bluuebunny/crossref_metadata_2025 huggingface dataset:
3D MRE-based novel score predicts hepatocellular carcinoma development in patients with chronic hepatitis B
Authors: Chen Haimei , Zhu Jie , Li Mengsi , Chen Jun , Yin Meng , Venkatesh Sudhakar , Ehman Richard , Wang Jin
Published: November 2024

Motivation: Identifying patients with chronic hepatitis B (CHB) who are at high risk of HCC development for close monitoring to improve prognosis is crucial. Goal(s): We aimed to develop a 3D MRE-based risk score to predict HCC development in CHB patients. Approach: The novel HCC risk score was developed using liver shear stiffness and LSS, age, platelet count, and albumin. Results: Our results showed that the risk score has excellent performance for the identiﬁcation of patients of HCC development, the cutoff value 55 of our risk score provided the high negative predictive value for HCC development at 3 and 5 years. Impact: MRE- based HCC risk score may be a non-invasively accurate tool for predicting HCC, which may provide a useful reference for decision-making in HCC surveillance strategy for CHB patients.
Influence of fat droplet size on liver R2* relaxometry by Monte Carlo simulation and phantom studies
Authors: Li Xiaoben , Wu Tingmiao , Reeder Scott , Hernando Diego , Wang Changqing
Published: November 2024

Motivation: Liver fat (hepatic steatosis) can confound R2*-based iron quantification in chemical shift encoded MRI, while the size of fat droplets may also affect liver R2*. However, it is infeasible to experimentally investigate the influence of fat droplet size in vivo on liver R2* due to tissue complexity. Goal(s): To investigate the influence of fat droplet size on liver R2* at both 1.5T and 3.0T. Approach: Monte Carlo simulation and phantom studies. Results: Liver R2* demonstrates a positive linear relationship with proton density fat fraction and remains relatively unaffected by fat droplet size. Impact: These findings may benefit phantom design and understanding of the underlying mechanisms of R2* characteristics in the presence of hepatic steatosis.
Whole Brain Multiparametric Mapping in Two Minutes Using a Dual-Flip-Angle Stack-of-Stars Blipped Multi-Gradient-Echo Acquisition
Authors: Feng Wenlong , Ding Zekang , Chen Quan , She Huajun , Du Yiping
Published: November 2024

Motivation: Multiparametric MRI of the brain can be used to improve the assessment of neurological diseases. However, the long scan time hinders its clinical applications. Goal(s): This study aims to develop a technique for fast whole brain multiparametric mapping. Approach: A dual-flip-angle stack-of-stars (SOS) blipped multi-gradient-echo sequence was developed to accelerate the acquisition. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation algorithm was proposed to improve the quantification of myelin water fraction (MWF). Results: The in vivo experiments have demonstrated good agreement between results of accelerated SOS and the reference, as well as good repeatability between two repeated accelerated SOS scans. Impact: Our technique can provide robust whole brain multiparametric mapping of MWF, T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+) with a two-minute scan, which has a great potential for neurological applications, such as multiple sclerosis.
High-resolution free-breathing simultaneous myocardial T1, T2 and T1ρ mapping with region-optimized virtual coils (ROVir)
Authors: Lyu Zhenfeng , Hua Sha , Hu Peng , Qi Haikun
Published: November 2024

Motivation: Cardiac parametric mapping with electrocardiogram-triggered single-shot acquisition has compromised spatial resolution due to limited quiescent period for data acquisition. Goal(s): To develop a high-resolution simultaneous myocardial T1, T2 and T1ρ mapping technique. Approach: Enhance the spatial resolution while reducing the FOV to make the acquisition window fit in the mid-diastolic quiescent period in the cardiac cycle. Subsequently, employ the ROVir technique to eliminate fold-over artifacts arising from FOV reduction. Results: The proposed technique achieved high-resolution multi-parametric mapping without a loss of quantitative precision. Impact: A novel framework was proposed to shorten the acquisition window and improve the spatial resolution of electrocardiogram-triggered cardiac parametric mapping beyond common k-space undersamping. High-resolution myocardial parametric mapping can provide more precise and reliable diagnostic information.
Novel Robust Threshold-Free Probabilistic 3D LGE Fibrosis Signature Technique for Left Atrial Fibrosis Quantification
Authors: Mehrnia Mehri , Kholmovski Eugene , Kim Daniel , Katsaggelos Aggelos , Passman Rod , Elbaz Mohammed
Published: November 2024

Motivation: Left atrial fibrosis assessment from 3D LGE-MRI is pivotal for predicting atrial myopathy and AF recurrence. However, current methods are clinically ineffective and sensitive to data uncertainties such as noise and inter-observer variability of thin LA wall segmentationGoal(s): Hence, we propose a novel, robust, and standardized probabilistic 3D LGE fibrosis signature technique for quantifying fibrosis burden. Approach: Our threshold-free signature technique probabilistically encodes multi-billion LGE intensity comparisons from the entire LA volume (not just LA wall). Results: We evaluated feasibility of our threshold-free method in quantifying LA fibrosis burden, and its stability against Rician noise and interobserver variability of LA volume segmentation. Impact: Our signature technique as an index of fibrosis burden is highly robust to inherent scan uncertainties including high power Rician noise and inter-observer LA segmentation variability. As a result, our method increases potential clinical utility of 3D LGE MRI
Mitigating Geometric Distortion & Susceptibility Artifacts in cDTI via SAP-M2-EPI: A feasibility study
Authors: Sadighi Mehdi , Kara Danielle , Mai Dingheng , Nguyen Khoi , Chen Shi , Kwon Deborah , Nguyen Christopher
Published: November 2024

Motivation: We aimed to enhance in vivo cardiac diffusion tensor imaging (cDTI), a technique challenged by limitations, especially in high-BMI patients, causing notable aliasing and distortion issues. Goal(s): Our primary goal was to introduce and validate Short-Axis-PROPELLER-M2-EPI (SAP-M2-EPI) for cDTI. The focus was on reducing aliasing and distortion artifacts while ensuring robust motion correction. Approach: SAP-M2-EPI combines motion-compensated diffusion gradients with PROPELLER, effectively minimizing motion artifacts and suppressing aliasing and distortion. Results: Our study shows that SAP-M2-EPI successfully mitigates motion artifacts and significantly reduces aliasing and distortion, particularly beneficial for high-BMI patients. This innovative approach holds great promise for enhancing cDTI diagnostic accuracy. Impact: Impact: SAP-M2-EPI’s success offers clinicians a potent tool for enhancing cDTI diagnoses, especially in high-BMI patients. It opens doors to in-depth cardiac research, encourages further methodological innovations, and ultimately promises better patient care through more accurate imaging.
3D Image Enhancement for High-Resolution ky-kz Accelerated 3D LGE CMR
Authors: Demirel Omer , Morales Manuel , Street Jordan , Manning Warren , Nezafat Reza
Published: November 2024

Motivation: Prolonged scan times in high-resolution 3D late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging hinders the full potential in clinical applications. Goal(s): The primary goal of this study was to develop and evaluate a 3D enhanced-resolution for 2D (ky-kz) accelerated 3D LGE imaging. Approach: A 3D generative adversarial network was implemented to enhance the spatial resolution of 2D-accelerated 3D LGE images. Results: The proposed method at 6-fold acceleration (3-fold in ky and 2-fold in kz) maintained intricate scar details and improved image quality. Impact: The improvement in acquisition speed by 2D acceleration may benefit patients presenting with heavy respiratory motion and may be less sensitive to contrast washout.
Complex B1+ field-based conductivity mapping in the human myocardium at 3T
Authors: Siuryte Paulina , Meerbothe Thierry , Zhang Yi , Henningson Markus , Tourais Joao , van de Steeg-Henzen Christal , Tao Qian , Mandija Stefano , Weingärtner Sebastian
Published: November 2024

Motivation: While electrical property tomography is gaining popularity, cardiac applications are limited due to inadequate cardiac B1+ mapping. Thus, conductivity mapping in the heart using complex B1+ maps is yet unexplored. Goal(s): To measure myocardial conductivity from the complex B1+ distribution in the heart at 3T. Approach: A novel |B1+| mapping method was adapted for free-breathing B1+ maps, followed by conductivity reconstruction via 1D polynomial fitting in saline phantoms and four healthy subjects. Results: Phantom results show excellent correlation with expected values (R2=0.95). In-vivo, conductivity is largely homogenous with 0.69±0.13S/m average in-plane conductivity across all subjects, in line with the literature. Impact: Electrical properties are a valuable biomarker, however, the translation to cardiac imaging remains limited. In this work, complex B1+ field-based conductivity is reported in the human myocardium at 3T, using a novel Bloch-Siegert shift-prepared cardiac B1+ mapping technique.
Interventional molecular MRI of early myocardial injury in a pig model of ischemia and reperfusion
Authors: Reiss Simon , Heidt Timo , Thielmann Julien , Maier Alexander , von zur Mühlen Constantin , Bock Michael
Published: November 2024

Motivation: Cardiac MRI has become the gold standard for non-invasive characterization of myocardial tissue. However, current MRI techniques only indirectly represent cardiac inflammation. Goal(s): To assess if interventional molecular MRI allows for visualization of the cellular processes during the inflammatory response after myocardial infarction. Approach: Iron-labeled P-selectin contrast agent was injected in pigs after 40 minutes of myocardial ischemia. To increase sensitivity, the contrast agent was injected into the coronary artery via an MR-guided intervention. Results: Infarcted myocardial segments could be visualized using the iron-labeled contrast agent by increased R2* values both in vivo and ex vivo. Impact: The intracoronary injection of molecular contrast agents using interventional MRI can add valuable information for preclinical studies of the early cellular processes after myocardial ischemia.
Simultaneous 3D T1, T2, and fat-fraction mapping with respiratory-motion correction, for comprehensive liver tissue characterisation at 0.55T
Authors: Tripp Donovan , Neji Radhouene , Kunze Karl , Crabb Michael , Prieto Claudia , Botnar René
Published: November 2024

Motivation: Mulitparametric quantitative MRI is a powerful tool for diagnosis of liver disease, but current clinical sequences will acquire 2D slices in separate scans, prone to misregistration. Goal(s): Demonstrate the simultaneous in-vivo acquisition of T1, T2, and fat fraction maps over the whole liver from a single free-breathing scan at 0.55T. Approach: A dictionary-matching-based framework with non-rigid respiratory motion corrected reconstruction was validated in a cohort of ten healthy subjects. Results: T1, T2, and fat fraction values acquired in phantoms and in vivo showed good agreement with values from corresponding reference scans. Impact: Our technique promises an efficient means to acquire multiple parameter maps providing comprehensive staging and diagnosis of non-alcoholic fatty liver disease, believed to affect over two billion people worldwide.
Accelerating Quantitative MRI using Self-supervised Deep Learning with Model Reinforcement
Authors: Bian Wanyu , Jang Albert , Liu Fang
Published: November 2024

Motivation: Quantitative MRI (qMRI) is time-consuming and requires substantial efforts for acceleration to cut down the acquisition time. Goal(s): This paper proposes a novel self-supervised learning framework that uses model reinforcement, RELAX-MORE, for accelerated qMRI reconstruction. Approach: The proposed method uses an optimization algorithm to unroll an iterative model-based qMRI reconstruction into a deep learning framework, enabling accelerated MR parameter maps that are highly accurate and robust. Results: The proposed method generates high quality MR parameter maps that correct for image artifacts, removes noise, and recovers image features in regions of imperfect image conditions. Impact: This work demonstrates the feasibility of a new self-supervised learning method for rapid MR parameter mapping, that is readily adaptable to the clinical translation of qMRI.
Towards ultrafast submillimeter T2* and QSM quantification at 3T using spherical Echo Planar Time Resolved Imaging (sEPTI)
Authors: Wang Nan , Nishimura Mark , Yurt Mahmut , Gao Mengze , Abraham Daniel , Alkan Cagan , Liao Congyu , Cao Xiaozhi , Zhou Zihan , Setsompop Kawin
Published: November 2024

Motivation: To further improve the image quality, SNR, and reduce scan time by reducing averages for submillimeter T2* and QSM at 3T Goal(s): To achieve whole-brain 0.75-mm T2* and QSM quantification using sEPTI within a single average scanApproach: We developed: (1) an iterative data-driven B0 update pipeline for accurate and high SNR B0 map; (2) data-driven eddy-current correction approach to reduce artifacts; (3) a physics-informed unrolled network to boost the SNR of the reconstructed image to achieve 2X acceleration by reducing the need of averages. Results: sEPTI achieved whole-brain 0.75-mm T2* and QSM quantification within 84 seconds with the potential for wide applicationsImpact: The work presented synergetic improvements in B0 update, eddy-current correction, and unrolled-network based SNR-boosted reconstruction for sEPTI, which achieves whole-brain 0.75-mm distortion-free and blurring-free T2* and QSM quantification at 3T in 84 seconds with the potentials for wide applications.
Temporal Structured Low-Rank Reconstruction for First-Pass Myocardial Perfusion Imaging
Authors: Chen Xi , Li Debiao , Christodoulou Anthony G.
Published: November 2024

Motivation: First-pass myocardial perfusion imaging is a powerful tool for assessing coronary artery disease, but needs high levels of undersampling to achieve sufficient spatial coverage, spatiotemporal resolution, and motion robustness. Goal(s): To develop efficient temporal image reconstruction models which can leverage linear time-invariant models of dynamic contrast enhancement without identifying an arterial input function or assuming tissue transfer function shapes. Approach: We propose a novel temporal structured low-rank modeling technique to implicitly leverage linear time-invariant models of dynamic contrast enhancement. Results: Temporal structured low-rank modeling outperforms conventional low-rank methods, especially as a local constraint. Impact: Temporal structured low-rank modeling has the potential to improve spatial coverage, spatial resolution, and/or motion robustness for first-pass myocardial perfusion MRI.
High-Resolution Oblique Coronal MRI with Optimal Flexed-Knee Angle for Anterior Cruciate Ligament Tear Diagnosis
Authors: Liao Yunjie , Chen Can , Liu Xiao , Liang Qi , Peng Song , Wu Peng , Han Lu , Hu Pengzhi
Published: November 2024

Motivation: Anterior cruciate ligament (ACL) injuries are prevalent in the realm of knee injuries. Conventional MRI methodologies employed for diagnosing ACL tears exhibit low accuracy. Goal(s): Evaluate the diagnostic efficacy of high-resolution coronal MRI performed at an optimal flexion angle specifically for ACL tears. Approach: Healthy volunteers and patients are scanned to find the optimal flexion angle and compare the image quality with traditional extended-knee positioning approach. Results: The implementation of high-resolution coronal imaging at the ideal flexion angle (30 degrees) has the potential to enhance ACL visualization and improve diagnostic accuracy when compared with conventional techniques. Impact: The utilization of high-resolution coronal imaging at the optimal flexion angle (30 degrees) demonstrated a substantial enhancement in the visualization of the anterior cruciate ligament (ACL), resulting in a notable improvement in diagnostic accuracy as compared to conventional techniques.
Quantitative analysis of induced tendon degeneration using magic angle insensitive ultra-short echo time magnetization transfer
Authors: Feuerriegel Georg , Marth Adrian , Goller Sophia , Hilbe Monika , Sutter Reto , Sommer Stefan
Published: November 2024

Motivation: Ultra-short echo time (UTE) imaging combined with magnetization transfer (MT) allows for magic angle effects (MAE)-insensitive quantification of short T2 tissues, but clinically feasible applications are rare. Goal(s): The objectives of this study were to qualitatively and quantitatively assess changes in bovine flexor tendons before and after collagen degradation. Approach: 3D UTE MT imaging was compared to UTE T2* mapping at 0°, 27°, 55° and 90° relative to the B0 field within a clinically feasible acquisition time. Results: Compared to UTE T2* mapping, UTE MT imaging was significantly less affected by the MAE and demonstrated a better performance in differentiating partial tendon tears. Impact: UTE MT imaging is a reliable and reproducible method for quantifying tendon degeneration that is robust to the magic angel effect, acquired within a clinically feasible scan time, and could therefore be a useful tool in the diagnosis of tendinopathies.
Importance of ACL substructure composition for quantitative analysis using UTE
Authors: Rothe Maik , Bohndorf Klaus , Brill Richard , Wohlgemuth Walter , Gussew Alexander
Published: November 2024

Motivation: Quantitative MR-imaging of ligaments needs special approaches like ultra-short echo-time (UTE) imaging. Most quantitative studies of the anterior cruciate ligament (ACL) regard it as a uniform structure and do not consider differences in ligament composition at different anatomical positions. Goal(s): This study is aimed to use UTE to evaluate anatomical position specific T1 and T2* parameters of the ACL. Approach: The region specific ACL T1 and T2* values of 10 healthy volunteers were investigated by quantitative UTE mapping. Results: Quantitative mapping revealed that T1 and T2* values decrease from the distal to the proximal ACL endings, due to different fractions of free water. Impact: This study reveals that the anterior cruciate ligament (ACL) shows severe differences in quantitative values between its proximal and distal ends. The ACL region plays an important role in quantitative analysis and should be considered for assessments of pathologies.
Quantitative 3D T2* Mapping of Meniscus Before and After Meniscal Root Repair at 7 Tesla
Authors: Kajabi Abdul Wahed , Zbyn Stefan , Steinberger Collin , Smith Jesse , Knutsen Karsten , Tollefson Luke , Metzger Gregor , LaPrade Rob , Ellermann Jutta
Published: November 2024

Motivation: Meniscal tears are a significant cause of osteoarthritis, and failure rate of meniscal repair remains high. MRI assessment of meniscus at 7T provides high signal-to-noise ratio and allows 3D evaluation of the tissue. Goal(s): Investigate and follow-up meniscal tissue integrity in pre- and post-repair patients. Approach: Quantitative 3D T2* mapping of the lateral and medial menisci in patients with posterior horn root tears in the medial meniscus and compare against matched controls. Results: Significantly increased T2* values were identified beyond the tear in both lateral and medial menisci of pre-repair patients and the values remained significantly elevated six months post-repair. Impact: Utilizing high-resolution 7 Tesla 3D T2* mapping, this study quantitatively and longitudinally assesses meniscal tissue integrity of patients who underwent medial meniscal posterior root tear repair, which has significant impact on management and standard of care for the patients.
Histology-informed biophysical diffusion MRI model selection for enhanced liver cancer immunotherapy assessment
Authors: Grussu Francesco , Bernatowicz Kinga , Palombo Marco , Tozzi Caterina , Simonetti Sara , Serna Garazi , Grigoriou Athanasios , Voronova Anna , Garay Valezka , Corral Juan Francisco , Vidorreta Marta , García Pablo García-Polo , Merino Xavier , Mast Richard , Roson Núria , Escobar Manuel , Vieito Maria , Toledo Rodrigo , Nuciforo Paolo , Garralda Elena , Perez-Lopez Raquel
Published: November 2024

Motivation: Multi-compartment liver diffusion MRI (dMRI) provides innovative markers of intra-cellular fraction (F) and cell size (CS). However, practical implementations for histologically-meaningful F and CS computation in the clinic are still sought. Goal(s): To deliver a compact approach for F and CS estimation, informing model design with histology. Approach: We compared 5 implementations of a standard two-compartment model for their ability to provide F and CS estimates that agree with reference biopsies in liver tumours. Results: The best approach consisted of fitting a single-compartment model of intra-cellular diffusion to high b-value images. This provides promising metrics that stratify the risk of progression in immunotherapy. Impact: We deliver a clinically-feasible liver diffusion MRI approach for intra-cellular fraction, cell size and density estimation. It consists of fitting a single-compartment model of restricted diffusion to high b-value images, and provides metrics that may inform on cancer immunotherapy response.
Towards a Generalizable Foundation Model for Multi-Tissue Musculoskeletal MRI Segmentation
Authors: Hoyer Gabrielle , Tong* Michelle , Majumdar Sharmila , Pedoia Valentina
Published: November 2024

Motivation: To evaluate the potential of foundation models for medical imaging analysis. Goal(s): To understand the limitations of foundation models trained for the natural imaging domain, and assess the challenges for translation to complex musculoskeletal anatomy in a rich medical image domain. Approach: A diverse collection of musculoskeletal MRI data was used to assess the generalizability of SAM when applied to a variety of segmentation tasks common to the medical research and clinical setting. Results: SAM performed decently on zero-shot of medical data. The ability of SAM to perform well when finetuned on a spectrum of data, is somewhat lacking and requires additional evaluation. Impact: A foundational model for generalizable musculoskeletal MRI segmentation, such as one fine-tuned on the Segment Anything Model (SAM) has the potential to overcome challenges with generalizability for widespread usage beyond a specific task, reducing burden in medical imaging pipelines.
Peer-to-Peer Generative Learning for Architecture-Agnostic Federated MRI Reconstruction
Authors: Nezhad Valiyeh Ansarian , Elmas Gökberk , Çukur Tolga
Published: November 2024

Motivation: Federated learning (FL) enables privacy-preserving training of deep reconstruction models across multiple sites to improve generalization at the expense of lower within-site performance. Yet, existing methods require a common model architecture across sites, limiting flexibility. Goal(s): Our goal was to devise an architecture-agnostic method for collaborative training of heterogeneous models across sites. Approach: We introduced a novel peer-to-peer generative learning method (PGL-FedMR), where individual sites share a generative prior for their MRI data with remaining sites, and prior-driven synthetic data are used to train reconstruction models at each site. Results: PGL-FedMR improves across-site generalization over local models, and within-site performance over conventional FL. Impact: Improvements in within-site and across-site performance for MRI reconstruction through PGL-FedMR, coupled with the ability to handle heterogeneous architectures, may facilitate privacy-preserving multi-institutional collaborations to build reliable reconstruction models for many applications where data are scarce including rare diseases.
Imaging transformer for MRI denoising with SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
Authors: Xue Hui , Hooper Sarah , Rehman Azaan , Pierce Iain , Treibel Thomas , Davies Rhodri , Bandettini W Patricia , Ramasawmy Rajiv , Javed Ahsan , Yang Yang , Moon James , Campbell-Washburn Adrienne , Kellman Peter
Published: November 2024

Motivation: MR denoising using the CNN models often requires abundant high quality data for training. In many applications, such as higher acceleration and low field, high quality data is not available. This study overcome this limitation by developing a SNR unit based training scheme and a novel imaging transformer (imformer) architecture. Goal(s): To develop and validate a novel imformer model for MR denoising, enabling generalization across field-strengths, imaging contrasts, and anatomy. Approach: SNR unit training scheme and imaging transformer architectureResults: Imformer models outperformed CNNs and conventional transformer. The SNR training enables storng generalization. Impact: Recovery high-fidelity MR signal from very low SNR inputs; Enable 0.55T MRI model training.
Dual-confidence-guided feature learning for semi-supervised medical image segmentation
Authors: Zhou Yudan , Cai Shuhui , Cai Congbo , Lin Liangjie , Chen Zhong
Published: November 2024

Motivation: Obtaining a large medical image dataset with accurate annotations is challenging, thus limiting the practical application of deep learning in clinical practice. Goal(s): Developing a novel semi-supervised algorithm for a limited set of labeled images. Approach: Building a dual-branch network with dual-confidence-guided constraints for tumor feature learning, enabling the model to learn accurate and comprehensive feature representations. Results: In brain tumor segmentation, this algorithm achieved accurate tumor boundary segmentation using only 1% and 10% of labeled training data, and obtained segmentation results close to fully supervised learning when 20% of the training data was labeled. Impact: Our dual-confidence-guided semi-supervised feature learning model can achieve accurate brain tumor region segmentation with limited labeled training data, speeding up the application of deep learning technology in clinical research and providing assistance for clinical diagnosis.
Continuous Spatio-Temporal Representation with Implicit Neural Representation and Neural Ordinary Differential Equation in DSC-MRI
Authors: Lee Junhyeok , Choi Kyu Sung , Park Jung Hyun , Hwang Inpyeong , Chung Jin Wook , Choi Seung Hong
Published: November 2024

Motivation: Dynamic Susceptibility Contrast MRI (DSC-MRI) aids in diagnosing cerebrovascular conditions, but simultaneously achieving high spatial and temporal resolutions is challenging, limiting the capture of detailed perfusion dynamics. Goal(s): To develop a deep learning framework for spatio-temporal super-resolution in DSC-MRI to enhance the capture of perfusion dynamics. Approach: Our proposed model utilizing bi-directional Neural ODE, feature extraction, and a local implicit image function to improve DSC-MRI images and address spatial and temporal resolution constraints. Results: The reconstructed results outperform other methods, with enhanced NMSR, PSNR, and SSIM metrics, providing visual confirmation of accurate MR signal approximation and perfusion parameter calculation. Impact: The spatiotemporal super-resolution of DSC-MRI with deep learning allows for more accurate assessment of perfused tissue dynamics and tumor habitat, as well as more freedom in choosing acquisition weights between spatial and temporal during MRI acquisition.
Neural Implicit Quantitative Imaging
Authors: Zimmermann Felix , Hufnagel Simone , Schuenke Patrick , Kofler Andreas , Kolbitsch Christoph
Published: November 2024

Motivation: 3D quantitative MRI presents a challenging inverse problem. The application of learned reconstruction methods is hindered by the need for extensive training data and the large size of high-resolution voxel representations of multi-dimensional data. Implicit neural fields have shown promise in cine imaging and slice-to-volume registration. Goal(s): Explore the use of neural fields for representing 3D high-resolution quantitative parameters in qMRI. Approach: We integrate motion correction, sensitivity map estimation, and 3D parameter neural fields into an end-to-end, scan-specific optimization without training data. Results: Demonstration of feasibility in the context of cardiac qMRI and initial results of whole-heart 3D T1 maps. Impact: Introduction of implicit neural fields into qMRI, allowing for continuous representation of the quantitative parameters in 3D space. Our novel end-to-end reconstruction with motion correction, sensitivity map estimation provides fast high-resolution, whole-heart T1-maps without relying on training data.
In vivo mapping of sodium homeostasis disturbances in individual ALS patients: a brain 23Na MRI study
Authors: Grapperon Aude-Marie , El Mendili Mohamed Mounir , Maarouf Adil , Ranjeva Jean-Philippe , Guye Maxime , Verschueren Annie , Attarian Shahram , Zaaraoui Wafaa
Published: November 2024

Motivation: ALS is a neurodegenerative disease leading to progressive motor deficit and death within few years. There is an unmet need to identify non-invasive biomarkers at the individual level to predict disease progression. Goal(s): To study disease severity at the individual level in ALS by mapping abnormal sodium homeostasis using brain 23Na-MRI. Approach: 27 ALS patients were explored by brain 23Na-MRI. Individual map of abnormal total sodium concentration (TSC) was computed for each patient compared to a local database of 62 controls. Results: This study mapping sodium homeostasis disturbances at the individual level in ALS patients evidenced association between TSC increase and disease severity. Impact: This pilot study mapping sodium homeostasis disturbances at the individual level in ALS patients through 23Na-MRI evidenced association between TSC increase and disease severity and may be a future biomarker to help stratifying patients and evaluating new therapeutics.
Myotonic Dystrophy type 1: susceptibility in Thalamus and Brainstem as biomarker of clinical impairment
Authors: Fiscone Cristiana , Rochat Magali , De Pasqua Silvia , Mitolo Micaela , Bianchini Claudio , Vornetti Gianfranco , Bartiromo Fiorina , Manners David , Avoni Patrizia , Liguori Rocco , Lodi Raffaele , Tonon Caterina
Published: November 2024

Motivation: QSM is a valuable tool for investigating neurodegenerative conditions, including DM1, a genetic multisystem disorder affecting the central nervous system. Goal(s): The objective of this research is to identify biomarkers of clinical impairment by exploring magnetic susceptibility in sub-cortical areas of DM1 brains. Approach: We developed an automated pipeline for segmenting various structures and their sub-units. DM1 susceptibility values were compared to healthy controls and correlated with clinical and laboratory data. Results: Thalamus and brainstem were identified as key structures, showing increased iron concentration and correlation with disability and polysomnography scores, contributing to a comprehensive understanding of DM1 and its symptomathology. Impact: Examining iron accumulation in sub-cortical structures through QSM contributes to a complete understanding of DM1 as a neurodegenerative disorder. Thalamus and brainstem, crucial in autonomic functions, exhibit alterations and correlations with clinical measurements, suggesting central origins of DM1 symptomatology.
A Universal Bz Coil for Uniform Multiphoton Excitation in High-Field MRI
Authors: Drago John , Davids Mathias , Stockmann Jason , Guerin Bastien , Wald Lawrence
Published: November 2024

Motivation: Contrast in high-field MRI is obscured by the spatially non-uniform excitation flip angle profile of conventional birdcage transmit coils. Goal(s): We demonstrate that a single $$$B_z$$$ coil operated in the kHz range can supplement a birdcage to create a spatially-uniform flip angle profile using multiphoton excitation. Approach: We use a stream function boundary element method to optimize the $$$B_z$$$ coil windings to produce homogeneous nonselective multiphoton excitations across a universal pulse database and validate with Bloch simulations. Results: The single $$$B_z$$$ channel achieved a mean flip angle NRMSE of 13.9% for a 90º target MP-pTx pulse in test subjects. Impact: The design method provides a simplified hardware configuration and reduced local SAR concerns compared to either conventional pTx or our previous work using a full shim array in conjunction with multiphoton parallel transmission.
Multinuclear MRI Using a Single Adaptable Transmit Hardware
Authors: Gudino Natalia
Published: November 2024

Motivation: Routine studies of nuclei other than 1H are constrained by the need of separate fixed tuned hardware. Goal(s): To increase flexibility of the multinuclear setup by developing an adaptable single transmit hardware to allow excitation of many low-frequency nuclei and 1H. Approach: The conventional remote broadband amplifier was replaced by an optically controlled dual-tuned on-coil amplifier for 1H and X-nuclei excitation. The amplifier can be automatically tuned to the selected frequency by pulse-width-modulation of an optically transmitted pulse. Results: Automatic tuning of a first prototype was possible for excitation of 13C, 23Na and 129Xe, while performance of 1H excitation at 7T was unaffected. Impact: The presented technology combined with new adaptable receive hardware can advance the implementation of routine multinuclear studies to extend research of X-nuclei and their potential clinical use.
Dynamic tracking of cardiac motion fields using multi-frequency scattering parameters of an RF array – an MRI based feasibility study
Authors: Steensma Bart , van den Berg Cornelis
Published: November 2024

Motivation: To enable high frame rate spatial mapping of cardiac mechanical motion with an array of RF antennas. Goal(s): Investigate the feasibility of estimating 2D motion fields based on measurements of wideband multi-channel RF scattering parameters. Approach: Paired CINE MRI and multi-channel wideband (55-1300 MHz) RF scattering measurements were acquired in vivo. Motion fields were determined from MRI, a Gaussian process regression model was trained and tested to predict motion fields from the RF scattering parameters. Results: 2D motion fields in a 4Ch CINE image of the heart can be reconstructed with high precision (RMS error 0.66mm) based on RF scattering measurements. Impact: We demonstrated feasibility of high precision and high framerate spatial motion mapping with RF antennas. Further validation with real-time MRI is warranted. This method could be applicable for motion tracking during medical imaging or in a low complexity care setting.
Improved 3D multi-contrast CMR for high-quality anatomical imaging and joint T1/T2 mapping in a single free-breathing scan
Authors: Kokhanovskyi Ivan , Crabb Michael , Ganter Carl , Castillo-Passi Carlos , Kunze Karl , Neji Radhouene , Karampinos Dimitrios , Makowski Marcus , Prieto Claudia , Botnar Rene
Published: November 2024

Motivation: Cardiovascular MR (CMR) provides comprehensive assessment of heart disease. However, conventional CMR examinations involve multiple sequential 2D acquisitions under breath-hold conditions. Goal(s): To devise and develop a novel 3D free-breathing sequence for simultaneous assessment of cardiovascular anatomy via bright- and black-blood imaging and myocardial tissue quantification in a single scan. Approach: Implementation of an improved iNAV-based 5-heartbeat interleaved sequence (proACTION) with distinct IR and T2 preparation modules and non-rigid motion correction for robust and accurate myocardial tissue quantification. Results: proACTION provides accurate delineation of cardiac and vascular structures, while demonstrating good agreement with conventional mapping sequences in healthy subjects. Impact: Comprehensive 3D whole-heart tissue characterization and clinically relevant anatomical information can be obtained in an efficient, free-breathing, and easier to use one-click-scan with the proposed proACTION approach.
Diffusion MRI of the Abdomen with Motion-robust Diffusion Encoding, Multi-shot Readout, and Optimized Slice-specific Shimming
Authors: Tollefson Aidan , Volety Srijyotsna , Lan Patricia , Guidon Arnaud , Wu Gaohong , Tamada Daiki , Pirasteh Ali , Hernando Diego
Published: November 2024

Motivation: Single-shot and multi-shot M1-optimized diffusion imaging (MODI) are recent DWI methods used to mitigate motion and distortion artifacts, yet they often experience chemical shift-based fat suppression failures in the abdomen. Goal(s): To optimize fat suppression in multi-shot MODI-DWI of the abdomen. Approach: Slice-specific chemical shift-encoded (CSE) data-informed optimization of shims is combined with single-shot and multi-shot MODI-DWI in 7 subjects imaged at 3T. Results: Improved fat suppression and water signal excitation were observed alongside the motion and distortion artifact reduction provided by multi-shot MODI-DWI. Unwanted fat signal was reduced through this technique in areas of interest such as the liver, spleen, and ribcage. Impact: Motion-robust, low-distortion DWI of the abdomen, with reliable fat suppression is demonstrated by combining multi-shot EPI, M1-optimized DW waveforms, and an optimized slice-by-slice shimming approach. This combined method may enable improved detection and staging of cancer in the abdomen.
Deep Learning Based Reconstruction for Multi-shot DWI of the Breast: Comparison of Quantitative ADC and Distortion
Authors: Chien Ning , Cho Yi-Hsuan , Chen Yi-Chen , Yeh Cheng-Ya , Chang Yeun-Chung , Lee Chia-Wei , Lin Chien-Yuan , Lan Patricia , Wang Xinzeng , Guidon Arnaud , Liu Kao-Lang
Published: November 2024

Motivation: Diffusion-weighted imaging (DWI) in breast imaging is constrained by image distortion, which can be mitigated through the utilization of multi-shot DWI (MUSE). Goal(s): We conducted a pilot study to investigate the impact of deep-learning reconstruction (DLRecon) on MUSE image quality. Approach: Compared with the non-DL MUSE images, the MUSE DLRecon showed higher SNR without affecting the mean ADC value. Moreover, employing a higher shots in MUSE DL with reduced NEX could provide less-distortion DWI. Results: Our preliminary results suggest the feasibility of MUSE-DWI in breast imaging with a higher number of shots. Impact: Our results suggest that the DLRecon could be beneficial for the regions prone to distortion and requiring a high density of diffusion direction information, in the complex diffusion modeling, all while maintaining a feasible scan time in breast MUSE imaging.
Motion-robust distortion-free breast diffusion-weighted MRI using DW-PROPELLER with deep learning reconstruction
Authors: Wang Pingni , Biswas Debosmita , Wilmes Lisa , Hylton Nola , Joe Bonnie , Senff Michael , Guidon Arnaud , Lan Patricia , Wang Xinzeng , Partridge Savannah
Published: November 2024

Motivation: EPI-based DWI suffers from ghosting, chemical shift, and distortion artifacts. FSE-based DW-PROPELLER has been shown to overcome the above artifacts but at the cost of longer scanner time. Goal(s): To evaluate the combination of DW-PROPELLER with a deep learning (DL)-based reconstruction to provide motion-robust distortion-free high spatial resolution breast DWI. Approach: Phantom and in-vivo breast images were acquired using DW-PROPELLER followed by both conventional and DL reconstruction. Results: DW-PROPELLER with DL showed less distortion, less chemical shift artifacts, and increased SNR and sharpness compared with multi-shot DW EPI in both phantom and in-vivo breast imaging. Impact: This work demonstrated the feasibility of using a deep learning-based approach to improve image sharpness, reduce noise, and chemical shift artifacts for motion-robust and distortion-free high spatial resolution diffusion-weighted breast imaging.
A new kinetic model for characterization of glucose delivery, transport and metabolism for MRS and dynamic glucose enhanced (DGE) MRI of the brain
Authors: Seidemo Anina , Knutsson Linda , Yadav Nirbhay , Wirestam Ronnie , Sundgren Pia , van Zijl Peter
Published: November 2024

Motivation: While PET, MR spectroscopy, and DGE CEST MRI can describe sugar uptake and utilization using a 2-tissue-compartment model, such a model is not appropriate for DGE CEST MRI of tumors, as the exchange properties of sugar hydroxyl protons may differ between tissue compartments. Goal(s): To develop a 3-tissue-compartment model (blood, EES and cell) suitable for DGE MRI. Approach: We modified the mass balance equations and simulated compartmental D-glucose concentrations from D-glucose levels of venous plasma. Results: The 3-tissue-compartment model was able to reproduce MRS literature brain D-glucose dynamic uptake curves, as well as experimental DGE MRI signal in brain tumors at 7 T. Impact: A 3-tissue-compartment model is necessary for correct quantification of DGE MRI in malignant brain tumors. Our proposed model is expected to improve modeling and assessment for all metabolic substrate uptake imaging methods in situations of BBB breakdown.
Unsupervised PK Model-free BBB Leakage Detection in DCE-MRI using Generative Adversarial Networks
Authors: Jang Joon , Lee Junhyeok , Lee Hyochul , Hwang Inpyeong , Choi Seung Hong , Park Jung Hyun , Kim Hyeonjin , Choi Kyu Sung
Published: November 2024

Motivation: Arterial input function (AIF) in DCE-MRI is often degraded due to noise, motion, and partial volume. This may lower the overall reliability of the resulting pharmacokinetic (PK) parameters. Goal(s): Our goal was to develop a robust, fast method for detecting blood-brain barrier (BBB) leakage signals without PK models. Approach: We employed a fast anomaly detection using generative adversarial networks (f-AnoGAN) for unsupervised detection of the leakage signals. Results: The results were highly correlated with the traditional Ktrans maps, and more robust against reduced temporal data points, which may be used for shorter scan time and/or higher spatial resolution. Impact: Our proposed method may allow fast and robust detection of BBB leakage signals in the case where the scan time is highly limited, and consequently, the traditional approach with PK models may not be suitable.
Evaluating metabolic disruption following radiotherapy in the developing brain: a preclinical juvenile model
Authors: Helsper Shannon , Sterpin Edmond , Himmelrecih Uwe
Published: November 2024

Motivation: Cognitive performance in paediatrics is severely impacted by current brain tumour treatment plans such as radiotherapy. Goal(s): Our goal is to decipher the underlying mechanism of this cognitive decline, which remains unknown and is particularly difficult to decipher in paediatric patients due to confounding developmental variables. Approach: Longitudinal 1H MRS analysis in the brain following radiotherapy in a juvenile rat model provides valuable insight into metabolic disruption. Results: Myo-inositol levels, linked to other neurodegenerative and cognitive conditions, were elevated in the hippocampus and cerebellum. Deviance in N-acetyl-aspartate levels between irradiated and healthy rats over a developmental period of 12.5 weeks was also revealed. Impact: 1H MR spectroscopy reveals valuable insight into longitudinal impacts of radiotherapy on the developing brain. A juvenile rat model enables acute and chronic alterations in inflammatory markers, membrane synthesis, bioenergetics and viability to be monitored, distinguishing irradiation and development effects.
Longitudinal Changes of BBB Permeability and transcytolemmal permeability in Alzheimer’s Disease Mice: A Non-Contrast MRI Study
Authors: Xiong Chuhan , Yin Yu , Zhu Qinfeng , Ba Ruicheng , Jin Zhecheng , Wei Zhiliang , Lin Zixuan , Wu Dan
Published: November 2024

Motivation: BBB disruption is demonstrated in Alzheimer’s disease (AD) but how does it change during the progression of disease, and its relationship with transcytolemmal water exchange are not clear. Goal(s): We aimed to evaluate the longitudinal changes of water exchange across BBB and across cytomembrane in AD mice. Approach: BBB permeability and transcytolemmal permeability to water were assessed in 3xTg-AD mouse from 6 to 10 months of age using WEPCAST and tDKI MRI, respectively. Results: Elevation of BBB permeability in AD mice started as early as 6 months. Transcytolemmal permeability was found to increase in the hippocampus. Impact: Current results suggested the potential role of BBB and transcytolemmal permeability as a biomarker in the early detection of AD. Their co-increase may be related to the altered glymphatic function.
Frequency Modulated Continuous Wave Radar-based respiratory motion correction for cardiac MRI: Initial Results
Authors: Diao Jemon , Liu Yang , Zhu Jiayu , Xu Jian , Zhou Zijian , Qi Haikun , Hu Peng
Published: November 2024

Motivation: Cardiac MRI is susceptible to motion-induced artifacts because of the sequential data acquisition process. Goal(s): Evaluate the feasibility of utilizing a Frequency Modulated Continuous Wave (FMCW) Radar as a quantitative respiratory motion correction signal for free-breathing cardiac MRI. Approach: A short calibration scan was performed to establish a motion model relating the FMCW Radar signal to the respiratory-induced heart motion. The established model was then applied during the imaging scan to perform retrospective motion correction for each k-space readout line. Results: The FMCW radar showed good correlation to the respiratory-induced heart motion, and the proposed method effectively improved the image quality. Impact: This study demonstrated the feasibility of utilizing FMCW radar as a surrogate to accomplish motion correction in free-breathing cardiac MRI.
Respiratory Triggered MRI using an NMR-on-a-chip Sensor
Authors: Bschorr Fabian , Hüfken Thomas , Lobmeyer Tobias , Dreyer Frederik , Zhao Jianyu , Anders Jens , Rasche Volker
Published: November 2024

Motivation: We propose an NMR-on-a-chip sensor as contactless und hysteresis-free alternative for conventional respiratory belts in respiratory-triggered MRI. Goal(s): The objective of this work was to demonstrate the feasibility of a local field probe for monitoring respiratory motion induced magnetic field changes as respiratory motion surrogate. Approach: Respiratory belt and field probe signal were recorded simultaneously clearly showing the accurate identification of the respiratory stage by the field probe. Results: The field probe signal was analysed and fed back to the MR scanner in real-time for proofing its applicability for triggered lung MRI, yielding a sharp lung-liver interface compared with the non-triggered version. Impact: The feasibility of NMR-on-a-chip sensors for monitoring physiologically-induced magnetic field variations is shown. They enable contactless, hysteresis-free and easy-to-use monitoring of physiologically-induced field variations, which can be fed back to the scanner for real-time respiratory motion monitoring and triggering.
High resolution 3D isotropic non-rigid motion compensated T1 Dixon of Liver at a hybrid PET-MR scanner
Authors: Penney Jake , Ambarki Khalid , Monnet Aurélien , Necib Hatem , Vilgrain Valérie , Kunze Karl-Philipp , Botnar René , Prieto Claudia , Sinkus Ralph
Published: November 2024

Motivation: In current clinical practice, liver MRI scans often suffer from motion artifacts. This issue typically arises because patients struggle to maintain breath-holding. Goal(s): Our goal is to produce a high-quality, isotropic 3D Dixon T1 scan without the need for breath-holding. Approach: . Our method involves using a navigator to estimate liver motion, enabling us to calculate non-rigid motion fields for image reconstructionResults: This approach yields high-quality free-breathing isotropic T1 3D Dixon liver data with a voxel size of 1.3mm³, surpassing the quality of the gold standard non-isotropic breath-hold Dixon T1 liver scan. Impact: This work aims to deliver previously unseen high-quality free-breathing isotropic 3D Dixon liver data that can surpass the current clinical standard breath-hold non-isotropic T1 3D Dixon liver scans.