized Lumbosacral Spinal Nerve Roots 3D Reconstruction and Computer Simulation for Spinal Cord Stimulation
Authors: Zhou Yuxing , Liu Jionghui , Zhang Wenqi , Chu Ying-Hua , Jia Fumin
Published: November 2024

Motivation: Spinal cord stimulation requires personalized 3D reconstructed model to address challenges arising from individual variability. Goal(s): This study aims to image the entire spinal cord with lumbosacral nerve roots and propose a method for reconstructing a 3D model for simulation. Approach: Three MRI sequences were collected for reconstruction and nerve roots annotation. Then the 3D spinal cord model was reconstructed using a custom interpolating algorithm guided by anatomical rules. Results: A tailored imaging protocol and reconstruction method designed for the spinal cord and its nerve roots have been proposed, resulting in a 3D personalized spinal cord model. Impact: The protocol offers an effective guide for researchers and clinicians conducting spinal cord and nerve roots imaging. Additionally, it enables the creation of personalized computational spine models with nerve roots and rootlets from MRI images, facilitating simulation studies.
The Association of Brain Functional Network Segregation with Working Memory and Negative Symptoms in Schizophrenia
Authors: Liu Siwei , Kok Bing Cai , Rekhi Gurpreet , Ang Mei San , Lau Jia Ming , Foo Jia Nee , Chan Raymond C.K. , Lee Jimmy , Zhou Juan
Published: November 2024

Motivation: Empirical findings suggest that negative symptoms of schizophrenia could be improved by cognitive training regime. Goal(s): This study seeks to (1) understand how brain network architecture supporting task performance may be related to negative symptoms and (2) whether better task performance could be linked to differences in intrinsic functional network architecture. Approach: Schizophrenia patients underwent resting state and dual-modality N-back task fMRI scans. Network segregation was summarised using the system segregation index for each network. Results: Functional network segregation during both rest and task was associated with negative symptom severity and task performance. Impact: The current study highlighted the common ground of altered network segregation between negative symptoms and task performance in schizophrenia and encouraged future study on improving negative symptoms and network communication through cognitive training interventions.
Two functional connectivity based subtypes of MDD and related biological mechanisms
Authors: Li Qian , Li Haoran , Wang Yaxuan , Long Fenghua , Chen Yufei , Wang Yitian , Gong Qiyong , Li Fei
Published: November 2024

Motivation: There’s a large clinical heterogeneity presented in MDD and inconsistent MRI evidence on abnormal functional connectivity (FC) in MDD, let alone the unclear biological mechanisms underlying the neuroimaging alterations. Goal(s): To identify FC based subtypes of MDD and their genetic mechanisms and neurotransmission patterns. Approach: Consensus clustering of FC was applied to subtyping MDD. Correlation analyses were used to explore the underlying biological mechanisms of FC alterations in each subtype. Results: Two stable neurophysiological MDD subtypes were found. While the two subtypes were indistinguishable by clinical symptoms, FC alterations of each subtype had distinct spatial correlations with cognition, gene, and neurotransmission profiles. Impact: Our findings suggested the presence of two neuroimaging subtypes in MDD and the two subtypes can be characterized by different genetic mechanisms, neurotransmitter receptor/transporter profiles, and cognition types, providing new clues to understand the pathophysiology of MDD.
AID-DTI: fast and high-fidelity diffusion tensor imaging with detail-preserving model-based deep learning
Authors: Fan Wenxin , Li Cheng , Yang Jing , Zou Juan , Zheng Hairong , Wang Shanshan
Published: November 2024

Motivation: Existing methods tend to suffer from Rician noise, leading to detail loss during the reconstruction of DTI-derived parametric maps. This issue becomes particularly pronounced when sparsely sampled q-space data are used. Goal(s): Our goal was to facilitate fast and high-fidelity estimation of DTI metrics. Approach: We propose a novel SVD-based regularizer, which can effectively preserve fine details while suppressing noise during network training. Results: Experimental results consistently demonstrate that the proposed method estimates DTI parameter maps with finer details, outperforming current state-of-the-art methods. Impact: The proposed method may facilitate fast and high-fidelity DTI with a newly designed SVD-based regularizer, and it has a potential to become a practical tool in clinical and neuroscientific applications.
A Contrastive Learning for Accelerating Diffusion Tensor Imaging with High Adaptability to Diffusion Gradient Schemes
Authors: Jung Siyun , Kim Jae-Yoon , Kim Dong-Hyun
Published: November 2024

Motivation: High-quality DTI requires numerous DWIs, extending scan times; however, despite deep learning's advances in reconstructing DTI with fewer DWIs, its adaptability across various gradient protocols remains limited, challenging its clinical application. Goal(s): Our aim is to enable consistent, high-quality DTI reconstructions from fewer DWIs across different gradient schemes, enhancing adaptability in various clinical environments. Approach: We employ self-supervised contrastive learning to extract and preserve key features between datasets derived from the same data with different gradient sampling methods. Results: Our method reliably enhanced diffusion tensor maps from reduced DWIs across various gradient sampling schemes, outperforming both conventional methods and state-of-the-art deep learning model. Impact: Our method creates high-quality DTI from fewer DWIs, reducing scan times and easing patient burden, while showing consistent performance across various gradient sampling schemes, ensuring high adaptability and ease of use in diverse clinical settings.
pTx Pulseq in hybrid sequences Universal Pulses, made Truly Universal
Authors: Roos Thomas , Nam Kyung Min , Versteeg Edwin , Gosselink Mark , Hoogduin Hans , Klomp Dennis , Siero Jeroen , Wijnen Jannie
Published: November 2024

Motivation: Advancing MRI sequence development by integrating parallel transmit capabilities with the open-source and widely-used Pulseq framework. Goal(s): To integrate pTx capabilities into the Pulseq framework, facilitating the design of universal pTx pulses that enhance imaging homogeneity and quality. Approach: Development of 'pTx-Pulseq' as a backwards-compatible extension, validated through single-channel control and complex sequence operation, culminating in a hybrid sequence that enhances a native MP-RAGE with Pulseq flexibility. Results: Effective control of pTx channels using pTx-Pulseq, yielding uniform imaging results and demonstrating the potential of hybrid sequencing for improved MRI applications. Impact: 'pTx-Pulseq' empowers researchers to universally and easily harness pTx technology, allowing for the creation of truly universally pTx pulses that reduce the burden of B1+ inhomogeneity and elevate the quality of high-field MRI.
Technical Considerations for Implementing Multi-Center and Multi-Platform Quantitative DCE-MRI to Predict Breast Cancer Therapy Response
Authors: Moloney Brendan , Li Xin , Hirano Michael , Eddin Assim Saad , Lim Jeong Youn , Biswas Debosmita , Kazerouni Anum , Tudorica Alina , Li Isabella , Bryant Mary Lynn , Wille Courtney , Pyle Chelsea , Rahbar Habib , Hsieh Su Kim , Rice-Stitt Travis , Dintzis Suzanne , Bashir Amani , Hobbs Evthokia , Zimmer Alexandra , Specht Jennifer , Phadke Sneha , Fleege Nicole , Holmes James , Partridge Savannah , Huang Wei
Published: November 2024

Motivation: Determine best-practice quantitative DCE-MRI for predicting breast cancer (BC) response to neoadjuvant chemotherapy (NAC) in a multi-center (MC) and multi-vendor platform (MP) setting. Goal(s): Evaluate effects of different pharmacokinetic analysis approaches on Ktrans and its predictive performance. Approach: 15 BC patients treated with NAC underwent longitudinal DCE-MRI at 3 sites using 3T systems from 3 vendors. Variations in analysis included Tofts model vs. Shutter-Speed model (SSM), ROI- vs. voxel-based analysis, and using fixed vs. measured R10. Results: Different analysis approaches resulted in significantly different Ktrans, with SSM Ktrans from voxel-based analysis using fixed R10 showing highest predictive accuracy for response. Impact: Voxel-based SSM analysis using fixed R10 takes advantage of greater range of SSM Ktrans changes in response to therapy, mitigates R10 measurement errors, and may be the best-practice quantitative DCE-MRI for predicting NAC response in a MC and MP setting.
Twstr: A Resonant, Matched MRI Coil without any Discrete Components
Authors: Maravilla Julian , Arias Ana , Lustig Michael
Published: November 2024

Motivation: Component-less MRI coils have the potential to increase the strength and flexibility of array elements making them suitable for implantables, multi-modal imaging, and body conformal applications. Goal(s): As a result, this work strives to demonstrate a resonant, matched MRI coil without the use of discrete components. Approach: A Twstr coil is composed of a single Twisted-Pair wire manipulated by twisting and cutting such that the coil presents a match at its resonant frequency. Results: Twstr coils have a high quality factor, similar SNR performance in a Rx-Only configuration, and outstanding TRx capabilities when compared to a standard loop coil. Impact: Twstr coils are component-less, flexible MRI coils made from a single piece of Twisted-Pair wire. Such coils eliminate the need for discrete components on a coil providing a viable solution for implantable and multi-modal imaging coils without compromising performance.
Physics-informed and uncertainty-aware deep learning approach for liver PDFF quantification
Authors: Meneses Juan , Arrieta Cristobal , Irarrazaval Pablo , Andia Marcelo , Long Carlos Sing , Gana Juan , Galgani Jose , Tejos Cristian , Uribe Sergio
Published: November 2024

Motivation: Most Deep Learning (DL) methods to estimate liver PDFF require reference results for training and can only calculate deterministic outputs with unknown uncertainty. Goal(s): To estimate liver PDFF using a fully-unsupervised DL method for MR water-fat separation capable of quantifying uncertainty. Approach: We propose a physics informed DL-based framework which can be trained purely on chemical shift-encoded MR images. Our method estimates stochastic R2* and Δf maps, enabling uncertainty quantification, which are then used to obtain stochastic water-only and fat-only components. Results: Liver PDFF estimations showed good agreement with a reference technique, and uncertainty maps associated with imperfections in the considered physical model. Impact: The proposed physics-informed DL model requires only MR data for training, which facilitates the data gathering process. Moreover, our uncertainty-aware approach can quantify the uncertainty associated to the final estimations, which may be of significant value in clinical practice.
Associations between blood markers of redox regulation and brain white matter microstructure display distinct signatures in psychosis
Authors: Pavan Tommaso , Alemán-Gómez Yasser , Steullet Pascal , Schilliger Zoe , Dwir Daniella , Jenni Raoul , Cleusix Martine , Alameda Luis , Do Kim , Conus Philippe , Klauser Paul , Hagmann Patric , Jelescu Ileana
Published: November 2024

Motivation: It is unclear whether Glutathione peroxidase (GPx) and reductase (GRed) activity, peripheral proxy of redox homeostasis, could be linked to white matter alterations in psychosis. Goal(s): We seek to link white matter alterations to processes connected to neuroinflammation, namely raising from dysregulation of the glutathione redox homeostasis. Approach: We applied diffusion kurtosis imaging and White Matter Tract Integrity – Watson to patients data and analyzed the maps via Tract-Based Spatial Statistics(TBSS) and regression contrast analysis. Results: We found selective and widespread association of kurtosis metrics with glutathione redox enzymes that significantly dissociate between patients and controls. Impact: Our findings reveal that Redox GSH dysregulation in patients may impact WM microstructure, indicating therapeutic possibilities and reinforcing the connection between microstructure and neuroinflammation. Furthermore, the neat selectivity of the kurtosis metrics highlights potential for widespread clinical research applications.
Joint suppression of cardiac bSSFP cine banding and flow artifacts based on twofold phase-cycling and a dual-encoder neural network
Authors: Chen Zhuo , Gao Juan , Chen Haiyang , Tang Xin , Emu Yixin , Hu Chenxi
Published: November 2024

Motivation: Cardiac bSSFP cine imaging suffers from banding and flow artifacts caused by the off-resonance. Although fourfold phase cycling suppresses the banding artifacts, it invokes flow artifacts and prolongs the scan. Goal(s): To develop a twofold phase-cycling sequence with a neural-network-based reconstruction for a fast and joint suppression of banding and flow artifacts in cardiac cine imaging. Approach: We compared the method with standard bSSFP and regular phase cycling in the left ventricle and atrium in 10 healthy subjects. Results: Needing only 10 heartbeats, the proposed method robustly suppressed both artifacts in the presence of anatomical variations. Impact: Banding and flow artifacts are common in bSSFP cine imaging, especially with cardiac devices or high-field MR. The proposed method provides a robust and practical tool for suppression of them and improves the reliability of cine MRI.
Time-Resolved pCASL MRA Using A Multi-Echo 3D-Radial SPGR Sequence
Authors: Petrovic Andreas , Soellradl Martin , Okell Thomas , Lai Leon , Amukotuwa Shalini , Bammer Roland
Published: November 2024

Motivation: To improve signal, spatial and temporal resolution, and acquisition time for time resolved ASL imaging for cerebral angiography. Goal(s): To exploit a time-resolved multi-echo radial 3D ASL sequence to acquire ASL MRA data in a shorter amount of time. Approach: We performed three flip angle optimized scans with a 1, 2, and 3 echo readout, respectively, and compared image quality and acquisition time. Results: Using a 3-echo readout, scan time could be reduced from 9:32 min to 6:23 min, without the loss of image quality. Multi-echo scans even showed more details than in the single-echo case. Impact: Multi-echo 3D radial ASL angiography enables substantial scan time reduction for high-resolution time-resolved cerebral angiography. This will improve clinical applicability and scanner throughput, avoid the use of contrast agents, and is of direct benefit to patients.
Sub-space Low-rank Imaging for mapping of blood-brain barrier Water Exchange Rate (SLIWER) using multi-PLD diffusion-weighted pCASL
Authors: Shao Xingfeng , Zhao Chenyang , Guo Rong , Shou Qinyang , Liang Zhi-Pei , Lawrence Keith S St , Wang Danny
Published: November 2024

Motivation: Non-invasive MRI mapping of the blood-brain barrier (BBB) function using water as an endogenous tracer can be a valuable tool for early detection of subtle BBB dysfunctions. Goal(s): To develop an advanced MRI technique and reconstruction methods for reliable BBB water exchange rate (kw) mapping. Approach: We introduce a Sub-space Low-rank Imaging method for mapping BBB Water Exchange Rate (SLIWER) with an innovative pulse sequence termed motion compensated diffusion weighted pCASL (MCDW-pCASL). Results: The SLIWER method demonstrated high test-retest reliability, indicating its potential in clinical settings, such as in evaluating cerebral small vessel disease (cSVD). Impact: We developed a reliable tool for early BBB dysfunction detection, potentially transforming the diagnosis and treatment of neurological disorders such as cerebral small vessel disease.
DiSpect Consistently and Repeatably Reveals Modulation and Redistribution of Venous Blood Flow Caused by Functional Brain Activation
Authors: Karasan Ekin , Liu Chunlei , Lustig Michael
Published: November 2024

Motivation: DiSpect can trace blood draining from the capillary bed through the cerebral venous system and map venous territories. Goal(s): Determine whether DiSpect can detect blood flow changes in the veins during neural activation. Approach: DiSpect was performed during a motor cortex task and at baseline for two subjects, each with two repeats to ensure consistency and repeatability. Results: Modulation and redistribution of flow were observed during the task, specifically in veins near the BOLD fMRI activated regions. The measurements showed good repeatability for both subjects. Impact: BOLD contrast is affected by a complex interplay of several physiological processes. DiSpect measures changes in venous blood flow dynamics during neural activation and can potentially help to better understand the venous sources of the BOLD signal.
Histopathological Validation of Microstructure-Informed Susceptibility Source Separation (MI-SSS) for Brain Iron and Myelin Quantification
Authors: Şişman Mert , Nguyen Thanh , Gillen Kelly , Dimov Alexey , Spincemaille Pascal , Pitt David , Gauthier Susan , Wang Yi
Published: November 2024

Motivation: Myelin and iron carry significant roles in several neurodegenerative disease processes. The development of noninvasive imaging modalities for myelin and iron quantification and validation of these modalities are important steps in clinical MRI research. Goal(s): MI-SSS is developed for the improved estimation of brain myelin and iron and here it is aimed to validate MI-SSS maps with histopathological quantification techniques. Approach: An ex vivo whole brain is scanned; myelin and iron biomarkers maps are reconstructed and the results are correlated against histopathological findings. Results: Both susceptibility maps showed significant correlation with histopathological myelin and iron quantifications presenting accurate performance of MI-SSS. Impact: Myelin and iron quantification carry significant clinical importance for diagnosis and monitoring of neurodegenerative diseases. MI-SSS is developed to provide an improved and practical framework for this purpose. Here, the MI-SSS is validated against gold standard histopathological findings.
A Hydrogen Peroxide-Responsive Multinuclear 1H and 19F MRI Contrast Agent for Quantitative Application – Preliminary Phantoms Validation
Authors: Beyers Ronald , Karbalaei Sana , Bashir Adil , Goldsmith Christian , Denney Thomas
Published: November 2024

Motivation: Multinuclear contrast agents (CAs) may provide improved sensitivity and specificity for the detection/quantification of biomolecular processes. Goal(s): To develop a multinuclear 1H and 19F agent that shortens the T1 relaxation times for both the 1H and 19F signals only when hydrogen peroxide (H2O2) is present. Approach: Developed the CA: Fe(II)-F2H4qp4 -- an iron(II) complex with a fluorinated quinol-containing macrocyclic ligand. This T1-shortening CA is designed to activate only in the presence of H2O2. Results: Initial phantom tests with an 1H/19F frequency-selectable Inversion Recovery Look Locker sequence demonstrate a dual capability to quantify changes of both 1H and 19F signal T1 values. Impact: The multinuclear Fe(II)-F2H4qp4 agent's ability to quantify changes of both 1H and 19F signal T1 values in an H2O2 environment improves the sensitivity and specificity to superoxide-related pathologies and may allow expanding to other biomarkers.
in vivo longitudinal imaging unravels the origin of neuromelanin-MRI contrast in a rat model of Parkinson’s disease
Authors: Perot Jean-Baptiste , Ruze Anthony , Rebbah Sana , Cadin Capucine , Le Troter Arnaud , Soustelle Lucas , Mouton Laura , Valabregue Romain , Parent Annabelle , Santin Mathieu , Vila Miquel , Lehéricy Stéphane
Published: November 2024

Motivation: Neuromelanin-MRI contrast is a promising biomarker for Parkinson's disease, but still needs investigation as the biological and physical origins of the contrast are still unclear. Goal(s): The objective was to unravel the mechanisms behind neuromelanin-MRI contrast, both biologically and physically, and to better understand the role of neuromelanin in Parkinson's disease. Approach: We performed in vivo longitudinal neuromelanin-MRI coupled with quantitative multiparametric imaging on a rat model of Parkinson's disease based on accumulation of neuromelanin, with histological validation. Results: Results show that contrast increases with neuromelanin accumulation and decreases with neuronal loss. The contrast arises from T1 reduction due to paramagnetic neuromelanin-iron complexes. Impact: We provide first in vivo validation and better understanding of neuromelanin-MRI as a biomarker of neuronal loss in Parkinson's disease. Results also suggest a pathogenic threshold of neuromelanin accumulation triggering neurodegeneration. Investigating this hypothesis may lead to new therapeutic window.
Real-time radiation beam imaging on an MR linear accelerator using quantitative T1 mapping
Authors: Tran Brandon , Lawrence Liam , Binda Shawn , Chugh Brige , Lau Angus
Published: November 2024

Motivation: Direct imaging of radiation beam effects could enable more accurate dosimetry and in vivo dose verification. Goal(s): Our goal was to detect immediate changes in T1 relaxation due to water radiolysis induced oxygen depletion. Approach: We used dynamic T1 mapping on an MR-Linac to simultaneously irradiate and image water phantoms. Results: We observed real-time changes in T1 with a T1/Dose slope of 0.71 ms/Gy. The current sensitivity limit was estimated to be 3 Gy for a 10 min scan. Three-dimensional spatial patterns in T1 were consistent with the predicted dose profile. Impact: Real-time visualization of radiation beam effects using quantitative T1 mapping may enable new radiation dosimetry methods. This study may lead to volumetric in vivo dose verification and imaging of transient oxygen depletion in high dose rate (“FLASH”) radiotherapy.
Changes in vessel density in genetic cerebral small vessel disease (CADASIL) revealed by high-resolution black-blood MRI: A pilot study
Authors: Yang Zidong , Mendoza Steve , Li Yingying , Ying Yunqing , Cheng Xin , Shi Yonggang , Yang Qi , Wang Danny
Published: November 2024

Motivation: Cerebral small vessel disease (cSVD) is a leading cause of vascular dementia in the elderly worldwide. No existing MRI methods can directly visualize cerebral small vessels. Goal(s): Evaluation of a novel pipeline for mapping small blood vessels using high-resolution black-blood MRI in genetic cSVD (CADASIL) patients. Approach: Small blood vessels were segmented and quantified in 10 CADASIL patients and 10 matched healthy controls. Results: Significantly lower vessel density has been found in the hippocampus of the patients, whereas the vessel density is significantly higher in cortical white matter of patients compared to the control. Impact: Visualization and quantification methods of small cerebral blood vessels from high-resolution black blood MRI which would facilitate the study of cSVD mechanisms.
Identification of constitutive parameters of carotid atherosclerotic plaques by CINE MR imaging
Authors: Shen Rui , Tong Xinyu , Qiao Huiyu , Huo Ran , Wang Tao , Chen Zuoguan , Xu Ning , Liu Jiachen , Yu Shuwan , Zhao Xihai
Published: November 2024

Motivation: Beyond structural features of carotid plaque and hemodynamic parameters, the hemodynamic and structural metrics were determined by image-based computer simulations and the constitutive characteristics of carotid plaques were ignored. Goal(s): We aimed to propose a method for identification of carotid plaque constitutive parameters using CINE MR images. Approach: A novel MRI-based method to identify constitutive parameters of carotid plaque compositions was proposed and the calculated values from the proposed method were compared with the reference and ex-vivo validation. Results: We found that calculated values were consistent with the reference and experimental results. The constant D2 could identify plaque compositions with different stiffness. Impact: Our study proposed a novel MRI-based method for identifying constitutive parameters of carotid plaque compositions. The constant D2 could indicate different components of carotid plaques.