bluuebunny/crossref_metadata_2025 huggingface dataset:
An open-source platform for image simulation, denoising, and super-resolution for point-of-care MRI devices
Authors: Mach Mathieu , Webb Andrew
Published: November 2024

Motivation: Low-field MRI is increasingly being applied in lower- and middle-income countries, but due to limited resources, training is scare. Goal(s): Provide an open-source plateform for simulation, teaching, and a denoising and super-resolution pieline of low-field MRI images. Approach: Using 3D maps of relaxation times, proton density, B0 and low-field system-specific parameters, such as limited gradient linearity, simulation of low-field images are created. Application of bm4d denoising and AI super-resolution on low-field images is additionally proposed. Results: We provide an open-source graphical interface that can simulate and generate multiple sequences of low-field MRI, and a denoised and super-resolution pipeline increasing low-field image enhancement. Impact: This study provides a simple open-source python platform to simulate point-of-care low-field MRI images, reflecting specific system-specific parameters for teaching purposes, and a fast advanced denoising and AI-based super-resolution pipeline for low-field images.
QRadAR: A Toolbox for Quantitative Magnetic Resonance Radiomics Analysis and Reliability
Authors: Roberts Alexandra , Zhang Jinwei , Romano Dominick , Akkus Sema , Kopell Brian , Spincemaille Pascal , Wang Yi
Published: November 2024

Motivation: Radiomic feature robustness as an input to a downstream model is an important consideration for model reliability. Generating a subset of robust, reproducible, and repeatable features is an important step in determining predictive or indicative features. Goal(s): To provide a framework for radiomics robustness, repeatability, and reproducibility. Approach: A Python implementation using the pyradiomics, scikit-learn, numpy, and other open-source library is provided as tool to quickly summarize the radiomic features surviving differing sampling, time point, or field strength acquisitions. Results: The QRadAR Toolbox provides researchers and clinicians with a collection of reliable features for downstream model input. Impact: The QRadAR Toolbox provides researchers and clinicians with a collection of reliable features for downstream model input by providing a providing Python a framework for radiomics robustness, repeatability, and reproducibility.
A Novel Pipeline to Automatically Harness Log File Data for Enhanced MRI Parameter Analysis, Patient Care and Radiology Utilisation
Authors: Lally Oscar , Buckley Molly , Gabriel Elizabeth , Jackson Laurence , Price Anthony , Shah Simon
Published: November 2024

Motivation: A deeper understanding of how information in log files can contribute to service improvement, for example reducing patient backlog and improving patient safety. Goal(s): To construct an automated data pipeline that analyses and processes log files, returning quantitative results and graphical visualisations that can be interpreted in a clinically useful way. Approach: We obtained log files from our scanner fleet and constructed a Python codebase to read, analyse and interpret data pertaining to time utilisation and patient exposure. Results: We have demonstrated the code’s capability to provide detailed exposure monitoring as well as insights into how productively we use time on our scanners. Impact: Our work will help us to optimise the patient pathway, improve patient safety and investigate how more obscure parameters can affect our service delivery. Our code will be open source, enabling others to benefit and contribute, improving services more widely.
CHEAP and SLOW: a comprehensive acquisition protocol for downfield, upfield, and spectral editing 1H-MRSI at 7T
Authors: Weng Guodong , Radojewski Piotr , Slotboom Johannes
Published: November 2024

Motivation: Integration of downfield, upfield, and spectral editing MRSI in clinical studiesGoal(s): Generate high resolution downfield (0.37 ml) and upfield (0.2 ml) in vivo MRSI at 7TApproach: CHEAP-ESPI and SLOW-EPSI were used for downfield and upfield (spectral editing) MRSI, respectively, in two healthy volunteers and one glioma patient. Results: A 4-minute acquisition with CHEAP-EPSI suffices for downfield MRSI (ATP/GSH+ and NAA+), while a 9-minute acquisition with SLOW-EPSI is adequate for upfield (NAA) and spectral editing (2HG, GABA, and Glx) MRSI. Impact: The combination of CHEAP-EPSI and SLOW-EPSI enables the measurement of downfield, upfield, and edited 3D MRSI within approximately 13 minutes, making it readily integrable into clinical routine examinations or scientific studies.
Assessment of Radiomic Features of Metabolism in Advanced Prostate Cancer using Hyperpolarized 13C MRI with Whole Abdominopelvic Coverage
Authors: Chen Hsin-Yu , de Kouchkovsky Ivan , Bok Robert , Ohliger Michael , Wang Zhen , Gebrezgiabhier Daniel , Nickles Tanner , Carvajal Lucas , Gordon Jeremy , Larson Peder , Kurhanewicz John , Aggarwal Rahul , Vigneron Daniel
Published: November 2024

Motivation: Hyperpolarized (HP) 13C-pyruvate MRI can address limitations of PSMA-PET for monitoring therapy and evaluating treatment-emergent, lethal subtypes of prostate cancer. Goal(s): To establish and characterize a novel radiomics framework of tumor metabolism in advanced prostate cancer based on whole abdominopelvic HP MRI. Approach: We extracted 316 metabolic features from 16 patients. Following feature selection and classification, their prognostic values were evaluated using uni- and multivariate survival analyses. Results: Metabolic feature kPL,median (pyruvate-to-lactate conversion rate) significantly predicted both progression-free (p<0.01) and overall (p<0.05) survivals with longer median PFS (11.2 vs 0.5 months) and OS (NR vs 18.4 months) in the lower- vs higher-kPL subgroups. Impact: A novel radiomics framework based on whole abdominopelvic hyperpolarized 13C-pyruvate MRI extracted and evaluated 316 metabolic features of advanced prostate cancer. Selected features significantly predicted clinical outcome measures (PFS and OS), strongly supporting further investigation of their prognostic values.
Clinically Significant Prostate Cancer Following Negative Biopsies for PIRADS 4 and 5 Lesions: A Multicenter Study
Authors: Nguyen Evie , Banerjee Imon , Nadella Meghana , Varner Jacob , Takashashi Naoki , LeGout Jordan , Stanton Melissa , Frendl Daniel , Abdul-Mush Haider , Tan Nelly
Published: November 2024

Motivation: To understand the risk of clinically significant prostate cancer (csPCa) in patients with negative biopsies for PIRADS categories 4 and 5 lesions, addressing a critical gap in clinical decision-making following discordant prostate MRI-biopsy findings. Goal(s): To determine the prevalence of csPCa among patients with negative biopsy for PIRADS 4 or 5 lesions. Approach: A multicenter retrospective study, utilizing Natural Language Processing (NLP) to analyze patient demographics, clinical, imaging and pathologic outcomes, followed by statistical analyses. Results: In 44% patients was found to have csPCa after initial discordant prostate MRI- biopsy. Impact: This study underscores the high risk of csPCa in patients with initial negative biopsies for PIRADS 4 or 5 lesions, potentially guiding clinicians in patient management and informing follow-up strategies.
Automatic planning of T2-weighted fetal scans at 0.55T using fetal brain landmark detection
Authors: Silva Sara Neves , Verdera Jordina Aviles , McElroy Sarah , Colford Kathleen , Cleri Michela , Ozenne Valéry , Hall Megan , Story Lisa , Rutherford Mary , Pushparajah Kuberan , Hajnal Jo , Hutter Jana
Published: November 2024

Motivation: Fetal MRI plays an important role in clinical and research settings. The variability of the fetal position and extensive fetal motion, however, create challenges limiting the use of fetal MRI mainly to specialist centres. Goal(s): Real-time fully automatic planning of true radiological fetal brain planes for anatomical TSE scans. Approach: Deep-learning based detection of key landmarks in the fetal brain on a whole-uterus EPI scan enables the subsequent automatic calculation of the radiological plane for the TSE scan. Results: Prospective results on three fetal MRI scans on a clinical low-field 0.55T MRI scanner illustrate the ability of the framework to perform diagnostic planning. Impact: Fully automated planning of radiological planes for low-field fetal MRI demonstrates time efficiency and carries the potential to significantly widen accessibility to fetal MRI beyond specialist centres.
Ex-vivo 4D Flow MRI for Evaluation of Aortic Valve Pathologies in a Mock Circulatory System
Authors: Gober Leah , Rice James , Stellon Michael , Roldán-Alzate Alejandro
Published: November 2024

Motivation: The Ross Procedure is a complex cardiac surgery that utilizes the pulmonary valve to replace a diseased aortic valve. More work is needed to improve preoperative candidacy. Goal(s): To develop and validate an ex-vivo model of the aortic valve in combination with a mock circulatory system. Approach: The left ventricle was mounted on a circulatory loop with preservation of aortic valve anatomy and application of hemodynamic flow to assess valve characteristics. Results: A successful system was built and 4D Flow MRI performed with resultant functional quantification and representative curves mimicking ventricular inflow and aortic outflow. Impact: 4D Flow MRI, in combination with an ex-vivo left ventricular mock circulatory system, provides a method to study aortic flow and assess valvular abnormalities or preoperative candidacy in cardiac surgery.
Accelerated Free-Breathing Liver Fat/R2* Quantification in Pediatrics Using XD-GRASP Multi-Echo Stack-of-Radial MRI: A Retrospective Study
Authors: Zhong Xiaodong , Tipirneni-Sajja Aaryani , Nickel Marcel , Morin Cara , Abramson Zachary , Han Fei , Deshpande Vibhas , Kannengiesser Stephan
Published: November 2024

Motivation: Free-breathing liver fat and iron quantification is of growing interest in pediatric patients. However, motion compensation is necessary for quantification accuracy, resulting in prolonged acquisition times. Goal(s): This study was to retrospectively evaluate a newly developed technique with XD-GRASP reconstruction in pediatric patients. Approach: Data with oversampled k-space radial views were undersampled to fewer radial views. All data were reconstructed and compared between a self-gating method and the proposed XD-GRASP method. Results: When applied to data with undersampled radial views, the proposed XD-GRASP method reduced image artifacts and improved PDFF and R2* results compared to the self-gating method. Impact: The proposed multi-echo stack-of-radial MRI method using motion-resolved reconstruction and multi-dimensional regularization may allow accelerated free-breathing liver PDFF and R2* mapping in pediatric patients.
Feasibility of MRI-based lung tissue mechanics computational models of the paediatric lung
Authors: Soo Megan , Kumar Haribalan , Cornfeld Daniel , Condron Paul , Emsden Taylor , Potter Leigh , Holdsworth Samantha , Tawhai Merryn , Chan Ho-Fung
Published: November 2024

Motivation: There is a scarcity of personalised computational physiology models of the paediatric lung because most models have previously been derived for the adult lung from CT images. Goal(s): We aim to derive personalised computational models of the paediatric lung from novel structure-function lung MRI techniques. Approach: In this feasibility study, lung ZTE MR images from healthy children were used to create finite element soft tissue deformation mechanics models. Results: Simulations of regional supine lung tissue densities were shown to be similar to lung ZTE MRI densities, demonstrating the strong potential for developing computational paediatric lung models from MR images. Impact: A computational physiology model of soft tissue deformation was created from lung ZTE MR images of healthy children, demonstrating the potential of using novel regional lung structure-function information for personalised paediatric computational models.
Evaluation of MR Elastography-Based Biomarkers for Detecting Skull-Brain Interface Decoupling Changes in Response to Repetitive Head Impacts
Authors: Shan Xiang , Murphy Matthew , Sui Yi , Zheng Keni , Hojo Emi , Manduca Armando , Ehman Richard , Huston John , Yin Ziying
Published: November 2024

Motivation: The growing concern about subconcussive, repetitive head impacts (RHI) has prompted the need for non-invasive RHI detection methods. Goal(s): To understand if there are alterations of the skull-brain interface due to RHI exposure and explore potential imaging biomarkers for characterizing RHI. Approach: Four MR Elastography (MRE)-based parameters were compared between RHI(-) and RHI(+) groups, encompassing assessment of cortical stiffness, capabilities of motion dampening, and strain mediation at the skull-brain interface. Results: Our findings revealed increased cortical stiffness, rotational transmission ratio, and adjusted NOSS in individuals with high RHI exposure, suggesting a degeneration of the skull-brain interface decoupling performance. Impact: This study sheds light on RHI-induced changes at the skull-brain interface, proposing three potential non-invasive biomarkers for monitoring such alterations. These findings hold promise for aiding medical professionals in identifying individuals at high RHI exposure risk.
Whole cord diffusion imaging of post-mortem human spinal cord injury reveals extent and potential timeline of axonal swelling and degeneration
Authors: Lesack Nikolai , Morris Sarah , Swift-LaPointe Taylor , Yung Andrew , Prevost Valentin , George Shana , Bauman Andrew , Kozlowski Piotr , Samadi Farah , Fournier Caron , Parker Lisa , Dong Kevin , Streijger Femke , Moore G.R. Wayne , Velenosi Adam , Hirsch-Reinshagen Veronica , Kwon Brian , Laule Cornelia
Published: November 2024

Motivation: Following spinal cord injury (SCI) changes in tissue microstructure occur throughout the length of the cord which are not detectable with conventional MRI. Goal(s): To characterize whole cord diffusion MRI metrics in human SCI post-mortem tissue, including the effect of injury-to-death interval on diffusion MRI metrics. Approach: Two full-length spinal cords were imaged at 7T. DTI and ActiveAx metrics were extracted from white matter tracts. Results: Changes in fractional anisotropy, axon density, and axon diameter were observed downstream of the injury epicentre in the case with a longer injury-to-death interval. Transience in diffusion metrics may indicate the extent of axonal degeneration and swelling. Impact: Diffusion MRI may be a useful tool in understanding the extent and progression of spinal cord injury. Insight into axonal swelling and degeneration following spinal cord injury could aid clinicians in predicting patient prognosis.
Predicting flow velocity from fMRI inflow signals using physics-informed deep learning
Authors: Ashenagar Baarbod , Lewis Laura
Published: November 2024

Motivation: fMRI has been used to measure large scale cerebrospinal fluid (CSF) flow dynamics with high sensitivity and temporal resolution, however the measured signal is not quantitative. Goal(s): Our goal is to develop a physics-based neural network framework for flow quantification directly from fMRI flow-enhanced signals. Approach: We designed a neural network that can use fMRI data as input to predict flow velocity. We then trained the model on a simulated dataset generated using a physics-based model. Results: Validation on phantom and human data showed accurate predictions of flow velocity when using measured fMRI signals as input into the neural network. Impact: Here, we significantly increase quantitative information obtainable from fMRI which will enable neuroimaging researchers studying fluid flow dynamics to take advantage of the high sensitivity and temporal resolution of fMRI to obtain flow signals that are physically interpretable.
Model-free detection of task-evoked neural activity in the whole brain with structurally constrained synchronization of fMRI signals
Authors: Li Luying , Wu Min , Yin Ting , Zhang Xinlan , Lui Su , Yang Zhipeng , Zhao Yu
Published: November 2024

Motivation: The nonlinear nature of neurovascular coupling and background brain activities that are unrelated to extrinsic stimuli in tasks could result in an inadequate mapping of the task-evoked brain activations with the conventional-GLM in fMRI. Goal(s): The aim of this study is to propose a new approach to map task-evoked brain activation without the linear assumption. Approach: we proposed a model-free approach to map task-evoked activation in the whole brain by measuring increases in BOLD signal synchronization within anatomical structures. Results: Compared to the GLM approach, the model-free approach could detect regions of brain activations beyond the conventional-GLM's characterization, especially in the white matter. Impact: The model-free approach detects task-evoked brain activations by measuring changes in BOLD signal synchronization within local anatomical structures, which is expected to serve as a standardized tool to measure neural activities with nonlinear hemodynamic responses.
Clinically Feasible Diffusion Reconstruction for Highly-Accelerated Cardiac Cine MRI
Authors: Qiu Shihan , Pan Shaoyan , Liu Yikang , Zhao Lin , Xu Jian , Liu Qi , Chen Terrence , Chen Eric , Chen Xiao , Sun Shanhui
Published: November 2024

Motivation: The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processing time poses a challenge. Goal(s): To develop a clinically feasible diffusion-model-based reconstruction pipeline to improve the image quality of cine MRI. Approach: A multi-in-multi-out diffusion enhancement model together with fast inference strategies were developed to be used in conjunction with a reconstruction model. Results: The diffusion reconstruction reduced spatial and temporal blurring in prospectively undersampled clinical data, as validated by experts’ inspection. The 1.5s/video processing time enabled the approach to be applied in clinical scenarios. Impact: The proposed diffusion reconstruction pipeline provides a practical solution to cardiac cine reconstruction with enhanced quality for clinical usage. This pipeline may be transfered to the clinical application of other diffusion-based methods.
Deep-learning based motion-compensated A-LIKNet for cardiac Cine MRI reconstruction
Authors: Xu Siying , Ghoul Aya , Hammernik Kerstin , Kuebler Jens , Krumm Patrick , Lingg Andreas , Rueckert Daniel , Gatidis Sergios , Kuestner Thomas
Published: November 2024

Motivation: Cardiac Cine MRI is commonly used for assessing cardiac function. However, extended acquisition times may cause patient discomfort or can result in respiratory motion artifacts and slice misalignments due to multiple breath-holds. Goal(s): We aim to accelerate data acquisition into a single breath-hold ($$$\sim$$$24×) with spatial-temporal sharing along the cardiac cycle for accurate morphological and functional reconstruction. Approach: We integrated inter-frame motion field estimations with a deep learning-based reconstruction. The motion-compensated A-LIKNet was trained on 115 subjects and tested on 14 subjects. Results: The proposed method reconstructs high-quality images, especially improving morphological accuracy, and thus enables cardiac Cine imaging in a single breath-hold. Impact: The proposed deep learning-based motion-compensated A-LIKNet can efficiently reconstruct highly undersampled cardiac Cine MRI for up to 24× accelerated acquisitions of a single breath-hold. Results demonstrate higher morphological authenticity, sharper details, and reduced artifacts compared to other methods.
Model-Assisted Deep Learning-Based Reconstruction of Accelerated Golden-Angle Radial Data for Free-Breathing Dynamic Contrast-Enhanced MRI
Authors: Mostapha Mahmoud , Nickel Dominik , Lazar Laszlo , Janardhanan Nirmal , Arberet Simon , Boll Daniel , Nadar Mariappan
Published: November 2024

Motivation: GRASP allows for free-breathing DCE-MRI with high spatial and temporal resolution. However, the current 4D iterative reconstruction is slow and still suffers from streaking artifacts, limiting clinical use. Goal(s): Develop a DL solution that significantly reduces the reconstruction time and improves image quality. Approach: A model-assisted DL reconstruction combining a sparsity model with an efficient 3D spatiotemporal network for fast and robust reconstruction of accelerated scans with high resolution. Results: A sparsity-constrained DL-based can provide robust and fast reconstructions with improved image quality, evidenced by the superior quantitative metrics and the qualitative analysis of cases under-represented in the training data. Impact: GRASP offers high-resolution 4D free-breathing DCE-MRI; however, it still suffers from under-sampling artifacts and long reconstruction times. A model-assisted DL reconstruction can reduce the reconstruction time, improve image quality, and increase system robustness—essential in translating to clinical practice.
Clinical evaluation of patients with recurrent glioblastoma using hyperpolarized carbon-13 metabolic imaging
Authors: Vaziri Sana , Autry Adam , Gordon Jeremy , LaFontaine Marisa , Chen Hsin-Yu , Kim Yaewon , Villanueva-Meyer Javier , Larson Peder , Vigneron Daniel , Bush Nancy Ann Oberheim , Chang Susan , Clarke Jennifer , Xu Duan , Lupo Janine , Li Yan
Published: November 2024

Motivation: Despite aggressive treatments, patients with GBM have a median overall survival of 14-16 months and a need for noninvasive evaluation of therapeutics is apparent. Goal(s): To assess whether treatment-induced metabolic changes can be observed in patients using parameters derived from hyperpolarized 13C metabolic imaging data. Approach: 19 patients with recurrent GBM were followed for at least 6 months following treatment initiation and evaluated at various timepoints using HP-13C imaging. Results: A difference in trends following treatment was observed in pyruvate-to-lactate conversion for patients who received anti-angiogenic treatments as compared to those who received a protein kinase inhibitor. Impact: Given the challenges associated with evaluating progression and response to therapy in patients with glioblastoma using conventional MRI, this study provided evidence that hyperpolarized carbon-13 techniques can detect serial changes in dynamic metabolism which might help predict disease status.
Variational diffusion models for blind MRI inverse problems
Authors: Oscanoa Julio , Alkan Cagan , Abraham Daniel , Gao Mengze , Nurdinova Aizada , Ennis Daniel , Setsompop Kawin , Pauly John , Mardani Morteza , Vasanawala Shreyas
Published: November 2024

Motivation: Diffusion models have shown state-of-the-art performance in solving inverse problems. However, current solutions typically consider cases only when the forward operator is fully known, which limits their applicability to the wide variety of MRI inverse problems. Goal(s): Develop a general method for blind MRI inverse problems with unknown forward operator parameters. Approach: We extend the RED-diff framework, which has the key strength of not requiring training or fine–tuning for each specific task. We test our method for image reconstruction with off-resonance and motion correction. Results: Our blind RED-diff framework can successfully approximate the unknown forward model parameters and produce accurate reconstructions. Impact: We demonstrate the potential of current diffusion models to readily tackle a wide range of blind inverse problems in MRI without application-specific re-training or fine-tuning. Image reconstruction with motion and off-resonance correction are the first demonstration applications.
CMRDiff: Multi-sequence CMR synthesis
Authors: Xie Puguang , Li Zhongsen , Ma Yu , Xiao Jingjing
Published: November 2024

Motivation: The synthesis of multi-sequence cardiac magnetic resonance (CMR) images is of great significance to shorten the scan durations and expand the beneficiary population from CMR examination. Goal(s): Achieving accurate synthesis is particularly challenging due to the inherent suboptimal image quality and the persistent interference from noise. Approach: We first propose a novel method based on diffusion model, CMRDiff, for multi-sequence CMR synthesis. Results: We evaluated the proposed CMRDiff on the MICCAI2020 MyoPS Challenge dataset. Our experiments demonstrate that CMRDiff outperforms other state of-the-art multi-modal MRI synthesis methods. Impact: We design the first denoising diffusion probabilistic modelin the literature for multi-sequence CMR synthesis, promising to serve as an effective tool for multi-sequence CMR synthesis.
Best of both MoCo worlds: combining fast pilot tone motion sensing with retrospective SAMER correction
Authors: Huang Yantu , Tan Huixin , Wang Ce , Xiao Nan , Splitthoff Daniel Nicolas , Polak Daniel , Nickel Dominik , Hilbert Tom , Kober Tobias
Published: November 2024

Motivation: Model-based retrospective motion correction has shown good results but sometimes lacks enough information to accurately derive motion parameters. Goal(s): To use the pilot tone to address the drawbacks of retrospective methods by providing them with high-frequency motion information for more robust and efficient motion correction. Approach: We use pilot tone to refine and increase the temporal resolution of motion parameters for the Scout Accelerated Motion Estimation and Reduction (SAMER) method. Results: Motion phantom and volunteer tests show improved image quality of pilot tone + SAMER compared to SAMER-only while the reconstruction takes clinically acceptable 20s. Impact: Our results demonstrate that pilot tone can be used to improve the precision and temporal resolution of a model-based retrospective motion correction method, while being robust and fast. This will help to further mitigate motion artifacts in clinical routine.
PHIMO: Physics-Informed Motion Correction of GRE MRI for T2* Quantification
Authors: Eichhorn Hannah , Hammernik Kerstin , Spieker Veronika , Saks Elisa , Weiss Kilian , Preibisch Christine , Schnabel Julia
Published: November 2024

Motivation: T2* quantification from GRE-MRI is particularly impacted by subject motion due to its sensitivity to magnetic field inhomogeneities. The current multi-parametric quantitative BOLD motion correction method depends on additional k-space acquisition, extending overall acquisition times. Goal(s): To develop a learning-based motion correction method tailored to T2* quantification that avoids redundant data acquisition. Approach: PHIMO leverages multi-echo T2* decay information to identify motion-corrupted k-space lines and excludes them from a data-consistent deep learning reconstruction. Results: We are able to correct motion artifacts in subjects with stronger motion, approaching the performance of the current motion correction method, while substantially reducing the acquisition time. Impact: PHIMO reduces strong motion artifacts in T2* maps by utilizing T2* decay information in an unrolled DL reconstruction. PHIMO avoids redundant data acquisition compared to a current correction method and reduces the acquisition time by over 40%, facilitating clinical applicability.
Motion resolved rapid 3D multiparametric brain mapping with self-navigation
Authors: Fujita Shohei , Jun Yohan , Yong Xingwang , Cho Jaejin , Gagoski Borjan , Bilgic Berkin
Published: November 2024

Motivation: While 3D multiparametric mapping acquisitions can provide rich and quantitative information, their long acquisition time renders them susceptible to motion. Goal(s): To develop a rapid, multiparametric technique for motion-robust brain mapping. Approach: 3D-QALAS acquisition with Cartesian variable-density sampling was implemented to achieve self-navigation while maintaining high scan efficiency. Brain position was estimated for each TR and incorporated in the reconstruction’s forward model. Results: The proposed method enabled reconstruction of motion-resolved datasets at a time resolution of 4.5s with tracking accuracy of <0.2 degrees and <0.5mm, providing T1 and T2 maps with significantly reduced artifacts and improved agreement with measurements from motion-free scans. Impact: We propose an efficient, whole-brain quantitative scan at 1mm3 resolution in 3:36min and incorporate self-navigated motion-correction, thereby obviating the need for navigators or external hardware. This benefits clinical translation especially for imaging unsedated children in clinical and research settings.
Multiparametric quantitative MRI for assessment of clinical response to M032 oncolytic virotherapy in patients with high-grade glioma
Authors: Gallegos Carlos , Mansur Ameer , Estevez-Ordonez Dagoberto , Markert James , Sorace Anna
Published: November 2024

Motivation: Standard-of-care MRI in high-grade glioma (HGG) immunotherapy offers limited value for early response assessment and monitoring given its inability to distinguish tumor progression from treatment-induced inflammatory responses. Goal(s): This study aims to evaluate multiparametric MRI and voxel-wise habitat mapping of vascular and cellular properties to assess response to M032 virotherapy in HGG. Approach: Multiparametric quantitative assessment of cellularity and vascularity, through DWI-MRI and DSC-MRI, was explored for the early evaluation of intratumoral changes post-immunotherapy and associations with overall survival. Results: Anatomical and quantitative MRI metrics revealed changes early over the course of therapy and showed significant associations with overall survival in this cohort. Impact: Characterization of multiparametric quantitative MRI metrics associated with early immunotherapy positive response can aid in the assessment and monitoring of therapeutic efficacy and allow for optimization of clinical care in patients with high-grade glioma.
Prospective performance of an MRI algorithm for early re-direction of breast cancer neoadjuvant treatment
Authors: Onishi Natsuko , Gibbs Jesiica , Li Wen , Price Elissa , LeStage Barbara , Symmans William , Yau Christina , Kornak John ,   the I-SPY 2 Imaging Working Group,   the I-SPY 2 Investigator Network, DeMichele Angela , Esserman Laura , Hylton Nola
Published: November 2024

Motivation: In our preliminary study of breast cancer patients undergoing neoadjuvant treatment in the I-SPY 2 TRIAL, functional tumor volume (FTV)-based algorithm using 3-week and 6-week MRI successfully identified sub-optimal responders as potential candidates for early treatment re-direction. Goal(s): We aimed to evaluate the performance of the algorithm using data collected after the requirement for 6-week MRI based on 3-week response was officially added. Approach: We tested PPV and sensitivity of the algorithm in 146 patients enrolled in I-SPY 2 between October 2021 and June 2022. Results: The combined 3-week and 6-week MRI algorithm showed high PPV and high sensitivity in identifying sub-optimal responders. Impact: In the I-SPY 2 neoadjuvant breast cancer trial, an MRI-based algorithm demonstrated its ability to identify sub-optimal responders at 6 weeks of treatment. This will impact response-based personalization of treatment in future clinical trials and ultimately treatment in the clinic.
Validating Quantitative Transport Mapping (QTM) on a Perfused Liver Phantom
Authors: Romano Dominick , Zhang Qihao , Şişman Mert , Hu Renjiu , Weppner Benjamin , Nguyen Thanh , Spincemaille Pascal , Prince Martin , Wang Yi
Published: November 2024

Motivation: To validate deep learning based Quantitative Transport Mapping (QTMnet) on a perfused tissue phantom. Goal(s): Evaluate the accuracy of QTMnet derived flow and compare to traditional tracer-kinetic flow estimation. Approach: We developed a workflow to prepare porcine liver as a perfusion phantom1. We perfused n=8 porcine livers with a controllable pump and acquired DCE-MRI. We then estimated the liver flow with QTMnet and traditional tracer-kinetics. Results: QTMnet accurately estimates our phantom flow (mean error: -2.82%, mean absolute error: 10.0%). Furthermore, QTMnet flow estimation was more accurate than traditional tracer-kinetics flow estimation (mean error: -43.29%, mean absolute error: 58.9%, P<0.00001). Impact: Our liver phantom workflow allows demonstrating accuracy of estimated flows. Superior accuracy was observed using QTMnet compared to traditional tracer-kinetics. Accurate estimation of liver blood flow allows better diagnosis and follow-up in the imaging of primary and secondary liver cancer.
Pilot Results Investigating Treatment Effects on Neurometabolites in Major Depressive Disorder: A 7T MRS Study of the Posterior Cingulate Cortex
Authors: Rajkumar Ravichandran , Farrher Ezequiel , Schnellbächer Gereon , Hagen Jana , Collee Maria , Ramkiran Shukti , Latheef Alna Reem Al , Veselinović Tanja , Shah N. Jon , Neuner Irene
Published: November 2024

Motivation: This research addresses a critical gap by investigating the impact of depression treatment on neurometabolites in the PCC. Goal(s): This exploratory study aims to investigate the relationship between neurometabolite levels in the PCC and assess its impact on treatment. Approach: Structural MRI and MRS data were acquired from 16 MDD patients and 16 healthy controls. The concentration of neurometabolites was quantified. ANOVA models were used to assess differences between groups. Results: Treatment effectively reduced depressive symptoms but did not significantly alter neurometabolite levels in the PCC. Factors such as medication, small sample size, and short follow-up intervals may have contributed to these results. Impact: This research highlights that, despite effective treatment response in improving depressive symptoms in MDD patients, neurometabolite levels in the PCC were not significantly altered, emphasizing the necessity for further, more extensive research to comprehensively understand MDD and its treatment.
Eight-channel dual-tuned coaxial‐transmission‐line coils array for human head imaging at 10.5 Tesla
Authors: Payne Komlan , Zhao Yunkun , Bhosale Aditya Ashok , Zhang Xiaoliang
Published: November 2024

Motivation: The capability of coaxial-transmission-line (CTL) RF coils to exhibit multimode operating frequencies make them versatile for applications involving dual-nuclear coil resonators for Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy studies. Goal(s): Design eight-channel dual-tuned CTL coils array for human head imaging at 10.5 Tesla and address the electromagnetic coupling issue between elements of the array. Approach: The high impedance feature of the high-frequency mode helps to achieve sufficient decoupling for 1H channels while the magnetic wall technique is used to decouple the low-frequency mode tuned to heteronuclear frequency. Results: A well-decoupled array of dual-tuned CTL coils is feasible for head imaging at 10.5T. Impact: The feasibility of advanced multichannel dual-tuned RF coil array can contribute to more informative imaging and spectroscopy, which is valuable in various medical and research applications.
Local SAR and Uncertainty Estimation for Brain Imaging by Bayesian Deep Learning
Authors: Meliado E.F. , Mandija S. , van den Berg C.A.T. , Raaijmakers A.J.E.
Published: November 2024

Motivation: Local SAR cannot be measured during an MRI examination. Deep learning approaches are proving to be a solution for on-line subject-specific SAR assessment. Goal(s): The brain is the region of greatest clinical interest for ultra-high field MRI. Therefore, we apply for brain imaging a deep learning approach presented for local SAR assessment for body imaging. Approach: The Bayesian deep-learning approach maps the relation between subject-specific complex B1+-maps and the corresponding local SAR distribution, and predicts the spatial distribution of uncertainty at the same timeResults: The Bayesian deep-learning approach for local SAR assessment in brain outperforms the previous application for prostate imaging. Impact: The application of Bayesian deep-learning can allow the reduction of overly conservative RF safety constraints that limit the performance of UHF-MRI. Furthermore, the joint estimation of uncertainty can help the acceptance of such methods in clinical contexts.
Assessment of the Inter-Subject Variability of Peak Local Specific Absorption Rate for a Head Coil at 10.5T
Authors: Ates Mert , Haluptzok Tobey , Adriany Gregor , Metzger Gregory , Ugurbil Kamil , Eryaman Yigitcan , Sadeghi-Tarakameh Alireza
Published: November 2024

Motivation: The safety factor, which scales SAR matrices used in real-time SAR monitoring, is commonly dominated by inter-subject variability. However, the contributions from various sources to that variability have not been fully evaluated. Goal(s): Assess the impact of different human model variations and different patient positions inside the coil, on the predicted peak local SAR for 10.5T head applications. Approach: The SAR inter-subject variability was investigated via EM simulations of two human models along with a wide variety of head positions inside an 8-channel coil at 10.5T. Results: The variability between head models was significantly more consequential than variations in a head model’s position. Impact: Simulating realistic scenarios with wide appropriate variables, to calculate SAR with a more accurate inter-subject variability on peak local SAR, has the potential to improve patient safety without compromising the scanning quality at ultrahigh field MRI.
A high permittivity and conformable gel pad fabricated by the PVA freeze-thaw method for dielectric shimming in ultra-high-field MRI
Authors: Li Mengyu , Tang Keyi , Zhou Shufeng , Zuo Zhentao , Zhu Huabin , Shan Shanshan , Liu Chunyi
Published: November 2024

Motivation: Utilize new material to fabricate high-permittivity pads for addressing the B1 inhomogeneity and safety issues in ultra-high-field MRI scanning. Goal(s): We aim to develop a new high permittivity pad with flexibility which can fit various body shapes. Different sizes and mass proportions of barium titanate powder were explored to achieve optimized mechanical properties and desired permittivity value. Approach: The gel pad is fabricated using the PVA freeze-thaw method, resulting in a stable gel structure that incorporates barium titanate powder, thereby possessing excellent mechanical properties and high permittivity. Results: Experimental results demonstrate of the gel pad's potential for clinical applications in ultra-high-field MRI scanning. Impact: This abstract introduces a novel gel pad with high permittivity that can be conformed to different shapes of scanned objects. It highlights the potential of the gel pad in addressing safety issues in ultra-high-field MRI scanning.
Efficient RF Shimming Strategies for Cardiac MRI at 5T
Authors: Li Jiaxu , Li Nan , Zhou Liqiang , Shen Zhenhua , Liu Shengping , Zhang Xiaoliang , Li Ye
Published: November 2024

Motivation: Enhance RF shim efficiency, reduce power, and provide uniformity for ultra-high field cardiac imaging. Goal(s): To significantly enhance excitation efficiency, reduce excitation power, and mitigate the risk of SAR exceeding safe levels, while minimizing loss of uniformity. Approach: Optimizing excitation intensity and uniformity through joint loss function and validating the approach with simulation models and in vivo imaging. Results: The research results indicate that, when compared to MLS, the proposed Eff-MLS leads to an average 3.3% reduction in CV, while improving safety excitation efficiency by 442.26% in the simulation model. Similar effects were also observed in in-vivo experiments. Impact: By enhancing RF shim efficiency and reducing the required excitation power while maintaining uniformity, this approach paves the way for more precise, high-resolution cardiac imaging at ultra-high field strengths. The potential impact includes broader applications of ultra-high field CMR.
Safety of Implanted Auditory Prostheses at 7T
Authors: Fierens Guy , Clemence Matthew , Verhaert Nicolas , Bowtell Richard , Dewey Rebecca
Published: November 2024

Motivation: While scanning individuals with active hearing implants (e.g., cochlear implants) at 1.5 and 3 T has become commonplace, scanning these patients at ultra-high field strengths (e.g., 7 T) is likely to be associated with an increased risks of damaging the device or causing soft-tissue damage, pain, and/or discomfort. Goal(s): To evaluate the safety of three different active hearing implants in the 7 T MR environment. Approach: Five potential interactions between the devices and the MR environment were assessed using industry-recommended practices for 1.5/3 T. Results: Preliminary findings show no adverse effects within the predefined test conditions. Impact: While scanning individuals with active hearing implants at 1.5/3 T has become commonplace, 7 T is associated with significantly greater safety risks. This study is the first to provide some confidence in the safety of such implants at 7 T.
Improving Accuracy and Repeatability of Cartilage T2 Mapping in the OAI Dataset through Extended Phase Graph Modeling
Authors: Barbieri Marco , Gatti Anthony , Kogan Feliks
Published: November 2024

Motivation: Current methods for T2 fitting in the OAI dataset are based on exponential models, which are inherently sub-optimal as they do not account for stimulated echoes and B1 inhomogeneities. Goal(s): To study whether EPG-Model fitting methods improve accuracy and repeatability of T2 mapping in the OAI dataset compared to conventional methods. Approach: We set up three EPG modelling approaches: nonlinear-least-square, dictionary matching, and deep learning. We used simulations and data from the OAI dataset to evaluate accuracy, repeatability. Results: We found that EPG-based methods had higher accuracy and repeatability than exponential-based methods commonly used to compute T2 maps in the OAI dataset. Impact: We have demonstrated that EPG-based methods improved accuracy and repeatability of T2 mapping in the OAI dataset over the commonly used mono-exponential fitting methods. This permits more robust analysis of T2 information in the OAI dataset, especially in longitudinal analyses.
Direct MRI of Collagen
Authors: van Schoor Jason , Weiger Markus , Baadsvik Emily , Pruessmann Klaas
Published: November 2024

Motivation: Diseases in the musculoskeletal system are often characterized by a change in collagen structure and content. Such diseases are common and methods to evaluate collagen are integral in diagnosis and monitoring. Currently, indirect techniques are used for MRI of collagen due to its extremely short T2. Goal(s): To directly image collagen. Approach: Bone and tendon specimens, as well as an in-vivo hand, are imaged using advanced short-T2 techniques. The rapidly decaying signal is captured at different echo times, and image subtraction is used to isolate the signal of interest. Results: Direct collagen MRI was successfully performed with decent SNR and resolution. Impact: Direct MRI of collagen is reported with the potential for improved evaluation of the collagen structure and content with possible applications in diagnosis and monitoring of collagen-related diseases.
Macromolecule Exchange and Non-Exchange Protons Multiparametric Imaging of Knee: using ZAP/CEST and T2* Mapping with δTE Ultra-Short TE.
Authors: Malis Vadim , Vucevic Diana , Bae Won , Kassai Yoshimori , Miyazaki Mitsue
Published: November 2024

Motivation: The study addresses the need for knee injury diagnosis by advancing MRI techniques to capture both structural and biochemical tissue characteristics. Goal(s): The goal is to develop advanced MRI biomarkers by integrating Z-spectrum/CEST with UTE techniques, improving visualization of knee structures for detection of injuries and pathologiesApproach: We used novel Z-spectrum/CEST and UTE sequences to characterize proton exchange and obtain detailed T2* mapping, aiming to reveal precise biochemical and ultrastructural knee tissue details. Results: Findings demonstrate improved T2* mapping and proton characterization in knee tissues, suggesting potential biomarkers for early pathology identification, although further validation is necessary for clinical application. Impact: Multiparametric imaging of macromolecular exchange and non-exchange protons using ZAP/CEST MRI and UTE imaging with tight intervals δTE offers detailed knee tissue visualization, with potential for developing precise diagnostic biomarkers.
Collagen Fibre Direction Estimation Using a Prototype Rotatable Low Field Scanner
Authors: Lanz Harry , Chappell Karyn , McGinley John , Gupte Chinmay , Amiras Dimitri , Ristic Mihailo
Published: November 2024

Motivation: Certain types of tendon and ligament pathologies are hard to diagnose using conventional MRI. This can lead to invasive procedures or under-informed decisions regarding treatment. Goal(s): The goal of this research is to develop a novel scanner and image analysis techniques in order to assess tendon/ligament structure and health non-invasively. Approach: Tendons/ligaments contain collagen fibres that produce different signal intensities at different B0 orientations, this is the "magic angle effect". We have developed a rotatable scanner to reorient B0 to exploit this effect. Results: This study shows successful tendon structure estimation of a bovine PCL using our scanner and image processing techniques. Impact: The results of this study provide a foundation to begin testing our methodology in-vivo. Our successful fibre estimation in a bovine PCL has shown our scanner captures the magic angle effect and our processing techniques can estimate collagen fibre directions.
Skeletal Muscle phosphocreatine assessment in diabetes and peripheral arterial disease with 1H MRI: a feasibility study
Authors: Wahidi Ryan , Li Ran , Zayed Mohammed , Hastings Mary , Xu Jiadi , Zhang Yi , Semenkovich Clay , Zheng Jie
Published: November 2024

Motivation: Both Type 2 Diabetes Mellitus (T2D) and peripheral artery disease (PAD) are linked to impaired mitochondrial function in peripheral tissue that may precede micro-vascular disorders. Goal(s): The goal is to demonstrate the feasibility of 1H-based MRI for dynamic quantification of skeletal muscle PCr (SMPCr) concentration in vivo on a 3T clinical MRI system, in healthy controls, T2D, and PAD. Approach: Dynamic 1H-based PCr imaging was developed and evaluated in human subjects in a rest-exercise-recovery protocol, based on Chemical Exchange Saturation Transfer (CEST) technique. Results: Reproducibility of PCr measurement and declines in measures of mitochondria function in aging and diseases are demonstrated. Impact: The 1H MRI technique was able to measure differences in assessing mitochondrial function in people with T2D and PAD, without additional hardware. This technical development may allow early diagnosis of complications associated with various peripheral disorders.
Longitudinal Assessment of Cartilage Thickness, T1ρ and T2 Changes in Patients with Mild Osteoarthritis using MRI and 3D Surface-Based Analysis
Authors: Kessler Dimitri , MacKay James , McDonnell Stephen , O’Callaghan Jennifer , Grainger Andrew , Roberts Alexandra , Janiczek Robert , Patterson Andrew , Lee Sarah , McCaskie Andrew , Graves Martin , Kaggie Joshua , Gilbert Fiona
Published: November 2024

Motivation: Osteoarthritis (OA) leads to cartilage degradation and pain, impacting patients' lives. MRI allows detailed cartilage assessment; however, limited sensitivity hinders early-phase clinical trials developing disease-modifying treatments. Goal(s): To apply 3D cartilage surface mapping in a homogeneous patient group over 12 months. Approach: Combined morphological and compositional cartilage MRI with 3D surface-based analysis to assess longitudinal changes within patients with mild OA. Results: Bi-directional cartilage thickness, T1ρ, and T2 alterations exceeding measurement errors were observed after 12 months. Medial femorotibial cartilage thinned, while lateral tibial cartilage thickened. Cartilage thickness changes correlated negatively with T1ρ and T2 changes in tibial and patellar cartilage. Impact: The results and methods presented can improve understanding of early structural and compositional changes in cartilage, monitoring disease progression and assessing the effectiveness of therapeutic interventions in OA.