bluuebunny/crossref_metadata_2025 huggingface dataset:
Sodium Coil dedicated Universal Sensitivity Map for scan time reduction of 7T MR in-vivo Sodium Imaging
Authors: Kim Sanghoon , Merugumala Sai , Lin Alexander
Published: August 2023

Sodium studies have shown subtle pathophysiologic changes in tissue sodium concentrations (TSC) in the early stage of the various diseases. One of the major challenges with measuring TSC is its low SNR. Phased array coils are used to increase sodium SNR, however, they result in an inhomogeneous receive profile that makes accurate quantitation of TSC difficult. Uniformity correction is thus required and is often done by generating a sensitivity map. A previous approach introduced the concept of utilizing a universal sensitivity map to reduce total scan time. We present an improved universal sensitivity map solution.
Functional MRI of large-scale brain networks involved in motor control using parallel transmission at 7 Tesla
Authors: Lu Yidi , Wu Chia-Yin , Hodono Shota , Jin Jin , Reutens David , Cloos Martijn
Published: August 2023

The standing wave artefact affects SNR and contrast of the images in Ultra-high field (UHF) functional magnetic resonance imaging (fMRI). One way to mitigate this effect is to use parallel transmission (pTx). In this study, we evaluate the benefits of pTx for studies that investigate large-scale brain networks involved in motor control. We show that, compared to the standard circularly polarized (CP) mode, activation patterns in the posterior lobule of the cerebellum, produced by a coordinated finger flexion-extension task in both hands, are better captured using subject-specific pTx pulses.
Chronic anemia: the effects on the connectivity of white matter
Authors: Zacarias Clio Gonzalez , Choi Soyoung , Leahy Richard , Wood John
Published: August 2023

Chronic anemia is commonly observed in patients with hemoglobinopathies, mainly represented by disorders in hemoglobin structure (e.g., sickle cell anemia, SCA) and hemoglobin synthesis (e.g., thalassemia syndrome). These hemoglobin disorders have been associated with white matter alterations. In this study, changes in white matter connectivity on chronic anemic patients were characterized by quantifying the volumetric mean of fractional anisotropy along the pathway of tracks connecting two ROIs (defined by BrainSuite’s BCI-DNI atlas) and comparing it with healthy individuals. SCA patients showed interhemispheric FA derangements but not to the same extent as changes observed in the watershed areas of non-SCA patients.
Q-FiberMapper - A framework for tractography and tractometry of clinical data
Authors: Boshkovski Tommy , Gallardo Guillermo , Peña-Nogales Oscar , Ramos Marc , Trivodaliev Kire , Rodrigues Paulo , Prchkovska Vesna
Published: August 2023

Despite recent advances in tractography, automatically reconstructing brain bundles in clinical settings remains a challenge. Here we present Q-FiberMapper (QFM), a framework that automatically preprocesses clinical data and reconstructs 33 major brain bundles with minimal user intervention. Furthermore, it derives insightful biomarkers and summarizes the findings in a human readable report. We validate QFM using a large cohort of 600 subjects, and show that it correctly reconstructs the shape and lateralization of major white-matter bundles. By simplifying and speeding the process of clinical reconstruction, QFM could help clinicians in the diagnosis and monitoring of brain pathologies.
Visualizing uterine fibroid perfusion after MR-HIFU ablations using T2-corrected IVIM and deep learning-based fitting – an explorative study.
Authors: Slotman Derk , Bartels Lambertus , Nijholt Ingrid , Heijman Edwin , Froeling Martijn , Boomsma Martijn
Published: August 2023

Blood volume fraction maps derived from diffusion weighted imaging using intravoxel incoherent motion (IVIM) modeling may be an alternative to contrast-enhanced imaging for visualization of local uterine fibroid perfusion, during magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) ablation procedures. In this study, blood volume fraction maps calculated with a T2-corrected IVIM model were compared to T2-uncorrected parameter maps using two fitting techniques. Based on general inspection, T2-corrected parameter maps from deep learning-based fitting were visually the most appealing. A preliminary evaluation showed a linear association between NPVs delineated on blood volume fraction maps and gadolinium contrast-enhanced T1w scans.
Shutter Speed Model based Quantitative DCE-MRI for Therapeutic Response Assessment of Pancreatic Ductal Adenocarcinoma: A Pilot Study
Authors: Holland Martin , Hormuth David , Jiang Xiaoyu , Christenson Chase , Morgan Desiree , Li Yufeng , Xu Junzhong , Yankeelov Thomas , Kim Harrison
Published: August 2023

Shutter Speed Model (SSM) based Ktrans, ve, kep, and τi in the pancreatic tumors before initiating chemotherapyt were 0.081±0.036 mm-1, 0.258±0.070, 0.320±0.152 mm-1, and 0.247±0.197 μs, respectively, without statistical difference between the responding and non-responding groups. The Ktrans in the tumors favorably responding to chemotherapy increased 72±14%, significantly larger than in the non-responding tumors (2±9%, p=0.0001). The ve in the responding tumors also significantly increased compared to the non-responding group (64±25% vs 3±9%, p=0.0036). However, no statistical difference was found between the responding and non-responding groups in either kep (6±11% vs 11±16%, p=0.6204) or τi (3±47% vs 147±280%, p=0.3408).
Intraoperative MRI-derived 3D ablation margins and correlation with local outcome after MRI-guided cryoablation of small renal tumors
Authors: de Jager Nienke , van Oostenbrugge Tim , Pätz Torben , Jenniskens Sjoerd , Fütterer Jurgen , Langenhuijsen Hans , Overduin Christiaan
Published: August 2023

MRI-guided cryoablation of small renal tumors relies on achieving sufficient ice ball coverage throughout the entire lesion for effective treatment. However, a volumetric approach to assess treatment margins intraoperatively is currently lacking. This work retrospectively derived three-dimensional ablation margins after cryoablation in 39 kidney tumors using co-registration of intraoperatively acquired pre- and post-ablation MR images. Minimal ablation margins were significantly smaller for cases with versus without local tumor progression. Radiological complete coverage (ablation margin >0 mm) was associated with local control. MRI-derived 3D ablation margins may present a useful intraprocedural tool to assess treatment success.
Developing and testing robotic MRI/CT fusion biopsy using a novel home-made interventional phantom
Authors: Johnston Edward , Fotiadis Nicos , Cummings Craig , Tyne Toby , Basso Jodie , Messiou Christina , Koh Dow-Mu , Winfield Jessica
Published: August 2023

MRI/CT fusion may enable MRI-guided biopsy without the requirement for dedicated interventional MRI facilities. Assessment and training in MRI/CT-fusion biopsy requires phantoms containing targets that can be seen on MRI but not on CT and can be biopsied. These requirements are not met using commercially available phantoms. We produced a phantom containing targets that can be appreciated on MRI but not CT, which is reproducible, can be biopsied and assessed for core adequacy. We successfully biopsied targets (1-3cm diameter) using a commercially available interventional robot equipped with work-in-progress MRI/CT-fusion software, including targets with steep out-of-plane angulations, within clinically reasonable timeframes.
Automated brain morphometry for sub-millimeter 7T MRI using transfer learning
Authors: Piredda Gian Franco , Venkategowda Punith , Radojewski Piotr , Hilbert Tom , Joseph Arun , Bonanno Gabriele , Wiest Roland , Egger Karl , Yang Shan , Thiran Jean-Philippe , Corredor-Jerez Ricardo , Maréchal Bénédicte , Kober Tobias
Published: August 2023

Large spatial signal variations due to field inhomogeneities complicate the application of automated brain morphometry at 7T. In this work, we propose to use transfer learning to adapt a template-based segmentation algorithm to sub-millimeter ultra-high field applications. More specifically, a convolutional neural network pre-trained on T1-weighted scans to extract the total intracranial volume (TIV) from MP-RAGE acquisitions was re-trained to retrieve the TIV mask directly from MP2RAGE volumes. The developed method proved to reliably deliver brain tissue masks and volumetry at 7T.
Reducing the impact of texture on deep-learning brain tissue segmentation networks trained with simulated MR images
Authors: Khalil Yasmina Al , Ayaz Aymen , Lorenz Cristian , Weese Jürgen , Pluim Josien , Breeuwer Marcel
Published: August 2023

Deep learning-based segmentation algorithms largely rely on the availability of extensive, clinically representative data. While collecting such data requires vast resources, image simulation has the potential of generating realistic data reproducing a wide range of scanner sequences or parameters. In this work, we present an MR image simulation pipeline and evaluate its potential for training a deep-learning network for segmenting several brain structures in T1-weighted images acquired from real scanners. We additionally demonstrate how to prevent performance degradation from the lack of tissue texture in simulated images by combining statistical texture analysis and filtering on the evaluation image set.
Generalisability of Automated CNN-based Renal Segmentation for Multi-Vendor Studies
Authors: Daniel Alexander , Buchanan Charlotte , Morris David , Li Hao , Noble Rebecca , Sousa João , Sourbron Steven , Thomas David , Priest Andrew , Francis Susan
Published: August 2023

Manual segmentation of the kidneys is very time consuming and reader dependent, this renders measurements of total kidney volume (TKV) in large multi-site studies impractical. Here we use a convolutional neural network (CNN), trained on data from a single MRI vendor, to segment the kidneys of volunteers scanned with a harmonised FSE image protocol on MR scanners from three different vendors (GE, Philips and Siemens). The kidneys were manually segmented by two readers, both of which demonstrated a significant difference in TKV across vendors; no significant difference in TKV was found in the segmentations produced by the CNN.
Finding the optimal temperature calibration for postmortem MRS thermometry in forensic medicine
Authors: Zoelch Niklaus , Heimer Jakob , Richter Henning , Thali Michael , Gascho Dominic
Published: August 2023

MRI and MRS are finding more and more their way into forensic medicine. Unlike in vivo measurements, however, the temperature of cadavers in forensic medicine varies considerably and affects the performed measurement. The present study investigated how well published calibrations measured in vivo or in phantoms are suited for postmortem MRS thermometry. Postmortem MRS thermometry would allow to estimate and possibly correct the effects of the local temperature in a forensic setting. The study reveals that despite strong postmortem changes, a reliable estimation of the local temperature over up to 60 hours after death is possible with available temperature calibrations.
Dual-echo single-shot SMS EPI for improved MR thermometry
Authors: Mooiweer Ronald , Tomi-Tricot Raphaël , Krafft Axel , Majeed Waqas , Bhat Himanshu , Razavi Reza , Neji Radhouene , Roujol Sébastien
Published: August 2023

MR thermometry using dual-echo single-shot EPI was evaluated in a phantom. Dual-echo EPI resulted in better temperature stabilities than the single echo acquisitions. This sequence was successfully combined with SMS, which also resulted in higher temperature stability than the single echo acquisitions.
Parametric Study of High Dielectric Constant Helmet Characterization
Authors: Poshtgol Parisa Lotfi , Soon Soo Han , Lanagan Michael , Furman Eugene , Chen Xinlian , Li Xin , Zhu Xiao-Hong , Chen Wei , Yang Qing X
Published: August 2023

Helmets conformal to the human head with high or ultra-high dielectric constant (HDC/uHDC) materials have been shown to enhance the SNR of entire human head along with a receive array. However, the dielectric resonance modes (DRMs) of the helmet have not been studies systematically. This investigation aimed to; 1) describe the characteristics of the DRMs and their RF field distributions; 2) establish the relationships between DRMs and the basic geometric parameters of the helmet using numerical modeling. Understand the DRMs of large uHDC structures are fundamentally important for future applications of uHDC materials for RF field reach.
2nd-order meander dipoles for 7T head coil passive RF shimming
Authors: Gomez Tania del Socorro Vergara , Mamberti Roxane , Dubois Marc , Georget Elodie , Antonakakis Tryfon , Vignaud Alexandre , Kober Frank , Enoch Stefan , Abdeddaim Redha
Published: August 2023

Active and passive RF shimming approaches have been proposed to diminish the B1+ inhomogeneities commonly found in a birdcage coil at 7T. In a previous work, we have introduced a meander dipole based on two 3rd-order Hilbert fractals as an alternative solution for passive shimming. In this work we optimized their design using six 2nd-order Hilbert fractals. Simulations and in vivo MRI at 7T using these structures showed strong B1+ enhancement in the area between the two meander dipoles whereas B1+ was reduced in regions below and above the fractal pads.
Ultra-high resolution human functional imaging using 10.5 Tesla
Authors: Vizioli Luca , Moeller Steen , Grant Andrea , Tavaf Nader , Sadeghi-Tarakameh Alireza , Eryaman Yigitcan , Radder Jerahmie , Lagore Russell , Van de Moortele Pierre-François , Auerbach Edward , Adriany Gregor , Yacoub Essa , Ugurbil Kamil
Published: August 2023

With the development of accelerated acquisition protocols, it is possible to achieve functional brain mapping with submillimeter resolution. This permits studying the human brain at the mesoscopic scale. Typical submillimeter images measure 0.8 mm. isotropic voxels, barely enough to study human functional mesoscopic responses. Here we acquire functional images at 10.5 T with the unprecedented spatial resolution of 0.4 mm. isotropic voxels. Using NORDIC to suppress thermal noise, we demonstrate the feasibility of achieving meaningful brain mapping at these ultra-high resolutions, where single voxels contains but a few thousand cells, further bridging the gap between fMRI and optical imaging
Laminar layer 7T fMRI-EEG reveals human alpha oscillations are predominately from superficial and deep layers
Authors: Marsh Daniel , Sokoliuk Rodika , Aquino Kevin , Pakenham Daisie , Wilson Ross , Panchuelo Rosa Sanchez , Coleman Sebastian , Brookes Matthew , Hanslmayr Simon , Mayhew Stephen , Francis Susan , Mullinger Karen
Published: August 2023

EEG alpha (8-13Hz) oscillations occur throughout the cortex but the generating mechanisms are poorly understood. Opinion is divided between alpha being driven by bottom-up, top-down or both of these processes. Using simultaneous 7T-fMRI-EEG with an eyes open/closed paradigm, we assess the generator of alpha by performing layer-fMRI analysis of GE-BOLD data to determine the strongest BOLD-alpha negative layer correlations. We show that, after accounting for draining vein effects using spatial deconvolution, alpha-BOLD correlations are strongest in the superficial and deep layers suggesting they are predominately driven by top-down processes.
Longitudinal brain imaging reveals brain white matter changes after COVID-19 in the UK Biobank
Authors: Maximov Ivan , van der Meer Dennis , de Lange Ann-Marie , Westlye Lars
Published: August 2023

The COVID-19 pandemic has caused a global health crisis. There are a few indications that this disease has harmful consequences on neurological functioning, besides brain changes following COVID-19 infection have not yet been fully understood. Here, we used UK Biobank (UKB) longitudinal diffusion MRI data acquired before and after COVID-19 tests along the ongoing UKB study. We evaluated brain age gap metrics for the participants with positive and negative test results in order to evaluate COVID-19 consequences on the brain.
Ultrahigh-Field 7T MRI of the Brain of COVID-19 Patients with Neurological Symptoms: An Initial Study
Authors: Rashid Shams , Khegai Oleksandr , Jette Nathalie , Belani Puneet , Pawha Puneet , Saju Sera , Navis Allison , Mathew Brian , Goldstein Jonathan , Gururangan Kapil , Hao Qing , Singh Anuradha , Becker Jacqueline , Delman Bradley , Balchandani Priti
Published: August 2023

Since late 2019, COVID-19 has emerged as a global pandemic that has infected 200 million and killed 5 million. A significant proportion of COVID-19 patients continue to have persistent neurological sequelae after recovery, which are not well understood. In this study, we report our preliminary neuroradiological findings from ultrahigh field MRI at 7T in patients with post-COVID neurological symptoms. We show that numerous heterogeneous abnormalities are present in 7T MR brain images. We expect that these findings may pave the way to explain neurological symptoms in post-COVID patients.
Free-breathing low-field MRI of the lung exhibits functional damages associated with persistent symptoms in Covid-19 patients
Authors: Lévy Simon , Heiss Rafael , Grimm Robert , Grodzki David , Voskrebenzev Andreas , Vogel-Claussen Jens , Fuchs Florian , Strauss Richard , Achenbach Susanne , Klett Daniel , Schmid Jonas , Kremer Andreas , Uder Michael , Nagel Armin , Bickelhaupt Sebastian
Published: August 2023

Free-breathing lung images were acquired at 0.55T in 73 Covid-19 patients, on average 5.4 months after the symptoms onset. Perfusion, fractional ventilation and Flow-Volume Loop correlation (FVLc) maps were extracted with the Phase-Resolved Functional Lung analysis technique, and percentages of defect areas were calculated. The most relevant predictors of the presence of persistent symptoms were the areas with concurrent perfusion and FVLc defects, and the areas without defects. Patients could be classified as symptomatic or asymptomatic with an accuracy of 71% when fitting a regression model with these predictors on the entire dataset and their combined score was significantly different.
Hyperpolarized 129Xe MRI is sensitive to variations in gas exchange impairment in patients with long haul COVID-19
Authors: Mummy David , Bier Elianna , Lu Junlan , Leewiwatwong Suphachart , Bechtel Aryil , Dummer Isabelle , Kabir Sakib , Korzekwinski Jennifer , Williford Katherine , Martindale Shelby , Giovacchini Coral , Shaz David , Mammarappallil Joseph , Alenezi Fawaz , Kim Raymond , Driehuys Bastiaan , Que Loretta
Published: August 2023

Many patients who recover from COVID-19 have symptoms that persist long after the acute phase of the disease has subsided, including fatigue and dyspnea on exertion. There is an unmet need for understanding the diverse cardiac and pulmonary causes of these symptoms and to monitor patients longitudinally. We imaged N=6 subjects with long-haul COVID using both cardiac MRI and hyperpolarized 129Xe MRI and spectroscopy. While cardiac imaging did not reveal structural or functional abnormalities, we observed a wide variety of findings on 129Xe MRI, with subjects who had been hospitalized exhibiting the most pronounced gas exchange impairment.
Exploring the use of Echo Planar Image Correction (EPIC) for intra operative Diffusion Tensore Imaging. – Initial results
Authors: Vatnehol Svein Are , Vik-Mo Einar , Undseth Ragnhild Marie
Published: August 2023

Intra operative MRI with Diffusion Tensor Imaging allows identification of white mater tracks during surgery allowing for a more aggressive approach by the surgeon while preserving eloquent structures. However DTI is prone to artefacts from B0 inhomogeneity. In this abstract we present our initial experiences on the effect of a commercially available Echo Planar Imaging Correction in the intraoperative setting. While overall image quality is increased, further studies on a larger number of patients are required before the clinical effect can be assessed.
Lung segmentation with deep learning for 3D MR spirometry
Authors: He Zhongzheng , Barrau Nathalie , Barakat Claire Pellot , Maître Xavier
Published: August 2023

Current MR lung image segmentation has huge challenges compared to CT images, specifically in terms of low contrast, non-homogeneity. We developed a series of processing to accelerate the manual correction of reference standard lung masks by the auto-seeds region growing. Finally, we developed a 3D automatic MRI lung segmentation method using deep learning with a limited dataset (41 volumes for training and 4 volumes for validation). In the primary result, this lung segmentation archived a Dice score of 0.917±0.013. In the case of limited data, it provides us a new way for MR lung segmentation.
Automatic fibroglandular tissue segmentation in breast MRI using a deep learning approach
Authors: Ouadahi Fares , Bernard Anais , Brun Lucile , Rouyer Julien
Published: August 2023

An accurate fibroglandular tissue (FGT) segmentation model was designed using of a deep learning strategy on T1w series without fat suppression. The proposed method combined a dedicated preprocessing and the training of a two-dimensional U-Net architecture on a multi-centric representative database to achieve an automatic FGT segmentation. The final test of the generated model exhibited overall good performances with a median Dice similarity coefficient of 0.951. More contrasted performances were obtained when correlating the gland density with the discrepancy between ground truth and prediction. Indeed, the lower the breast density, the greater the uncertainty in the segmentation.
Three-dimensional reconstruction and characterization of bladder deformations
Authors: Ogier Augustin , Rapacchi Stanislas , Bellemare Marc-Emmanuel
Published: August 2023

Pelvic floor disorders are prevalent diseases and only 2D dynamic observations of straining exercises at excretion are available in clinics. The understanding of three-dimensional pelvic organs mechanical defects is not yet achievable. We proposed a complete methodology for the 3D representation of the bladder combined with 3D representation of the location of the highest strain areas on the organ surface. We assessed the potential of our method on eight control subjects for the reconstruction of bladder during intense straining from forced breathing exercises. The proposed methodology provided, for the first time, a proper 3D+t spatial tracking of bladder non-reversible deformations.
Quantifying Relative Displacement and Phase at the Skull-Brain Interface using MR Elastography
Authors: Diano Alexa , McIlvain Grace , Knutsen Andrew , Vidhate Suhas , Pham Dzung , Johnson Curtis
Published: August 2023

This study uses a novel multishot spiral magnetic resonance elastography (MRE) pulse sequence to simultaneously measure skull and brain motion in vivo in a single acquisition. Results in a healthy volunteer and a fat-water phantom showed a reduced transmission of motion from the skull to the brain in all three directions of motion. Additionally, the skull and brain appear to be out of phase in motion in both the x (left-right) and z (superior-inferior) directions. This research provides a basis for future studies quantifying skull-brain coupling including with multiple actuation frequencies and excitation directions.
Characterization of tumor mechanical properties in glioma patients using 3D phase-gradient inversion in multifrequency MR elastography
Authors: Shahryari Mehrgan , Gottheil Pablo , Hain Elisabeth , Herthum Helge , Tzschätzsch Heiko , Meyer Tom , Käs Josef , Siebert Eberhard , Prinz Vincent , Sack Ingolf
Published: August 2023

Clinical MRI is an important method for the delineation and characterization of gliomas for resection planning and therapy monitoring in neurosurgery. Here, we used a 3D curl- and phase-gradient based inversion algorithm in multifrequency magnetic resonance elastography (MRE) to generate maps of the mechanical tumor properties, wave speed and wave damping. Overall, our method improved the spatial resolution of MRE maps in glioma patients and allowed precise measurement of tumor mechanical properties. In the future, the method could help with characterization, surgical planning and treatment monitoring of neuro tumors.
Acute Lower Body Negative Pressure Changes Human Brain Stiffness in vivo Measured with MR Elastography
Authors: Kramer Mary , McIlvain Grace , Sanjana Faria , Horvat Fiona , Martens Christopher , Johnson Curtis
Published: August 2023

Lower body negative pressure (LBNP) is a non-invasive physiological method known to decrease cerebral blood flow. This technique was used to study the brain’s response to altered cerebrovascular hemodynamics and showed that, on average, brain stiffness decreases by 2.28% in response to ten minutes of LBNP application and decreased cerebral blood flow. By decreasing and increasing cerebral blood flow by turning the LBNP on and off repeatedly in 10-minute blocks, brain stiffness was shown to increase by 3.02% on average from the initial application of LBNP to the final application of LBNP.
Constant-Tissue Model for Comparison of Supine and Prone Breast Coil SNR
Authors: McKay-Nault Jessica , Moran Catherine , Hess Jeremiah , Vincent Jana , Robb Fraser , Daniel Bruce , Hargreaves Brian
Published: August 2023

Recent work has developed supine breast imaging for improved correlation with surgery and comfort but will likely require breast-specific coils to maximize the SNR. Comparing prone and supine SNR can be difficult due to substantial deformation between the positions and heterogeneity of the patient population. We measured SNR in a constant-tissue model to reduce dependence on tissue heterogeneity and provide an overall SNR across the volume of interest. We compared SNR of a novel 60-channel supine coil and a standard prone coil. In the cosntant-tissue images, the supine 60-channel coil increased SNR by 33%, 78% and 80% across 3 volunteers.
Construction and characterisation of a 7 Tesla flexible body coil with 10 transmit dipoles and 30 receive loops
Authors: Papoutsis Konstantinos , Clément Jérémie , Ogier Stephen , Hajnal Joseph , Goh Vicky , Cook Gary , Ipek Özlem
Published: August 2023

We present the first continuous 30-channel loop receive coil array combined with the 10-channel dipole parallel-transmit array for 7 Tesla body imaging. Array comprises a flexible anterior part with 6 dipoles and 18 loops, with 35cm longitudinal coverage along with a hard plastic posterior part containing 4 dipoles and 12 loops. Special features were added to help patient comfort and overcome cabling limitations. Simulations with computational human model show adequate B1+ coverage in areas of interest such as the prostate. Phantom images were taken showing promising results. Further development will follow, and human imaging is planned in the near future.
High reproducibility of sandwich spatial saturation neuromelanin imaging (sandwichNM): multicenter and test-retest results
Authors: Ji Sooyeon , Choi Eun-Jung , Sohn Beomseok , Kim Eung Yeop , Baik Kyoungwon , Shin Na-Young , Moon Won-Jin , Park Seongbeom , Song Soohwa , Lee Phil Hyu , Shin Dong Hoon , Lee Jongho
Published: August 2023

The reproducibility of the recently proposed sandwich spatial saturation neuromelanin (sandwichNM) imaging, which uses product sequences, is evaluated by a multi-center/multi-vendor traveling-subject study. Additionally, test-retest scans acquiring data in two different days are performed and evaluated. When compared to a conventional MT-weighted GRE NM imaging method, sandwichNM demonstrates higher contrast ratios and smaller variations across scanners, and higher intra-class coefficient and lower coefficient of variation in the test and retest scans, revealing higher reproducibility over the conventional method.
Structural and functional correlates of disinhibited behaviors in Essential Tremor
Authors: Aumann Megan , Phan Tony , Hett Kilian , Darby Ryan , Claassen Daniel
Published: August 2023

Emerging evidence has implicated the cerebellum in not just motor, but cognitive and behavioral roles in the brain. Previous research in cerebellar diseases have reported impulsive behaviors, but it is unknown if Essential Tremor (ET) patients present with these behaviors and where they localize. Here, in 105 ET patients, we measured disinhibition using the Frontal Systems Behavior Scale (FrSBe) and assessed the relationship between disinhibition scores and grey matter volume in the cerebellum, as well as functional correlates of disinhibition-related grey matter atrophy. These results are the first to evaluate neurobiological changes associated with disinhibition in ET.
Cerebral oxygen extraction fraction (OEF) mapping in cognitively impaired and intact elderly
Authors: Cho Junghun , Chiang Gloria , Dyke Jonathan , Zhang Hang , Zhang Qihao , Tokov Michael , Nguyen Thanh , Spincemaille Pascal , Kovanlikaya Ilhami , Amoashiy Michael , de Leon Mony , Wang Yi
Published: August 2023

Cerebral metabolic dysfunction is known to underlie cognitive impairment. This study using a novel challenge-free MRI-based oxygen extraction fraction (OEF) mapping method, namely “QQ”, demonstrated that lower OEF in white matter and hippocampus was associated with greater white matter hyperintensities in cognitively impaired, but not cognitively intact, elderly, whereas older age was association with decreased OEF in cortical gray matter in the cognitively intact. This study suggests that QQ-based OEF mapping may be a useful tool readily and widely available for investigating metabolic dysfunction underlying dementia.
Optimal Transport driven Cycle-consistent Generative Adversarial Network (OT-CycleGAN) for an accurate MR water-fat separation
Authors: Meneses Juan , Arrieta Cristobal , Maggiora Gabriel della , Irarrazaval Pablo , Tejos Cristian , Andia Marcelo , Uribe Sergio , Long Carlos Sing
Published: August 2023

MRI water-fat separation is an ill-posed inverse problem usually addressed using complex numerical methods. This problem is related to an MR signal physical model that includes the effects of R2* signal decay ratio and main magnetic field inhomogeneities (Δf), which induce non-linearities that are related to the ill-posedness of the inverse problem. In this work, we propose an Optimal Transport driven Cycle-consistent Generative Adversarial Networks (OT-CycleGAN) framework, which is physics-based, and could use partially labeled training data to estimate the non-linear components (R2* and Δf), and posteriorly compute the water-fat images through a conventional least-squares approach.
L-carnitine Supplementation used as a Tool for Detecting Hepatic Flexibility of Acetylcarnitine using 1H Magnetic Resonance Spectroscopy.
Authors: Savic Dragana , Mózes Ferenc , Green Peregrine , Burrage Matthew , Allen Gabrielle , James Timothy , Hodson Leanne , Neubauer Stefan , Pavlides Michael , Valkovič Ladislav
Published: August 2023

This study investigated the in vivo effects on acetylcarnitine levels in the liver after an injection of L-carnitine. L-carnitine facilitates transport of fatty acids into the mitochondria. We show that a single injection of L-carnitine modulated acetylcarnitine levels in the liver and that it modulated several blood markers in the healthy volunteer. Further studies are needed to understand the plasma metabolic changes observed with L-carnitine supplementation.
Characteristics of maturation-related differences in rabbit cartilage by quantitative µMRI and PLM
Authors: Xia Yang , Mantebea Hannah , Batool Syeda , Singh Amanveer , Hammami Mohammed , Badar Farid
Published: August 2023

Immature and mature articular cartilage from the humeral joints of rabbits were studied quantitatively and at microscopic resolutions by µMRI and polarized light microscopy (PLM). µMRI data revealed a number of differences between the immature and mature cartilage, including total thickness and T2 relaxation values. PLM data revealed in addition the cellular differences between the tissues. The mature cartilage has a clearly defined tidemark, which was absent in the immature tissue. The ability to differentiate specific maturation-related characteristics in cartilage could benefit translational studies of degenerative diseases such as osteoarthritis.
Non-Invasive Multi-Modal Imaging of Body Composition and Bone Density in Genetically Modified Fshb Mice
Authors: Serkova Natalie , Slack Julia , Steiner Jenna , De Schutter Anna , AlKassi Aaya , Henry Jamie , Brown Mark
Published: August 2023

We report on a multi-modal quantitative MRI/ CT imaging protocol for characterizing the comprehensive body composition and bone health in a genetically modified mouse model. Follicle stimulating hormone (FSH) is directly involved in the regulation of estrogen production, osteoclasto-genesis, and adiposity. In this study we show that the deletion of FSH gene (-/-) in the mouse results in increased adiposity and decreased tibia density in male and female mice as they age. Multi-parametric imaging provides a unique opportunity to quantify visceral adiposity levels, muscle mass, and bone density in mutant animals, non-invasively and in real time.
Assessing metabolic differences in rodents on high fat diet using Deuterium Metabolic Imaging
Authors: Ehret Viktoria , Ustsinau Usevalad , Friske Joachim , Scherer Thomas , Fürnsinn Clemens , Helbich Thomas , Philippe Cécile , Krššák Martin
Published: August 2023

Deuterium Metabolic Imaging (DMI) is a novel method to assess metabolism in vivo using 2H MR Spectroscopic Imaging (MRSI) combined with the administration of deuterated substrates. In this pilot study, we applied 2D DMI following an intravenous injection of deuterated glucose and palmitic acid to evaluate the differences in liver metabolism of rats on standard and high fat diet at 9.4T. The spectra show a lower uptake of glucose and a higher uptake of palmitic acid after injection in high fat diet rats, indicating that liver metabolism is slowed down in rats with fatty livers.
Sequence comparison and test-retest analysis for 31P-MRS in mouse brain at 7 Tesla
Authors: Cherix Antoine , Tachrount Mohamed , Lerch Jason
Published: August 2023

31P-MRS is challenging in small samples as it suffers from long T1s, short T2s and low nucleus sensitivity (γ). Thus, ultra-high field has been generally preferred for investigating the mouse brain. Less is known about its feasibility at lower field strength with more readily available scanners. Here, we assess the applicability of 31P-MRS in mouse at 7T to study neuroenergetics by comparing 3D-ISIS, PRESS and sLASER. Then, by performing a test-retest analysis and power calculations we assessed the relevance of our method for potential preclinical studies application.
Tracking disease progression in mouse models of polycystic kidney disease with high resolution MRI and automated postprocessing
Authors: Schmid Florian , Koukos Georgios , Sooknah Matt , Assili Sanam , Riegler Johannes
Published: August 2023

We present an improved MRI acquisition and data processing pipeline to assess disease progression in mouse models of polycystic kidney disease. High-resolution anatomical T2 weighted images as well as T2 mapping are used to track changes in kidney volume, cyst burden and tissue composition. We established versatile deep-learning automatic kidney segmentation, trained on a range of kidney disease stages, animal models and image resolutions.
Feasibility of Cardiovascular Magnetic Resonance Imaging of In Vivo Mouse Heart using Multitasking at 9.4T
Authors: Wang Zhongmiao , Ruan Yang , Gao Qichan , Lei Hongxia , Zhai Renkuan , Xing Yao , Zhang Zhongqi , Xu Jian , Liu Qi
Published: August 2023

The feasibility of cardiac T1 mapping in mouse is demonstrated at 9.4T using Multitasking, an ECG-free and free-breathing technique. High spatial- and temporal-resolution T1 maps of healthy mouse hearts without either respiratory or cardiac triggering were obtained. This technique simplifies experimental setup and opens possibilities of investigating numerous heart disease/transgenic mouse models.
Correlation methods between X- ray phase contrast imaging, MRI and histology for the study of the nervous central system
Authors: Maugeri Laura , Nicaise Charles , Guidi Maria , Jankovski Aleksandar , Malucelli Emil , Sierra Alejandra , Abdollahzadeh Ali , Salo Raimo A. , Egidi Irene , Gigli Giuseppe , Giove Federico , Cedola Alessia , Fratini Michela
Published: August 2023

Many serious pathologies of the central nervous system (CNS) are related to anomalous development or damages to the vascular and neuronal networks. Here, we show our approach based on MRI/XPCT, XPCT/ HISTOLOGY combination in order to study neuronal and vascular alterations following a damage in mouse models.
MR Spectroscopy of HP [1-13C]Pyruvate in an In Vitro Model of Epilepsy
Authors: Jhajharia Aditya , Serra Riccardo , Bachani Muznabanu , Olu-Owotade Jemima , Zhu Minjie , Rogers Joshua , Ksendzovsky Alexander , Mayer Dirk
Published: August 2023

In this study, we investigated hyperpolarized (HP) magnetic resonance spectroscopy (MRS) as a means to identify differential lactate release in an in vitro model of epilepsy. When neurons are chronically activated, they increase LDHA expression and upregulate glycolysis as a means of cellular energy metabolism, thus increasing the production of lactate. Using MRS of HP [1-13C]pyruvate, we showed conversion to lactate in a chronic model of epilepsy. These results indicate that metabolic imaging of HP [1-13C]pyruvate can potentially be used as a tool to identify lactate elevations and thus the epileptic focus in epilepsy patients.
Estimating Hemodynamic Response Function Using Simultaneous fMRI and Calcium Recording
Authors: gerdekoohi Shabnam khorasani , Sah Pankaj , Chuang Kai-Hsiang
Published: August 2023

· Evoked BOLD and calcium signals were recorded in the visual pathway using standard (TR=1s) and ultrafast (TR=0.3s) EPI of two TEs.

· Hemodynamic response function was estimated based on neuronal calcium activity. HRF estimated from ultrafast fMRI shows faster kinetics in the lateral geniculate nucleus than the visual cortex.

· BOLD signal was predicted from calcium signal convoluted by HRF. Using ultrafast fMRI significantly improved the accuracy of the predicted BOLD.
Reconstruction of 3D EPI timeseries including a correction of different acquisition times
Authors: Bianchi Samuel , Heinzle Jakob , Engel Maria , Kasper Lars , Pruessmann Klaas
Published: August 2023

Standard fMRI acquires volumes as stacks of slices with 2D sequences. Acquisition time differences within a volume can be corrected post hoc using a sinc interpolation in image space (“slice timing correction”). In 3D sequences, timing correction is not possible in image space. Here, we verify an approach that rests on a sinc interpolation of timeseries in k-space before image reconstruction. Particularly, we investigate the artifacts which get removed by timing correction and quantify effects on the power spectra of timeseries in image space for 3D EPI.
Model-based self-navigated water/fat decomposition for segmented diffusion-weighted EPI
Authors: Dong Yiming , Riedel Malte , Koolstra Kirsten , van Osch Matthias J.P. , Börnert Peter
Published: August 2023

Multi-shot EPI readout-approaches provide high spatial resolution at reduced geometric distortions and improved SNR in diffusion weighted imaging (DWI). As a specific challenge, multi-shot acquisition data require corrections for motion-induced, shot-specific phase errors, e.g. using additional navigator signals or appropriate self-navigation. Furthermore, proper fat-suppression is challenging in DWI, especially at B0 critical regions, making the use of chemical-shift encoding interesting. Therefore, an iterative, model-based reconstruction algorithm with self-navigation and water/fat decomposition, is proposed in this work. In-vivo examples in the leg and head-neck regions demonstrate improved water/fat separation as compared to acquisition-navigator approaches, while measurement times can be shortened.
Fast $$$T_{2}^{*}$$$ and QSM mapping using temporal CS with a Complementary Stochastic Sampling Scheme
Authors: Iglehart Charles , Bilgin Ali , Saranathan Manojkumar
Published: August 2023

We develop the motivation for and demonstrate the functionality of a temporal model-based complex multi-echo reconstruction algorithm coupled with a Complementary Stochastic Sampling procedure allowing for temporal sparsity to be leveraged . We demonstrate results for magnitude and phase images as well as parameter maps.
Preclinical Evaluation of Two Compressed Sensing Methods for DTI
Authors: de Souza Diego Alves Rodrigues , Mathieu Hervé , Deloulme Jean-Christophe , Barbier Emmanuel
Published: August 2023

Compressed Sensing (CS) is not routinely implemented at the preclinical level, especially in case of multiple receivers. In this study, we evaluate preclinical Kernel Low-Rank and Conventional CS reconstruction schemes at 9.4T using a 4-channel receive coil and spin-echo data. By analyzing diffusion parametric maps and white-matter tracts, we evaluate the median absolute error, the structural similarity index measure and the mean fiber length as a function of the acceleration factor and of the CS reconstruction pipeline.
Off-resonance correction in MRF using Deep Learning in fingerprint space
Authors: Coronado Ronal , Castillo-Passi Carlos , Maggiora Gabriel della , Uribe Sergio , Tejos Cristian , Prieto Claudia , Besa Cecilia , Irarrazaval Pablo
Published: August 2023

Magnetic Resonance Fingerprinting (MRF) acquisitions with balanced Steady State Free Precession (bSSFP) and spiral trajectories are prone to off-resonance artifacts. These artifacts affect the reconstruction of the tissue maps (T1 and T2). We propose to use a UNet CNN feed with fingerprints corrupted by off-resonance to generate corrected fingerprints with only aliasing in the bSSFP-MRF sequence. The feasibility of the proposed approach was evaluated in simulations and in-vivo brain data. Our method improved the NRMSE values for both quantitative maps T1 and T2. Considerably reducing the effects of the off-resonance by UNet-MRF in comparison to classical bSSFP-MRF.
Measurements of composite signals with MR-based neuronal current imaging: one step closer to clinical application.
Authors: Capiglioni Milena , Kiefer Claus , Wiest Roland
Published: August 2023

We evaluated the performance of stimulus-induced rotational saturation contrast (SIRS) to assess the possibility of detecting neuronal currents. We analyzed composite signals with multiple frequencies to evaluate the ability of the technique to be used as a filter of spectral components. We conclude that the method can separate and distinguish frequency components and reconstruct the distribution of spectral components between individually acquired signals. These tests are the basis for moving towards the clinical application of this sequence to locate fields with frequencies associated with specific pathologies.
Simultaneous Multi-Slice Acceleration of Multi-Echo EPI Provides Rapid and Accurate Quantitative Susceptibility Mapping
Authors: Kiersnowski Oliver , Fuchs Patrick , Wastling Stephen , Thornton John , Shmueli Karin
Published: August 2023

Simultaneous multi-slice (SMS) acquisition is increasingly used to accelerate echo planar imaging (EPI). EPI acquisitions have been used for quantitative susceptibility mapping (QSM) but, to utilise SMS, an investigation into the effect of SMS on EPI-QSM accuracy is necessary. Here, we show that SMS has no significant effect on magnetic susceptibility maps and values, and can, therefore, provide accurate QSM within a short TR. We also show, for the first time, that multi-echo phase images can be acquired using an EPI sequence (highly) accelerated using SMS and parallel imaging, leading to more accurate QSM reconstruction compared to standard single-echo EPI.
Phase filtering methods significantly impact the quality of susceptibility tensor reconstruction
Authors: Chen Jingjia , Liu Chunlei
Published: August 2023

Phase filtering is a very important step in obtaining a good susceptibility tensor. We compare and illustrate the effects of different phase processing methods on the quality of susceptibility tensor reconstruction with different numbers of orientations. In general, tensor reconstructed from variations of the SHARP phase filtering methods show the most robustness against the large field inhomogeneity and produce tensor elements that are spatially and anatomically more consistent. Compared to the original STI reconstruction, asymmetric STI reduces some of the variations induced by phase filtering methods.
Comparison of Quantitative Susceptibility Mapping Methods for Brain Iron Imaging at 7T
Authors: Yao Jingwen , Morrison Melanie , Jakary Angela , Avadiappan Sivakami , Chen Yicheng , Glueck Julia , Driscoll Theresa , Geschwind Michael , Nelson Alexandra , Hess Christopher , Lupo Janine
Published: August 2023

Quantitative susceptibility mapping (QSM) is a promising tool to investigate iron dysregulation in neurodegenerative diseases. A diverse range of methods has been proposed to generate accurate and robust QSM images. In this study, we evaluated the performance of different dipole inversion algorithms for brain iron imaging at 7T, including iLSQR, iterative methods with regularization (STAR-QSM, FANSI, HD-QSM, MEDI), single-step methods (QSIP, SSTV, SSTGV), and deep learning methods (QSMGAN, QSMnet+). We found that SSTV/SSTGV provided the best performance in terms of correlation with age, correlation with iron, and the differentiation between healthy control and premanifest Huntington’s disease individuals.
XSIM, a Susceptibility-Optimised Similarity Index Metric: Validation with 2016 and 2019 QSM Reconstruction Challenge Datasets
Authors: Milovic Carlos , Tejos Cristian , Irarrazaval Pablo , Shmueli Karin
Published: August 2023

The Structural Similarity Index (SSIM) has become a popular quality metric to evaluate Quantitative Susceptibility Mapping (QSM) in a way that is closer to human perception than the Root-Mean-Squared-Error (RMSE). However, SSIM may over-penalize errors in diamagnetic tissues and under-penalize them in paramagnetic tissues. Extreme susceptibility artifacts may also compress the dynamic-range, resulting in unrealistically high SSIM scores (hacking). To overcome these problems we propose XSIM: SSIM implemented in the native QSM ppm range with new susceptibility-optimized internal parameters. We validated XSIM using data from both QSM challenges. XSIM avoids bias and metric-hacking, promoting sharp susceptibility maps and preventing over-regularization.
Observing hyperintensity region within substantia nigra in cynomolgus monkey
Authors: Oh Chungseok , Jeon Chang-Yeop , Seo Jincheol , Shin Hyeong-Geol , Ji Sooyeon , Park Seongbeom , Song Soohwa , Shin Dong Hoon , Lee Youngjeon , Lee Jongho
Published: August 2023

In this study, a hyperintensity region within substantia nigra is explored in cynomolgus monkeys over a wide range of ages. This region is similar to that of humans, which is often called as a swallow tail sign in healthy subjects. This nigral hyperintensity appears consistently in SMWI, QSM, and T2*-weighted images, particularly in aged animals.
Quantitative Analysis of Deep Nuclei in Patients with Parkinson’s disease (PD) using STrategically Acquired Gradient Echo (STAGE) Imaging
Authors: Liu Zhaoxi , Zhang Yiwei , Wang Han , Xu Dan , Wu Bo , Haackeb E. Mark , You Hui , Feng Feng
Published: August 2023

Patients with Parkinson’s disease (PD) showed increased iron deposition in the substantia nigra, red nucleus, dentate nucleus and globus pallidus compared with healthy controls. Besides, the T1 value, T2* value and R2* value of deep nucleus also altered in PD patients. Which suggested the STrategically Acquired Gradient Echo (STAGE) imaging could provide a good performance in quantitative analysis in multi-modal parameters.