bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond qMRI: Biological tissue properties from single-subject unsupervised deep learning with theoretical signal constraints
Authors: Benslimane Ilyes , Grabner Günther , Hametner Simon , Jochmann Thomas , Zivadinov Robert , Schweser Ferdinand
Published: August 2023

Most quantitative MRI (qMRI) parameters co-depend on multiple tissue properties, limiting their clinical value. Here, we introduce a biophysically constrained autoencoder network that accepts multiparametric MR data and outputs underlying biological tissue parameters. The method requires no ground truth data, no knowledge of the (generally unknown) biophysical model parameters, and a single subject provides sufficient training data. We validated the method using ex vivo iron and myelin stains.
MR-Thermometry based targeting for histotripsy treatments in ex-vivo tissues
Authors: Gupta Dinank , Choi Dave , Allen Steven , Hall Tim , Xu Zhen , Noll Douglas
Published: August 2023

The accuracy of using MR-Thermometry for pre-treatment targeting for histotripsy was evaluated on ex-vivo tissues. Eight brain samples were treated with an ultrasound array capable of performing both heating and histotripsy treatments. Heating was performed at array focus while MR-Thermometry images were acquired. Subsequently, histotripsy lesions were also made at the focus and post-treatment images were acquired. The location of MR-Thermometry estimated focal-zone was compared with the observed histotripsy lesion location to assess the accuracy of MR-Thermometry targeting. The mean error in estimated focus was about 1mm in all axes, suggesting MR-Thermometry would be suitable for pre-treatment targeting for histotripsy.
Inhomogeneous Magnetization Transfer (ihMT) imaging of the human brain at 7T
Authors: Girard Olivier , Soustelle Lucas , Troalen Thomas , Hertanu Andreea , Forodighasemabadi Arash , Guye Maxime , Ranjeva Jean-Philippe , Varma Gopal , Alsop David , Duhamel Guillaume
Published: August 2023

Inhomogeneous Magnetization Transfer (ihMT) MRI has raised interest for myelin imaging. Applications at ultra-high field are appealing for SNR considerations but are challenged by the reduction of available RF power due to regulatory SAR constraints and the need to account for inhomogeneities of the RF excitation field (B1+). In the current study we present experimental data acquired at 3T which validate two B1+-bias removal strategies. Then we further evaluate them at 7T and show preliminary results towards a robust ihMT protocol free from B1+ bias.
Image acceleration with an 8-channel local B0 coil array compatible with parallel imaging in a 9.4T human MR scanner
Authors: Tian Rui , Loktyushin Alexander , Buckenmaier Kai , Steffen Theodor , Scheffler Klaus
Published: August 2023

A recent idea of spread spectrum MRI utilizes rapid modulations of localized magnetic fields to speed up image acquisitions. To push this concept further, we experimentally demonstrated 2D FLASH scans at 9.4T accelerated by 3-fold with modulation of a newly built 8-channel local B0 coil array, and 6-fold together with parallel imaging. Moreover, for FLASH and single shot spiral acquisitions, we designed and simulated another two modulation schemes for the B0 coil array to further investigate the advantages of independent control over each local coil for imaging acceleration.
Concurrent laminar CBF, CBV, T2-BOLD and CMRO2 fMRI at 7T in human primary motor cortex
Authors: Shao Xingfeng , Hua Jun , Wang Danny JJ
Published: August 2023

In this study, we propose a novel pulse sequence to simultaneously acquire laminar ASL, VASO and T2-BOLD signals with high spatial resolution. Experiments were performed on the M1 to characterize concurrent layer-dependent CBF, CBV, T2 BOLD and CMRO2 signal changes to sensory input and motor output. Both positive CBF/CBV/CMRO2 and negative VASO profiles show a clear ‘double-peak’ pattern, which is consistent with the hypothesis that FT engages neural activity of somatosensory input in the superficial layers and motor output in the deep layers. The BOLD response mainly peaked in superficial layers due to dominant contribution of pial veins.
Correction of diffusion pore imaging (DPI) data in the presence of extraporal water and transmembrane water exchange
Authors: Ludwig Dominik , Laun Frederik B. , Klika Karel D. , Rauch Julian , Ladd Mark E. , Bachert Peter , Kuder Tristan A.
Published: August 2023

Diffusion pore imaging might open a new window into pathologies by providing histology-like information non-invasively by estimating pore size and shape distributions. For current pore imaging approaches, closed pores filled with an NMR visible diffusing medium are assumed, while extraporal components and exchange are neglected, which limits applicability. We propose a method based on Gaussian phase approximation to suppress effects of extraporal fluids and transmembrane water exchange and compare the approach to a filter-based method. Thus, one main obstacle for in vivo applications is reduced, the required high gradient amplitudes may be obtained using local gradient coils in the future.
Improving oxygenation quantification from streamlined qBOLD data using amortized variational inference
Authors: Simpson Ivor , McManamon Ashley , Stone Alan , Blockley Nicholas , Colasanti Alessandro , Cercignani Mara
Published: August 2023

Streamlined qBOLD acquisitions enable experimentally straightforward observations of brain metabolism. High quality R2’ maps are easily derived; however, the oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) are more ambiguously defined from noisy data. Accordingly, standard approaches yield noisy and underestimated OEF maps and overestimate DBV.

This work uses synthetic data to learn models for voxelwise prior distributions, which are subsequently leveraged in an amortized variational Bayesian inference model. We demonstrate our approach enables inference of smooth OEF and DBV maps, with a physiologically realistic distribution, and illustrate voxelwise differences in OEF between subjects at rest and undergoing hyperventilations.
Interplay of Iron and Copper in the Neuromelanin-Related Paramagnetic Relaxation Enhancement
Authors: Wallstein Niklas , Pöppl Andreas , Capucciati Andrea , Pampel André , Jäger Carsten , Zucca Fabio A. , Monzani Enrico , Casella Luigi , Zecca Luigi , Möller Harald E.
Published: August 2023

Neuromelanin-sensitive MRI receives interest as potential biomarker in neurodegenerative diseases, such as Parkinson’s and Alzheimer’s disease. It is known that human neuromelanin pigments bind large quantities of toxic metal ions, especially iron but also other transition metals including copper. These melanin-iron complexes are a potential source of paramagnetic relaxation enhancement of water proton. In relaxometry investigations, we found deviations from a simple linear concentration-dependent T1 shortening in synthetic neuromelanins containing different amounts of iron and copper. Knowledge of the occupation of distinct metal binding sites seems crucial for contrast optimization or attempts to quantify metal content by MRI.
Microscopic fractional anisotropy may be sensitive to unilateral hippocampal abnormalities in temporal lobe epilepsy
Authors: Arezza Nico , Burneo Jorge , Khan Ali , Baron Corey
Published: August 2023

Drug-resistant temporal lobe epilepsy (TLE) can often be treated surgically, but successful intervention depends on the use of imaging to localize the epileptic focus. Here, microscopic fractional anisotropy (μFA), fractional anisotropy (FA), and mean diffusivity (MD) were investigated to assess their sensitivities to abnormalities in TLE. μFA was significantly reduced in the ipsilateral hippocampal subfield containing the cornu ammonis 3/4 and dentate gyrus (p=0.0044), suggesting that it may be sensitive to pathological hippocampal abnormalities. Furthermore, differences between ipsilateral and contralateral μFA and MD, but not FA, correlated with ipsilateral atrophy in that same region.
Long-term effects of stimulant treatment on regional cortical thickness development in ADHD
Authors: van der Pal Zarah , Walhovd Kristine , Amlien Inge , Kaiser Antonia , Geurts Hilde , Reneman Liesbeth , Schrantee Anouk
Published: August 2023

Stimulant medication is commonly used in treatment for attention-deficit/hyperactivity disorder, yet its effects on brain development remain unclear. This study investigated the long-term age-dependent effects of stimulants on cortical development after a 4-year naturalistic follow-up of adolescents and adults with ADHD using T1-weighted scans. Medication use was higher in adolescents than adults, and ADHD symptoms improved in both age groups. In line with literature on cortical development, analyses revealed reductions in apparent cortical thickness in adolescents only. However, we observed no effect of medication use on change in cortical thickness, suggesting previously identified psychostimulant effects may be transient.
SNR-efficient SSFP with k-space aliasing
Authors: Lally Peter , Statton Ben , Matthews Paul , Chiew Mark , Miller Karla , Bangerter Neal
Published: August 2023

Steady state free precession (SSFP) imaging with unbalanced gradients (e.g. FISP, PSIF, DESS) causes aliasing in k-space which is often overlooked, or at best, minimised with large spoilers. Here we exploit this phenomenon and use the aliased signals to increase the SNR-efficiency of SSFP imaging.
Ultra-high field done ultra-fast:
Enhancing Wave-CAIPI using an single-axis insert head gradient
Authors: Roos Thomas , Versteeg Edwin , Siero Jeroen
Published: August 2023

Acceleration techniques like SENSE have enabled significant decreases in scan time, but the $$$G$$$-factor penalty on SNR limits attainable accelerations.

Wave-CAIPI lowers this $$$G$$$-factor by spreading aliasing and taking advantage of the coil sensitivity distributions. A high performance single-axis insert gradient is utilised to increase the attainable wave amplitudes and thereby increasing the effectivity of Wave-CAIPI.

Simulations and 7T phantom & in-vivo acquisitions show significant improvements in $$$G$$$-factor when using Wave-CAIPI, especially when utilizing the higher performance of the insert gradient.

Not only are the $$$G$$$-factors lower but also show increased spreading and lack hard edges, allowing for even faster acquisitions.
Fast acquisitions for mean kurtosis and microscopic fractional anisotropy
Authors: Coelho Santiago , Szczepankiewicz Filip , Fieremans Els , Novikov Dmitry
Published: August 2023

We propose two acquisition protocols that minimize the number of directions needed for estimating MD, FA, MK, and $$$\mu$$$FA. Using symmetric trace-free decompositions of the diffusion, kurtosis, and covariance tensors, we design acquisitions that cancel unnecessary tensor elements, thereby reducing the number of directions needed to generate the maps. Our protocols consist of $$$3b_1+6b_2=9$$$ DWIs for MD+MK in a 1-minute scan, and $$$6b_1^\text{LTE}+6b_2^\text{LTE}+3b_{1.5}^\text{STE}=15$$$ DWIs for MD+FA+MK+$$$\mu$$$FA in a 2-minute scan. We show the feasibility of these approaches on a healthy volunteer.
Along-tract quantification of the BOLD hemodynamic response function in white matter
Authors: Schilling Kurt , Li Muwei , Rheault Francois , Gao Yurui , Ding Zhaohua , Anderson Adam , Kang Hakmook , Landman Bennett , Gore John
Published: August 2023

We measured the variations of the BOLD hemodynamic response function (HRF) along white matter (WM) pathways. We find that the WM HRF is different to that of the gray matter (GM), and has a prominent negative dip and smaller peak signal. Further, we find that the HRF changes along WM pathways, and is different between pathways. Characterizing the variations of the WM HRF along and across pathways may provide insight into the biophysical basis of BOLD effects in WM and the relationships between WM structure and neurovascular coupling.
Differential diagnosis of primary liver cancer using APT and quantitative DIXON techniques
Authors: Lin Tao , Wang Jiazheng , Sun Peng , Chen Lihua , Song Qingwei , Pu Renwang , Zhao Ying , Ren Xue , Xu Qihao , Liu Ailian
Published: August 2023

Hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) are the most common types of primary liver cancer, which differ greatly in terms of pathogenesis, biological behavior, histological morphology, treatment, and prognosis. This retrospective study revealed that APT combined with quantitative DIXON technique could improve the performance for differentiating HCC from ICC.
Diffusion restriction comparison between Gleason 4 fused and cribriform glands within patients using whole mount prostate pathology
Authors: Duenweg Savannah , Fang Xi , Bobholz Samuel , Lowman Allison , Brehler Michael , Kyereme Fitzgerald , Iczkowski Kenneth , Jacobsohn Kenneth , Banerjee Anjishnu , LaViolette Peter
Published: August 2023

This study used prostate histology and multi-parametric magnetic resonance imaging (MP-MRI) to evaluate diffusion differences in Gleason pattern 4 gland morphology. After surgery, tissue was sliced using slicing jigs, annotated by a board-certified pathologist, and digitally contoured to differentiate lumen and epithelium. Slides were co-registered to the T2-weighted MRI scan. Two linear mixed models were fitted to the MP-MRI data to consider the different hierarchical structures. Model (1) considers patient as random effect, and Model (2) adds a nested effect for slide. We found that cribriform glands were more diffusion restricted than fused glands in Gleason Grade 4 tumors.
Automatic detection of spatio-temporal patterns of interictal epileptic activity with fMRI
Authors: Tobías Cristina , Uruñuela Eneko , Ferrer-Gallardo Vicente , Goldberg Hannah , Engelman Christine , Lowe Mark , Jones Stephen , Caballero-Gaudes César
Published: August 2023

We propose a novel methodology to identify spatio-temporal patterns of interictal epileptic activity in refractory epileptic patients using only BOLD functional MRI. It is based on clustering the activity-inducing signal deconvolved from the fMRI data with the Infomap algorithm. The proposed approach was validated on data acquired during a finger tapping task, and evaluated in four epileptic patients scanned at 7T. This method obtained activation maps that were concordant with the results obtained with EEG-informed GLM and MEG-based dipole source localization in 3 out of 4 patients, demonstrating its potential for mapping epileptic activity based only on fMRI data.
Automated lesion prediction and characterisation of focal cortical abnormalities: a MELD study
Authors: Wagstyl Konrad , Ripart Mathilde , Consortium MELD , Spitzer Hannah , Baldeweg Torsten , Adler Sophie
Published: August 2023

Identification of subtle epilepsy-causing focal cortical dysplasias (FCD) on MRI remains an outstanding challenge during presurgical assessment of patients. The Multi-centre Epilepsy Lesion Detection (MELD) project created an MRI lesion detection algorithm using a large, heterogenous cohort. The algorithm had a sensitivity of 67%, performing well on unseen test sites. Analysis of MRI lesions revealed distinct subgroups, with differing histopathological subtypes, imaging features and detection rates. Individual patient reports highlight a predicted lesion’s location, imaging features and their relative saliency to the classifier. This tool has the potential to improve presurgical lesion identification on MRI from patients with epileptogenic FCD.
Multimodal Lesion Phenotyping Improves Seizure Outcome Classification after Traumatic Brain Injury: An EpiBioS4Rx Study
Authors: Garner Rachael , Bennett Alexis , Sharma Akul , Morris Michael , La Rocca Marianna , Barisano Giuseppe , Cua Ruskin , Vespa Paul , Toga Arthur , Duncan Dominique
Published: August 2023

Posttraumatic epilepsy (PTE), or recurrent seizures after traumatic brain injury (TBI), is a debilitating complication of TBI. We present a multimodal approach to classify seizure outcomes using computed tomography (CT) and magnetic resonance imaging (MRI) features that characterize lesion phenotypes. Five logistic regression models to predict seizure outcome are presented, using patient demographics and clinical information in conjunction with CT and MRI variables that describe lesion characteristics including contusion type and location as well as whole-brain lesion volumetrics. The optimal model utilized all four categories of features, yielding 91.4% sensitivity, 75% specificity, and 0.886 area under the curve performance.
Non-invasive metabolic biomarkers of interneuron cell transplantation therapy in an epilepsy model
Authors: Radoul Marina , Qiao Kai , Hong Donghyun , Parekh Mansi , Hampel Philip , Sevilla Eric , Traver David , Kim Hannah , Bershteyn Marina , Maury Yves , Priest Catherine , Nicholas Cory , Chaumeil Myriam
Published: August 2023

Interneuron transplantation targeting GABAergic network dysfunction is a novel alternative therapeutic approach for chronic focal epilepsy. However, in vivo monitoring of response to such cellular therapeutics remains challenging. Here, we combined high resolution in vivo and ex vivo 1H MRS to investigate the metabolic alterations in epileptic hippocampus in a preclinical model of chronic mesial temporal lobe epilepsy, and the effect of human inhibitory interneuron transplantation on metabolism. We discovered that hippocampal levels of GABA, NAA/Cr, GLX/Cr, GABA/GLX and GABA/NAA were reversed to healthy control levels in epileptic mice transplanted with inhibitory interneurons, providing unique biomarkers of therapeutic response.
Diagnostic performance of magnetic resonance elastography in mice with NASH and significant metabolic liver disease.
Authors: KHALFALLAH Meryem , Doblas Sabrina , Julea Felicia , Postic Catherine , Valla Dominique , Paradis Valérie , Garteiser Philippe , Van Beers Bernard
Published: August 2023

Nonalcoholic steatohepatitis (NASH) and significant metabolic liver disease (MLD) are progressive forms of nonalcoholic fatty liver disease (NAFLD). MR elastography parameters have been shown to be useful for assessing NAFLD/NASH and liver inflammation. To assess the role of viscoelastic parameters in diagnosing NASH and significant MLD, MRE hepatic examinations were performed in mice with NAFLD. Our results showed that the diagnostic performance of MR elastography was higher in significant MLD than in NASH. This may be explained by inflammation and fibrosis occurring in indeterminate NASH cases included in MLD, and by poor performance of MR elastography to detect hepatocyte ballooning.
Deep Learning Reconstruction: Clinical Utility for 3D MRCPs Obtained by Different k-Space Data Acquisition Methods in IPMN Patients
Authors: Matsuyama Takahiro , Ohno Yoshiharu , Yamamoto Kaori , Ikedo Masato , Yui Masao , Takeda Saki , Iwase Akiyoshi , Oshima Yuka , Hamabuchi Nayu , Hanamatsu Satomu , Obama Yuki , Nagata Hiroyuki , Ueda Takahiro , Ikeda Hirotaka , Murayama Kazuhiro , Toyama Hiroshi
Published: August 2023

We hypothesized that deep learning reconstruction (DLR) and multiple k-space data by means of each of the repetition time (TR) techniques (Fast 3D mode multiple: Fast 3Dm) are more useful than parallel imaging (PI) and compressed sensing (CS) for shortening acquisition time and improving image quality and IPMN evaluation capability on 3D MRCP. The purpose of this study was thus to compare the utility of DLR used for PI, Fast 3Dm and CS for improvement of acquisition time, image quality and IPMN evaluation capability on 3D MRCP for patients with IPMN.
Rapid quantitative magnetization transfer imaging: utilizing the hybrid state and the generalized Bloch model
Authors: Assländer Jakob , Gultekin Cem , Zhang Xiaoxia , Duchemin Quentin , Liu Kangning , Charlson Robert , Shepherd Timothy , Fernandez-Granda Carlos , Flassbeck Sebastian
Published: August 2023

We combine two recently proposed biophysical models, the hybrid state and the generalized-Bloch model, to describe magnetization transfer. Combined into a single model, they facilitate quantitative magnetization transfer imaging of the whole brain with 1mm isotropic resolution in 12 minutes. We optimized an MR-Fingerprinting-like pulse sequence, and validated the approach in two multiple sclerosis patients and two controls.
Addressing Concomitant Gradient Phase Errors in Chemical Shift-Encoded MRI with a Pass-Specific Phase Fitting Method
Authors: Roberts Nathan , BS  , Hernando Diego , Panagiotopoulos Nikolaos , Reeder Scott
Published: August 2023

This work presents a complex-based fitting method to address concomitant gradient (CG) phase errors for time-interleaved (i.e., multi-pass) chemical shift-encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R2* through a joint estimation of pass-specific phase terms. The proposed method does not require prior knowledge of gradient waveforms. The proposed fitting method removed significant PDFF and R2* estimation errors in both phantom and in vivo evaluations away from isocenter. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even when the imaging volume was centered at isocenter.
The TMSMR 28 channel RF coil: whole head imaging for the 3-axis TMS multichannel system
Authors: de Lara Lucia Navarro , Stockmann Jason , Keil Boris , Mareyam Azma , Daneshzand Mohammad , Wald Larry , Nummenmaa Aapo
Published: August 2023

Multichannel Transcranial Magnetic Stimulation is an emerging technology for non-invasive stimulation of the human brain. Combining this technique with fMRI offers the unique benefits of studying the causal relationships between the cortical and subcortical nodes of large-scale brain networks. For this reason a whole head 28-channel RF coil array was developed to be integrated with the first 3-axis-TMS multichannel system. We have analyzed how the SNR of the constructed array changes when placing the stimulation units. Additionally, we compared the SNR/g-factor maps with commercial available 32/20-channel RF coils. The results show that the RF coil is performing as expected.
Fixel-based analysis of aging white matter reveals selective fiber-specific degeneration
Authors: Han Ana , Chad Jordan , Dhollander Thijs , Chen J. Jean
Published: August 2023

White matter (WM) microstructural aging is often studied with diffusion MRI via voxelwise metrics such as fractional anisotropy (FA). Decreasing FA with advancing age is frequently interpreted as WM microstructural degeneration, but relying on FA for this purpose only makes sense if a voxel contains a single fiber tract. In this work we use fixel-based analysis (FBA) to investigate the association of fiber-specific measures with age among each individual "fixel" within a voxel. We find intra-voxel differences in age associations of crossing fixels, demonstrating that traditional voxel-based analyses are inappropriate for probing age-related fiber degeneration in scenarios of multi-fiber crossings.
Hyperpolarized 129Xe MR Imaging in Neonates with Bronchopulmonary Dysplasia: Feasibility and Challenges
Authors: Stewart Neil , Higano Nara , Mukthapuram Shanmukha , Willmering Matthew , Arnsperger Anita , Pratt Ronald , Loew Wolfgang , Rao Madhwesha , Schulte Rolf , Wild Jim , Woods Jason
Published: August 2023

We report the first-ever experience in performing HP 129Xe MRI in neonates. The neonates had prematurity-related lung disease (bronchopulmonary dysplasia), a major cause of morbidity/mortality that remains poorly characterised. The feasibility of imaging during a short (<3s) breath-hold apnea was demonstrated. Spiral-based 129Xe ventilation imaging showed good image quality (SNR>20) and sufficient sensitivity to detect mild ventilation abnormalities. Dynamic 129Xe spectroscopy revealed the existence of resonances near the conventional tissue/plasma and red blood cells resonances observed in children and adults. With further data, our work may impact on the management of infant lung diseases in the neonatal period and beyond.
High-resolution dynamic 3D UTE Lung MRI using motion-compensated manifold learning
Authors: Zou Qing , Torres Luis , Fain Sean , Jacob Mathews
Published: August 2023

UTE radial MRI methods are powerful tools for probing lung structure and function. However, the challenge in directly using this scheme for high-resolution lung imaging applications is the long breath-hold needed. While self-gating approaches that bin the data to different respiratory phases are promising, they do not allow the functional imaging of the lung and are often sensitive to bulk motion. The main focus of this work is to introduce a novel motion compensated manifold learning framework for functional and structural lung imaging. The proposed scheme is robust to bulk motion and enables high-resolution lung imaging in around 4 minutes.
Age-related changes in human skeletal muscle microstructure and architecture assessed by DT-MRI and their association with muscle strength
Authors: Cameron Donnie , Reiter David , Adelnia Fatemeh , Ubaida-Mohien Ceereena , Bergeron Christopher , Choi Seongjin , Fishbein Kenneth , Spencer Richard , Ferrucci Luigi
Published: August 2023

Here we apply diffusion-tensor-(DT)-MRI to study muscle microstructural and architectural changes with healthy ageing in 94 participants (median age=56, range=22-89yrs). Fractional anisotropy (FA) and mean diffusivity (MD), were calculated for 12 thigh muscles, as were pennation angle, fascicle length, fibre curvature, and physiological cross-sectional area (PCSA) for the rectus femoris and biceps femoris longus. Knee extension/flexion torques were also measured. FA and MD were significantly associated with age (β=0.34 and −0.34, p<0.05), as were architecture parameters. Pennation angle and PCSA were positively associated with strength. This may prove useful for studying muscle response to interventions designed to delay sarcopenia.
The value of water T2 relaxation time in the early detection of neuromuscular diseases: a retrospective biopsy-controlled analysis in 83 patients
Authors: Balsiger Fabian , Locher Noah , Wagner Benedikt , Scheidegger Olivier
Published: August 2023

The diagnostic ability of quantitative water T2 mapping using multi-slice multi-echo sequences for the early detection of neuromuscular diseases (NMDs) was compared to fat-suppressed T2-weighted turbo inversion recovery magnitude (TIRM) MRI. Water T2 mapping had a significantly higher sensitivity and diagnostic ability in detecting muscle abnormalities than the subjective grading of TIRM MRI, prior to late-stage fatty infiltration signal alternations in T1-weighted MRI. Normal appearing TIRM MRI does not rule out disease activity in muscles in NMDs. Our findings suggest considering water T2 mapping over TIRM MRI for early detection of NMDs in clinical practice.
Oral delivery of 2H-labeled fumarate for deuterium magnetic resonance spectroscopic imaging of tumor cell death in vivo
Authors: Hesse Friederike , Wright Alan , Somai Vencel , Bulat Flaviu , Brindle Kevin
Published: August 2023

Cell death is an important imaging target for assessing early tumour treatment response and the effectiveness of therapy. We show here that 2H-labelled fumarate can be administered orally to detect cell death and assess early tumour treatment response in a subcutaneous lymphoma (EL4) model. Following oral gavage, 2H spectra were acquired from tumors with a time resolution of 5 min. Within 48h after chemotherapeutic drug (etoposide) treatment the tumor malate/fumarate signal ratios increased similarly to those measured after intravenous injection.
Use of Double-Echo Steady-State (DESS) sequence in the evaluation of pudendal nerve- A pilot trial.
Authors: Kus Joseph , Ramasamy Shakthi , Ploussard Brett , Cara Joyce , Bennis Stacey , Fitzgerald Collen , Shea Steve , Goldberg Ari , James Judy , Jawahar Anugayathri
Published: August 2023

Pudendal neuralgia is a common cause of chronic pelvic pain, especially in females. This is caused by pudendal nerve entrapment and can be a severely disabling neuropathic pain syndrome. It is currently a clinical diagnosis and most of the time a diagnosis of exclusion without definitive imaging criteria. We retrospectively compared DESS with the routine T2, T1 and DWI described in literature for the evaluation of pudendal nerves in patients with unresolved pelvic pain. Our study showed that DESS is effective and better than T2 and DWI combined sequences for diagnosing pudendal neuropathy.
Optimization of dual flip angle T1 mapping at 7T with B1 transmit variability
Authors: Mangal Jyoti , Dokumaci Sila , Leitao David , Tomi-Tricot Raphael , Ajanovic Amer , Ogier Stephen , Wilkinson Tom , Giles Sharon , Bridgen Pip , Prieto Claudia , Hajnal Joseph , Malik Shaihan , Carmichael David
Published: August 2023

Quantitative MRI at 7T has advantages of enhanced resolution and uniform tissue contrast however protocol optimisation can be challenging as B1(+) field variability is increased. We maximized the precision of T1 estimation for a dual flip angle SPGR acquisition using Cramer-Rao Lower Bound framework and validated the results using a Monte Carlo simulation and both phantom and in-vivo experiments. For a TR of 20ms, simulations suggested optimal flip angles of 4° and 26° similar to in-vivo results of 4° and 28°. By accounting for other parameters, the CRLB framework can be flexibly extended to optimize more complex mapping protocols.
A novel deep learning framework on brain functional networks for diagnosis of psychiatric diseases
Authors: Poury Milad Mashhady Ali , Ameri Ali , Masoudnia Saeed , Tavakoli Hosna , Ghasemi Faezeh , Rostami Reza , Nazem-Zadeh Mohammad-Reza
Published: August 2023

We developed a predicting algorithm based on brain connectivity to quantify the altered brain regions in schizophrenia, bipolar, and attention deficit hyperactivity disorders, to help diagnose them using neuroimaging biomarkers. Functional connectivity was utilized to construct brain graphs, on which the node2vec framework was applied to produce the node embeddings. The concatenation of embeddings was used to derive the region feature vectors to feed support vector machine (SVM) classifiers. Also, we build a model to assist the diagnosis of disorders using a weighted voting ensemble. The achieved accuracy proved to outperform to the state-of-the-art models.
Optimisation of Structural MR Imaging Sequences in a Neonatal Cohort at 64 mT
Authors: Cawley Paul , Padormo Francesco , Consortium UNITY , Dillon Louise , Hughes Emer , Almalbis Jennifer , Robinson Joanna , Maggioni Alessandra , Cromb Daniel , Arlinghaus Lori , Hu Houchun Harry , Williams Steve , Counsell Serena , Arichi Tomoki , Rutherford Mary , Hajnal Joseph , Edwards A. David
Published: August 2023

Point-of-care Magnetic Resonance scanning is a novel and potentially transformative technology, utilising Ultra-Low Field permanent magnets to facilitate bedside neuroimaging. Through iterative T2w sequence optimisation, we demonstrate the feasibility of using ultra-low field portable 64mT MR scanning in neonates. This pilot data demonstrates that images can provide sufficient contrast for tissue differentiation and identify pathological lesions. Scanning with ongoing intensive care was both feasible and safe.
Axonal diffusivities from two-shell PGSE data
Authors: Pizzolato Marco , Andersson Mariam , Canales-Rodríguez Erick , Dyrby Tim
Published: August 2023

The strongly diffusion-weighted MRI signal contains information about the axonal parallel and perpendicular diffusivities. Powder averaging has simplified the estimation of the perpendicular diffusivity, however it is difficult to estimate the parallel one because, as we show, the powder-averaged signal at strong diffusion weightings is insensitive to it. In this work we propose a method that enables the estimation of both diffusivities from only two conventional linear PGSE signal shells collected at high b-values. The method is tested on public MGH-HCP data to retrieve axonal diffusivities and calculate the MR radius in white matter.
Rapid Multi-shell Diffusion MRI Enabled by Learning Compact and Rotation Invariant q-Space Representations
Authors: Mani Merry , Yang Baolian , Magnotta Vincent , Jacob Mathews
Published: August 2023

A modified reconstruction is proposed for highly accelerated dMRI. The method employs machine learning in a model-based setting. The current work improves the generalizability of the deep-learned plug-and-play prior employed in the reconstruction, for enabling utilization of the reconstruction from a wide range of acquisition settings. This is achieved by learning a compact q-space representation in a rotation invariant space. The method is tested for the reconstruction of combined multi-band and in-plane accelerated data from both single-shell and multi-shell experiments. The reconstruction error is shown to be less than 3% for net acceleration of R=12 for single- and multi-shell cases.
Classification of MS patients into disability levels using deep learning approaches based solely on routinely-acquired MRI
Authors: Coll Llucia , Carbonell-Mirabent Pere , Cobo-Calvo Álvaro , Arrambide Georgina , Vidal-Jordana Ángela , Comabella Manuel , Castilló Joaquín , Rodríguez-Acevedo Breogán , Zabalza Ana , Galán Ingrid , Midaglia Luciana , Nos Carlos , Salerno Annalaura , Auger Cristina , Alberich Manel , Río Jordi , Sastre-Garriga Jaume , Oliver Arnau , Montalban Xavier , Rovira Àlex , Tintoré Mar , Pareto Deborah , Lladó Xavier , Tur Carmen
Published: August 2023

The ability of existing MRI biomarkers to predict MS patients’ prognosis is limited and inaccurate to be used at the individual level. We aimed to assess the ability of Convolutional Neural Networks (CNNs) to classify relapse-onset MS patients into non-disabled and markedly disabled using only MRI images. T1w and T2w-FLAIR images of 538 MS patients were used to train and test two CNN approaches which were compared also with (conventional) logistic regression models. The results showed that the CNN models performed better, having the intrinsic potential to improve after the inclusion of regional priors and other valuable clinical data.
Multiple sclerosis related fatigue: Altered resting-state functional connectivity of the Default Mode Network.
Authors: Li Yujing , Wang Jun , Yang Tingli , Zhang Pengfei , Ai Kai , He Xiaoli , Zhao Haiying , Ding Yuan , Wang Rui , Li Min , Ren Xinying , Xiong Diaohan , Zhang Jing
Published: August 2023

The objective of this study was to elucidate the no-motor component of fatigue mechanism in multiple sclerosis (MS) patients by studying the resting state functional connectivity (RS-FC) of default mode network (DMN). 12 with fatigue (F) and 10 without fatigue (nF) MS underwent resting sate magnetic resonance imaging (MRI). We selected 11 priori regions within the DMN as the regions of interests (ROIs) and ROI to ROI and ROI to global FC were calculated. Compared to nF-MS patients, F-MS patients showed abnormal increased functional connectivity in brain regions associated with cognitive function within the DMN.
Fully automated aortic pulse wave velocity calculation from 4D flow MRI with AI-based segmentation
Authors: Johnson Ethan , Berhane Haben , Scott Michael , Jarvis Kelly , Barker Alex , Markl Michael
Published: August 2023

Pulse wave velocity (PWV) is an important measure of vessel stiffness and can be quantified from 4D flow MRI. Accurate assessment of PWV requires placement of multiple analysis planes in an imaged volume, which typically is performed manually to some degree, such as through use of a vessel segmentation made by an experienced human observer. Here we present evaluation of a fully-automated method for calculating PWV in the thoracic aorta, incorporating an artificial intelligence (AI) convolutional neural network to segment the aorta. Estimates of PWV using AI segmentations were compared those from human-observer segmentations and found to be similarly reliable.
Towards 2D phase-contrast of tricuspid valve flow
Authors: Lamy Jerome , Seemann Felicia , Vera Ricardo Gonzales , Heiberg Einar , Peters Dana
Published: August 2023

Tricuspid valve flow evaluation is important for evaluation of regurgitation, used as a surrogate of pressures in the RV and as a criterion for evaluation of diastolic dysfunction. While 4D flow methods have interesting possibilities for retrospective valve flow evaluation its practical use is still limited. Here we present a method for direct tricuspid valve flow evaluation in a single breath-hold using 2D valve-following phase contrast sequence with a dynamic slice plane.
Assessment of Lipid Biosynthesis and Turnover in Renal Cell Carcinoma Cells and Tissues Using NMR-Resolved Stable Isotope Experiments
Authors: Crooks Daniel , Yang Ye , Lane Andrew , Fan Teresa , Brender Jeffrey , Krishna Murali , Linehan W. Marston
Published: August 2023

NMR-based analyses of lipids can shed insight into the global complement of cellular lipids, and elucidate the fuel sources and pathways contributing to lipid biosynthesis in cells grown in the presence of 13C-labeled fuels. We utilized 1H-13C HSQC NMR analysis of cellular lipids derived from FH- and mtDNA deficient UOK271 cells and observed robust reductive carboxylation of glutamine that resulted in formation and incorporation of 13C-glutamine-derived acetyl groups into lipid chains.
Imaging response to radio-chemotherapy in glioblastoma tumor models using deuterium metabolic imaging
Authors: Hesse Friederike , Wright Alan , Somai Vencel , Bulat Flaviu , Brindle Kevin
Published: August 2023

Metabolic imaging of brain tumor responses to radio-chemotherapy can give an early indication of treatment outcome. We show here that Deuterium Metabolic Imaging (DMI) with 2H-labeled fumarate is more sensitive than diffusion weighted 1H imaging (DWI) in detecting early evidence of cell death following radio-chemotherapy in orthotopically implanted patient-derived glioblastoma xenografts. 2H spectra were acquired from tumors with a time resolution of 5min, following an injection of 2H-labelled fumarate. Within 48h after the last chemo-radiotherapy treatment (CRT) the rate of tumor malate production from labelled fumarate increased significantly, whereas changes in ADC values were only detectable 7 days post treatment.
MRSI-detected pattern in glioblastoma patients one month after concomitant chemoradiotherapy
Authors: Ungan Gulnur , Escoda Albert Pons , Ulinic Daniel , Arús Carles , Vellido Alfredo , Majós Carles , Julià-Sapé Margarida
Published: August 2023

A blind source separation method (cNMF) was used to extract characteristic metabolic patterns from PRESS MRSI 3T acquired from areas of contrast enhancement in a retrospective set of 31 glioblastoma patients, one month after the end of concomitant chemoradiotherapy with temozolomide. The aim was to evaluate whether these patterns were predictive of true progression or pseudoprogression. They were used as input for supervised classifiers, achieving a maximum of 81% balanced accuracy. A moderate association between extracted patterns and outcome was detected by Cramer’s V. Spatial source distribution with nosologic maps points to MRSI-detected metabolic heterogeneity as cause for classifiers’ performance.
Accelerated MRI Thermometry with Multi-Echo Multi-Slice GRE
Authors: Zur Yuval , Pinhas Itzhak , Shapira Boaz
Published: August 2023

An accelerated multi echo GRE sequence is presented for Focused Ultrasound Thermometry. An under sampled k space dataset is acquired during heating, to reduce scan time and enable multi-slice acquisition. Prior to heating, a fully sampled baseline image is acquired. Based on the baseline image, an iterative reconstruction algorithm fills-in the missing lines of each hot image. Accelerations of up to x15 with 16 echoes enable acquisition of 5 – 10 slices in 3.5 sec. Real-time reconstruction of 800 msec/5 slices was implemented on a FUS-MRI machine.
Deep generative MRI reconstruction for unsupervised Gibbs ringing correction
Authors: Cordero-Grande Lucilio , Ortuño-Fisac Enrique , O'Muircheartaigh Jonathan , Hajnal Jo , Ledesma-Carbayo María Jesús
Published: August 2023

MRI reconstruction is formulated as the retrieval of the parameters of a deep decoder network fitted to the observations by an image formation model including the truncation of high-frequency information. Solutions without Gibbs ringing at any prescribed image grid can be obtained naturally by the model without training or ad-hoc post-corrections. We present quantitative and visual results for spectral extrapolation of magnitude images at different scales in an in-silico experiment and a high resolution ex-vivo brain MRI scan. After minor modifications to deal with complex data, the architecture is applied to 2D parallel imaging showing promising visual results.
Real time visual feedback for reproducible head motion
Authors: van Niekerk Adam , Berglund Johan , Ryden Henric , Sprenger Tim , Norbeck Ola , Avventi Enrico , Skare Stefan
Published: August 2023

The timing and magnitude of volunteer head motion has a significant impact on artefact level. It can therefore be difficult to reproduce motion correction results. Moreover, it is of interest to replicate patient motion retrospectively, in volunteers, to better understand the efficacy of a motion correction method. We attempt to solve this by stamping motion updates with a synchronisation “tag”. A rolling model is used to project the volunteer’s pose onto an MRI compatible display. The “tag” synchronised pose from a previous scan is then shown alongside the volunteer’s current pose, allowing them to track and hence reproduce the motion.
Prospective 3D FatNav motion correction for 7T Terra
Authors: Klodowski Krzysztof , Halabrin Juraj , Dragonu Iulius , Rodgers Chris
Published: August 2023

Ultra-high field (7T) imaging can deliver images of brain structure and function at previously inaccessible spatial resolutions down to ~100um. However, subject motion, particularly for patients causes blurring which can lose some of the benefit of 7T imaging. The 3D FatNav approach to motion correction embeds short fat-excitation imaging modules in dead-time in an MRI pulse sequence. We are developing a prospective FatNav module for Siemens 7T Terra scanners. We present here a prospective FatNav module that embeds FatNav into a host pulse sequence, that separates FatNav and main image data during online reconstruction, that computes motion updates and that applies these in GRE imaging sequence in real time.
MR-derived g-ratio is sensitive to longitudinal change and associated with disability progression in early multiple sclerosis
Authors: York Elizabeth , Meijboom Rozanna , Bastin Mark , Kampaite Agniete , Hernandez Maria Valdes , Thrippleton Michael , Connick Peter , Chandran Siddharthan , Hunt David , Waldman Adam
Published: August 2023

There is a pressing need for longitudinal in vivo biomarkers sensitive to heterogeneous pathology in relapsing-remitting multiple sclerosis (RRMS). The MR-g-ratio may be derived from myelin-sensitive magnetisation transfer saturation (MTsat) and multishell diffusion-weighted MRI but its relevance as a longitudinal biomarker and correlate of disability progression in RRMS is previously unexplored. Fifty-nine patients with recently diagnosed RRMS contributed g-ratio data at baseline and one year. G-ratio showed a significant decrease in normal-appearing white matter (NAWM) but not T2 FLAIR white matter lesions over one year. Both g-ratio in NAWM and lesions were, however, associated with clinical disability progression.
4D flow MRI: Ex-vivo swine model allows distinction between flow patterns induced by aortic valve replacement and surgical pathway alone.
Authors: Balks Maren Friederike , Saisho Hiroyuki , Fujita Buntaro , Schaller Tim , Sadat Najla , Ensminger Stephan , Barkhausen Jörg , Frydrychowicz Alex , Oechtering Thekla Helene
Published: August 2023

Hemodynamic outcome after aortic valve replacement (AVR) seems dependent on the type of replacement. The impact of the surgical pathway (aortotomy) itself on hemodynamics is still unclear. We proposed an ex-vivo swine model for comprehensive evaluation of aortic hemodynamics after different types of AVR with 4D flow MRI. Postoperative flow changes could be attributed not only to the implanted valve but also to the aortotomy. The new neocuspidization Ozaki procedure compared favorably to a biological valve as it induced fewer secondary flow patterns. Among the three different AVR methods, the mechanical valve allowed for hemodynamics that most closely approached physiology.
Towards reproducible Arterial Spin Labelling in the myocardium: Impact of blood T1 time and imaging readout parameters
Authors: Bozic-Iven Masa , Rapacchi Stanislas , Pierce Iain , Thornton George , Tao Qian , Schad Lothar , Treibel Thomas , Weingaertner Sebastian
Published: August 2023

Despite promising results, clinical translation of myocardial arterial spin labelling (myoASL) is hampered by insufficient reproducibility and robustness. We investigated the influence of physiological and sequence parameters on FAIR-myoASL in simulations as well as phantom experiments, and developed a correction method based on separately acquired T1 maps. Our simulation and phantom results show acquisition related MBF differences, potentially undermining the reproducibility of myoASL measurements. Inaccuracies between true and reconstruction blood T1, further render the sequence susceptible to heart rate variations, particularly for larger T1 mismatch. Using accurate blood T1 times in reconstruction may improve robustness and reproducibility.
Rapid and High Resolution Pelvic MRI Using Deep Learning Reconstruction
Authors: Atkins Melany , Guidon Arnaud , Vinski Michael , Schrack Thomas , Harris Heidi , Bayram Ersin
Published: August 2023

MRI plays an important role in pelvic assessment. For instance, it is the modality of choice for rectal cancer staging, gynecologic cancer staging, uterine fibroid evaluation and ovarian tumor characterization. Due to the complex nature of the anatomy and clinical demands of these protocols, high resolution thin slice volumetric scans are desired but low SNR, prolonged scan times and motion artifacts remain problematic. In this work, we deploy a combination of recent technical advances in particular high density flexible coils, compressed sensing, and deep learning reconstruction to tackle these challenges and report our feasibility results.
Magnetic Resonance Elastography As a Marker for Prediction of Hepatocellular Carcinoma in Patients with HBV-Related Decompensated Cirrhosis
Authors: Chen Haimei , Zhu Jie , Li Mengsi , Lin Li , Yin Ziying , Chen Jun , Yin Meng , Ehman Richard , Wang Jin
Published: August 2023

Hepatitis B virus (HBV)-related decompensated cirrhosis is well-known risk factor for developing hepatocellular carcinoma (HCC). Therefore, it is critical to assess the risk of developing HCC in these patients. Magnetic resonance elastography (MRE) has promise in predicting future events in many chronic liver diseases, but its prognostic role in predicting HCC development of HBV-related decompensated cirrhosis remains unclear. In our study, we evaluated the performance of baseline liver stiffness measurement (LSM) by MRE in predicting HCC development in patients with HBV-related decompensated cirrhosis. Our results showed that MRE-based LSM was associated with HCC development and is independently predictive of HCC development in patients with HBV-related decompensated cirrhosis.
Predictive value of T1 mapping in cervical cancer recurrence after treatment
Authors: Liu Jie , Li Shujian , Cao Qinchen , Nickel Marcel , Cheng Jingliang , Zhu Jinxia
Published: August 2023

We investigated the feasibility of T1-mapping to predict cervical cancer (CC) recurrence after treatment. Our results show that quantitative T1 values of the primary tumor could effectively predict the CC recurrence after surgery or concurrent chemoradiotherapy (CCRT). These findings suggest that the T1-mapping method could be valuable for evaluating CC recurrence after treatment, and native T1 values of the primary tumor could predict cervical cancer recurrence.