bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-time MRI in axial plane allows quantitative evaluation of mandibular condyles motion symmetricity
Authors: Isaieva Karyna , Leclère Justine , Dubernard Xavier , Felblinger Jacques , Vuissoz Pierre-André
Published: August 2023

Current diagnosis of temporomandibular disorders includes clinical examination and MRI; however, static MR images in only two key positions are not sufficient for detection of some cases of temporomandibular disk displacement. We acquired jaw opening and closure movements for 5 healthy volunteers with a real-time MRI in axial plane. The condyles were segmented with a convolutional neural network approach and motion curves of their mass centers were calculated. It was shown that the proposed protocol gives straighforward evaluation of condylar motion assymetry.
Comparison of New MR Approaches for Accelerated Knee Imaging
Authors: Goyal Ananya , Beaulieu Christopher , Fung Maggie , Kolupar Trevor , Chaudhari Akshay , Stevens Kathryn , Kogan Feliks
Published: August 2023

Conventional knee MRI protocols use numerous 2D-FSE sequences with multiple contrasts, which have long scan times and don’t fully use modern parallel imaging and improved SNR technologies.In this abstract, we outline four approaches that reduce protocol times to <6 minutes and potentially add diagnostic value through quantitative data or oblique reformats.These include an accelerated conventional 2D protocol, SNR-efficient 3D qDESS and CUBE approaches, and a thin-Slice protocol with high slice resolution.We propose a study that will evaluate the performance of each of these knee MRI protocols, and determine diagnostic utility and confidence with respect to fluid sensitivity and tissue pathologies.
Correcting for gradient non-linearity in concurrent field monitoring
Authors: Dubovan Paul , Gilbert Kyle , Baron Corey
Published: August 2023

Concurrent field monitoring (FM) via integration of field probes in a radiofrequency coil provides advantages over sequential field monitoring that include patient-specific corrections, as well as improvements to user workflow. However, specific design considerations can require placing field probes far from isocentre where gradient fields are no longer linear, reducing data integrity when fitting high order spatially varying terms. We propose a three-part correction algorithm that seeks to correct these errors and compare FM data, as well as reconstructed images, before and after correction. Correction improved integrity of FM data and enhanced quality of anatomical and diffusion weighted images.
Convex Optimized Diffusion Encoding (CODE) with Partial Fourier Imaging for EPI Diffusion Weighted Imaging
Authors: Middione Matthew J. , Cork Tyler , Loecher Michael , Sprenger Tim , Guidon Arnaud , Vasanawala Shreyas , Ennis Daniel B.
Published: August 2023

Diffusion weighted imaging typically uses monopolar (MONO) diffusion gradient waveforms, which may have sequence dead time that extends the TE and reduces the SNR. Partial Fourier (PF) imaging is routinely used in DWI to shorten the TE (improving SNR), but can lead to image blurring. Convex Optimized Diffusion Encoding (CODE) is a constrained optimization technique that designs time-optimal diffusion encoding gradient waveforms without sequence dead time. CODE produces a shorter TE than MONO, which leads to increased SNR. Herein, we show that CODE without PF has increased SNR and reduced image blurring compared to MONO with PF=6/8.
Optimal Control of the contrast in a MP-RAGE sequence: an application on the pelvis
Authors: Vernier Benoît , Van Reeth Eric , Lapert Marc , Hamelin Olivier , Beuf Olivier , Ratiney Hélène , Pilleul Frank
Published: August 2023

MRI contrast enhancement by Optimal Control is a new approach to design optimal magnetization preparation. This allows to maximize the contrast between target tissues characterized by their relaxation times. Recent numerical implementations have made possible the optimization of such preparation in a steady state sequence without full recovery between each repetition. This abstract demonstrates the contrast flexibility offered by this approach when combined with a MPRAGE sequence on pelvis imaging at 3T.
Fast 3D Isotropic High-Resolution MRI of Mouse Brain Using a Variable Flip Angle RARE Sequence With T2 Compensation @9.4T
Authors: Hung Lisa , Herrman Karl-Heinz , Reichenbach Jürgen
Published: August 2023

Some applications require T2-weighted mouse brain MRI with isotropic high resolution (100µm3), but at 9.4T the short T2 of mouse brain limits the echo train length of RARE sequences and exacerbates T2-decay artifacts. Adapting a RARE sequence by using variable ﬂip-angles allows a reduction in scan time from 19min to 7-9min with similar image quality. However, long RARE echo trains and strong imaging gradients can unintentionally cause substantial diﬀusion weighting. To minimize the diﬀusion eﬀects crusher gradients were optimized and the variable ﬂip angles were kept above 40°.
Simultaneous T2-weighted Real-time MRI of 2 Orthogonal Slices
Authors: Hickey Samantha , Reichert Andreas , Bortfeld Thomas , Bock Michael
Published: August 2023

In cancer radiotherapy, MR-guidance allows for superior tumor visualization and real-time target volume tracking. Real-time pulse sequences for MR-guidance require high acquisition speeds and good tumor-to-background contrast, which is often achieved with T2-weighted acquisitions. Here, we combine a real-time sequence with orthogonal slices with a T2w echo-shifted contrast and demonstrate its use under breathhold and free-breathing conditions in a volunteer.
Evaluation of breast cancer using IVIM-Kurtosis and compartmental tracer kinetic models through semi-automated segmentation
Authors: Bove Natalia Massaccesi , Padin Trinidad González , Fino Daniel , Brandi Nicolás Moyano , Lisazo Clara , Salcedo Leandro , Nicolini Federico González , Ariza Pedro , Isoardi Roberto , Lorca María , Allard Cristian , Saucedo Verónica
Published: August 2023

This study aims to evaluate the correlation between the IVIM-DKI models (which describe pure and pseudo diffusion) and the quantitative and semiquantitative parameters from dynamic contrast-enhanced (DCE) MRI (that analyze vascular permeability and pharmacokinetics). A Python algorithm was implemented to adjust the intensities of 12 b-values DWI to a biexponential function modeling the IVIM and DKI. Then, the statistical association between these parameters and the DCE MRI was evaluated with a Pearson’s correlation coefficient. The f and D* factors are both good biomarkers for the evaluation of perfusion properties, according to the examined correlation between all the parameters.
Comparison between IVIM-DKI, MRE and DCE-Tofts quantitative techniques at 3.0 T multiparametric prostate protocol
Authors: Padin Trinidad González , Brandi Nicolas Moyano , Pópolo María Del , Bove Natalia Massaccesi , Chacon Clara , Gonzalez Federico , Isoardi Roberto , Ariza Pedro , Dominguez Andrés , H Eduardo , de Figuereido M.S.G , Villamil Daniel Fino
Published: August 2023

Since there is no clear relationship between the coefficients of the DWI biexponential model and permeability and pharmacokinetics, we aim to correlate the coefficients associated to the IVIM-DKI model, MRE, and quantitative and semiquantitative maps of the multiparametric prostate protocol. Through a Python algorithm, the DWI data acquisition was fitted to an IVIM-DKI function after a semi-automatic segmentation. Then, PR, PCa and healthy tissue were evaluated, and the IVIM-DKI parametric maps were contrasted with the DCE and MRE through a Pearson’s correlation test. Empirical relationships were established between the pseudo-perfusion models, semiquantitative maps and the variables of the compartmental models.
Multi-parameter Magnetic Resonance Quantitative Evaluation of Pancreatic Cancer with Vascular Invasion
Authors: Zhou Mi , Yin Long-Lin , Wu Yunzhu
Published: August 2023

In this study, the sensitivity, specificity and accuracy of quantitative parameters derived from T2WI+DKI+DCE combined model for pancreatic cancer vascular invasion were evaluated based on the pathological results as the gold standard. Combined T2WI+DKI+DCE quantitative analysis can improve the specificity and accuracy of diagnostic efficiency of pancreatic cancer vascular invasion. There were significant differences in MD, MK, Ktrans, Kep and Ve between vascular invasion group and non-vascular invasion group. The diffusion parameters and perfusion information are highly consistent, which can provide reliable evidence for preoperative non-invasive diagnosis and treatment of pancreatic cancer.
A generalized deep learning network for fractional anisotropy reconstruction: application to epilepsy and multiple sclerosis
Authors: Gaviraghi Marta , Ricciardi Antonio , Palesi Fulvia , Brownlee Wallace , Vitali Paolo , Prados Ferran , Kanber Baris , Wheeler-Kingshott Claudia Gandini
Published: August 2023

Quantitative maps obtained from Diffusion Tensor are very useful for investigating microstructural changes that occur in brain diseases. However, the long acquisition times required for a fully sampled diffusion-weighted space makes their clinical use unfeasible. Here we have adapted a U-net that obtains reliable Fractional Anisotropy (FA) maps from a reduced set of 10 Diffusion Weighted volumes (that can be acquired in less than 1 min). Our network was applied to two independent, clinical datasets, without retraining, and produced FA that retained clinical sensitivity and characteristic FA value distributions in the brain white matter.
A diffusion MRI tractometry approach in cerebral small vessel disease
Authors: Chamberland Maxime , Tuladhar Anil , Dewenter Anna , Cai Mengfei , Jacob Mina , Telgte Annemieke ter , Wiegertjes Kim , Zwiers Marcel , Marques José , Tax Chantal , Duering Marco , de Leeuw Frank-Erik , Norris David
Published: August 2023

In a cohort of 54 patients with sporadic cerebral small vessel disease, associations between diffusion MRI measures and processing speed were investigated both at low and high b-values, revealing complementary microstructural information. Associations with processing speed found by skeletonization were confirmed with an independent tractometry approach, which was further utilized to identify a set of association tracts associated with cognition.
A separation between motor and sensory somatotopic maps in the human cerebellum
Authors: Brouwer Emma , Priovoulos Nikos , van der Zwaag Wietske
Published: August 2023

We investigated the organisation of the cerebellar digit map with three distinct tasks (flexing/extending/stroking) using B1-shimmed, high-resolution fMRI at 7T. For all tasks, the positions of the COG of the digit representations formed an orderly progression in at least one of the lobules. The distance between the motor task activations for flexing and extending of the digits were smaller than from either motor task to stroking clusters, indicating a separation between somatosensory and motor clusters in cerebellar lobule V.
Brain-to-brain interaction in parent-child eye contact
Authors: Lee Ray , Friedman Joshua , Khadar Alaa , Karaiskaki Andrea , Gura Nadiya , O'Brien Maria , Sajda Paul , Tottenham Nim
Published: August 2023

Parent-child interaction is a significant part of human life, and a large portion of such interaction is carried out by eye contact. However, how the dyadic brain networks enable eye contact is not well understood. Here, we take advantage of fMRI hyperscan and concurrent eye tracking to measure the BOLD responses and pupil sizes during eye contact between parent and child. Our initial analysis begins to reveal some of the brain networks supporting the parent-child bond. A better understanding of such mechanisms may have a significant impact on human social life, and improve parent-child interaction therapy for many psychiatric diseases.
In vivo direct imaging of visually evoked neuronal responses at milliseconds temporal resolution
Authors: Toi Phan Tan , Kim Jun-Ho , Park Jang Woo , Park Jang-Yeon
Published: August 2023

There has been a long-standing demand for high temporospatial resolution in non-invasive neuroimaging. Using our previously proposed approach for direct imaging of neuronal activity (DIANA-fMRI) with a high temporal resolution of milliseconds, we continued to demonstrate DIANA-fMRI performance in mice in vivo at 9.4T using visual stimulation. The DIANA signal change was significantly increased (~0.2-0.4%) in response to flashing light stimulus, and it was found that DIANA responses of sSC, V1, and V2 were sequentially activated in that order. The DIANA response times of sSC, V1, and V2 were consistent with previous electrophysiological studies.
Power Laws for Neurovascular Coupling between Cerebral Blood Flow and Oxygen Metabolism
Authors: Li Linqing , Blockley Nicholas , Marrett Sean , Derbyshire Andy , Bandettini Peter
Published: August 2023

We previously developed (CMRO2/CMRO20)=(CBF/CBF0)(1-α/β)(1-1/β)as special power relation (SPR) for brain activation. In this work, based on different perspective of SPR, we derive that functional activity induces general power relation (GPR) (CMRO2/CMRO20)=(CBF/CBF0)α/β. When α=0.38,β=1.5, both powers (SPR and GPR) are calculated to be 0.25,which is approximately equivalent to inverse of conventional coupling constant of 4. By equalizing two powers, the relationship of α and β parameters can be established. We also show that any coupling pairs between changes of CMRO2,CBF,CBV and OEF can be reduced into power laws. Finally, we propose the power law for quantification CMRO2 changes during CO2 calibration.
Regional variation in the linear relationship between breath-hold cerebrovascular reactivity and BOLD fMRI activation
Authors: Williams Rebecca , Specht Jacinta , MacDonald M. Ethan , Pike G. Bruce
Published: August 2023

Cerebrovascular reactivity (CVR) and task-based BOLD fMRI signals are closely linked. Understanding whether the relationship between CVR and task-based BOLD responses varies across the brain is important for interpreting BOLD, particularly in studies of aging where both CVR and BOLD activation differences are observed. Therefore, this work aimed to investigate the linear relationship between breath-hold (BH) CVR and task-based BOLD across the cerebral cortex to different cognitive tasks. Significant linear relationships were observed in posterior regions independent of task, while anterior regions were task-specific. These findings might contribute to understanding age-related posterior-anterior BOLD activation differences commonly observed in fMRI studies.
Evaluating cerebrovascular reactivity dynamics through a Bayesian inference approach
Authors: Pinto Joana , Craig Martin , Croal Paula , Blockley Nicholas , Chappell Michael , Bulte Daniel
Published: August 2023

Cerebrovascular reactivity (CVR) has been shown to be an important parameter that is altered in certain pathologies. Analysis strategies using MRI data typically assume similar responses across the brain, neglecting the need and potential of modelling temporal features. In this work, we propose and test a novel method for the evaluation of CVR dynamics based on a variational Bayesian approach. Although this method yields similar CVR results to more standard approaches, it is more time efficient and has the potential to improve modelling by incorporating non-linear and biophysically informed models.
Optical and fMRI responses to activation of GABAergic parvalbumin and somatostatin neurons.
Authors: Vo Thanh Tan , Im Geunho , Kim Seong-Gi
Published: August 2023

The GABAergic neurons directly and indirectly regulate hemodynamics. Thus, investigating neurovascular coupling of subtype interneurons is highly important to interpret fMRI data, especially optogenetic fMRI. However, role of subtype interneurons to fMRI is not known. Here, we measured multi-wavelength optical imaging and CBV-weighted fMRI to investigate hemodynamic and metabolic responses of two most common interneuron subtypes, parvalbumin (PV) and somatostatin (SOM). PV induced biphasic hemodynamic responses, initial decrease and later increase, whereas SOM produced only positive hemodynamic responses. In both PV and SOM interneurons, dilation was initiated from the cortical surface.
High-Field Magnetic Resonance Microscopy of Aortic Plaques in a Mouse Model
Authors: Gullette Sean , Andrews Stephen , Whalen Courtney , Mattie Floyd , Ge Ximing , Ross Catharine , Castro Rita , Neuberger Thomas
Published: August 2023

Currently, histological methods of plaque analysis in aortas from murine models of atherosclerosis do not allow for a holistic view of the vascular lesions. Using high-field MRI, plaque volume in Apoe-/- mice can be analyzed, and when compared to traditional histology, has a higher throughput and is non-destructive. Using a 3D gradient echo sequence at 14 tesla, high-resolution images of the aortas were achieved. The images were segmented and quantified providing a 3-dimensional view of plaque distribution and volume. Overall, using a high-field MRI system allowed for a detailed and complete view of vascular components.
Plaque to Myocardium Ratio in T1-weighted Magnetic Resonance Imaging­: Analysis of Variabilities and Method for Standardization
Authors: Lu Meng , Han Hui , Li Debiao , Xie Yibin
Published: August 2023

Plaque to Myocardium Ratio (PMR) based on T1-weighted MRI is an important quantitative biomarker to classify high-risk coronary plaque. However, it is calculated based on relative signal intensities, therefore, sensitive to variations in physiological and acquisition conditions. In this work, Bloch simulations were performed to explore the impact of heart rate, echo spacing, flip angle, and the number of readout segments on PMR. A computational model was further proposed to effectively reduce the acquisition-related PMR variations demonstrated in simulations and in vivo studies. The proposed method may potentially improve the precision of PMR and facilitate its comparison in longitudinal studies.
Whole-Heart Free-Breathing 3D Cardiac Cine with Fast Respiratory Motion Compensated Reconstruction
Authors: Meineke Jakob , Schülke Christophe , Nehrke Kay , Keupp Jochen
Published: August 2023

Whole-Heart, Free-Breathing 3D Cardiac Cine MRI with a cartesian, water-selective, balanced SSFP acquisition and spiral-like undersampling is combined with fast, non-rigid motion-compensated reconstruction. It demonstrates the feasibility of routine cardiac cine MRI with minimal planning effort and minimum patient discomfort by avoiding the need for breathholds. The combined acquisition and reconstruction time is below 5 minutes, including computation of deformation vector fields, and minimizes image production delay by starting reconstruction on partially acquired data.
sim2real: Cardiac MR image simulation-to-real translation via unsupervised GANs
Authors: Amirrajab Sina , Khalil Yasmina Al , Lorenz Cristian , Weese Jürgen , Pluim Josien , Breeuwer Marcel
Published: August 2023

There has been considerable interest in the MR physics-based simulation of a database of virtual cardiac MR images for the development of deep-learning analysis networks. However, the employment of such a database is limited or shows suboptimal performance due to the realism gap, missing textures, and the simplified appearance of simulated images. In this work we 1) provide image simulation on virtual XCAT subjects with varying anatomies, and 2) propose sim2real translation network to improve image realism. Our usability experiments suggest that sim2real data exhibits a good potential to augment training data and boost the performance of a segmentation algorithm.
Prospective Evaluation of Machine Learning Prescription of Cardiac MRI Planes in Children with Congenital Heart Disease
Authors: Hong Cheng , Bahrami Naeim , Sheth Vipul , Vasanawala Shreyas
Published: August 2023

Cardiac MRI plays an important role in defining cardiac anatomy and function in children with heart disease. Prescription of diagnostic planes in cardiac MRI requires specialized training, limiting availability. Machine-learning based prescription has the potential to allow rapid, consistent acquisition of these planes independent of operator, but performance in congenital heart disease is unknown. This study evaluates the utility of such a system which demonstrates performance in children with mild to moderate heart disease similar to healthy adult volunteers. As expected, the system does not generate acceptable results in severe intracardiac anomalies.
CNN-based Off-resonance Correction in Cardiac Spiral MRI
Authors: Wang Shishuai , Ferreira Pedro , Khalique Zohya , Gorodezky Margarita , Roehl Malte , Pu Jialin , Pennell Dudley , Nielles-Vallespin Sonia , Scott Andrew
Published: August 2023

Spiral trajectories are time efficient but are susceptible to off-resonance artefacts. Many approaches to off-resonance correction require a high-quality B0 field map. Here we train a convolutional neural network to remove the off-resonance artefacts using simulated cardiac spiral MRI and validate our methods by applying this network to diffusion tensor cardiovascular MR (DTCMR) data acquired with spiral trajectories.
Improving U-Net based segmentation in cardiac parametrical T1 mapping by incorporating bounding box information
Authors: Viezzer Darian , Hadler Thomas , Blaszczyk Edyta , Fenski Maximilian , Gröschel Jan , Lange Steffen , Schulz-Menger Jeanette
Published: August 2023

Parametric mapping images contain to a large extent irrelevant background information. In order to hide some of it, we incorporated bounding box information into a U-net based segmentation network. Our dataset consisted of 845 training, 102 validation and 146 test T1 maps of native and post-contrast myocardium from different clinical studies, including healthy volunteers and patients with inflammatory heart disease, muscular dystrophies or chronic myocardial infarction. While cropping the image input improved the segmentation itself, a second input of the bounding box mask reduced the mean absolute and mean squared T1 deviation, which is clinically preferred.
Rapid Free-breathing 3D SPirAl Respiratory and Cardiac Self-gated (SPARCS) Cine Acquisition Using an Undersampled Stack-of-Spirals
Authors: Wang Xitong , Wang Junyu , Zhou Ruixi , Salerno Michael
Published: August 2023

Cardiac cine images are the gold standard techniques for analyzing cardiac function. Clinical breath-held ECG-gated Cartesian cine imaging requires 10-12 breath-holds to cover the left ventricle. Our group has developed a continuous-acquisition respiratory and cardiac self-gated cine sequence (SPARCS) for free-breathing cardiac function acquisition using 2D spiral acquisition can suffer from through-plane motion. Thus, we develop a rapid 3D self-gated cine technique using a variable density undersampled stack of spiral gradient echo sequence to provide 3D coverage of the ventricle enabling thinner slice acquisition and improved robustness to through-plane motion.
Changes in CMR Parameters and Prediction of Cardiac Complications in Thalassemia Major: Fibrosis Tells Us More than Iron.
Authors: Meloni Antonella , Pistoia Laura , Giuliano Pietro , Giunta Nicola , Schicchi Nicolò , Grassedonio Emanuele , Renne Stefania , Positano Vincenzo , Pitrolo Lorella , Roberti Maria Grazia , Sanna Paola Maria Grazia , Cademartiri Filippo , Pepe Alessia
Published: August 2023

Seven-hundred and nine patients with thalassemia major who performed a baseline and a 1st follow-up CMR scan after 18 months were followed prospectively in order to evaluate the predictive value of changes in CMR parameters (myocardial iron, biventricular function, and replacement myocardial fibrosis) for cardiac complications. During a mean follow-up of 89.4±33.3 months, cardiac events (heart failure, arrhythmias, and pulmonary hypertension) were recorded in 7.1% of patients. In the univariate Cox regression analysis, cardiac iron clearance and replacement myocardial fibrosis were identified as univariate prognosticators but in the multivariate analysis only myocardial fibrosis remained an independent predictor factor.
Increased GABA in the periaqueductal grey of patients with chronic low back pain detected using 1H-magnetic resonance spectroscopy
Authors: Sirucek Laura , Zoelch Niklaus , Schweinhardt Petra
Published: August 2023

Preclinical studies suggest a role of altered γ-aminobutyric acid (GABA)ergic inhibitory tone in the periaqueductal grey (PAG), a key brain area for descending pain modulation, as mechanism contributing to chronic pain. The present 1H-magnetic resonance spectroscopy study investigated GABA, and glutamate/glutamine, concentrations in the PAG of patients with chronic low back pain (CLBP). Using a point resolved spectroscopy sequence with optimized frequency alignment, adequate spectral quality was achieved and increased GABA concentrations (p=0.027) identified in CLBP patients compared to pain-free controls. This finding supports dysregulations in descending pain modulation as factor contributing to chronic pain in humans.
Hybrid diffusion imaging in chronic traumatic brain injury: Longitudinal investigation and correlation with clinical outcome
Authors: Muller Jennifer , Kang KiChang , Middleton Devon , Alizadeh Mahdi , Vedaei Faezeh , Zabrecky George , Monti Daniel , Wintering Nancy , Bazzan Anthony , Wu Chengyuan , Wu Qianhong , Mohamed Feroze
Published: August 2023

Traumatic brain injury (TBI) is a major cause of death and disability worldwide. Currently, non-invasive and longitudinal assessment in TBI is still limited. In the current study, we applied an advanced hybrid diffusion imaging sequence (HYDI) to capture both diffusion tensor imaging and neurite orientation dispersion and density imaging to develop more sensitive biomarkers associated with longitudinal outcomes after TBI. We both contrasting and complementary correlates between diffusion metrics and clinical outcomes, suggesting HYDI to have potential clinical impact for treatment monitoring after TBI.
A Novel Acquisition Strategy for Volumetric Diffusion-Weighted Imaging using Variable Density TSE-CASPR
Authors: Fonseca Sebastian , Lin Sheng-Qing , Zhou Limin , Wang Yiming , Madhuranthakam Ananth
Published: August 2023

Diffusion weighted imaging (DWI) is a highly valuable MR imaging technique in the clinic. Single-shot EPI is the reference standard sequence for DWI due to its speed, however it suffers from severe distortion artifacts that can obscure potential pathologies. In this abstract, we present a novel 3D acquisition strategy that uses a fast spin echo readout and variable density sampling for volumetric DWI. The oversampled center region serves as navigator to correct phase errors. We present preliminary results in brains of healthy volunteers compared to the standard sequences used in DWI.
Self-Gated Zero Echo Time Imaging of the Lung
Authors: Frantz Hanna , Lobmeyer Tobias , Metze Patrick , Hüfken Thomas , Stumpf Kilian , Rivoire Julien , Murad Hizami , Rasche Volker
Published: August 2023

Zero echo time (ZTE) imaging is an established approach for three-dimensional imaging of tissues and materials with ultrashort T2* relaxation times. An intrinsic disadvantage of this approach are missing data points in the center region of k-space due to hardware limitations. These missing points are often retrospectively interpolated or subsequently acquired using single-point imaging approaches or additional ZTE acquisitions with decreased resolutions. The presented approach relies on an interleaved combination of ZTE read-outs with different resolutions in combination with Compressed Sensing, to acquire the k-space center, thus enabling k-space based self-gating.
Predicting Perfusion Augmentation Using Deep Learning without Vasodilators
Authors: Zhao Moss , Hussein Ramy , Moseley Michael , Zaharchuk Greg
Published: August 2023

We present a deep learning technique to predict cerebral perfusion after vasodilation challenges. A 3D convolutional neural network (CNN)-based encoder-decoder architecture was constructed to transform ASL perfusion images acquired pre-vasodilation into post-vasodilation images using an improved attention-gated 3D U-Net. Results showed that the prediction and ground truth were not significantly different. This technique will enable a drug-free MR procedure to study the hemodynamic of patients with high risk cerebrovascular diseases.
Grey Matter Connectome Data Analysis and Classification of Multiple Sclerosis Clinical Profiles
Authors: Barile Berardino , Stamile Claudio , Van Huffel Sabine , Sappey-Marinier Dominique
Published: August 2023

Multiple Sclerosis (MS) is an autoimmune inflammatory disease characterized by white matter (WM) lesions and gray matter (GM) degeneration leading to cognitive and physical impairments. Recently, brain connectivity techniques were developed to better characterize such brain damages in association with the clinical profiles of MS patients. In this study, we proposed a complete automated pipeline to first extract global graph metrics from the morphological brain connectivity based on GM tissue thickness and second to train a higher-level ensemble of four machine learning models for the classification of MS clinical profiles using only the T1-weighted image modality.
Analysing The Role Of Model Uncertainty in Flourine-19 MRI using Markov Chain Monte Carlo methods
Authors: Javanbakhat Masoumeh , Starke Ludger , Waiczies Sonia , Lippert Christoph
Published: August 2023

Deep learning (DL) has achieved state of the art results in semantic segmentation of numerous medical imaging applications. Despite promising results deep learning models tend to produce point estimates as outputs which leads to overconfident, miscalibrated predictions. These overconfident predictions are specifically problematic in medical applications. Hence, providing a measure of a system’s confidence to identify untrustworthy predictions is essential to guide clinical decisions. Here we propose a 3D Bayesian segmentation model to provide uncertainty estimation for the Fluorine-19 MRI dataset based on Stochastic Gradient Markov Chain Monte Carlo methods.
Deeping-Learning based acceleration for Serial MR imaging using Transformer (SMR-Transformer): Comparison with CNN on Three Datasets
Authors: Liu Chuyu , Chen Shuo , Chen Yibing , Li Rui , Song Xiaolei
Published: August 2023

Serial image acquisition is always required for quantitative and dynamic MRI, in which the spatial and temporal resolution as well as the contrast is restricted by acquisition speed. Herein we employed a novel transformer based deep-learning method for reconstruction of highly under-sampled MR serial images. The network architecture and input were designed to take advantages of Transformer’s capacity on global information learning along the redundant series dimension. SMR-transformer was compared with 3D Res-U-Net, on a self-acquired CEST dataset, a cardiac dataset from OCMR and a diffusion dataset from HCP. Both images and quantitative comparison indicated SMR-Transformer allowed fast serial MRI.
Dissolved-phase 129Xe longitudinal relaxation times at low and high magnetic field strengths
Authors: Bryden Nicholas , Kelley Michele , McHugh Christian , Branca Rosa
Published: August 2023

We provide longitudinal relaxation measurements of hyperpolarized (HP) 129Xe gas dissolved in a variety of solvents at both low and high magnetic field strengths. The method of measuring T1 presented here is less sensitive than more commonly used methods to RF flip angle miscalibration, which has caused the significant variation in dissolved-phase 129Xe T1 values reported in the past. A field dependent study of gas depolarization by hollow membrane fibers commonly used to dissolve xenon in blood or other solvents is also included, which provides insight to experimental limitations on their use in both field regimes.
Initial Evaluation of Neuroimaging at 0.55T
Authors: Lavrova Anna , Ropella-Panagis Kathleen , Dudek Nancy , Morehouse Joel , Kurokawa Ryo , Kurokawa Mariko , Itriago-Leon Pedro , Moritani Toshio , Seiberlich Nicole
Published: August 2023

The purpose of this study was to determine which sequences can be immediately deployed for brain and spine imaging on a low-field 0.55T MRI system, with the goal of generating optimized protocols which can be used at other sites for routine clinical neuroimaging. The image quality of 174 brain and spine images was rated by two neuroradiologists. Almost all brain (T1w, T2w, FLAIR, DWI, MRA) and spine (T1w, T2w, DIXON) sequences received image quality scores corresponding to acceptable diagnostic image quality. These sequences form numerous neurological MRI protocols, which based on these results could be collected at 0.55T.
Simulation Evidence for use of a Denoising Auto-Encoder (DAE) to Improve Ultra-Low Field (64mT) MRI with a High Field (3T) Prior
Authors: MacDonald M. Ethan , Fikre Eremiahs , Vega Fernando , Addeh AbdolJalil
Published: August 2023

In this work, the denoising autoencoder is applied to simulated low field, low resolution, low signal-to-noise images and used to recover the high field, high resolution, high signal-to-noise paired image. Different types of noise, gaussian and chi-squared, is added in simulation. We found that the denoising autoencoder worked slightly better for normally disturbed noise, but not in all cases. We found a linear trend between the model performance with RMSE and the standard deviation of the added noise. This work demonstrates the use of simple and robust denoising autoencoder to improve low field MRI.
Scan acceleration by oversampling in a 70 mT MRI scanner
Authors: Galve Fernando , Algarín José Miguel , Guallart Teresa , Pellicer Rubén , Pallás Eduardo , González José Manuel , Vives Yolanda , Bosch Rubén , López Guillermo , Rigla Juan Pablo , Borreguero José , Ríos Alfonso , Benlloch José María , Alonso Joseba
Published: August 2023

Here we present accelerated images by PhasE-Constrained Over Sampled (PECOS) MRI in our home-made Halbach MRI scanner (70 mT). We show projection images of a phantom obtained in our “PhysioMRI” scanner (Fig. 1(a)), a home-made scanner designed for musculoskeletal imaging at low field strengths. We use cartesian turbo spin echo (TSE) sequence to sample the k-space. Image reconstructions are performed by phase conjugate reconstruction and by PECOS.
fMRI in the Mouse Spinal Cord during peripheral somatosensory Stimulation
Authors: Allelein Amon , Pradier Bruno , Chen Huifen , Faber Cornelius
Published: August 2023

The spinal cord is an important hub for the integration and processing of peripheral somatosensory stimuli within the central nervous system, however, mouse spinal cord functional imaging is not yet established. We successfully performed BOLD fMRI in the mouse spinal cord using 1 electric and 3 different mechanical stimulation modalities in one session. Graph theory-based network analyses showed strong positive correlations within the dorsal spinal cord laminae of L4 and L5. A negative correlation between the dorsal and ventral regions within the same segment suggests the presence of a vascular steal effect.
Multilevel Comparison of Neural Networks for Ventricular Function Quantification in CMR accelerated by Compressed Sensing
Authors: Hadler Thomas , Ammann Clemens , Gröschel Jan , Schulz-Menger Jeanette
Published: August 2023

Three popular convolutional neural networks were trained on short-axis cine MR images of the heart acquired by a prototype 2-shot 2D Compressed Sensing sequence. Network performance was evaluated on the level of clinical results and segmentation quality. Analysis revealed high correlation for quantitative results between all networks and a human expert. Automatic segmentation of the right ventricle is significantly more difficult than the left ventricle and shows more outliers. Segmentation decision errors concentrate in basal and apical slices, with the largest millilitre differences in the basal slices. Fast acquisition and automated image analysis promise high efficiency in CMR.
Accelerating multi-contrast multidimensional motion-corrected non-Cartesian iterative reconstructions with the Toeplitz approach
Authors: Phair Andrew , Cruz Gastao , Botnar René , Prieto Claudia
Published: August 2023

Iterative reconstructions for multi-contrast multidimensional non-Cartesian MRI can require considerable computation time, with a large fraction dedicated to non-uniform fast Fourier transforms (NUFFTs). The Toeplitz approach has been previously shown to allow NUFFT operations to be replaced by computationally efficient fast Fourier transforms (FFTs) without loss of accuracy. Herein, we combine this approach with a 3D multi-contrast low-rank cardiac-motion-corrected radial reconstruction with low-rank patch-based regularisation to achieve a ~13.3-fold computational speed-up.
Data-Efficient Uncertainty Quantification for Radial Cardiac Cine MR Image Reconstruction
Authors: Brahma Sherine , Schäffter Tobias , Kolbitsch Christoph , Kofler Andreas
Published: August 2023

Due to the black-box nature of Deep Learning (DL) algorithms, uncertainty quantification (UQ) is a promising approach to assess their risk in medical applications. However, UQ is challenging in imaging techniques like non-Cartesian multi-coil CINE MRI because the data is high-dimensional, and the acquisition process is computationally demanding. In this work, i) we propose to utilize spatio-temporal (ST) networks, demonstrating efficient UQ in a high-dimensional setting, and ii) we show a reduction in uncertainty by adopting the forward model of radial multi-coil 2D cine MR in the reconstruction process. UQ is performed using MCMC dropout with additional aleatoric loss terms.
Diffeomorphic Image Registration for CINE Cardio MR images using deep learning
Authors: Amsel Daniel , Yoon Seung Su , Wetzl Jens , Maier Andreas
Published: August 2023

Diagnostic applications often require the estimation of organ motion. Image registration enables motion estimation by computing deformation fields for an image pair. In this work, voxelmorph, a framework for deep learning-based diffeomorphic image registration is used to register CINE cardiac MR images in four-chamber view. Additionally, the framework is extended to a one-to-many registration to also utilize temporal information within a time-resolved MR scan. Registration performance as well as the performance of a valve tracking application using this approach are evaluated. The results are comparable to a state-of-the-art registration method, while noticeably reducing the computation time.
3D Multiscale Weighted Total Variation Registration for MR Image-Guided Catheter Interventions
Authors: Patel Jaykumar , Sheagren Calder , Hassan Saqeeb , Jouybari Fatemeh Rastegar , Macgowan Christopher , Wright Graham
Published: August 2023

During MR-guided cardiac catheter intervention, the catheter may be misaligned due to the respiratory motion of the heart. To improve the myocardial border alignment, GPU-based edge-preserving image registration is developed to accurately align highly undersampled 3D cone-trajectory image-based navigators for motion characterization. The edge-preserving registration technique improved myocardial border alignment across differing spatial resolutions and acceleration factors in-silico.
Biventricular function using a novel real-time free-breathing compressed sensing cine sequence with R-R normalization and motion correction
Authors: Negm Ahmed , Pang Jianing , Mcgee Kiaran , Iverson Holly , Halverson Maria , Davids Rachel , Rajiah Prabhakar , Bratt Alexander , Williamson Eric , Young Phillip , Foley Thomas , Leiner Tim , Francois Christopher , Bi Xiaoming , Collins Jeremy
Published: August 2023

CMR is the gold standard for assessing biventricular size and function. bSSFP Seg Cine is a standard cine method, but requires breath-holding which prolongs table time and limits utility in dyspneic patients. A novel real-time technique RTCSCineMoCo combines free-breathing acquisition with compressed sensing and motion correction. In 100 subjects RTCSCineMoCo generated similar results to Seg Cine for LVEF, LV end-diastolic mass, and RVESV with agreement including no difference at Bland-Altman analysis for all LV and RV measures. The shorter table time for RTCSCineMoCo and ability to robustly image dyspneic patients are important enhancements for clinical practice.
Impact of Gadolinium injection to the variable Flip Angle scheme of Tag CMR including SENC and SPAMM
Authors: Nguyen Vivian , Goes Jacob , Gorre Donovan , Wang Hui , Vaicik Marcella , Patel Amit , Kawaji Keigo
Published: August 2023

SENC and SPAMM tagging Cardiac Magnetic Resonance (CMR) are specifically optimized for acquisition before contrast injection and tuned to the end-systolic phase. While SPAMM tagging is a non-quantitative approach that indirectly derives functional motion from the displacement of the saturated tags in the myocardium, SENC directly computes myocardial tissue compression (strain) in percentage units. Furthermore, SENC quantitation pipeline bypasses the signal intensity map that exhibits the decay of the embedded strain measurements. In this study, we examine both SPAMM and SENC post-Gd measurements to specifically indicate the effect of the variable RF pulse train tuned to target tissue T1.
Identification of a single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma
Authors: Anil Aliya , Stokes Ashely , Chao Renee , Hu Leland , Alhilali Lea , Karis John , Bell Laura , Quarles C Chad
Published: August 2023

Reliable differentiation of tumor recurrence and treatment effects in glioblastoma patients is still a prevailing challenge. The purpose of this study is to identify the optimal threshold for generating fractional tumor burden (FTB) maps derived from single-dose, dual-echo based standardized relative cerebral blood volume measurements. To establish the threshold, dual-echo data was compared to the well-validated, double-dose single echo standardized FTB map. In summary, with the optimized threshold, the single-dose, dual-echo approach yielded FTB maps that strongly agreed with the reference standard, providing a compelling option for clinical use.
MRI of individuals with cochlear implants: surgical planning, current practice, success rates, and stakeholder opinions
Authors: Dewey Rebecca , Dineen Robert , Clemence Matthew , Dick Olivier , Bowtell Richard , Kitterick Pádraig
Published: August 2023

A cochlear implant (CI) contains a magnet implanted under the scalp. MRI of CI users is associated with safety concerns, significant discomfort, and image distortion. A CI placed under a swimming cap is a feasible tool for observing the effect of CI location on image usability within a single subject and potentially informing surgical planning. 35-70% of radiological features in the head were deemed unaffected by the implant. Online survey results highlight the need for consistent publication of clear, succinct, and standardised information for healthcare professionals and CI users. CI user consultation is scarce, meaning their views are often neglected.
Robust and fast RF pulse design of rectangle excitations using a hybrid CNN framework with signal modeling
Authors: Zhang Yajing , Ruan Guohui , Zhao Yan , Huang Xianrui , Van Cauteren Marc
Published: August 2023

Radio frequency (RF) pulses play a key role in magnetic resonance imaging. However, current MRI systems mostly use pre-defined RF waveforms with minimal adaptions. In this work, we propose a novel hybrid framework to combine convolutional neural network (CNN) with signal modeling by feature extractions. The result demonstrates that the proposed method provides more robust pulse design estimation result than using a generalized CNN framework for any desired rectangle excitations.
Practical RF-pulse shape designs to minimize off-resonance artifacts in dissolved-phase hyperpolarized 129Xe MRI
Authors: Lu Junlan , Leewiwatwong Suphachart , Driehuys Bastiaan , Mugler John
Published: August 2023

Minimizing artifacts in 129Xe gas exchange MRI requires selectively exciting the broad dissolved phase resonances, without exciting the much larger gas phase pool. This requires not only a short, selective pulse, but also overcoming pulse distortions imposed by the RF amplifier. Here, we demonstrate a novel, practical RF pulse based on augmenting the traditional Hanning window pulse with tunable DC bias and sub-lobes in the time-domain. We characterized the performance through simulations, phantom, and in vivo testing and determined that the tunable DC bias parameter creates a robust dissolved-phase excitation while minimizing gas-phase contamination.
Quantitative Reduced Field-of-view Imaging using 3D Tailored Inner Volume Excitation and Pattern Recognition
Authors: Jiang Yun , Nielsen Jon-Fredrik , Gulani Vikas , Seiberlich Nicole
Published: August 2023

The goal of this study is to achieve small field-of-view (FOV) T1 and T2 mapping using 3D tailored inner volume (IV) excitation and pattern recognition based on MR Fingerprinting.
Image Quality Transfer improves the potential clinical value of low-field MRI
Authors: Figini Matteo , Lin Hongxiang , D'Arco Felice , Ogbole Godwin , Espagnet Maria Rossi , Oyinloye Olalekan , Yaria Joseph , Nzeh Donald , Atalabi Mojisola , Ronan Lisa , Carmichael David , Cross Judith , Lagunju Ikeoluwa , Fernandez-Reyes Delmiro , Alexander Daniel
Published: August 2023

We applied Image Quality Transfer to enhance the contrast and resolution in the slice direction of low-field structural MRI, using a deep learning model trained on simulated images. Six radiologists blindly reviewed the enhanced images compared to low- and high-field images from 12 paediatric patients with epilepsy. Results demonstrated significant improvement of the visualisation of brain structures in sagittal and coronal orientations, and marginal improvement of the contrast between grey and white matter. If these promising results are confirmed in a larger study and in lesions, IQT could be an important tool to enhance the diagnostic power of low-field MRI.
A deep learning-based
quality control system for co-registration of prostate MR images
Authors: Sunoqrot Mohammed R. S. , Selnæs Kirsten M. , Abrahamsen Bendik S. , Patsanis Alexandros , Nketiah Gabriel A. , Bathen Tone F. , Elschot Mattijs
Published: August 2023

Multiparametric MRI (mpMRI) is a valuable tool for the diagnosis of prostate cancer. Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of mpMRI in prostate cancer. Co-registration of diffusion-weighted and T2-weighted images is a crucial step of CAD but is not always flawless. Automated detection of poorly co-registered cases would therefore be a useful supplement. This work shows that a fully automated quality control system for co-registration of prostate MR images based on deep learning has potential for this purpose.
QC of image registration using a DL network trained using only synthetic images
Authors: Li Yiheng
Published: August 2023

To perform robust quality control of medical imaging registration, we propose a method that can QC co-registration for multiple organs, without the restriction of the modalities. A rule-based image synthesis pipeline is used to generate random contrasts and shapes as training images. ResNet34 is trained to predict image alignment. Two MRI datasets with the spine or brain as subjects are used as external validation sets. The proposed model trained with synthetic images is validated on either one of the real MRI datasets and outperforms the same model trained on the other MRI dataset, which shows better generalizability.
Flow Effects on Spatial Spectral Excitation of Hyperpolarized Agents
Authors: Walker Christopher , Michel Keith , Harlan Collin , Xu Zhan , Martinez Gary , Schellingerhout Dawid , Lai Stephen , Bankson James
Published: August 2023

Simulations were used to evaluate the effect of rapid vascular flow on spatial spectral pulses used for hyperpolarized MRI. Simulation results show that flow effects reduced the on-resonance excitation angle while increasing the off-resonance excitation in a velocity dependent manner. These excitation impacts will be particularly important when trying to estimate an arterial input function. Flow may also produce measurable lactate signal in flowing pyruvate, an effect that was observed in a hyperpolarized study of the thyroid.