bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of a new MRE transducer - placed between tissue and coil
Authors: Kiss Lorenz , Wolf Marcos , Wampl Stefan , Körner Tito , Nguyen Quang , Königshofer Markus , Meyerspeer Martin , Schmid Albrecht
Published: November 2024

Motivation: Design of a compact MRE transducer prototype that fits between patient and coil for direct stimulation of tissue. Goal(s): The main goal of this study is to design and construct a new MRE transducer that can independently vary frequency and amplitude, is free of any magnetic parts and is suitable for cardiac MRE. Approach: Using computer aided design (CAD) and different manufacturing processes, a functional transducer prototype was built that transforms pressurized air into gravitational force. Results: A prototype that can induce tissue vibrations is presented. Its effectivity was verified by acceleration and phantom measurements. Impact: The transducer induces waves whose amplitude and frequency can be selected independently. Its shape minimizes the distance between coil and patient for reducing MR signal losses with a comparatively large surface area for efficient wave transmission, optimized for cardiac MRE.
Repeatability and reproducibility report on a novel gravitational MR Elastography device
Authors: Wang Jie , Darwish Omar , Sinkus Ralph , Wyban Michael , Handa Shinya , Petropoulos Labros
Published: November 2024

Motivation: We want contribute to establish MR Elastography as a reliable imaging technique for liver characterization. Goal(s): To validate the repeatability and reproducibility of a novel, gravitational hepatic MRE system using a generalized multi-shot GRE-MRE sequence. Approach: 57 health volunteers underwent 2D and 3D hepatic MRE scans on a 3T Siemens scanner. The repeatability was evaluated through repeated volunteer scans without repositioning, while reproducibility was performed by re-positioning the volunteer after each acquisition. Results: The repeatability and reproducibility coefficients of 2D-MRE were 0.11, 0.20 and for 3D-MRE, 0.21, 0.24, respectively. Repeatability and reproducibility for the 2D-MRE to 3D-MRE cases were 0.44 and 0.45, respectively. Impact: We evaluated a new MRE system provides sufficient mechanical vibration which results in high repeatability and reproducibility. This, in combination with the fast GRE-MRE sequence providing sufficient SNR and PNR, serves as a valuable solution.
Application of MR elastography (MRE) to measure oral posture related changes in the stiffness of the zygomaticus major muscle
Authors: Hojo Emi , Glaser Kevin , Hulshizer Thomas , Rossman Phillip , Roberts Neil
Published: November 2024

Motivation: The MR elastography (MRE) phase-gradient (PG) technique allows measurement of tissue stiffness for small structures. Goal(s): To use the PG technique to measure oral postural related changes in stiffness of the zygomaticus major (ZM) muscle in a small cohort of participants. Approach: The phase image of the first harmonic of Fourier-transformed, directionally filtered MRE wave images was analysed. The gradient of the change in phase along a 1D-profile drawn in the direction of the long axis of ZM corresponds to the wavenumber and provides a measure of ZM stiffness. Results: ZM stiffness increased significantly in mouth-open posture compared to mouth-closed posture. Impact: The feasibility of using the PG technique to measure oral posture related changes in the stiffness of ZM has been demonstrated. The method can potentially be applied to support the development of surgical treatments to rectify impaired oral posture.
In vivo MR Elastography of mice liver: Comparison of motion encoding strategies between RF optimal control and oscillating gradients.
Authors: Ageron Tiffany Bakir , Koon Kevin Tse Ve , Sango-Solanas Pilar , Van Reeth Eric , Beuf Olivier
Published: November 2024

Motivation: Preclinical Magnetic Resonance Elastography (MRE) in small animal models offers valuable insights but often requires invasive methods. This study aims to develop non-invasive MRE for small animal liver examinations. Goal(s): The specific goal is to compare conventional MEG-based MRE with OC-RARE MRE in terms of signal quality and motion encoding. Approach: A non-invasive MRE setup was created for in vivo mouse liver studies. Both MEG and OC-RARE MRE were tested on four healthy mice. Results: OC-RARE MRE showed superior Signal-to-Noise Ratios and improved wave visualization. Notable standard deviations highlight challenges. Nevertheless, OC-RARE MRE holds promise for small animal MRE research advancement. Impact: hese results underscore a novel wave motion encoding strategy, offering substantial benefits for short T2 tissue studies, potentially reducing high technical error rates and fostering MRE's broader clinical application.
Predictive Potential of IVIM for Vessels Encapsulate Tumor Clusters and Recurrence-free Survival in Hepatocellular Carcinoma
Authors: Li Min , Li Xinming , Quan Xianyue , Ren Yufan , Xu Yongzhou , Guo Congyue , Lyu Jiaqi , Zhang Ge , Lu Haojun
Published: November 2024

Motivation: To explore a more accurate non-invasive method for predicting VETC pattern in HCC. Goal(s): To estimate the potential of preoperative IVIM in predicting of VETC pattern in HCC. Approach: Investigating the correlation between IVIM-derived parameters and the VETC pattern, and constructing a predictive model. Results: Our results showed that VETC HCC exhibited a declining f value trend and outperformed conventional imaging-clinical models when an integrated model was established, incorporating intratumoral necrosis and high-level AFP. Furthermore, this model is capable of identifying individuals at high risk of postoperative recurrence. Impact: To our knowledge, this study marks the first time diffusion sequences have been used to predict VETC in HCC, which offers a fresh perspective and paves the way for more accurate VETC direction in the future.
Probabilistic Brain Tumor Segmentation for Everyone
Authors: Luo Jie , Chen Cheng , Kim Sekeun , Hu Rui , Li Quanzheng
Published: November 2024

Motivation: Probabilistic segmentation offers notable advantages in the context of brain tumor delineation on MRI. However, existing methods are not accessible to most medical institutes, rendering their clinical relevance questionable. Goal(s): we present a foundation model-based probabilistic brain tumor segmentation approach designed for straightforward integration into clinical applications. Approach: We employ a parameter-efficient few-shot learning strategy to fine-tune the foundation model, thereby enabling it to output the tumor mask and uncertainty for the brain tumor segmentation task. Results: The proposed method achieves a competitive performance with training on only five cases. It has the potential for a substantial impact on clinical practice. Impact: The proposed foundation model-based probabilistic brain tumor segmentation method is open-source and achieves a competitive performance with only five training cases. Such characteristics make it a valuable asset for healthcare institutions that have difficulties developing their proprietary probabilistic segmentation models.
Discrimination between Benign and Malignant Lung Lesions Using a Tri-Compartmental Restriction Spectrum Imaging Model
Authors: Liu Xue , Meng Nan , Jiang Han , Zhou Yihang , Yuan Jianmin , Wang Zhe , Yang Yang , Wang Meiyun
Published: November 2024

Motivation: An accurate non-invasive detection method is required to identify benign and malignant lung lesions. Goal(s): To assess the predictive value of the tri-compartmental RSI model in distinguishing between benign and malignant lung lesions. Approach: In a prospective study, 137 suspected lung tumor patients who underwent PET/MRI scans were included. Results: Elevated RSI-C1, SUVmax, and lower ADC, RSI-C3 were observed in the malignant group compared with benign group (all P < 0.001). The AUCs, ranked from highest to lowest, were 0.819 (SUVmax) > 0.811 (RSI-C3) > 0.770 (RSI-C1) > 0.745 (ADC). The combined model of RSI-C1, RSI-C3, and SUVmax showed an AUC of 0.900. Impact: Our study provides preliminary evidence of the potential of RSI-MRI technology to enhance non-invasive imaging of lung lesions. PET/MRI combined with metabolic parameter is helpful to optimize the clinical diagnosis of lung lesions.
Working Memory Prognostication After Concussion Using Glymphatic Biomarkers
Authors: Li Yi-Tien , Chen Cheng-Yu
Published: November 2024

Motivation: Addressing persistent working-memory decline (PWMD) in concussion patients is crucial, but prognostic methods are limited. This study explores the potential of the glymphatic system as a novel biomarker. Goal(s): Determine if early measurement of glymphatic dysfunction within 1 month post-concussion can predict PWMD. Approach: A 1-year prospective observational study was conducted, assessing glymphatic function, microhemorrhage, sleep quality, and neurocognitive tests within 1-month of injury. Results: Significant correlations were found between 1-year digit span scores and glymphatic diffusivity and sleep quality. Lower glymphatic function and poor sleep quality correlated with unfavorable long-term working memory outcomes. The 1-year digit span score could be reliably predicted. Impact: This research highlights the importance of monitoring sleep quality and glymphatic function, offering potential therapeutic targets to prevent persistent working-memory decline in concussion patients.
Gadolinium-Loaded Melanin-Induced Magnetic Resonance Imaging and Thermoradiotherapy in Glioblastoma Multiforme
Authors: Shi Ying , Lian Jianxiu , Ma Yuefei , Liu Pengfei
Published: November 2024

Motivation: Glioblastoma multiforme(GBM) is characterized by highly invasive growth, resulting in poor treatment efficacy, high recurrence rate and a short life expectancy. Goal(s): Maximizing removal of tumor tissue, while minimizing damage to brain function areas and enhancing treatment effectiveness holds significant clinical significance. This necessitates precise delineation of GBM edge and ntegration of multiple treatment strategies. Approach: T1WI mDIXON and T1 mapping was performed on a 3.0T MR scanner. Multi-level tumor models will be established to assess the potential ability of Gd-MNP-PEGs and underlying molecular mechanisms of thermoradiotherapy. Results: Gadolinium-loaded and PEGylated Melanin nanoparticles performed notable photothermal effect, radiosensitization and the ability of MRI. Impact: Gd-MNP-PEGs was formed and utilized for integration of diagnosis and treatment to precisely define the boundaries of GBM and enhance the therapeutic outcome.
Test-retest repeatability of renal MRI parameters in healthy volunteers comparing ROI-based and tissue segmentation based image analysis
Authors: Liang Cecilia , Loster Isabelle , Küstner Thomas , Gückel Brigitte , Kühn Bernd , Schick Fritz , Seith Ferdinand , Martirosian Petros
Published: November 2024

Motivation: Multiparametric MRI of the kidneys is a promising technique for renal diagnostics, but the diversity of imaging protocols and analysis strategies hinders clinical translation. Goal(s): Our goal was to assess the repeatability of a multiparametric MRI protocol comparing ROI-based and tissue segmentation based analysis. Approach: Ten volunteers were examined with a multiparametric MRI protocol including ASL, IVIM, BOLD, T1 and T2 mapping twice with one week between visits. Results: Good repeatability of the multiparametric protocol could be achieved. T1 and T2 values showed less variability compared to perfusion and diffusion related functional parameters. Tissue segmentation showed better repeatability compared to ROI-based analysis. Impact: Our study demonstrates relatively high repeatability of multiparametric functional MRI of the kidneys. The results of the image analysis methods suggest, that manual segmentation is to be preferred over ROI-based analysis, if automated segmentation is not available.
The value of IVIM-DWI and DCE-MRI in predicting molecular subtypes of breast cancer
Authors: Lin Ting-ting
Published: November 2024

Motivation: To analyze the value of imaging examination in accurate diagnosis of breast cancer. Goal(s): Provide an non-invasive examination for the prediction of molecular subtypes of breast cancer before treatment. Approach: The quantitative parameters of IVIM-DWI and DCE-MRI in patients with breast cancer without any invasive examination and treatment were compared with pathological molecular subtypes, so as to analyze their diagnostic value in the prediction of molecular subtypes. Results: DCE-MRI and IVIM-DWI were correlated with immune prognostic factors of breast cancer and had differential diagnostic value for different molecular subtypes. Impact: DCE-MRI and IVIM-DWI could provide a non-invasive diagnostic method for predicting molecular subtypes of breast cancer and provide a reference for further development of personalized treatment plans.
Simultaneous R2* Relaxometry and Dixon Imaging of Liver and Kidney at 3T Using Bilateral Orthogonality Generative Acquisitions Method
Authors: Boğa Çelik , Henning Anke
Published: November 2024

Motivation: Improving the quality of body R2*( T2* ) images by removing transmit field inhomogeneity while utilizing Dixon imaging in body at 3T. Goal(s): Implementation of Bilateral Orthogonality Generative Acquisitions method for simultaneously obtaining homogeneous R2*( T2* ) and Dixon imaging fro kidney and liver at 3T. Approach: Bilateral Orthogonality Generative Acquisitions method was improved to include phase effect that enables the use of Dixon Imaging. Multi-echo acquisitions are utilized for R2* estimation. Results: Implementation of Bilateral Orthogonality Generative Acquisitions method enables the simulataneous R2*( T2* ) and Dixon imaging and eliminates the central brightnening effect. Impact: Simultaneous homogeneous R2*( T2* ) and Dixon imaging is implemented within same scan time required for Dixon imaging while removing the central brightening effect in body imaging at 3T.
Enabling reproducible measurements of Fat Fraction and Iron content using an SI traceable reference phantom
Authors: Cashmore Matt , Clarkson Cailean , Tatman Ben , Obee Katie , Clarke Jack , Smith Nadia , Brochu Frederic , Cooke Elizabeth , Ford-Scille Asha , Goldring Jessica , Hanson Robert , Ntata Asante , Rhodes Susan , Busoni Simone , McCann Aaron , McGrath Cormac , Ferrero Riccardo , Manzin Alessandra , Troia Adriano , Hill Sarah , Rai Sumiksha , Strepokytov Stanislav , Ward-Deitrich Christian , Bosnjakovic Alen , Tofts Paul , Dispinar Tugba , Un Ilker , McDowell Amy , Wastling Stephen , Thornton John , Zafeiropoulos Nick , Curtis Sian , Scott Richard , Elbert Holly , Delve Jonathon , Ingham Cameron , Deumić Amar , Pokvić Lejla Gurbeta , Smajlhodžić-Deljo Merima , Hall Matt
Published: November 2024

Motivation: Quantitative MRI is a powerful tool for measuring a variety of biological parameters, with two common biomarkers of interest being fat fraction and Iron content. Goal(s): We present here a test object for these parameters which is supported by fundamental metrology and traceable to the SI system. Approach: Initial scan data taken at 1.5T is compared with traceable measurements of phantom propertiesResults: We see significant variation seen in clinical results of the same phantom even with standardised protocols, outside the range of phantom validation. Impact: We demonstrate a new gold standard and verified phantom for fat and iron measurement, traceable to primary standards. We present results using standardised MRI protocols which is vital for understanding and improving standards and best practice guidelines in the future.
A Convolutional Neural Network Approach to Personalized Neuropil Density Prediction
Authors: Chang Brian , Akif Adil , Onofrey John , Hyder Fahmeed
Published: November 2024

Motivation: Bottom-up energy budgets provide a way to quantify electrical activity in the brain using metabolic imaging. However, existing models are not patient-specific, instead using generalized neural cell counts, preventing direct measures of cognitive activity in the brain. Goal(s): Our goal was to use a convolutional neural network (CNN) to demonstrate the possibility of predicting individualized neural cell counts. Approach: Multi-modal MRI from nine patients was used to model neural and synaptic density predictions, which were compared to silver standard counts using correlation coefficient in a cross-validation study. Results: The model demonstrates an ability to predict patient-specific energy budgets. Impact: The success of machine learning methods in predicting neural cell and synaptic density paves the way for the use of CNNs to generate patient-specific energy budgets, improving understanding of brain energetics at a microscopic level in health and disease.
Gadolinium contrast-enhanced lesion segmentation in multiple sclerosis: a deep-learning approach.
Authors: Greselin Martina , Lu Po-Jui , Melie-Garcia Lester , Ocampo-Pineda Mario , Galbusera Riccardo , Cagol Alessandro , Weigel Matthias , de Oliveira Siebenborn Nina , Ruberte Esther , Benkert Pascal , Müller Stefanie , Achtnichts Lutz , Vehoff Jochen , Disanto Giulio , Findling Oliver , Chan Andrew , Salmen Anke , Pot Caroline , Bridel Claire , Zecca Chiara , Derfuss Tobias , Lieb Johanna M. , Remonda Luca , Wagner Franca , Vargas Maria I. , Pasquier Renaud Du , Lalive Patrice H. , Pravatà Emanuele , Weber Johannes , Gobbi Claudio , Leppert David , Kappos Ludwig , Kuhle Jens , Granziera Cristina
Published: November 2024

Motivation: Detection of contrast-enhanced lesions (CELs) is fundamental for the diagnosis and monitoring of Multiple Sclerosis (MS) patients. This task is time-consuming and variable in the clinical setting. However, only a few studies reported automatic approaches. Goal(s): To develop a deep-learning tool to automatically detect and segment CELs in clinical MRI scans from MS patients. Approach: We implemented a UNet-based network with an adapted sampling strategy to overcome the scarcity of CELs. We considered the data imbalance to weight the training loss function. Results: The model performance was evaluated for different lesion-volume ranges and achieved high performance even in low-volume lesions. Impact: We developed a deep-learning method fulfilling clinical needs in detecting and segmenting lesions characterized by low volume, low numbers per patient and heterogeneous shapes.
A multi-scale pyramid residual weight network for medical image fusion
Authors: Liu Yiwei , Zhang Shaoze , Zhao Xihai , He Zuo-Xiang
Published: November 2024

Motivation: At present, the multi-modal fusion image has the problems of weak functional information performance and much noise. Goal(s): Based on the existing technology, this research increases the retention of functional information and improves the display quality of the fused image. Approach: In this study, a multi-scale pyramid convolutional neural network model based on residual structure is constructed, which can extract deeper semantic information while retaining shallow context information. Results: By constructing a new convolutional neural network, the loss of functional information in the fused image is reduced, the noise of the fused image is reduced, and the image quality is improved. Impact: The multimodal image fusion technology proposed in this paper preserves the texture information of MRI and CT, and the functional information of PET/SPECT at the same time, which makes more dimensions available for clinical diagnosis in the future.
Automated Pancreatic Segmentation and Quantitative Calculation Based on nnUnet
Authors: YingHao Li , SuCheng Wang , ZhongQi Zhu , HongZhi Wang , RenFeng Li , LiHui Wang , Qing Lu
Published: November 2024

Motivation: Pancreatic diseases often exhibit spatial non-uniformity. Achieving automated segmentation of different pancreatic regions and conducting quantitative calculations of volume and fat content can effectively assist physicians in diagnosis and treatment. Goal(s): Developing a segmentation network to achieve the automatic segmentation of the pancreas and to perform quantitative calculations of volume and fat content in diffrent regions. Approach: Sample acquisition was performed using Dixon sequences, and training was conducted using an improved nnUnet network. Additionally, an automated pancreatic segmentation and quantitative calculation method was developed. Results: With a training dataset consisting of 800 cases, the network achieved a segmentation Dice coefficient of 0.92. Impact: To save professional physician annotation time for early detection and diagnosis of pancreatic diseases, as well as for quantifying changes before and after pancreatic treatments, and to assist in clinical drug therapy.
Harmonizing Multicenter Datasets: Enhancing Consistency and Longitudinal Alignment using NLP and Realignment Algorithms
Authors: Arnold Thomas , Yao Lanhong , Duffy Ben , Zaharchuk Greg , Chamberlain Ryan , Sibille Ludovic
Published: November 2024

Motivation: Cohesive multicenter imaging datasets are critical for research, yet variability across institutions poses a significant challenge, especially when aggregating retrospective data for longitudinal disease monitoring. Goal(s): Here, we present a method for harmonizing multicenter data that produces consistent series descriptions and enhances brain alignment between longitudinal time points. Approach: We employed an NLP pipeline to standardize series descriptions and an automated algorithm to realign images. We applied these tools to ADNI imaging collected across multiple sites, scanners, and time points. Results: The pipeline consolidated 101 unique series descriptions into 17 standardized descriptions. The alignment algorithm reduced orientation error and improved longitudinal image consistency. Impact: Our methodology can impact clinical workflows by streamlining multicenter data analysis and enhancing longitudinal disease monitoring. These techniques improve image consistency between time points, which can facilitate disease monitoring and allow radiologists to assess changes in chronic disorders.
A comparative study to assess the flow of meningeal lymphatic vessels in healthy volunteers and brain disorders using the IR-ALADDIN technique
Authors: Kim Jun-Hee , Yoo Roh-Eul , Choi Seung-Hong , Park Sung-Hong
Published: November 2024

Motivation: The difference in mLVs outflow between healthy control (HC) and brain disorder patients may contribute to toxic protein aggregation and cognitive decline. Goal(s): To demonstrate mLVs structure and flow information of brain disorder patients and compare quantitative flow metrics between HC and patientApproach: We applied IR-ALADDIN to acquire mLVs images around superior sagittal sinus in 20 HCs and 9 patients with various brain disorders such as meningioma, hydrocephalus. Results: The mLVs size was reduced in patients compared to HC with no significant difference in mLVs velocity, leading to overall mLVs flow reduction in patients. Impact: The reduced mLVs flow in brain disorder patients was confirmed using a non-invasive technique. This suggests the possibility to study relationship between brain disorders and waste clearance through the mLVs flow in further studies.
ISMRM - Open Science Initiative for Perfusion Imaging (OSIPI): The multi-delay Arterial Spin Labeling Challenge
Authors: Oliveira Icaro , Kashyap Sriranga , Mutsaerts Henk , Petr Jan , Pinto Joana , Woods Joseph , Zhao Moss , Paschoal Andre
Published: November 2024

Motivation: The OSIPI ASL Challenge is a community initiative motivated by open science principles that aim to establish good practices in ASL image analysis and Cerebral Blood Flow (CBF) quantification. Goal(s): The second ASL challenge's main goal is to provide a thorough comparison of existing post-processing pipelines focusing on Multi-PLD methodology. Approach: The second roadmap will provide different datasets; a population dataset which will bring real variability to the challenge and synthetic data which allows straightforward ground truth comparison. Results: The second edition of the ASL Challenge will contribute to gaining new insights into the potential sources of variability within the multi-PLD analysis pipeline. Impact: Through the second edition of the ASL Challenge, we seek to enhance our understanding of multi-PLD analysis in the ASL community. Its success could establish a consensus on the processing of multi-PLD ASL data, positively influencing clinical and scientific practices.
Multi-Tag Time-SLIP Simulation Beyond the General Kinetic Model
Authors: Malis Vadim , Miyazaki Mitsue
Published: November 2024

Motivation: We identified a gap in understanding multi-tag Time-SLIP MRI dynamics, crucial for advanced perfusion analysis, particularly in varying physiological and pathological states. Goal(s): Our goal was to develop a comprehensive simulation tool to accurately predict signal changes in multi-tag Time-SLIP ASL MRI across diverse flow conditions. Approach: We employed MATLAB to simulate numerically non-selective and selective multi-tag Time-SLIP pulse sequences, applying Bloch equations to model tissue-specific magnetization and blood flow perfusion dynamics. Results: Simulations showed distinct magnetization patterns between odd and even pulse tags, aligning with physiological flow rates. Impact: This simulation tool enables researchers to customize Time-SLIP MRI protocols for detailed study of fluid dynamics across the body, from blood to CSF flow. It provides a solid foundation for developing more comprehensive ASL-related simulations.
Imaging Artifacts of Novel Laser-cut Venous Stents: Dependence between Stent Design and Radiofrequency Shielding
Authors: Regler Lisa , Reiss Simon , Verloh Niklas , Uller Wibke , Bock Michael
Published: November 2024

Motivation: RF shielding up to 95% in stents creates image artifacts that can impact an accurate diagnosis of vessel patency after stent implantation. Goal(s): The association between design parameters of novel venous stents and their RF shielding properties were investigated. Approach: Therefore, field simulations and measurements were performed of the relative induced B1 in venous stents with different lengths and cell geometries. Results: Edge length of the stent cells and their orientation relative to the B1 transmit field determine the amount of RF shielding. Impact: The work provides information about the correlation of venous stent geometries and RF shielding artifacts. Sequence parameters e.g. excitation flip angle could be adapted for different stent models to possibly achieve higher intraluminal signal in post-implantation MRI venography.
Automated Vendor-Independent Open-Source Quality Assurance Protocol using Pulseq
Authors: Chen Qingping , Zijlstra Frank , Littin Sebastian , Nielsen Jon-Fredrik , Zaitsev Maxim
Published: November 2024

Motivation: Ensuring comparable performance of MR protocols across vendors and over time duration. Goal(s): To implement an easy-to-use vendor-independent quality control pulse sequences and data analysis routines. Approach: Relying on Pulseq as a vendor-independent MR pulse sequence environment, we implemented the established quality assurance protocols (ACR/fBIRN). Following the image reconstruction from the acquired data, performed either on the scanner or off-line in Gadgetron, images are analyzed by the open-source Matlab pipeline. Results: The proposed protocol has been tested on three 3T Siemens scanners with over a decade difference in the manufacturing date and has been successfully executed on a 3T GE scanner. Impact: The proposed protocol and post-processing scripts allow for easy and streamlined quality assurance, contributing an essential component for Pulseq to become usable in large scale multicenter imaging studies.
Inhomogeneity-informed Field-fitting for Quantitative Susceptibility Mapping (if-QSM)
Authors: Roberts Alexandra , Dimov Alexey , Nguyen Thanh , Spincemaille Pascal , Wang Yi
Published: November 2024

Motivation: Inhomogeneity in measured multi-gradient echo (mGRE) field data corrupts reconstructions of quantitative susceptibility maps by obscuring the tissue field of interest with strong background field. Goal(s): To extend the voxel spread function (VSF) library implementation to a nonzero phase offset and demonstrate improvements on QSM. Approach: The measured field was estimated and inhomogeneity contributions computed using the extended library implementation. The inhomogeneity field was then estimated and subtracted from the total field to reduce the influence of strong background fields in the QSM reconstructionResults: Inhomogeneity-informed field-fitting for QSM is shown to improve total field reconstructions of the brain, carotid, and cervical spine. Impact: The voxel spread function (VSF) library implementation is extended to include initial phase offset contributions and reduce the effect of field inhomogeneity in quantitative susceptibility map (QSM) reconstruction.
Towards an Intraoral Coil Array Design for Dental MRI
Authors: Tesfai Agazi , Hilgenfeld Tim , Bock Michael , Özen Ali Caglar
Published: November 2024

Motivation: In dental diagnostics MRI provides an improved soft tissue contrast for endodontic, craniomaxillofacial and implant applications with better visibility of anatomical structures. Goal(s): An intraoral coil array is introduced for dental MRI to investigate feasibility, achievable signal gain and parallel acquisition performance. Approach: Coil element size, material, and shape properties are investigated with respect to image SNR. The array is adjusted to the dental anatomy on a 3D phantom to estimate the sensitivity and the g factor of parallel imaging. Results: Intraoral coil array improves SNR, spatial resolution and provides a homogenous B1 receive profile. It allows parallel imaging to minimize measurement time. Impact: Intraoral coil arrays can enhance MRI of small dental structures, required for endodontics, while increasing the spatial coverage in oral cavity. Compared to single-loop coils, a more homogeneous receive sensitivity can be achieved and parallel imaging becomes feasible.
Brain Tissue Displacement and Strain Measures in an Alzheimer’s Disease Cohort using DENSE
Authors: Doctor Caroline , Rivera Leonardo , Eisenmenger Laura , Johnson Sterling , Johnson Kevin
Published: November 2024

Motivation: Cardiac driven motions may affect Alzheimer's Disease. Goal(s): The goal was to provide preliminary results on the success of measuring the displacement and strain of brain tissues due to Cardiac Arterial Pulsations (CAPs) using DENSE (Displacement ENcoding with Stimulated Echoes) in patients with AD and age-comparable controls. Approach: DENSE scan data from a sample of 133 volunteers was processed and evaluated for trends in the derived displacement and strain information. Results: High variability was found in the displacement measures, and future work is needed to determine the confounding factors behind the variability and to what degree those factors can be minimized going forwardImpact: DENSE MR was used to measure displacement of brain tissue from cardiac effects in Alzheimer’s disease (AD) patients and age-comparable controls. Preliminary results are inconclusive and future work is needed to determine what confounding factors are affecting the displacement measures.
Blood brain barrier permeability characterization in the NOD-EAE mouse model of secondary progressive multiple sclerosis using MRI
Authors: Shazeeb Mohammed Salman , Hagan Nellwyn , Ying Xiaoyou
Published: November 2024

Motivation: Blood brain barrier (BBB) dysregulation is one of the earliest signs of multiple sclerosis (MS) and the mechanism underlying BBB breakdown is not completely understood. Goal(s): We sought to use the non-obese diabetic experimental allergic encephalomyelitis (NOD-EAE) mouse model of secondary progressive MS to understand BBB breakdown in efforts to explore potential MS therapeutics. Approach: MRI was used to quantify BBB permeability metrics using gadolinium contrast agent. Results: We quantified the spatial and temporal characterization of BBB permeability in NOD-EAE mice with progressing disease using MRI. These quantifying parameters can potentially be used to test the effect of therapeutic agents on BBB breakdown. Impact: The NOD-EAE mouse model of secondary progressive multiple sclerosis (SPMS) can potentially be used to assess blood brain barrier characteristics using contrast-enhanced MRI in efforts to test therapeutic agents that can be used in the treatment of SPMS.
CEST MRI detects antiretroviral therapy-induced metabolomic alterations in brains of a rodent model
Authors: LIU YUTONG , Gauthier Gabriel , Summerlin Micah , Bade Aditya
Published: November 2024

Motivation: The neurotoxicity of antiretroviral (ARV) drugs has been reported to affect neurocognition. Goal(s): In this study, we tried to link CEST results of ARVs and metabolites to elucidate the effects of ARVs on metabolic alterations. Approach: Mice administrated with TDF/3TC/DTG were scanned using CEST MRI to detect 3TC (at 1 and 2 ppm) and TDF (at 3 ppm). Metabolites were also measured using CEST MRI. Results: Results showed that when used in combination, MRI is not sensitive to the CEST contrasts of 3TC and TDF. Glutamate, creatine and NOE were affected by TLD indicating the toxicity of TLD. Impact: The study showed the potential to use CEST MRI to elucidate the effects of antiretroviral drugs on the neuropathologic outcomes by testing the association of MRI measurements of ARVs and metabolic imaging results.
Good agreement of turbulent kinetic energy assessment by compressed sensing-accelerated 4D flow MRI in aortic stenosis patients
Authors: Park Sungho , Jin Ning , Han Dongyeop , Lee Bae Young , Kwon Minseong , Yi Jeong-Eun , Huh Hyungkyu
Published: November 2024

Motivation: Compressed sensing (CS) acceleration has improved the clinical applicability of 4D flow MRI. However, but no studies have investigated turbulent kinetic energy (TKE) assessment using CS-accelerated 4D flow MRI. Goal(s): This study aims to validate TKE assessment in CS 4D flow MRI compared to conventional 4D flow MRI. Approach: The effect of CS acceleration on TKE assessment was evaluated by in vitro coarctation model. In addition, TKE assessment was further validated in healthy subjects and aortic stenosis (AS) patients. Results: TKE parameters had good agreement in AS patients at the ascending aorta, while healthy subjects had significant differences. Impact: TKE estimation has been limited due to asymmetric velocity encoding scheme, requiring additional MR scans. This study firstly validates the reliability of TKE using CS 4D flow with reduced scan time in AS patients.
Adiabatic T1rho-mapping of subacute myocardial ischemia with ultra-short echo time 3-D imaging in ex vivo mice
Authors: Räty Iida , Paajanen Antti , Nissi Mikko , Kettunen Sanna , Ruotsalainen Anna-Kaisa , Laidinen Svetlana , Ylä-Herttuala Seppo , Ylä-Herttuala Elias
Published: November 2024

Motivation: Conventional CMR techniques have many limitations, such as slowness and inability to provide contrast-agent free 3-D assessments of myocardium in the cardiac diseases. Goal(s): The aim of this study is to develop a faster, high-resolution 3-D CMR imaging method for quantitative imaging of the myocardium after myocardial infarction (MI). Approach: Mice hearts were imaged ex vivo 7 days after the factitious MI by using an ultra-short echo time 3-D T1ρ technique (MB-SWIFT-CS). Results: The T1ρ relaxation times were elevated in the infarct area. The findings were validated by 2-D CMR maps and histopathology to confirm ischemia, edema, and fibrosis in the myocardium. Impact: This study presents a quantitative ultra short echo time 3-D CMR method for ex vivo assessment of myocardium after factitious myocardial infarction in mice. The method allowed rapid comprehensive 3-D myocardial evaluation by utilizing compressed sensing and relaxation time mapping.
Vulnerable plaques are associated with white matter hyperintensities: a finding on high-resolution vessel wall magnetic resonance imaging.
Authors: Li Jiayu , Shi Ying , Lian Jianxiu , Liu Pengfei
Published: November 2024

Motivation: Cerebral small vessel disease (CSVD) is a common disease in the elderly with uncertain causes. We wanted to explore whether intracerebral macrovascular disease is related to CSVD. Goal(s): This study was to explore the relationship between atherosclerotic plaque characteristics and wall changes and white matter hyperintensities (WMH) associated with CSVD. Approach: As a non-invasive technique, high-resolution vessel wall magnetic resonance imaging can display vascular image and measure plaque parameters and vascular wall changes. Using the tools, the differences between WMH groups were analyzed. Results: WMH was associated with unstable plaques. Age, wide distribution and significant enhancement were independent factors affecting WMH. Impact: Unstable atherosclerotic plaque may cause CSVD, suggesting that clinicians should pay more attention to patients with ischemic stroke. The plaque vulnerability parameter may be a new index to evaluate the degree of WMH.
Interaction of neurofluids flow dynamics studied by PC-MRI
Authors: Owashi Kimi , Liu Pan , Metanbou Serge , Capel Cyrille , Balédent Olivier
Published: November 2024

Motivation: Cervical-level is often chosen to estimate Cerebral Blood-Volume Change (CB-VC) during cardiac cycle. Due to the heterogeneity in extracranial cerebral veins anatomy and their high compliance, we hypothesize that the intracranial level could be a better choice to investigate blood and CSF interactions. Goal(s): To determine the best level for studying the interaction of neurofluids flow dynamics. Approach: Using PC-MRI, CB-VC and CSF-Volume Change (CSF-VC) were calculated in 36 volunteers at intracranial and extracranial levels, and their interactions were compared by linear regressions. Results: The interaction between CSF-VC and CB-VC dynamics at intracranial level (R2:0.82±0.16) was higher (p<0.001) than at extracranial level (R2:0.46±0.36). Impact: This study highlights the greater consistency of spinal CSF-VC response to vascular volume dynamics measured intracranially rather than at the cervical level. These findings are valuable to consider for studying cranio-spinal neurofluids flow dynamics interactions, pressure and compliance.
Glymphatic function as a predictor of mild cognitive impairment to dementia conversion in Parkinson’s disease
Authors: Pang Huize , Wang Juzhou , Jiang Yueluan , Fan Guoguang
Published: November 2024

Motivation: Impaired glymphatic function is reported to be associated with cognitive function in Parkinson’s disease (PD). However, an evaluation of the role of the glymphatic dysfunction contributing to the dementia conversion of mild cognitive impairment (MCI) with use of MRI remains lacking. Goal(s): To evaluate the value of glymphatic function to predict the dementia conversion in PD with MCI. Approach: We calculated the water diffusion in the periventricular white matter using DTI-ALPS to evaluate the glymphatic function in PD with cognitive impairment during the follow-up. Results: The left DTI-ALPS is significantly lower in dementia converters, and is valuable for prediction of PD dementia conversion. Impact: The reduction of glymphatic activity, assessed by DTI-ALPS, was more severe in PD with MCI convert to dementia. Therefore, DTI-ALPS may assist in identifying PD with MCI at a high risk of dementia conversion before the onset of dementia symptoms.
Diffusion-weighted imaging-based fluidography for assessing cerebrospinal fluid dynamics in the brains
Authors: Fujiwara Shunrou , Ogasawara Kuniaki , Chida Kohei , Akamatsu Yosuke , Koji Takahiro , Miyoshi Kenya , Oikawa Kohki , Yoshida Jun , Kubo Yoshitaka , Yoshioka Yoshichika
Published: November 2024

Motivation: Few study has developed the 3-D image like DTI-tractography to show tendency of CSF dynamic through the whole brain. Goal(s): To develop DWI-fluidography for demonstrating tendency of CSF dynamic through the whole brain. Approach: DWI with multiple b values and MPGs was scanned, and calculated a statistical variation of DWI signals obtained by different MPGs at each b value. The normalized value of the summation of all variations was defined as a value in a voxel for DWI-fluidography. Results: The 3-D DWI-fluidography clearly showed differences of CSF dynamics at anatomical spaces filled with CSF, and the fluidography could reflect quantitative results with ADCs. Impact: The DWI-fluidgraphy has the potential to help us to diagnose/find/investigate CSF-related diseases in the brain. Then, it may open the door to new research area.
Simultaneous Acquisition of Temperature Mapping for Fatty and Nonfatty Biological Tissues based on Look-Locker Technique with dual echoes
Authors: Kim Sangwoo , Hwang Jinwoo , Lee Chulhyun , Oh Sukhoon
Published: November 2024

Motivation: Temperature errors in PRFS occur primarily in tissues containing adipose substances because fat changes its magnetic susceptibility with temperature. Goal(s): This study aimed to simultaneously monitor the temperatures of fat and non-fat tissues using Look-Locker (LL) technique with dual echoes. Approach: Two-point Dixon technique can be utilized to estimate the adipose components, which may aid in the separation of adipose tissue in PRFS. In addition, the method allows for a more refined Bo correction. Results: Compared to the temperature measured by the fiber-optic sensor, the PRFS and T1-based temperatures showed a small difference of about 0.11 ~ 0.22 ℃ and 0.06 ~ 0.15 ℃, respectively. Impact: his study yields an evidence that Look-Locker technique with dual echoes is suitable for simultaneous acquisition of temperature mapping for adipose and non-adipose tissues, providing an accurate temperature monitoring comparable to a fiber-optic sensor as well as rapid acquisition.
Needle Artifact Prediction by Modeling Dephasing in MR-Guided Interventions
Authors: Faust Jonas , Krafft Axel , Pang Jianing , Ladd Mark , Maier Florian
Published: November 2024

Motivation: MR-guided needle interventions benefit from prior knowledge of needle artifact size and shape, as the artifact is important for instrument visualization and localization. Goal(s): To investigate an analytical model for the dephasing artifact of a 20-gauge aspiration needle in GRE imaging based on material and imaging parameters. Approach: Model accuracy was evaluated in-vitro for B0 = 0.55T/1.5T/3T, res = (1mm)3/(2mm)3 and TE = 5ms/15ms/25ms using Dice score (DSC) and Hausdorff distance (dH) as metrics. Results: For isotropic voxel grids, the dephasing needle artifact could be well approximated by the model (DSC ≥ 86%, dH ≤ 2 voxels). Impact: The approximation of needle artifacts using an analytical model provides an instructive way for artifact size prediction and can potentially facilitate MR-guided intervention planning (e.g., the choice of imaging parameters, needle selection and system selection).
Field-based spatial self-registration of multi-coil hardware for B0 field control
Authors: Zinghini Isabelle , Macleod Ian , Ianniello Carlotta , Theilenberg Sebastian , Juchem Christoph
Published: November 2024

Motivation: Successful multi-coil B0 field control relies on reproducible hardware placement. Goal(s): Our goal was to detect hardware misplacements from MC-generated field patterns alone (i.e. without field probes) to allow spatial transformations for correction. Approach: We co-registered unique field maps before and after hardware displacements to derive the underlying translation and rotation parameters. Results: In simulation and preliminary scanner validation, hardware misplacements were detected with sub-millimeter/sub-degree precision. Impact: Field-based spatial self-registration for multi-coil field inserts is expected to allow optimal B0 field control even with differences in hardware placement, thus preserving the best shim performance.
Improved multinuclear parallel transmit optimization using multinuclear virtual observation points
Authors: Schmidt Simon , Metzger Gregory
Published: November 2024

Motivation: Managing peak local SAR for pTx-enabled studies at UHF is challenging, especially for multinuclear acquisitions. Goal(s): To evaluate the feasibility and potential advantages of multinuclear VOPs for pTx optimizations in multinuclear studies. Approach: Simulation data was used to perform L-curve analyses to quantify the achievable minimal excitation errors at different peak 10g local SAR levels using both mononuclear and multinuclear VOPs. Results: Multinuclear VOPs can substantially improve excitation performance at a set peak 10g local SAR level in multinuclear acquisitions by preserving the spatial correlation between the 10g local SAR resulting from each individual nucleus’s excitation. Impact: The improved 1H excitation performance enabled through multinuclear VOPs can lead to improved image quality and reduced scan times for a variety of multinuclear imaging applications.
A Next Generation Surface Array For Body Imaging at 7T
Authors: Haluptzok Tobey , Lagore Russell , Schmidt Simon , Metzger Gregory
Published: November 2024

Motivation: Improved RF coil performance is needed to realize the gains from UHF body imaging. Goal(s): Design a 7T body array with improved stability and increased transmit/receive performance. Approach: A 32 channel loop-dipole (32LD) array was constructed with a shield allowing for on board electronics. Dipoles were transceivers while loops were coupled in groups of three on transmit while receiving separately. Comparisons were made with an existing 16LD array. Results: The 32LD is more stable, has a lower flatter z-profile on transmit, 20% higher central SNR and supports parallel imaging on all axesImpact: The new 32LD array provides a more robust platform for clinical translation of UHF body imaging while approaching the theoretical gains in SNR and improved parallel imaging performance enabling increased spatiotemporal resolutions at 7T.
A comparison of different sources of soy lecithin for the production of MRI phantoms with systematic analysis of effects on T1, T2, and diffusion
Authors: Fritz Victor , Martirosian Petros , Machann Jürgen , Schick Fritz
Published: November 2024

Motivation: While soy lecithin has been shown to be a beneficial substance for the production of diffusion phantoms, there is no research to date on whether this applies generally or only to specific product sources of soy lecithin. Goal(s): To investigate the variability of the MR-related properties of three different types of soy lecithin (SL-1,SL-2,SL-3). Approach: Aqueous soy lecithin solutions of different concentrations were prepared for all three soy lecithin sources and examined using DWI and Relaxometry. Results: It was found that the MR-related properties of aqueous soy lecithin solutions are dependent on the type of soy lecithin used. Impact: This work shows that MR properties of soy lecithin strongly depend on the product source. Related effects must be considered for the production of phantoms with tissue-like relaxation and diffusion properties.
Joint pre-emphasis and post-processing method for improving GIRF-based spiral trajectory correction
Authors: Li Guangqi , Li Sisi , Guo Hua
Published: November 2024

Motivation: Gradient imperfections typically cause ringing and blurring artifacts in spiral imaging. Gradient impulse response function (GIRF) characterizes the gradient system and can be applied for gradient prediction in image reconstruction. However, the low-pass characteristic of the gradient system could cause a penalty of the achieved resolution. Goal(s): This work aims to improve the GIRF-based spiral trajectory correction. Approach: A joint pre-emphasis and post-processing method was introduced to correct spiral trajectory. The effectiveness of our proposed method was tested on the phantom and in-vivo experiments. Results: The ringing and blurring artifacts were further mitigated using our proposed method. Impact: A joint pre-emphasis and post-processing correction strategy was proposed in this study. The results of phantom and in-vivo experiments indicate that our proposed method yields good image quality and effectively reduces the loss of the actual resolution.