bluuebunny/crossref_metadata_2025 huggingface dataset:
Combined Update Using Grouped Isochromats for Fast Bloch Simulation
Authors: Takeshima Hidenori
Published: November 2024

Motivation: Computational cost of the Bloch simulation was high. Goal(s): This research aims to reduce the computational cost. Approach: A new computation method using grouped isochromats is proposed. The proposed method shared computation of the isochromats whose parameters were same for each part of gradients. The processing time of two sequences were evaluated using a phantom (consisting of approximately 4 million isochromats) with and without the proposed method. Results: The proposed method accelerated the simulation up to 7.7 times. Impact: The proposed method accelerated up to 7.7 times for simulating the Bloch equations. The proposed method shared computation of the isochromats whose parameters were same for each part of gradients.
Adjustment and Basic Imaging Sequences for the Open-Source MRI4ALL Console Using the PyPulseq and MaRCoS Libraries
Authors: Artiges Anais , Block Kai Tobias , Chen Luoyao , Craven-Brightman Lincoln , Martin Jonathan , Negnevitsky Vlad , Saimbhi Amanpreet Singh , Stockmann Jason , Sun Heng , Wiggins Roy , Zi Ruoxun , Geethanath Sairam
Published: November 2024

Motivation: Open-source imaging significantly advances MR accessibility. The construction of an open-source scanner required the development of an open-source consoleGoal(s): This work aims to develop acquisition tools to calibrate the system hardware, acquire signals in the form of 1D, 2D, and 3D images, and provide a visualization of the acquisition trajectories. Approach: Using the PyPulseq and the MaRCoS libraries, we implemented the adjustment (RF, gradients, shim), and acquisition sequences (1D, 2D, 3D) as well as a plotting tool for Cartesian trajectories. Results: The acquisition tools were run on the scanner, successfully defining calibration values, obtaining signals, and plotting trajectories. Impact: As part of the MRI4ALL Hackathon, this work integrates and advances a toolset for acquisition support, compatible with vendor-agnostic libraries like PyPylseq and MaRCoS. This demonstration contributes to the expedited construction of a standalone low-field MRI scanner in a laboratory.
A KomaMRI Phantom Extension for Integrated Dynamic Imaging
Authors: Villacorta-Aylagas Pablo , Castillo-Passi Carlos , Menchón-Lara Rosa María , Irarrázaval Pablo , Sierra-Pallares José Benito , Alberola-López Carlos
Published: November 2024

Motivation: KomaMRI is a newly released Pulseq-compatible MRI simulator. Albeit the simulator includes dynamic imaging, motion type is limited to analytical expressions. Goal(s): To provide KomaMRI with additional dynamic properties irrespective of the motion type. Approach: To expand the phantom class to account for sampled arbitrary trajectories and to interpolate spin positions at time instants needed for the simulation. The simulation kernel is valid almost “as is” and only the demagnetization of the spins leaving the volume needs to be accounted for. Results: 2D Cardiac cine with bright-blood effect, tagging and flow both with in-house and XCAT phantoms are dealt with now in KomaMRI. Impact: KomaMRI is expected to be used for designing and testing novel pulse sequences. The added capabilities provided by the extension we propose increase its potential associated by enabling the simulator to deal with any sort of motion for sequence design.
Joint q-Space Sampling Optimization and Reconstruction Framework for Accurate and Fast Diffusion Magnetic Resonance Imaging
Authors: Yang Jing , Li Cheng , Fan Wenxin , Zou Juan , Wu Ruoyou , Zheng Hairong , Wang Shanshan
Published: November 2024

Motivation: Current deep learning methods for fast dMRI signal estimation are limited in the accuracy and imaging speed. Goal(s): Our goal is to enhance the quality of signal estimation and imaging speed for dMRI, by introducing a new deep learning method. Approach: Our approach fully utilizes the information in both the diffusion gradient domain and spatial domain to design a joint sparse sampling optimization and reconstruction deep learning framework, along with a specifically designed loss function. Results: The proposed method achieved up to 15x acceleration while maintaining high estimation accuracy, increasing SSIM by 7% compared with other q-space learning approaches. Impact: The dMRI signal estimation performance of our method is promising, as it incorporates domain knowledge into the deep learning process. This approach improves the acquisition and reconstruction workflow of dMRI, benefiting clinical applicability.
Deep Learning-Driven Generation of Diffusion-Weighted Imaging for Acute Ischemic Stroke from Non-Contrast Computed Tomography
Authors: Li Zhihua , Li Mifang , Huang Zhenxing , Zhang Lingyan , Zheng Hairong , Hu Zhanli
Published: November 2024

Motivation: Noncontrast computed tomography(NCCT), commonly used for its rapidity in acute ischemic stroke(AIS) diagnosis, often fails to identify early ischemic changes, whereas MRI, despite its superior sensitivity , may introduce critical delays due to its lengthier image acquisition time. Goal(s): This study aims to investigate the feasibility of converting NCCT images of AIS patients to diffusion-weighted (DW) images using deep learning techniques. Approach: The proposed method utilizes an enhanced CycleGAN model to generate synthetic DW images from CT scans. Results: The synthetic DW images generated by our network achieved good performance with a PSNR of 28.30, an SSIM of 0.843, and an NMSE of 0.293. Impact: This work might be translated to clinical settings to help physicians make clinical decisions for patients by providing with high-quality MR images in emergency situations.
Data-Driven MRS Signal Decomposition Using Wavelet Analysis
Authors: Merkofer Julian , van de Sande Dennis , Amirrajab Sina , Nam Kyung Min , van Sloun Ruud , Bhogal Alex
Published: November 2024

Motivation: Magnetic resonance spectroscopy (MRS) is currently limited by noise, low spatial resolution, and artifacts that compromise the accuracy of metabolite quantification. Goal(s): This work aims to enhance MRS signal quality without compromising signal integrity, employing wavelet analysis for robust signal decomposition. Approach: A novel method utilizing wavelet analysis and a U-Net architecture creates masks that segment scalograms, effectively isolating individual metabolites in MRS signals. Results: The method has shown in simulations the ability to distinctly separate and characterize metabolite signals, offering a promising direction for refining MRS data analysis. Impact: Provides a data-driven method for MRS signal decomposition based on wavelet analysis that shows success in extracting metabolite and baseline information. It holds the potential for accurate characterization of nuisance signals, which could lead to improved MRS fitting.
Towards Prediction of Motion Affected Spectra for MRSI at 7T
Authors: Motyka Stanislav , Niess Eva , Strasser Bernhard , Shamaei Amir , Hingerl Lukas , Weiser Paul , Niess Fabian , Bogner Wolfgang
Published: November 2024

Motivation: Quality assessment of whole-brain MRSI spectra is usually based on post-quantification analyses, which does not reflect if the estimated metabolite concentration is true. Goal(s): Simulate effects of subject motion for the raw non-Cartesian MRSI kSpace data. Build a dataset of motion-corrupted MRSI data with a corresponding ground truth version. Train a classifier to assess the quality of MRSI data. Approach: Translations and rotations were simulated in the kSpace domain. A classifier is trained in a supervised fashion with the thresholded deviation between the motion-affected and original data as the target. Results: The classifier outperforms the CRLBs in the quality assessment of MRSI data. Impact: Simulation of subject motion effects on raw non-Cartesian kSpace MRSI data allows us to assess the quality of MRSI spectra and can lead us toward the understanding of lipid artifacts, which is the main limiting factor of MRSI.
Predicting cognitive performance at age 9 using multimodal MRI neuroimaging at age 7
Authors: Khobo Isaac , Meintjes Ernesta , Laughton Barbara , van Wyhe Kaylee , van der Kouwe Andre , Robertson Frances
Published: November 2024

Motivation: The relationship between multimodal MRI neuroimaging and future cognitive performance of children from low-socioeconomic status backgrounds remains incompletely understood. Goal(s): We aimed to predict cognitive performance at age 9 using multimodal MRI data of the same children at age 7. Approach: We implemented 10-fold cross validated support vector machines and regression modelling on a combination of structural, diffusion, and spectroscopic MRI to predict continuous scores and categories of cognitive performance. Results: We could predict whether children would fall into a poorer or better scoring category at age 9 with 76% accuracy, 81% specificity, and 72% sensitivity. Impact: We demonstrate the ability to predict overall cognitive performance at age 9 from neuroimaging 2 years earlier. This could facilitate identification of at-risk children who may benefit the most from earlier targeted interventions.
Segmentation of Multiple Sclerosis lesions using 7T multi-contrast MRI data
Authors: Petrova Anna , Dal-Bianco Assunta , Niess Eva , Krajnc Nik , Bogner Wolfgang , Grabner Günther , Rommer Paul , Motyka Stanislav
Published: November 2024

Motivation: The effective treatment of Multiple sclerosis (MS) requires reliable estimates of lesion load and hence precise lesion detection over time. However, current lesion load estimation is either qualitative or too time-consuming. Goal(s): Our study automates MS lesion segmentation by training DeepMedic for application to 7T multi-contrast MRI data of MS patients. Approach: Training with all four contrasts achieved the best results compared to Lesion Segmentation Tool (LST)—a conventional/non-deep-learning SPM-based MS lesions segmentation approach. Results: Our study highlights potential for automating MS lesion detection/segmentation for 7T multi-contrast MRI data, underscoring the importance of accurate ground truth data and high-quality databases for improved detection accuracy. Impact: The results of this research will impact the user-independent detection/segmentation of multiple sclerosis lesions, making manual assessment by clinicians obsolete and enable fully automated monitoring of lesions load as a quantitative radiological marker of disease progression.
Macromolecules from short echo time 7 Tesla brain 1HMRS as biomarkers of the Alzheimer’s disease continuum
Authors: Dell'Orco Andrea , Göschel Laura , Riemann Layla Tabea , Aydin Semiha , Ittermann Bernd , Tietze Anna , Scheel Michael , Fillmer Ariane
Published: November 2024

Motivation: To investigate the potential of macromolecule (MM) from 1HMRS as biomarkers for Alzheimer's Disease (AD). Goal(s): Enhance the MRS-only diagnostic prediction for the AD continuum by incorporating MM data. Approach: We predict the diagnosis of 143 individuals ranging from cognitively healthy to AD using only 1HMRS data, employing OPLSDA. We compare the model's performance with/without MM and validate the results with a second ML classifier. We also evaluate variable importance in classification. Results: The inclusion of MM signals improves AD diagnosis prediction when OPLSDA is used. Various MM peaks contribute to the classification. However, the transitional stage of MCI cannot be accurately classified. Impact: When combined with the appropriate method, MM signals can enhance the diagnosis of AD using MRS as a stand-alone marker, and important MM peaks belonging to the AD neurochemical fingerprint were identified.
An Alzheimer's Disease Progression Score Using Supervised Variational Autoencoders on MRI Anatomic Imaging Data
Authors: Sung Junhyoun , Shibata Dean , Chan Kwun Chuen Gary , Shui Lan , Haynor David
Published: November 2024

Motivation: Alzheimer's disease affects millions, but understanding its progression remains challenging. This study seeks to assess the severity of Alzheimer's from imaging data alone. Goal(s): To create a score that reflects how far Alzheimer's has progressed in a patient. Approach: Using brain scans and simple patient demographic information, we developed an imaging-based model that predicts the severity of Alzheimer's. Results: Our model successfully distinguishes between different stages of Alzheimer's, offering a reliable disease progression score. Impact: This work could lead to earlier detection and better tracking of Alzheimer's, informing treatment decisions and aiding in the objective development and evaluation of new therapies.
Deep learning-based estimation of future brain atrophy using baseline MRI and PET
Authors: Le Linh , Fletcher Evan , Qi Jinyi , Fan Audrey
Published: November 2024

Motivation: Prediction of brain atrophy, a key feature in Alzheimer’s Disease (AD), is critical to observe disease progression before the onset of irreversible atrophy. Goal(s): We aim to predict future cortical atrophy rates in the elderly population from baseline PET and MRI scans. Approach: We predict image-derived cortical atrophy rate as an anatomical biomarker of neurodegeneration using image-generation deep learning networks based on T1-weighted structural MRI and PET as inputs. Results: Both T1- and PET-based models can predict longitudinal atrophy maps from baseline, with greater average atrophy in AD and mild cognitive impairment compared to cognitively normal, consistent with the Tensor-Based Morphometry method. Impact: Predicting future brain atrophy from baseline imaging can show disease progression before the onset of irreversible atrophy. Early detection of cognitive impairment and Alzheimer’s Disease progression would support planning for patient care and monitoring new lifestyle interventions and pharmacological therapies.
CNN-based Automated Pipeline for Accurate Computation of Magnetic Resonance Parkinsonism’s Index Measurements
Authors: Venkategowda Punith B , Di Noto Tommaso , Corredor-Jerez Ricardo , Bodenmann Tobias , Swamy Madappa Shadakshari , Mehta Bhairav , Griffa Alessandra , Nadeau Sandrine , Allali Gilles , Chan Ling Ling , Dunet Vincent , Saini Jitender , Scheffler Max , Sinha Neelam , Maréchal Bénédicte
Published: November 2024

Motivation: Magnetic resonance parkinsonism index (MRPI) has shown promising results in differentiating progressive supranuclear palsy from idiopathic Parkinson’s disease and the Parkinson variant of multiple system atrophy (MSA-P). Goal(s): In this work, we propose a fully automated pipeline to calculate MRPI using a convolutional neural network (CNN). This can be a time-saving tool in making diagnoses in clinically ambiguous cases. Approach: Our method utilizes registration and deep learning-based segmentation techniques to extract relevant measurements from T1 weighted MRI images (T1w). Results: Experimental results demonstrated the robustness of our approach and its generalizability across different clinical settings. Impact: Automating the measurement of MRPI components with a deep learning based algorithm can help providing objective and reproducible measures. It may be beneficial for differential diagnosis of patients with Parkinsonian syndromes with significant savings in reporting time.
A Large-Scale Analysis of the Impact of Physical Exercise, BMI, and Lifestyle on Brain Age Predicted from T1-weighted MRI Scans
Authors: Lee Soojin , Garg Saurabh , Basar Saqib , Nguyen Thanh-Duc , Akbari Nasrin , Datta Madhurima , Rajendran Arun , Chodakiewitz Yosef , Niotis Kellyann , Attariwala Rajpaul , Hashemi Sam
Published: November 2024

Motivation: To study the effects of exercise, BMI and lifestyle factors on brain age. Goal(s): Developing a model for predicting brain age based on T1-weighted MRI scans. Approach: T1-weighted MRI scans of 8,770 individuals were examined. Normative brain age curves were generated with over 50,000 volumetric brain MRI scans. Results: Hypertension, type 2 diabetes, and smoking were associated with increased brain age, while exercise significantly decreased it. Pronounced effects of exercise were found in the overweight group, suggesting an increased benefit. The findings emphasize the importance of exercise in preserving brain volumes likely providing neuroprotective effects. Impact: Leveraging a brain age estimation model, we revealed protective effects of exercise on the aging brain, particularly pronounced in overweight individuals. This highlights the potential of brain age as a biomarker for monitoring and developing strategies to enhance brain health.
Graph Neural Networks Elucidating Mesial Temporal Lobe Epilepsy Through Simultaneously Acquired PET and DTI Data – A Pilot Study
Authors: Zhao Tianyun , Ying Jia , Yuan Siyu , Huang Hui , Zhang Miao , Luo Jie , Huang Chuan
Published: November 2024

Motivation: There is an urgent need to improve diagnostic accuracy and surgical outcomes for Mesial Temporal Lobe Epilepsy (MTLE) patients, particularly those with drug-resistant forms and unclear epileptogenic zones Goal(s): To explore the relation between structural connectivity and FDG PET uptake by using Graph Neural Network. Approach: Graphs were constructed based on diffusion images of the patients. A graph network was trained to predict FDG PET uptake in selected regions. Results: The graph network was able to predict FDG uptake in several regions such as thalamus, middle temporal, and entorhinal cortex. Whereas the network failed to predict uptake in some other regions. Impact: The study advances understanding of the underlying mechanisms in MTLE by illuminating the relationship between white matter structural connectivity and regional metabolic activity, which could lead to enhanced diagnostic approaches and targeted therapies.
Enhanced Solubility and Polarization of 13C-fumarate with Meglumine Allows in vivo Detection of Renal Gluconeogenesis
Authors: Huynh Mai , Erfani Zohreh , Nemri Sarah Al , Chirayil Sara , Kovacs Zoltan , Park Jae Mo
Published: November 2024

Motivation: Clinical translation of many hyperpolarized substrates, including 13C-fumarate, has been obstructed by its low solubility in water, causing rapid precipitation of the substrates after dissolution when prepared in conventional glassing solvents. Goal(s): The goal of this study was to enhance water solubility and glassing properties of fumarate. Approach: We introduced a new formulation of fumarate for DNP by using meglumine as a counterion. Results: Meglumine significantly improved the polarization performance of fumarate with excellent solubility and glassing properties and previously invisible products along gluconeogenesis were observed in rat kidneys in vivo. Impact: The solubilizing and vitrifying effect of meglumine counterion is not limited to fumarate. It is applicable to other 13C- and 15N-labeled compounds such as carboxylic acids and amino acids that have poor solubility and can form meglumine salts or adducts.
Evaluating Fetoplacental Response to Hypercapnia in Pregnant Rats: A comparison between T2* MRI and Photoacoustic Imaging
Authors: Darwish Fatimah Al , Coolen Bram , Alles Lindy , van Kammen Caren , Lely Titia , Strijkers Gustav
Published: November 2024

Motivation: T2* MRI and photoacoustic imaging (PAI) offer non-invasive oxygenation measures, but their comparative effectiveness for placental study remains untested. Goal(s): Our goal was to directly compare T2* MRI and PAI's ability and effectiveness to assess placental and fetal organ oxygenation responses under normoxic hypercapnia challenge. Approach: Using pregnant rats, the study involved sequential scans of fetoplacental units with T2* MRI and PAI under normoxic hypercapnia challenge. Results: We found discrepancies between MRI and PAI in detecting oxygenation changes. MRI displayed a marked response in placental oxygenation, not as prominently reflected in PAI measurements. Impact: T2* MRI could accurately captures fetoplacental responses to hypercapnia, outperforming photoacoustic imaging. Investigating this performance gap is essential before combining these techniques in preeclampsia and fetal growth restriction studies.
Monitoring Extracellular Oxygenation Modulation with myo-inositol tripyrophosphate using EPRI
Authors: Murley Grace , Chin Renee , Liang Xiaofei , Subasinghe Amali , Yang Euitaek , de la Cerda Jorge , Schuler William , Pagel Mark
Published: November 2024

Motivation: We showed previously that multispectral optoacoustic tomography (MSOT) measures oxygen saturation (%sO2) of intravascular hemoglobin which can indirectly evaluate the effect of a radiosensitizer, inositol tripyrophosphate (ITPP), on tumor oxygenation. Electron paramagnetic resonance imaging (EPRI) could serve as a more direct biomarker by measuring the extravascular, extracellular oxygen pressure (pO2) in pre-clinical tumor models. Goal(s): Validate prior MSOT results showing decrease in hemoglobin saturation with ITPP. Approach: Use EPRI to observe extracellular oxygenation before and after treatment with ITPP compared with vehicle control. Results: Tumors treated with ITPP demonstrated lower extracellular oxygenation compared to pretreatment levels (p = 0.003). Impact: An imaging biomarker to determine how much a radiosensitizer improves tumor pO2 would dramatically impact clinical care by potentially improving response to radiotherapy and immunotherapy. EPRI could evaluate the effect of a radiosensitizer allowing for more personalized treatment approaches.
Rapid Method for Chemical Shift Saturation Recovery (CSSR) Acquisition with 129Xe MR
Authors: Liu Xiaoling , Li Haidong , Zheng Yu , Li Hongchuang , Zhang Ming , Zhao Xiuchao , Han Yeqing , Zhou Xin
Published: November 2024

Motivation: Hyperpolarized 129Xe Chemical Shift Saturation Recovery (CSSR), commonly employed for assessing pulmonary physiological function, is time-consuming and prone to weak signals and potential errors at short exchange times. Goal(s): To accelerate the acquisition of CSSR while ensuring the precise physiological parameter extraction. Approach: Techniques of inversion recovery (IR) and look-locker (LL) were combined with conventional CSSR (refer to as IR-LL-CSSR), and the results were compared with that obtained by conventional CSSR and IR-CSSR. Results: By using the proposed method (IR-LL-CSSR), the acquisition could be accelerated for eight times, and meanwhile preserve the accuracy of the extracted physiological parameters. Impact: IR-LL-CSSR substantially accelerates CSSR acquisition with 129Xe MRS and also ensures a precise physiological parameter assessment, showing promise for improving the pulmonary assessment in clinic.
APT-CEST properties of a new biocompatible copolymer p(MPC-AE)5-5 hydrogel phantom: a preliminary study
Authors: Chow Steven Kwok Keung , Liu Tesi , Yang Chih-Tsung , Walls Angela , Nguyen Cao , Hung Chun-Jen , Withey Stephanie , Liebig Patrick , Mueller Marco , Dwyer Andrew
Published: November 2024

Motivation: Biocompatible materials with detectable APT effects are lacking for biomedical applications. Goal(s): To validate the APT properties of a new synthesised biocompatible copolymer p(MPC-AE)55 hydrogel which has potential exchange between its MPC and AE cross-linkage. Approach: An experimental phantom with variable copolymer concentration and existing egg protein model was imaged with a research application APT-CEST sequence at 3T and analysed both inline and using CEST-EVAL software. Results: APT of the new hydrogel increased accordingly with its concentration and this was validated by results for egg protein which agreed with previous work. Both analysis methods were in agreement. Impact: Understanding the properties of newly synthesized copolymer hydrogel extends its value in biomedical applications including potential for phantoms that could support translation of APT-CEST.
CEST imaging of ApoE –/– mouse brain during atherosclerosis development
Authors: Park Se Weon , Su Haoyun , Chan Kannie W.Y
Published: November 2024

Motivation: The molecular imaging and relationship between the brain and atherosclerosis are poorly understood. Goal(s): To study the brain during atherosclerosis development and the association of atherosclerosis and brain using CEST MRI. Approach: 3 months old ApoE –/– and C57BL/6 mouse brains were imaged using 3T preclinical MRI and CEST was applied, then three offsets, 3.5, –1.6 and –3.5 ppm, were extracted for post-processing. Results: ApoE –/– mouse showed higher APT and rNOE signals than WT in thalamus, hippocampus and cortex, which are associated with neuroinflammation and cholesterol deposition during atherosclerosis development. Impact: The underlying molecular changes of the brain during atherosclerosis development could enhance the identification of diseases at early stage using CEST MRI.
Assessment of Lipid Levels in Newly Diagnosed Diabetic Obese Patients Treated with GLP-1 Inhibitors Using MRI-PDFF
Authors: Zhao Yufei , Wang Xiaoyuan , Zhang Mengluan , Lv Yingqi , Li Ling , Peng Xingui
Published: November 2024

Motivation: GLP-1 receptor agonists have shown favorable effects in improving obesity and ectopic fat deposition in type 2 diabetes patients. MRI-PDFF can serve as a tool for continuous, dynamic assessment of lipid content changes in patients. Goal(s): Dynamic monitoring of fat content and lipid deposition changes in type 2 diabetes obese patients receiving glucagon-like peptide-1 receptor agonist treatment using MRI-PDFF. Approach: 21 male diabetic patients received 3-month treatment: semaglutide (n=12) or loxenatide (n=9). Clinical data collected, pre/post 3.0T MRI scans (T1WI, T2WI, MRI-PDFF) measured fat. Results: The semaglutide group showed significant fat reduction in multiple organs, while the loxenatide group reduced pancreatic fat fraction. Impact: Semaglutide effectively controls blood glucose and body weight in type 2 diabetes obese patients. It also significantly reduces SAT and VAT while alleviating ectopic fat deposition. MRI-PDFF represents a non-invasive tool for continuous assessment of lipid content changes following treatment.
Evaluating Glucose Dysfunction using Hepatic Quantitative Susceptibility Mapping in Patients with Type 2 Diabetes Mellitus
Authors: GONG Liya , GAO Mingxuan , WEN Junyan , CUI Wei , LIN Xuecong , LI Zhujia , LUO Jingwen , GUO Ying , WEN Ge
Published: November 2024

Motivation: The hepatic iron deposition in Type 2 Diabetes Mellitus (T2DM) patients could affect insulin resistance and glucose production. The R2*-based method for measuring iron content can be affected by factors like fat tissue and background magnetic fields. Goal(s): the study employed QSM method, which is insensitivity to the above confounder, to evaluate glucose dysfunction in T2DM. Approach: Hepatic R2* and QSM values were measured in 11 T2DM patients, and were correlated with glucose tolerance. Results: A negative correlation between QSM values and the insulin β-cells dysfunction was found, whereas R2* values did not show any significant correlation. Impact: Hepatic Quantitative Susceptibility Mapping may serve as a predictor of glucose metabolism dysfunction in patients with Type 2 Diabetes Mellitus and has shown to be more effective than hepatic R2* for this purpose.
3D vector MR elastography (MRE) assessed tissue heterogeneity increases with chronic liver disease progression
Authors: Wu Hao , Zhu Zheng , Li Jiahui , Qiu Caixin , Yaqoob Usman , Shah Vijay , Ehman Richard , Yin Meng
Published: November 2024

Motivation: Hepatic fibrosis, despite traditionally viewed as a diffuse occurrence, has been shown to vary spatially with disease progression. Goal(s): MR elastography (MRE) measures mechanical properties and their spatial variations can potentially provide holistic insights into tissue inhomogeneity. Approach: Twenty-five rats based a metabolic dysfunction associated steatotic liver disease (MASLD) model monthly underwent MRE to investigate tissue inhomogeneity during cirrhosis development. Results: Results demonstrated increases in both microscopic and macroscopic inhomogeneities with disease progression. In cirrhotic livers, while mean MRE measurements correlated subtly with histological fibrosis and portal pressure, tissue heterogeneity presented stronger associations. Liver tissue heterogeneity is a complementary predictor of disease progression. Impact: Assessing liver tissue heterogeneity via 3D vector MR elastography could enhance disease progression monitoring in chronic liver diseases and potentially predict clinically significant outcomes, offering a more comprehensive diagnostic approach than traditional mean liver stiffness and loss modulus measurements alone.
Repeatability and Reproducibility of Pancreatic Proton Density Fat Fraction Measurements Using Manually Drawn Regions of Interest
Authors: Castellanos Edgar , Du Kelly , Alba Diana , Hunt Peter , Koliwad Suneil , Noworolski Susan
Published: November 2024

Motivation: Determination of repeatability and reproducibility is vital to interpreting and determining measurable change of intra organ fat, specifically in small organs like the pancreas. Goal(s): The goal of this study is to determine if intra-user repeatability and inter-user reproducibility coefficients of manually drawn ROIs on pancreatic fat. Approach: The approach of this study was to compare manually drawn ROIs within the pancreas between two users and within a single user. Results: Results indicate that repeatability and inter-user reproducibility of manually drawn ROIs to determine the MRI measured pancreatic fat fraction were consistent within and across users. Impact: The repeatability and inter-user reproducibility of manually drawn ROIs to determine the MRI measured pancreatic fat fraction yielded consistent measures both within and across users.
PDFF diagnoses MASH in patients with severe obesity but without known liver disease
Authors: Panagiotopoulos Nikolaos , Agni Rashmi , Batakis Danielle , Ceriani Lael , Covarrubias Yesenia , Funk Luke , Grunvald Eduardo , Goodman James , Harris David , Hamilton Gavin , Horgan Santiago , Jacobsen Garth , Lidor Anne , Middleton Michael , Oechtering Thekla , Sappenfield Ryan , Tamada Daiki , Wolfson Tanya , Sirlin Claude , Reeder Scott
Published: November 2024

Motivation: To address the pressing need for non-invasive diagnosis of metabolic dysfunction-associated steatohepatitis (MASH). Goal(s): To evaluate the potential of proton-density fat-fraction (PDFF), corrected T1 (cT1), liver enzymes, and fibrosis scores to assist in the diagnosis of MASH. Approach: The study included study participants with obesity and at risk for MASH, undergoing bariatric surgery with intraoperative liver biopsy. Potential predictors and predictor combinations were evaluated as classifiers for MASH and steatosis. Results: PDFF distinguished MASH from non-MASH (AUC=0.85; 95%CI 0.79-0.91, p<0.0001). A cutoff of PDFF≥13.9% detected MASH with 90% specificity and 59% sensitivity. Neither cT1, liver enzymes, nor fibrosis scores significantly improved diagnostic performance. Impact: Our results suggest that PDFF alone may be sufficient for non-invasive detection of metabolic dysfunction-associated steatohepatitis (MASH). This novel use case for an established method has the potential to transform the diagnostic approach to MASH which currently necessitates invasive biopsy.
Performance of non-invasive biomarkers in identifying patients with at-risk metabolic dysfunction-associated steatohepatitis
Authors: Li Jiahui , Allen Alina , Mounajjed Taofic , Graham Rondell , Glaser Kevin , Manduca Armando , Venkatesh Sudhakar , Sirlin Claude , Shah Vijay , Ehman Richard , Loomba Rohit , Yin Meng
Published: November 2024

Motivation: MRE-assessed liver stiffness, MRI-derived fat fraction, AST, and FIB-4 are promising predictors for identifying at-risk MASH, which is defined as MASH with fibrosis stage 2 or higher. Some investigators have also proposed an additional criterion, NAS ≥ 4 with at least 1 point in each category. Goal(s): Assess prediction models for diagnostic accuracy in identifying at-risk MASH under both definitions. Approach: AUC and its 95% confidence intervals were used to assess the overall diagnostic accuracy. Results: The additional criterion influenced the performance of prediction models, but liver stiffness remains the most reliable single predictor among non-invasive biomarkers. Impact: At-risk MASH is defined as a MASH diagnosis with fibrosis stage ≥2. Adding a criterion of NAS≥4 with ≥1 point in each category impacts diagnostic accuracy but liver stiffness remains the most reliable single predictor.
Unified Shimming and RF coil (UNIC) Reduces Susceptibility Artifacts in Prostate DWI in Subjects with Metallic Hip Prosthesis at 3T
Authors: Long Ziyang , Malagi Archana , Serry Fardad Michael , Huang Liting , Albatany Mohammed , Zepeda Jeremy , Ma Lingceng , Yang Chia-Chi , Wang Lixia , Binesh Nader , Shan Yujie , Li Debiao , Yang Hsin-Jung , Han Hui
Published: November 2024

Motivation: Metallic implants in the body may cause severe image artifacts. Goal(s): To improve prostate DWI imaging in patients with metallic hip replacement using a novel B0 local shimming system. Approach: Unified Shimming and RF coil (UNIC) arrays were used to improve local B0 shimming. Improved DWI image quality was assessed at 3T MRI on subjects with hip prostheses. Results: UNIC arrays significantly improved B0 homogeneity and reduced DWI distortions in prostate, resulting in improved Dice and Jaccard coefficients. Impact: UNIC coil arrays can enable 3T prostate DWI MRI for patients with metallic hip implants and provide the necessary care for the fast-growing population.
Assessing Pulmonary Function: A Comparative Study at 0.55T and 1.5T
Authors: Wang Rui , Ma Qifan , Liu Mengxiao , Song Yang , Grimm Robert , Andreas Voskrebenzev , Jens Vogel-Claussen , Yuan Ying , Tao Xiaofeng
Published: November 2024

Motivation: The motivation for this study is to develop a non-invasive imaging technique for assessing pulmonary function without the need for ionizing radiation or potentially harmful contrast agents. Goal(s): To evaluate the impact of different magnetic field strengths (0.55T and 1.5T) on functional parameters derived from the PREFUL MRI technique. Approach: The study analyzed the data with MRLung software and conducting statistical comparisons to assess the differences in functional parameters, SNR, and CNR between the two field strengths. Results: VDP, mean perfusion, and mean ventilation exhibited significant changes at the lower field strength, with higher SNR at 0.55T compared to 1.5T. Impact: We demonstrate the potential of using a lower field strength (0.55T) MRI system for assessing pulmonary function, offering insights into the impact of field strength on functional parameters and quality, which may have implications for improving non-invasive pulmonary imaging methods.
Functional lung imaging with ultrashort echo times achieved by half pulses
Authors: Slawig Anne , Weng Andreas , Köstler Herbert
Published: November 2024

Motivation: While ventilation and perfusion mapping in lung can be realized by Cartesian imaging, low signal intensities, due to rapid relaxation, remain challenging and ultrashort echo times might improve robustness. Currently, the promising approach of half pulse excitation for 2D-UTE imaging was not yet employed for functional lung imaging. Goal(s): To evaluate the suitability of half pulse excitation for functional lung imaging. Approach: Functional lung imaging was performed in a healthy volunteer by radial acquisitions after sinc or half pulse excitation. Results: Complex sum of two half pulse acquisitions provides morphological depiction of lung tissue and ventilation maps, but no information on lung perfusion. Impact: The use of half pulses for functional lung imaging did not provide an improvement, as no information on perfusion can be gained. Therefore, other approaches are necessary to improve robustness in the detection of pathologies characterized by ventilation-perfusion mismatches.
Validation of mDixonQuant and IntelliSpace Portal for Liver Iron Estimation
Authors: Doyle Eamon , Peeters Johannes , Rodrigues Pedro , Wood John
Published: November 2024

Motivation: Simultaneous estimation of fat, water, and iron concentrations by MRI are now available on all three major MRI vendors, but the predicted liver iron concentration (LIC) values are sparsely validated. Goal(s): To cross validate LIC estimates generated by Philips mDixonQuant and IntelliSpace Portal (ISP) against LIC values measured by biopsy-validated, reference R2* and R2 methodsApproach: 51 subjects underwent MRI for clinical purposes, with collection of mDixonQuant, standard multiple-echo gradient echo, and Ferriscan R2 images. Results: R2* values generated by the default mDixonQuant and ISP packages yielded accurate LIC estimates using the Garbowski calibration for LIC < 25 mg/g. Impact: This work allows mDixonQuant and ISP to be used with confidence in the clinical setting to quantify liver siderosis in most subjects referred for iron quantification.
Retrospective Multisite Multisoftware Analysis of Intravoxel Incoherent Motion (IVIM) Breast MRI
Authors: Basukala Dibash , Mikheev Artem , Gilani Nima , Moy Linda , Pinker Katja , Partridge Savannah , Biswas Debosmita , Iima Mami , Bathen Tone , Thakur Sunitha , Sigmund Eric
Published: November 2024

Motivation: Intravoxel incoherent motion (IVIM) MRI is helpful in breast tumor characterization, but variable performance exists in the literature. Goal(s): Translational assessment of multisite breast lesion data based on the 1st order radiomics features from each IVIM parameters perfusion fraction (fp), pseudodiffusivity (Dp) and tissue diffusivity (Dt) derived from multiple software platforms. Approach: This work used retrospective anonymized breast MRI data from three sites employing three different software to estimate the 1st order radiomics of fp, Dp and Dt, their software robustness, and diagnostic utility. Results: Dtmean, Dtminimum, and fpmean showed robustness across site/software; and Dtmean, Dtminimum showed highest and most consistent diagnostic utility. Impact: Multiple 1st order radiomics features of tissue diffusivity (Dt) or perfusion fraction (fp) obtained from a heterogeneous multi-site dataset showed software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective trials.
Renal MRI Assessment of the Effects of High-Water Intake on Total Kidney Volume Growth in ADPKD
Authors: Dev Hreedi , Zhu Chenglin , Barash Irina , He Xinzi , Blumenfeld Jon , Prince Martin
Published: November 2024

Motivation: By measuring height-adjusted total kidney volume (ht-TKV), renal MRI monitors autosomal dominant polycystic kidney disease (ADPKD) progression and evaluates therapeutic interventions’ efficacy for slowing cyst growth. Goal(s): Since arginine vasopressin (AVP) stimulates cyst growth, reducing vasopressin with high-water intake (HWI) may slow ADPKD progression. Approach: We test this hypothesis using a case-crossover study with 7 ADPKD subjects, measuring ht-TKV changes on MRI during usual and high-water intake. Results: High-water intake decreased 24-hour urine osmolality (359 vs 202mOsm/kg, p=0.002) and rate of increase in annualized ht-TKV growth rate (7.1% vs 3.5%, p=0.003), suggesting that high-water intake can slow ADPKD progression. Impact: Decreasing the rate of ht-TKV increase, measured by renal MRI during high water intake, suggests this as a potential treatment to slow progression of ADPKD, forestalling end-stage kidney failure requiring dialysis or transplantation.
Dual-Venc 5D flow MRI for Increased Velocity Dynamic Range: An in vivo Validation Study
Authors: Weiss Elizabeth , Baraboo Justin , Ma Liliana , Falcão Mariana , Roy Christopher , Stuber Matthias , Markl Michael
Published: November 2024

Motivation: Single-venc 5D flow is useful for measuring the impact of respiration on hemodynamics, however, its single velocity encoding sensitivity (venc) limit its utility in congenital heart disease patients where both venous and arterial measurements are clinically necessary. Goal(s): We aimed to validate respiratory-resolved dual-venc 5D flow measurements in vivo. Approach: Nine healthy volunteers underwent CMR studies including dual-venc 5D flow, single-venc 5D flow, and 4D flow. Net flow and peak flow were compared. Results: We found good agreement of net flow and peak flow with both 4D flow and single-venc 5D flow MRI, with an 85% increase in velocity-to-noise ratio. Impact: Dual-venc 5D flow increases velocity-to-noise ratio by 85% compared to single-venc 5D flow with good agreement in respiratory-resolved flow measurements. The method may improve simultaneous measurement of venous and arterial flows, which is often necessary in congenital heart disease patients.
A Multi-Directional 4D PCMR Flow Phantom: Design and Experiments
Authors: Wang Kezhou , Otey Taylor , Luo Qingfei , Karaman Muge , Bhuiyan Enamul , Dan Guangyu , Ostergren Lauren , Charbel Fady , Zhou Xiaohong
Published: November 2024

Motivation: Accurate blood flow measurement is vital for the diagnosis of cardiovascular disorders. Existing phantoms focus primarily on validating flow using phase-contrast MR (PCMR) techniques along the three orthogonal directions. No phantom has been reported for the validation of flow in non-orthogonal orientations. Goal(s): To validate flow quantification accuracy on a phantom in non-orthogonal directions using 4D flow MRI. Approach: A multi-directional plexiglass phantom was designed and fabricated to evaluate accuracy of 4D flow PCMR using blood-mimicking flows within tubing controlled by a programmable pump. Results: The phantom was successfully used to validate flow in orthogonal and non-orthogonal directions simultaneously with 4D flow MRI. Impact: The flow phantom can be used to validate flow in 5 directions simultaneously with 4D flow MRI. The phantom has the potential to be used to optimize and standardize the 4D flow MR protocol parameters for clinical applications.
Evaluation of blood flow energy loss before and after endovascular aneurysm repair using 4D Flow MRI
Authors: Ikeda Shimpei , Mine Takahiko , Sekine Tetsuro , Abe Masashi , Happoh Seigoh , Mizushima Shohei , Kawase Yasuhiro , Fujii Masahiro , Hayashi Hiromitsu , Kumita Shin-ichiro
Published: November 2024

Motivation: To survey blood flow alteration after EVAR using 4D Flow MRI. Goal(s): To reveal how the degree of energy loss occur, and how interact with other parameters. Approach: Velocity, volume, reflux ratio, and degree of energy loss at proximal and within the treatment segment were analyzed. Each value gained pre and post EVAR were statistically compared, and the relation between energy loss and pulse wave velocity were evaluated. Results: After EVAR, the antegrade velocity and the volume increased at the aneurysmal orifice level, and the degree of energy loss through the treatment segment increased. Impact: EVAR facilitates aortic stiffness and increases the antegrade velocity and volume at treatment area. These alterations were considered as the main factors promoting further energy loss, which may concern with cardiac afterload.
Wall Shear Stress Measured with 4D Flow MRI Correlates with Biomarkers of Inflammation and Collagen Synthesis in Aortic Dilation
Authors: Hammaréus Filip , Trenti Chiara , Björck Hanna , Engvall Jan , Eriksson Per , Lekedal Hanna , Lundberg Anna , Swahn Eva , Jonasson Lena , Nilsson Lennart , Dyverfeldt Petter
Published: November 2024

Motivation: Hemodynamics and circulating biomarkers could offer urgently needed improved risk-stratification in individuals with aortic dilation. Goal(s): To explore correlations between hemodynamics markers measured with 4D Flow MRI and circulating biomarkers in aortic dilation individuals with tricuspid aortic valves. Approach: Wall shear stress (WSS) parameters were assessed from 4D flow MRI in cases with dilation and controls. Blood plasma samples were used to quantify the inflammation biomarker IL-6 and several extracellular matrix biomarkers including collagen type I α1 chain (COL1α1). Results: IL-6 correlated to time-averaged WSS (r=0.54, p<0.001), whereas COL1α1 correlated to the oscillatory shear index (r=0.61, p<0.001). Impact: The observed correlations between 4D Flow MRI-derived wall shear stress and circulating biomarkers of inflammation and collagen synthesis raises the intriguing possibility that altered aortic hemodynamics causes biomarker leakage from the aortic tissue into the circulation.
Preliminary 4D-Flow cardiac MRI assessment of ascending aorta in patients with sigmoid hypertrophic cardiomyopathy
Authors: Negm Ahmed , Cano Tomas Gonzalez , Halverson Maria , Iverson Holly , Magnuson Jessica , McGee Kiaran , Leiner Tim , Bratt Alexander , Foley Thomas , Rajiah Prabhakar , Collins Jeremy , Francois Christopher
Published: November 2024

Motivation: To establish accurate measures in predicting prognosis in patients with sigmoid HCM from their 4D-flow-derived hemodynamics. Goal(s): We explored the association between aortic stiffness and sigmoid HCM through measuring peak wall shear stress in the three ascending aorta segments: proximal, mid, and descending. Approach: We recruited 40 subjects and divided them into control and affected groups and then compared ascending aorta 4D flow hemodynamics. Results: Maximum diameters and peak flow velocity of ascending aorta were higher in the affected group. Impact: Assessing aortic hemodynamics with 4D Flow CMR in patients with hypertrophic cardiomyopathy will help us understand the relationship between aortic stiffness and left ventricular hypertrophy, which is associated with outcomes in hypertrophic cardiomyopathy patients.
Comparison of multi-excitation and multi-frequency MR elastography to estimate anisotropic mechanical properties of the human brain.
Authors: Caban-Rivera Diego , Van Houten Elijah , McGarry Matthew , Williams Lance , Diano Alexa , Bayly Phil , Paulsen Keith , Johnson Curtis
Published: November 2024

Motivation: MR elastography can estimate anisotropic mechanical properties of fibrous white matter, traditionally using multi-excitation approaches. Multi-frequency elastography from a single driver is more common and could expand measurements of anisotropy. Goal(s): Our goal was to compare mechanical anisotropy from multi-frequency and multi-excitation reconstructions. Approach: Transversely isotropic parameters were reconstructed using simulated and in vivo multi-frequency wave data, then compared between approaches and against ground truth maps. Adolescent and adult measurements were compared in white matter regions. Results: Multi-frequency elastography performed comparably with the multi-excitation approach in simulations. Higher shear anisotropy was observed in adults compared to adolescents, with no differences in tensile anisotropy. Impact: This study demonstrates that multi-frequency magnetic resonance elastography can reliably estimate anisotropic mechanical properties from single driver data, enabling broader application. Quantifying developmental changes in anisotropy of white matter provides new insights into brain mechanics during maturation.
Impact of Oral Contrast Agents on Terminal Ileum Viscoelastic Properties Assessed by MR Enterography and MR Elastography
Authors: Reiter Rolf , Loch Florian , Siegmund Britta , Kühl Anja , Neumann Gero-Mathias , Hamm Bernd , Braun Jürgen , Sack Ingolf , Ro Sa-Ra
Published: November 2024

Motivation: Although the feasibility of intestinal MR elastography has recently been demonstrated, the influence of bowel distension through oral contrast agents on gut viscoelastic properties remains elusive. Goal(s): To investigate the influence of oral contrast agent-based bowel distension on the viscoelastic properties of the gut in healthy volunteers. Approach: Healthy volunteers were scanned using MR enterography and MR elastography before and after the ingestion of 1000 ml of 2 % mannitol solution as oral contrast agent. Results: Our results suggest that the bowel distension in MR enterography has no systematic impact on viscoelastic tissue properties of the terminal ileum. Impact: This study suggests that bowel distension in MR enterography has no systematic impact on the assessment of viscoelastic tissue properties of the terminal ileum. Consequently, future studies investigating inflammatory bowel disease using intestinal MR elastography do not need to account for potential biases related to pre-stretched bowel walls after oral ingestion of contrast agents.