bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Technology Acceptance Model (TAM) in Telemedicine Application During Covid-19 Pandemic
Authors: Galuh Puspitarani Sudaryono Noverinda , Fadhiil Mahmud , Syarifah Syarifah , Rinawati Simanjuntak Evi
Published: August 2023

The COVID-19 pandemic hit the whole world, including Indonesia, forcing people to limit all activities outside their homes, including treatment activities to hospitals. This study aims to examine the application of the technology acceptance model (TAM) to telemedicine applications during the COVID-19 pandemic. The proposed research model is formulated from the extended technology acceptance model theory with empirical testing using data obtained from telemedicine user surveys. This study analyzed two additional external factors: privacy concerns and trust. Data is processed using SmartPLS software. A total of 406 telemedicine users participated in this study with male, n=206; 51%, female, n=200; 49%. Research respondents habitually used telemedicine applications during the COVID-19 pandemic that hit Indonesia. Among these respondents, 94.7% reported using telemedicine services during the COVID-19 pandemic. The most widely used telemedicine application, with a total of 59.7% of respondents, chose Halodoc. The external variable privacy concern does not affect the perceived usefulness of telemedicine used. However, trust and perceived usefulness are associated with a positive significance in telemedicine used during the COVID-19 pandemic in Indonesia. Privacy concerns have a limited impact on the perception of expediency but influence the ease of use of telemedicine apps. On the other hand, trust plays a vital role in shaping telemedicine's perceived usefulness and ease of use during the COVID-19 pandemic, as telemedicine has become indispensable for accessing healthcare services.
Training and Development of Productive Teachers in Improving Work Skills for Vocational High School (SMK) Level Students in Sigli
Authors: Riska Mutia , Khairuddin Khairuddin , Usman Nasir
Published: August 2023

Teacher guidance and development is urgently needed to improve the professional abilities of teachers in improving learning processes and outcomes through the provision of professional service-style assistance to teachers. Productive teachers will provide learning material that begins with making a Learning Implementation Plan which then evaluates the process and improves the learning system in the classroom by prioritizing material that can support students to be active, think creatively and be innovative. The purpose of this study was to find out an overview of the coaching and development of productive teachers in improving work skills for students at vocational high schools (SMK) in Sigli. This study used a qualitative approach with a descriptive research type. Data collection techniques using observation, interviews, and documentation. The data analysis technique used is descriptive qualitative analysis with data reduction techniques, data presentation, and drawing conclusions. Based on the research findings, it was found that: (1) Coaching in improving productive teacher performance skills at Sigli Vocational High School includes: coaching through MGMP, IHT (in the house training), teacher coaching through supervision, and pedagogical and professional competency development; (2) Productive teacher development strategies in improving work skills, namely by: continuing education, participating in training/workshops, promotions, development through promotions, assigning teachers to apprentices in industry to improve abilities/upskilling and update skills/reskilling; and (3) teacher participation in productive teacher training and development programs carried out by school principals has been very good. Teachers participate in every activity, are able to adopt ideas or programs to support the teaching and learning process, teachers also attend training to improve teacher competence.
Principal Leadership in Improving Teacher Discipline at Sigli 3 Public Elementary School and Block Sawah Public Elementary School, Pidie Regency
Authors: Adha Erni , Murniati Murniati , Usman Nasir
Published: August 2023

Principal leadership is a pattern of consistent behavior shown by leaders when leaders try to influence the activities of others. Good school principal leadership must be able to strive for increased discipline for teachers and the school environment. The purpose of this study was to find out how the principal's leadership in improving teacher discipline at SD Negeri 3 Sigli and SD Negeri Blok Sawah, Pidie Regency. This study used a qualitative approach with a descriptive research type. Data collection techniques using observation, interviews, and documentation. The data analysis technique used is descriptive qualitative analysis with data reduction techniques, data presentation, and drawing conclusions. Based on the research findings, it was found that: (1) Programs that are planned and carried out to improve teacher discipline include: setting rules, teaching discipline, learning planning discipline, learning implementation discipline, learning evaluation discipline; (2) The principal's strategy in improving teacher discipline is by: providing motivation, setting a positive example, admonishing (punishment) and give gifts (reward) for disciplined teachers, make direct observations during learning and extracurricular activities, then evaluate teachers by providing criticism and suggestions at teacher coordination meeting forums and conducting performance appraisals; and (3) Obstacles to school principals in improving teacher discipline, namely: lack of motivation in increasing discipline, distance and travel time to school, lack of family support, and the presence of some people who are less sensitive to reprimands and input.
Simultaneous lumen and vessel wall imaging with iT2Prep-BOOST for an efficient comprehensive assessment of aortic disease
Authors: Munoz Camila , Fotaki Anastasia , Hajhosseiny Reza , Kunze Karl , Neji Radhouene , Botnar René , Prieto Claudia
Published: August 2023

Bright- and black-blood imaging are key contrasts for the assessment of lumen and vessel wall integrity in aortic MRI. These contrasts are usually acquired separately, resulting in long and inefficient examinations. Here we extend a previously introduced motion-compensated interleaved acquisition (iT2Prep-BOOST) to produce high-quality co-registered 3D bright- and black-blood images from a short predictable scan of ~8min. The proposed iT2Prep-BOOST approach resulted in bright-blood images with improved contrast compared to conventional bSFFP images, and black-blood images with increased volumetric coverage and resolution compared to conventional HASTE images, showing promise for a comprehensive assessment of aortic disease from a single scan.
Diffusion-Weighted Imaging at 0.064 T
Authors: O'Halloran Rafael , Dyvorne Hadrien , Sacolick Laura , Schlemper Jo , Sofka Michal , Salehi Sadegh , By Samantha , Schleicher Riana , Knopp Edmond , Sheth Kevin , Kimberly W. Taylor
Published: August 2023

A sequence is described for DWI on a portable, 0.064T scanner. Images in a healthy subject and a patient with pathology are shown.
Interleaved 1H-MRI, 2H-MRSI and 13C-MRS for time-resolved in vivo elucidation of glucose metabolism in human liver at 7 T
Authors: Poli Simone , Emara Ahmed , Ballabani Edona , Buser Angeline , Tappy Luc , Bally Lia , Kreis Roland
Published: August 2023

An interleaved 2H-MRSI / 13C-MRS protocol to obtain a complete picture of glucose turnover in the human liver at 7T is presented. A dedicated triple-tuned surface coil was used and the setup was optimized for temporal and spatial resolution, SNR (under the restraints of SAR) and robustness to assess hepatic glucose uptake and glycogen production. Data quality and initial kinetic data after oral deuterated glucose load is reported. Further optimization is intended to establish absolute concentrations and to generate kinetic models of metabolic fluxes.
Characterization of Pulmonary Flow Hemodynamic Patterns in Patients with repaired Tetralogy of Fallot using 4D Flow MRI
Authors: Hudani Ashifa , Patton David , White James , Greenway Steven , Garcia Julio
Published: August 2023

Tetralogy of Fallot (TOF) occurs in 1 in 3,500 births and is the most common cyanotic congenital heart defect. Patients with repaired TOF (rTOF) require constant monitoring to prevent life-threatening adverse effects. Hence, this study used 4D Flow MRI to assess pulmonary flow hemodynamics in patients with rTOF. All hemodynamic parameters calculated along the main pulmonary were shown to be higher in patients compared to controls.
Early tumour response to radiotherapy assessed by magnetic resonance elastography
Authors: Lesbats Clementine , Roy Upasana , Reeves Emma , Boult Jessica , Jamin Yann , Cummings Craig , Sullivan James , Sinkus Ralph , Wennerberg Erik , Robinson Simon
Published: August 2023

Radiotherapy is widely used to treat cancer. In this study, we used MR elastography to evaluate early tumour response to radiation therapy. A significant increase in stiffness |G*| and elasticity Gd were determined 3 days after orthotopic 4T1 breast tumours were irradiated with a single 8Gy dose, compared to untreated control tumour-bearing mice. The increase in tumour stiffness was associated with an increased macromolecule pool measured by magnetisation transfer, and increased collagen deposition observed histologically.
Deep-Bloch Simulator Driven Recurrent Neural Network for Reliable Semisolid Magnetization Transfer Contrast MRF and CEST Imaging
Authors: Singh Munendra , Moghadas Babak , Jiang Shanshan , van Zijl Peter , Zhou Jinyuan , Heo Hye-Young
Published: August 2023

High-resolution MRF including a multi-pool saturation transfer model requires a huge dictionary or training dataset simulated with Bloch equations. Furthermore, intensive Bloch simulation tasks are inevitable for MRF schedule optimization. In this study, we developed a deep-learning-based ultrafast Bloch simulator and a recurrent neural network (RNN) for semi-solid macromolecular magnetization transfer contrast (MTC) MRF reconstruction. For the MRF training dataset generation, the deep-learning Bloch simulator required ~200x less time than a conventional Bloch simulation. A test-retest study showed excellent reliability of the tissue parameter quantification using the proposed RNN framework.
Unsupervised correction network for Nyquist ghost artifact and geometry distortion in echo planar imaging
Authors: Kim Jeewon , Kwon Kinam , So Seohee , Kim Byungjai , Lee Wonil , Park HyunWook
Published: August 2023

We propose a new correction scheme using a deep neural network with unsupervised learning to correct Nyquist ghosts and geometry distortions occurring in EPI. The proposed scheme includes NGAC-net and GDC-net. First, the NGAC-net estimates the phase error of k-space with the help of a ghost formulation operator and correlation loss. The NGAC-net produces two Nyquist ghost corrected images obtained by dual-polarity phase-encoding gradients. The GDC-net is trained to estimate the frequency-shift map using the two output images from the NGAC-net. Afterwards, an MR image generation operator utilizes the estimated frequency-shift map to obtain the geometry distortion corrected images.
Deep learning-based high-resolution pseudo-CT to detect cranial bone abnormalities for pediatric patients using MRI
Authors: Boroojeni Parna Eshraghi , Chen Yasheng , Eldeniz Cihat , Commean Paul , Skolnick Gary , Patel Kamlesh , An Hongyu
Published: August 2023

Head trauma is common in the pediatric population. Craniosynostosis is abnormal early fusion of a cranial suture, causing an irregular-shaped cranium.3D high-resolution head CT scans are commonly used in these pediatric patients to identify skull fractures and sutures. However, CT exposespediatric patients to ionizing radiationand increases risk of cancer. We developed a robust and automated deep learning method to convert MR images to pseudo-CT (pCT) that can facilitate translating MR cranial bone imaging into clinical practice. An average Dice Coefficient of 0.89 and mean absolute error of 72.45 HU between pCT and CT were achieved.
Bluetooth-enabled reconfigurable metamaterials for MRI
Authors: Philipp Dennis , Stoja Endri , Konstandin Simon , Wilke Robin , Betancourt Diego , Bertuch Thomas , Umathum Reiner , Jenne Juergen , Guenther Matthias
Published: August 2023

Bluetooth (BLE)-controlled, reconfigurable metamaterials (MTMs) for SNR enhancement in MRI are presented. These metasurfaces allow to be wirelessly interfaced and tuned during an MRI scan by means of a digital capacitor (DCAP), which is connected to a low-power microcontroller with BLE capabilities. Two prototypes are manufactured, one of which is a metasurface with adjustable resonance frequency, and the second one is dynamically tunable at the unit cell scale. It includes multiple DCAPS and, thus, is the first wirelessly reconfigurable MTM for MRI that offers field shaping capabilities, adjustable FoV, focal regions, sequence sync., and active detuning.
A Multi-Stage 3D Patch-wise Deep Learning Algorithm for Detection of New Multiple Sclerosis Lesions in Longitudinal MRI
Authors: Kang Junghwa , Jung Siyun , Yim Jeongmin , Jang Jinhee , Nam Yoonho
Published: August 2023

Detecting changes in multiple sclerosis (MS) lesions through follow-up MR images is an important but time-consuming and subjective process. In this work, we propose a fully automatic deep learning-based method to detect new MS lesions. The model was trained and tuned using the MSSEG2 challenge dataset. First, the brain and spinal cord masks were generated, and registration between two time points was performed. Then, new lesions and whole lesions were segmented by patch-wise inputs, respectively. The final mask for new lesions was produced by comparing these two segmentations, and in this way we could effectively reduce false-positives.
Use of pCASL MRI to quantify Cerebral Blood Flow and Blood-Brain Barrier Permeability in Patients with Ischemic Stroke
Authors: Mouchtouris Nikolaos , Alizadeh Mahdi , Flanders Adam , Wu Chengyuan , Mohamed Feroze , Gooch Reid , Tjoumakaris Stavropoula , Jabbour Pascal
Published: August 2023

In this pilot study, we apply diffusion-prepared pseudo-continuous arterial spin labeling (DP-pCASL) non-contrast MRI sequence to patients with anterior circulation ischemic strokes and determine the cerebral blood flow (CBF) and blood-brain barrier (BBB) permeability in the affected vascular territories. When comparing their imaging findings to 24 control hemispheres (12 healthy volunteers), we demonstrated that both the CBF and BBB of the affected MCA territory was significantly lower than the MCA territories in healthy volunteers. Additionally, the BBB permeability in the affected territory appears to be elevated in acute ischemic strokes but decreases in subacute strokes.
Receive Array Coil-driven Eddy Current Correction of Diffusion Weighted MRI Data
Authors: Yaghmaie Negin , Syeda Warda , Blunck Yasmin , Glarin Rebecca , Staeb Daniel , O'Brien Kieran , Kolbe Scott , Johnston Leigh
Published: August 2023

An eddy current correction algorithm is proposed that exploits the spatially distributed nature of the receive coil array with signal acquisition immediately preceding image readout in PGSE-EPI diffusion-weighted imaging. The array coil phase for each diffusion gradient direction is expanded using spherical harmonics to yield an estimate of the eddy current-induced field shift in the FOV, and the resultant eddy current-induced pixel shift maps. Distortion corrected diffusion-weighted images are subsequently produced using the estimated pixel shift maps for each diffusion direction, with the method demonstrated in phantom and in-vivo 7T experimental data.
Investigating exchange, structural disorder and restriction in Gray Matter via water and metabolites diffusivity and kurtosis time-dependence
Authors: MOUGEL Eloïse , Valette Julien , Palombo Marco
Published: August 2023

This work reports first-time measurements of the time-dependent diffusivity and kurtosis of both water and metabolites in vivo in the mouse gray matter (GM). Our aim is to exploit the complementary information provided by the diffusion of water and intracellular metabolites to investigate and potentially disentangle the role of exchange, structural disorder and restriction in GM. Our results show evidence that water diffusion-time dependence in GM is mostly driven by 1D short-range disorder, potentially alongside exchange. Conversely, metabolites’ diffusion-time dependence is exclusively driven by cellular restrictions, paving a new way to quantify noninvasively microstructural restrictions in GM.
Diffusion-MRI based Estimation of Cortical Architecture using Machine-learning (DECAM)
Authors: Zhu Tianjia , Ouyang Minhui , Huang Hao
Published: August 2023

Advanced diffusion MRI (dMRI) has enabled noninvasive microstructural assessment that can be only conventionally measured with histology1-9. However, analytical dMRI models are limited by their restrictive model assumptions, lack of validation, and biased microstructural measures. We have developed Diffusion-MRI based Estimation of Cortical Architecture using Machine-learning (DECAM), a data-driven dMRI-based method accurately estimating cortical soma and neurite densities (SD and ND) in the cortex10 leveraging a variety of complementary dMRI contrasts. By providing high-fidelity estimated soma and neurite density maps validated with histology, DECAM paves the way for data-driven noninvasive virtual histology for potential applications such as Alzheimer’s diseases.
Intercollicular interactions drive ipsilateral negative BOLD responses upon monaural auditory stimulation
Authors: Severo Frederico , Valente Mafalda , Shemesh Noam
Published: August 2023

Negative BOLD responses (NBRs) in rat Inferior Colliculus (IC) were recently observed upon monaural auditory stimulation, but their origins and importance remain poorly understood. Intercollicular communication is proposed as a prominent mechanism for auditory processing, including sound localization/lateralization & in gain control regulation. Here, we investigated intercollicular interaction via monoaural stimulation at 9.4T. Rats exhibited NBRs in the ipsilateral IC and positive BOLD responses (PBRs) in the contralteral IC. When the contralateral hemisphere was lesioned, the NBRs vanished in the ipsilateral IC. Our findings suggest that intercollicular interaction is essential for ipsilateral negative BOLD responses and for auditory processing.
Improved Myocardial Scar Visualization with Two-minute Free-breathing Joint Bright- and Black-blood Late Gadolinium Enhancement Imaging
Authors: Bustin Aurelien , Sridi Soumaya , Maillot Aurelien , Pineau Xavier , Nuñez-Garcia Marta , Sermesant Maxime , El Hamrani Dounia , Magat Julie , Naulin Jérôme , Clément-Guinaudeau Stéphanie , Bazin Claire , Dournes Gäel , Montaudon Michel , Laurent François , Jaïs Pierre , Stuber Matthias , Cochet Hubert
Published: August 2023

Black-blood late gadolinium enhancement (LGE) techniques are increasingly being used to uncover myocardial scar patterns that may be otherwise confused with blood signal on conventional bright-blood LGE, especially when involving the subendocardium. With signal-attenuated blood and dark muscle representation, these techniques may however be hampered by a lack of anatomical information, making spatial localization of myocardial injuries a challenging task. Here we aim to assess the clinical performance of a novel LGE technique that combines both bright- and black-blood imaging in a single time-efficient free-breathing exam to obtain LGE images with unprecedented scar contrast and localization.
3D Joint Reconstruction of Non-Contrast and Contrast-Enhanced CMR Multitasking
Authors: Mao Xianglun , Lee Hsu-Lei , Kwan Alan , Cao Tianle , Han Fei , Xie Yibin , Li Debiao , Christodoulou Anthony
Published: August 2023

Cardiovascular MR (CMR) is used to acquire function, morphology, and composition of the heart which aids in clinical diagnosis and management. While measures such as ejection fraction, ventricular dimensions, and presence/pattern of late gadolinium enhancement (LGE) have stood the test of time as diagnostic pillars, newer quantitative tissue property measurements such as T1, T2, and extracellular volume (ECV) can characterize diffuse fibrosis, inflammation, or infiltration. The purpose of this study was to integrate multiple quantitative measurements into a single 20-min free-breathing, non-ECG, motion-resolved whole ventricular 3D acquisition using CMR Multitasking, including cardiac function, pre-contrast T1/T2, ECV, and LGE images.
Multifrequency MR elastography for time-resolved shear wave speed quantification of the in-vivo human heart.
Authors: Anders Matthias , Warmuth Carsten , Tzschätzsch Heiko , Herthum Helge , Degenhardt Katja , Schmitter Sebastian , Schulz-Menger Jeanette , Braun Jürgen , Sack Ingolf
Published: August 2023

Cardiac MR elastography (MRE) has the potential to noninvasively characterize the underlying pathophysiology in heart failure with preserved ejection fraction based on abnormal stiffness values. However, the need for synchronizing MRE with cardiac motion, breathing and harmonic vibrations continues to be a challenge. We have developed a single-shot, spin-echo cardiac MRE sequence, which continuously acquires wave images at multiple frequencies with retrospective gating of wave phases relative to the cardiac phase to cover the propagation of shear waves over the full cardiac cycle. Our preliminary data show the dispersion of myocardial stiffness over frequency in systole and diastole.
Hyperpolarized [1-13C]-alanine monitors tumor immortality and detects response to therapy in patient-derived glioblastoma models in vivo
Authors: Batsios Georgios , Tran Meryssa , Gillespie Anne Marie , Taglang Celine , Ronen Sabrina , Costello Joseph , Viswanath Pavithra
Published: August 2023

Telomerase reverse transcriptase (TERT) expression is essential for tumor proliferation. TERT also reprograms metabolism by elevating NADH and upregulating the alanine transporter ASCT2. Here, we exploit these TERT-associated metabolic alterations for non-invasive imaging in live GBM cells and orthotopic tumors using hyperpolarized [1-13C]-alanine. Combined treatment with the TERT inhibitor 6-thio-2’-deoxyguanosine and the ASCT2 inhibitor V-9302 inhibits GBM proliferation, identifying a novel therapeutic opportunity. Importantly, lactate production from hyperpolarized [1-13C]-alanine is an early biomarker of response to treatment in vivo, prior to the onset of anatomical alterations. Our findings pave the way for improved therapy and response assessment for GBM patients.
Accelerated respiratory-resolved 4D-MRI with separable spatio-temporal neural networks
Authors: Terpstra Maarten , Maspero Matteo , Verhoeff Joost , van den Berg Cornelis
Published: August 2023

Four-dimensional (4D) respiratory-resolved imaging is crucial for managing respiratory motion in radiotherapy, enabling irradiation of highly mobile tumours. However, acquiring high-quality 4D-MRI requires long acquisition (typically ≥5 minutes) and long iterative reconstructions, limiting treatment efficiency. Recently, deep learning has been proposed to accelerate undersampled MRI reconstruction. However, it has not been established whether deep learning may reconstruct high-quality 4D-MRI from accelerated acquisitions. This work proposes a small deep learning model that exploits the spatio-temporal information present in 4D-MRI, allowing to split the reconstruction into two separated branches, enabling high-quality retrospectively-accelerated 4D-MRI acquired in ~60 seconds and reconstructed in 16 seconds.
Advanced Gradient-Free Selective Excitation Using the Bloch-Siegert Shift
Authors: Martin Jonathan , Srinivas Sai Abitha , Vaughn Christopher , Sun Heng , Griswold Mark , Grissom William
Published: August 2023

A class of selective RF pulses which use the Bloch-Siegert shift to localize selective excitation without B0 gradients has recently been proposed. Here we report an improved design method for both the frequency-gradient inducing component pulse and the frequency-selective component pulse, which reduces ripple in the magnetization profile and produces flatter passbands across the excited B1+ range. The pulses’ production of multiphoton resonances across B1+ and their suitability for fast gradient-free CPMG imaging are investigated. They are deployed for the first time on a low-field scanner to produce slice-selective selection.
Deoxyhemoglobin versus Gadolinium as Contrast in Dynamic Susceptibility Perfusion Imaging: Simulations and Scan Validations
Authors: Schulman Jacob , Sayin Ece , Poublanc Julien , Manalac Angelica , Fisher Joseph , Sobczyk Olivia , Duffin James , Levine Harrison , Mikulis David , Uludag Kamil
Published: August 2023

DSC-MRI requires bolus administration of gadolinium, an exogenous contrast agent with notable limitations. We used simulations to compare gadolinium with a deoxyhemoglobin bolus generated in the lungs as perfusion contrast and verified the findings in healthy human subjects. We found that the calculated cerebral blood volume is dependent on the contrast agent, the magnitude of deoxyhemoglobin concentration increase (dosage), and the baseline oxygen saturation. We also found a reduction of macrovascular contamination with deoxyhemoglobin contrast. This work reveals novel insights for the use of deoxyhemoglobin, an endogenous and safe contrast agent for determining perfusion in the human brain.
DTI of articular cartilage can predict 3-year radiographic progression in OA patients at early stage of disease
Authors: Raya Jose , Duarte Alejandra , Kijowski Richard , Krasnokutsky-Samuels Svetlana , Bencardino Jenny , Samuels Jonathan
Published: August 2023

The goal of this study is to validate DTI of articular cartilage at 3T as a biomarker for OA progression in a population at early stages of the disease and high likelihood of short-term progression. The goal of this study is to validate DTI of articular cartilage at 3T as a biomarker for OA progression in a population at early stages of the disease and high likelihood of short-term progression. We show that DTI has potential for prognosis of 3-year radiographic changes in a population with early stages of disease.
Deep Learning Predicts Synthetic T1rho Maps from T2 Maps for Knee MRI
Authors: Tong Michelle , Tolpadi Aniket , Beltran Alex , Majumdar Sharmila , Pedoia Valentina
Published: August 2023

This study explores the use a deep learning network to generate T1rho maps from T2 maps for knee MRI. T1rho maps have clinical value in the diagnosis of osteoarthritis in addition to T2 maps while T2 maps are more widely adopted and available in clinical datasets. This study found synthetic T1rho maps images maintain excellent fidelity for data collected in a research setting while performance is reduced for data collected in a clinical setting. This work elucidates the promise of deep learning in accelerating imaging protocols through domain adaptation as opposed to more common reconstruction approaches.
Prospective Head Motion Correction Using Orbital K-Space Navigators and a Linear Perturbation Model
Authors: Ulrich Thomas , Riedel Malte , Pruessmann Klaas
Published: August 2023

It has recently been proposed to estimate head motion from orbital k-space navigators based on a linear signal model of the complex-valued navigator signal. In this work, we describe the combination of this algorithm with prospective motion correction, forming a control circuit that tracks the head so that the linear model remains valid also for large motion ranges. This ability is demonstrated by implementation and in-vivo imaging at 7T.
Self-supervised Training for Single-Shot Tumor Tracking in the Presence of Respiratory Motion
Authors: Früh Marcel , Hepp Tobias , Schilling Andreas , Gatidis Sergios , Küstner Thomas
Published: August 2023

Real-time tumor tracking is a task of growing importance due to the increasing availability of modern linear accelerators paired with MR imaging, called MR-LINAC. Physiological motion can thereby impair focal treatment of moving lesions.Classical tracking approaches often work inadequately because they operate only at the pixel level and thus do not include image-level information.Contrarily, learning based tracking systems typically require a large, fully-annotated dataset which is an arduous task to create. In this work, we propose a framework for example-based single-shot tumor tracking, which is trained without presence of labels and investigated for lesion tracking under respiratory motion.
Denoising task-correlated head motion in motor-task fMRI data using multi-echo ICA
Authors: Reddy Neha , Stickland Rachael , Hemmerling Kimberly , Zvolanek Kristina , Caballero-Gaudes César , Bright Molly
Published: August 2023

Multi-echo independent component analysis (ME-ICA) has been shown to differentiate the effects of head motion from desired BOLD signal in fMRI data, but this method has not been tested in motor-task studies with high amounts of task-correlated head motion. We investigated four denoising models on multi-echo motor-task data with limited and amplified task-correlated motion: Aggressive, Moderate, and Conservative ME-ICA nuisance regression models and a conventional optimally combined (OC) model. ME-ICA models were found to better dissociate head motion and BOLD signal variance than the OC model. Among them, the Aggressive model had the most consistent activation results with amplified motion.
Progress on the commissioning of the Iseult 11.7T whole-body MRI: first images
Authors: Allard Jerome , Amadon Alexis , Aubert Guy , Belorgey Jean , Berriaud Christophe , Bonnelye Cédric , Boudoin Romain , Boulant Nicolas , Boussuge Thierry , Boumezbeur Fawzi , Brédy Philippe , Dietz Peter , Dilasser Guillaume , Drouen Yannick , Dubois Olivier , Faict-Bastin Sandrine , Insua Ignacio Gonzalez , Gras Vincent , Guihard Quentin , Guiho Patrice , Guillard Jean-Christophe , Jannot Vincent , Juster François-Paul , Koeber Felix , Koestel Brice , Le Bihan Denis , Leboeuf René , Lerman Cécile , Leprêtre Frédéric , Lotodé Ange , Nunio François , Quettier Lionel , Landes Hermann , Lannou Hervé , Massire Aurélien , Mauconduit Franck , Molinié Frédéric , Neyrial Hubert , Péron Cédric , Renou Luc , Roger Arnaud , Rouffiat Philippe , Ruth Wolfram , Schild Thierry , Sieber Patrick , Santin Mathieu , Schroeder Martin , Scola Loris , Sinanna Armand , Stepanov Vadim , Szmigiel Mathieu , Tellier Olivier , Touzery Robert , Védrine Pierre , Vignaud Alexandre , Walter Christian , Wiclow Karsten
Published: August 2023

The Iseult project started in 2001 and is a collaborative effort involving CEA and the University of Freiburg in academics, Guerbet, Siemens Healthineers and Bruker Biospin as industrial partners. One central aspect of the project has been the design by CEA of a whole-body magnet of 11.7T field strength with a 90-cm wide bore. After nearly 20 years of research and development, prototyping, integration and tests, first images have been acquired with this unique MRI scanner. Some key validation results are presented here.
First in-vivo 23Na human imaging at 10.5T using a combined 23Na-loop 1H-dipole transceiver array
Authors: Schmidt Simon , Erturk Arcan , Lagore Russell , Grant Andrea , Nagel Armin , Zbyn Stefan , Metzger Gregory
Published: August 2023

Performing sodium and proton imaging in the same study can provide a wealth of unique multinuclear insights for the study of pathologies and their treatment. However, the coils to perform such studies in the human body are limited and none were validated for human use at 10.5T until now. While both nuclei can benefit from increased SNR at 10.5T sodium suffers from low SNR due to the lower gyromagnetic ratio and natural abundance in the human body compared to 1H. First in-vivo results are presented for a 10.5T sodium-proton torso array following a safety validation study determining safe operating limits.
Deep-learning-informed parameter estimation improves reliability of spinal cord diffusion MRI
Authors: Gong Ting , Grussu Francesco , Wheeler-Kingshott Claudia Gandini , Alexander Daniel , Zhang Hui
Published: August 2023

The very low SNR in spinal cord diffusion MRI can make robust microstructure parameter estimation challenging. To address unreliable parameter estimations under such low SNR, we propose a deep-learning-informed maximum likelihood estimation (MLE) approach, where a deep-learning model is trained to initialise MLE efficiently and optimally. In testing NODDI-derived parameters, simulation and in vivo experiments suggest the DL-informed method can reduce outlier estimates from conventional grid-search MLE, and at the same time, avoid biases from pure DL estimation under the low SNR. The proposed method also speeds up the computation, making it a promising tool for future applications.
Neptune: a toolbox for spinal cord functional MRI data processing and quality assurance
Authors: Rangaprakash D , Barry Robert
Published: August 2023

Spinal cord fMRI data analysis involves niche pre- and post-processing steps due to the cord’s unique anatomy and higher distortions/physiological noise in fMRI data, requiring extensive and careful quality control (QC). However, there is paucity of open-source tools tailored to this need. Building upon 10 years of research and development, we present Neptune, a user-interface-based MATLAB toolbox. It can perform an array of tailored pre- and post-processing steps, including functional connectivity and statistics. It generates extensive QC plots and presents them to view in an elegant webpage format. We demonstrate the utility of Neptune on a 7T dataset.
Deep learning super-resolution of MR images of the distal tibia improves image quality and assessment of bone microstructure
Authors: Chan Trevor , Kamona Nada , Vu Brian-Tinh , Wehrli Felix , Rajapakse Chamith
Published: August 2023

We apply a probabilistic deep learning model to perform image super-resolution on magnetic resonance (MR) images. Our results show that the model is capable of high performance in MR; we upsample low resolution images of the distal tibia to 2x initial spatial resolution–equivalent to capturing 4x fewer samples in K-space–with the goal of reconstructing details in the trabecular architecture. We validate our results by comparing trabecular bone microstructure metrics across high-resolution ground truth, model-reconstructed, and low-resolution input images. By drastically reducing scan time for high-resolution imaging, these methods have the potential to make MRI assessment of bone strength clinically viable.
Impairments in cerebral blood flow and cerebrovascular reactivity in the APP23 mouse model of cerebral amyloidosis
Authors: Munting Leon , Kozberg Mariel , Hirschler Lydiane , Warnking Jan , Barbier Emmanuel , van der Kouwe Andre , Mandeville Joseph , Farrar Christian , Greenberg Steven , Bacskai Brian , van Veluw Susanne
Published: August 2023

Patients with cerebral amyloid angiopathy (CAA) have accumulations of amyloid-beta in the cerebral vasculature, which ultimately lead to stroke and dementia. MRI markers of CAA include microbleeds and reduced cerebrovascular reactivity (CVR). The APP23 mouse model with vascular amyloid-beta accumulation is known to have microbleeds and reduced cerebral blood flow (CBF). Here, using pseudo-Continuous Arterial Spin Labeling (pCASL)-MRI with a 10 % CO2 stimulation, we show that besides lower CBF, APP23 mice also have reduced CVR. Furthermore, in our data, a higher microbleed count was associated with lower CBF, but not with CVR.
Deformable Registration of Serial Micrographs to Post-Mortem MRI in the BigMac Dataset Using TIRL
Authors: Huszar Istvan , Smart Adele , Jbabdi Saad , Jenkinson Mark , Howard Amy , Miller Karla
Published: August 2023

The BigMac dataset combines extensive post-mortem MRI with histology and polarised light imaging (PLI) in a macaque brain. Adding a new extension to our recently developed platform, the Tensor Image Registration Library (TIRL), we address unique challenges associated with this dataset and successfully align 77 2-D polarised light micrographs to high-resolution structural MRI data.
Estimation of anisotropic mechanical properties of gastrocnemius during muscle contraction with MR elastography
Authors: Smith Daniel , Caban-Rivera Diego , Williams L. , McGarry Matthew , Van Houten Elijah , Bayly Phil , Paulsen Keith , Johnson Curtis
Published: August 2023

In this study, we utilized MR elastography (MRE) and transversely isotropic inversion to estimate anisotropic material parameters of muscle during contraction states, including passive muscle lengthening and isometric contraction. We collected MRE and DTI data on six subjects and took averages of the parameters within the medial and lateral heads of the gastrocnemius muscle and compared the results during the contraction states. We found significant differences between the estimates during the various states of contraction. Here we demonstrate that MRE and TI-NLI can generate anisotropic parameter estimates for muscle tissue while capturing changes to functional aspects of the tissue.
Inter-subject differences in SAR sensitivity to motion with parallel-transmit at 7T.
Authors: Plumley Alix , Goodwin Nathan , Kopanoglu Emre
Published: August 2023

Specific absorption rate (SAR) is sensitive to head motion, especially in parallel-transmit (pTx) due to channel interference. It is known that SAR distribution varies according to subject anatomy. Here, we investigate whether SAR sensitivity to motion also depends on the subject. We designed quadrature-mode and pTx pulses at a centred position and evaluated them at 29 displaced positions. We compared the motion-induced SAR change across 4 body-models. We observed some variation across models, but local-SAR at least doubled in all models’ worst-cases. Our findings suggest that the safety concerns surrounding motion effects on SAR are relevant for various populations.
Alterations in Temporal Lobe Functional Connectivity Differ Based on Clinical Outcomes in Patients with Mesial Temporal Sclerosis
Authors: Sathe Anish , Kogan Michael , Kang KiChang , Miao Jingya , Syed Mashaal , Ailes Isaiah , Matias Caio , Mohamed Feroze , Sharan Ashwini , Alizadeh Mahdi
Published: August 2023

Mesial temporal sclerosis (MTS) is a severe form of temporal lobe epilepsy. Resection is the treatment of choice for refractory MTS but can still show seizure recurrence. We used seed-to-voxel analysis via amplitude synchronization to determine alterations in functional connectivity in MTS based on seizure-free status one year post-resection. Positive and negative correlations between temporal lobe structures and other brain regions were calculated and compared. We found changes in connectivity in MTS between ascending reticular activating system structures such as the thalamus and brainstem and temporal lobe structures. We also found differences in connectivity alterations between seizure-free and non-seizure-free patients.
MRI Urodynamics: A 3D approach to Bladder Biomechanics
Authors: Gonzalez-Pereira Juan , Johnson Cody , Wells Shane , Bushman Wade , Roldan-Alzate Alejandro
Published: August 2023

Lower urinary track symptoms (LUTS) affect many older adults. Existing methods to evaluate the lower urinary tract are invasive and provide limited information about changes in bladder anatomy and detrusor muscle function. Use of non-invasive methods for the study of lower urinary tract anatomy and function has been limited. This pilot study demonstrates the feasibility of MRI urodynamics in healthy subjects and in LUTS patients. Future advancements in this study will be aimed at using the data acquired to further deepen the comprehension of the bladder voiding cycle.
Inter- & Intra-visit Reproducibility of Free-Breathing Magnetic Resonance Imaging in Pediatric Cystic Fibrosis Lung Disease
Authors: Munidasa Samal , Zanette Brandon , Couch Marcus , Grimm Robert , Seethamraju Ravi , Dumas Marie-Pier , Wee Wallace , Au Jacky , Braganza Sharon , Li Daniel , Ratjen Felix , Santyr Giles
Published: August 2023

Free-breathing lung MRI has been shown to be a responsive measure to CF pulmonary exacerbations treatments but have not been used to track stable disease progression longitudinally. In this study we determined the intra- and inter-scan reproducibility of free-breathing lung MRI in healthy and stable pediatric CF across 2 visits and compared to hyperpolarized Xenon MRI (Xe-MRI). Xe-MRI and free-breathing lung show a high intra-scan reproducibility in stable CF subjects, but free-breathing lung MRI showed a low inter-scan reproducibility. However, free-breathing lung MRI significantly correlated with Xe-MRI suggesting that it may be an alternative to expensive, and less wide-spread Xe-MRI.
Functional activities detected in the olfactory bulb and associated olfactory regions in the human brain using T2-prepared BOLD fMRI at 7T
Authors: Miao Xinyuan , Paez Adrian , Rajan Suraj , Cao Di , Liu Dapeng , Pantelyat Alex , Rosenthal Liana , van Zijl Peter , Bassett Susan , Yousem David , Kamath Vidyulata , Hua Jun
Published: August 2023

Conventional EPI-based BOLD fMRI can be challenging in olfaction related brain regions, such as the olfactory bulb (OB), mainly due to the large susceptibility artifacts. To date, few studies have demonstrated successful fMRI in the human OB. T2-prepared (T2prep) BOLD fMRI is an alternative approach developed especially for reducing such susceptibility artifacts. Here, olfactory fMRI was performed at 7T in 14 healthy participants. T2prep-BOLD showed greater functional sensitivity than GRE-EPI-BOLD in the OB and associated olfactory regions. Habituation effects and a bi-phasic pattern of fMRI signal changes were observed using T2prep-BOLD, which showed a good intra-subject reproducibility.
The Relative Contribution of the Vascular Architecture and Reactivity to the BOLD signal Formation
Authors: Roefs Emiel , Schellekens Wouter , Báez-Yáñez Mario , Bhogal Alex , Siero Jeroen , Petridou Natalia
Published: August 2023

In this study, we investigate the vascular contribution to the BOLD signal by comparing purely non-neuronal-related changes in the BOLD signal induced by gas manipulations with neuronal-related hemodynamic changes in the BOLD signal for different vascular compartments. Different vascular compartments were targeted by employing gradient-echo and spin-echo in combination with cortical depth estimations and pial vein segmentations. Our findings suggest that the increase in macro-vascular baseline venous blood volume (CBVv0) is the main contributor to the large GE-BOLD signal increase towards the pial surface and that normalization for this CBVv0-dependence is possible using a hyperoxia breathing task.
Using machine learning to build a population model of tongue muscle architecture based on mDIXON and diffusion tensor imaging
Authors: Lloyd Robert , Ball Iain , Bilston Lynne
Published: August 2023

Simulations of obstructive sleep apnoea (OSA) require detailed models of the muscle fibres within the tongue, to correctly capture the motion of the tongue. Diffusion weighted images (DWI) of the oral cavity were collected for 5 healthy controls. Fibre-orientation distributions (FOD) estimated from subject DWI, can resolve intersecting muscles in the tongue. The group averaged FOD reduced the influence of spurious peaks, which gave clearer boundaries between the intrinsic muscles of the tongue. These results may help fully automate the segmentation of the muscles within the tongue.
FAI Bone Morphology Correlates with Increased T2 Relaxations Times in the Hip Cartilage of Female Water-Treading Athletes
Authors: Rubin Elka , Langner Joanna , Black Marianne , Desai Arjun , MacKay James , Jones Carly , Hall Kimberly , Safran Marc , Kogan Feliks , Gold Garry
Published: August 2023

Water polo players and synchronized swimmers have previously been found to have an increased prevalence of femoroacetabular impingement morphology compared to the general population. In this study, we used MRI to identify regional patterns in the microstructure of the hip cartilage and joint of high-level female water polo players and synchronized swimmers. Compared to healthy controls, the water-treading athletes had significantly higher T2 relaxation times in the right hip and a significantly higher prevalence of cam morphology in both hips. This study suggests that microstructural and morphological differences are present in these athletes’ hip cartilage compared to controls.
Simultaneous perfusion, diffusion, T2*, and T1 mapping with MR Fingerprinting (MRF-PDT)
Authors: Fan Hongli , Bunker Lisa , Durfee Alexandra , Zhou Xiaohong Joe , Hillis Argye , Lu Hanzhang
Published: August 2023

Quantitative mapping of brain perfusion, diffusion, T2*, and T1 has a broad range of clinical applications. The present work aims to develop a novel pulse sequence that can simultaneously map perfusion, diffusion, T2* and T1 with MR fingerprinting, dubbed MRF-PDT, with a total scan time of <6 minutes. This technique was first demonstrated on healthy volunteers, then on two patients with ischemic stroke. All maps derived from MRF-PDT exhibited the expected image contrasts with quantitative values consistent with those reported in literature. In addition, test-retest studies confirmed the reproducibility of the proposed technique.
Simultaneous mapping of T1, T2, and T2* at 0.55T with Rosette MR Fingerprinting
Authors: Cummings Evan , Liu Yuchi , Jiang Yun , Ropella-Panagis Kathleen , Hamilton Jesse , Seiberlich Nicole
Published: August 2023

In this work, Rosette MRF was modified and deployed to simultaneously map T1, T2, and T2*. Mapping is demonstrated on the ISMRM/NIST phantom for verification of quantitative accuracy, and on four healthy volunteers to demonstrate potential feasibility in vivo.
Tissue classification of cerebral gliomas using MR fingerprinting signal and deep learning
Authors: Chen Yong , Boyacioglu Rasim , Weragoda Gamage , Martens Michael , Griswold Mark , Badve Chaitra
Published: August 2023

In this pilot study, we aim to analyze MR Fingerprinting (MRF) signal using deep learning network to assess the performance of tissue classification in gliomas. A U-Net based convolutional neural network was trained to learn glioma grades based on the SVD-compressed fingerprint acquired using MRF. Based on data acquired from a 5-minute MRF scan, the method shows great potential to accurately classify glioma grades without the need of image registration and contrast administration.
Online Gadgetron Reconstruction of 3D Magnetic Resonance Fingerprinting via a GPU-Accelerated Azure Kubernetes Cluster
Authors: Dupuis Andrew , Chen Yong , Boyacioglu Rasim , Stairs John , Hansen Michael , Chow Kelvin , Griswold Mark
Published: August 2023

Reconstruction of 3D Magnetic Resonance Fingerprinting acquisitions is computationally demanding, resulting in long processing times. GPU parallelization of the reconstruction’s NUFFT, pattern matching, and coil combination steps improves performance, but traditionally requires high-performance computers at the scanner. We propose an online reconstruction on a remote GPU-accelerated Kubernetes cluster. This allows many scanners or sites to share easily upgradeable and manageable computing resources. Additional calibration measurements, such as B1 maps, can also be transferred to allow inline B1 inhomogeneity correction. We also demonstrate that 3D-MRF reconstruction is robust with raw data compression that can be used to reduce site-to-cloud bandwidth requirements.
Influence of electric field and axon geometry on peripheral nerve stimulation chronaxie
Authors: Ferris Natalie , Klein Valerie , Guérin Bastien , Wald Lawrence , Davids Mathias
Published: August 2023

We calculate the impact of peripheral nerve geometry (bend angle, radius of curvature, and axon diameter) and electric field characteristics (hot-spot amplitude and extent) on the chronaxie of nerve stimulation to better understand the variability in experimental chronaxie values seen with MRI gradient coils.