bluuebunny/crossref_metadata_2025 huggingface dataset:
Trajectory correction enables Free running cardiac DIXON at 3T
Authors: Daudé Pierre , Troalen Thomas , Mackowiak Adèle L C , Piccini Davide , Yerly Jerôme , Pfeuffer Josef , Kober Frank , Gouny Sylviane Confort , Bernard Monique , Stuber Matthias , Bastiaansen Jessica A M , Rapacchi Stanislas
Published: August 2023

Free-running cardiac DIXON-MRI has potential for T2*/PDFF quantification to explore cardiac fat accumulation and alteration in metabolic diseases. DIXON at 3T suffers from rapid fat-water phase accrual and inhomogeneous B0. Consequently, bipolar echoes, as opposed to monopolar, are required to achieve equal/shorter than in-phase/out-of-phase echo spacing. However, distortions occur between even and odd echoes due to gradients imperfections. Thus, the existing framework was extended with a k-space trajectory correction based on gradient impulse response function(GIRF). Both monopolar or bipolar echoes without GIRF correction resulted in fat-water swaps and unreliable quantitative maps, that were resolved using GIRF-corrected bipolar free-running DIXON.
Inversion Recovery Based Magnetization Transfer Mapping in the Human Myocardium In the presence of Incomplete Bound Pool Saturation at 3T
Authors: Weingärtner Sebastian , Demirel Ömer , Tao Qian , Tourais Joao , Akcakaya Mehmet
Published: August 2023

Quantitative imaging of magnetization transfer (MT) may enable non-contrast assessment of myocardial scar and fibrosis. However, its application at 3T has so far been limited. In this work we investigate an inversion recovery based method for joint quantification of T1 and MT maps. A numerical binary spin-bath model is used to account for incomplete bound pool saturation in the presence of limited preparation durations. In vivo images were obtained with high visual map quality for both T1 and MT quantification, and comparable, low CoV across the two parameters (T1: 5.5+-0.6% and MT: 5.8+-0.9%).
Isotropic fixed time 3D late gadolinium enhancement MRI for left atrial fibrosis imaging
Authors: Adluru Ganesh , Mendes Jason , Ranjan Ravi , Kholmovski Eugene , DiBella Edward
Published: August 2023

Left atrial late gadolinium enhancement imaging is a promising tool to identify scar and fibrosis. Existing acquisition and reconstruction methods can suffer from long scan time, poor image quality, and inability to accurately quantify the fibrosis. Here we propose a fixed time isotropic imaging of the left atrium with a resolution of 1.25mm3. We use retrospective respiratory navigation to remove inconsistent data due to motion and use a constrained reconstruction framework with total variation and 3D block-matching regularizers to remove the data undersampling artifacts. Promising results showing gains from the isotropic acquisitions are presented in canine and human studies.
Single Breath-hold Simultaneous T2 and TRAFF2 mapping for approximate Spin-lock Dispersion Mapping in the Myocardium at 3T
Authors: Tourais Joao , Demirel Omer Burak , Tao Qian , Pierce Iain , Thornton George , Treibel Thomas , Weingärtner Sebastian , Akcakaya Mehmet
Published: August 2023

Spin-lock dispersion is a promising biomarker for the assessment of myocardial infarction. However, at 3T, the required range of T1⍴ maps acquired at different amplitudes suffers from specific absorption rate (SAR) limitations and off-resonance artifacts. Relaxation Along a Fictitious Field (RAFF) is an alternative to SL preparations with lower SAR requirements while still sampling relaxation in the rotating frame. Thus, a single breath-hold simultaneous TRAFF2 and T2 mapping sequence is proposed for sl dispersion mapping at 3T. High visual quality maps and accurate T2, TRAFF2, and SL dispersion values are achieved with the proposed sequence in phantoms and in vivo.
Enabling Pilot Tone cardiac triggering for complete cardiac examinations using an RF calibration procedure
Authors: Speier Peter , Huang Yan Tu , Hayes Carmel , Kroeker Randall , Rick Manuela , Schwertfeger Michael , Bacher Mario
Published: August 2023

Contactless cardiac triggering using Pilot Tone was initially demonstrated for steady-state triggered cine-type sequences that, per definition, are performed with continuous, uniform RF pulses. Here we describe a method that stabilizes Pilot Tone cardiac triggering in the presence of RF artefacts, thereby allowing for pilot tone triggering of complete cardiac MR examinations with a range of sequence flavors including those applying RF pulses intermittently. The method uses an additional RF calibration measurement and avoids the RF artefact subspace in a PCA-based multi-channel coil combination calculation. Signal examples at 1.5T demonstrate effective RF suppression.
Free-breathing pseudo-golden-angle bSSFP cine cardiac MRI for evaluation of biventricular function in patients with congenital heart disease
Authors: Kravchenko Dmitrij , Isaak Alexander , Zhang Shuo , Mesropyan Narine , Bischoff Leon , Vollbrecht Thomas , Weber Oliver , Pieper Claus , Kuetting Daniel , Hart Christopher , Attenberger Ulrike , Luetkens Julian
Published: August 2023

Cardiac MRI is currently the standard imaging modality for patients with congenital heart disease (CHD). However, the requirement for breath holds remains a big challenge in clinical practice and image quality is often significantly degraded by respiratory motion artifacts. We employed respiratory-triggered pseudo-golden-angle bSSFP imaging for free-breathing cine MRI and compared cardiac volumetry, function, and image quality with the standard breath hold technique. The proposed method showed good agreement with comparable diagnostic image quality and advantage in patients with limited breath hold capability. These demonstrated promise for a wider clinical routine application in patients with CHD.
Cine Image Based Cardiac Disease Classification Using Random Forest Classifier and Graph Based Deep Learning Approach
Authors: Varga-Szemes Akos , Chitiboi Teodora , Schoepf U. Joseph , Jacob Athira , Ghosal Sayan , Xiong Fei , Sharma Puneet , Aldinger Jonathan , Emrich Tilman
Published: August 2023

Existing work demonstrates the value of image-based cardiovascular diagnosis with AI. We aimed to develop and test a machine learning algorithm for cardiovascular disease classification based on cine image datasets of 570 consecutive patients. Disease classification was performed using a random forest (RF) classifier and a disease classification network based on graph attention networks. The fully automated deep learning algorithm showed high accuracy for cardiac disease classification based on cine images only. Such algorithm has the potential to improve the efficiency of the reading process, especially by identifying and filtering out patients with normal cardiac anatomy and function.
Strain-free in-vivo time dependent diffusion measures in the myocardium: A potential new biomarker ?
Authors: Alemany Ignasi , Rose Jan N , Ferreira Pedro F. , Nielles-Vallespin Sonia , Doorly Denis J. , Scott Andrew D.
Published: August 2023

Diffusion tensor cardiovascular magnetic resonance (DT-CMR) has proved to be a unique non-invasive method to investigate the myocardial microstructure. The time dependence of the diffusion tensor provides insights into the barriers that restrict free diffusion. We present a method to assess the time dependence of diffusion in the beating heart along with numerical simulations that demonstrate the sensitivity of this potential new biomarker to changes in myocardial microstructure including membrane permeability, extracellular volume fraction and cell hypertrophy.
A groupwise registration & tractography framework for cardiac architecture description by diffusion MRI: application to ventricular junctions
Authors: Magat Julie , Yon Maxime , Bihan-Poudec Yann , Ozenne Valéry
Published: August 2023

In this study, we developed a groupwise registration and tractography framework to investigate the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum (IVS) is presented. The study focuses on one fiber-bundle in the posterior junction and three fiber-bundles in the anterior junction.
Self organization of breath-hold induced cerebrovascular BOLD fMRI responses reveals physiologically-driven brain parcellation and networks
Authors: Moia Stefano , Bright Molly , Caballero-Gaudes César
Published: August 2023

Recent literature brought up the existence of physiological and vascular brain networks, i.e. areas showing synchronous responses to cardiac and respiratory fluctuations or hypercapnia. In this work, we show how breath-hold-induced BOLD fMRI time series from a dense mapping dataset can be parcellated into physiologically-driven networks, showing evidence of vascular contributions to the default mode network, in individuals and at the group level.
Improving measures of cerebrovascular reactivity using a sinusoidal hypercapnic challenge and dual-echo pseudocontinuous ASL
Authors: Milbourn Colette , Blockley Nicholas
Published: August 2023

New clinical tools are needed for the diagnosis and prognosis of cerebrovascular diseases. Cerebrovascular Reactivity (CVR) is a potential marker for brain health and can be induced using stressors to the brain like high carbon dioxide (hypercapnia) challenges. These challenges can be used to map CVR. Dual-echo pseudocontinuous Arterial Spin Labelling (pCASL) and Blood Oxygen Level Dependent (BOLD) weighted imaging was combined with sinusoidally modulated and conventional block hypercapnic challenges to map CVR. Preliminary results show qualtitative improvements to pCASL based CVR maps when using sinusoidal hypercapnic challenges compared with the conventional block.
Discrimination Between Benign and Malignant Lesions in the Breast with Restriction Spectrum Imaging on a Screening Breast MRI Cohort
Authors: Loubrie Stephane , Rodriguez-Soto Ana , Fang Lauren , Conlin Christopher , Andreassen Maren , Seibert Tyler , Hahn Michael , Dialani Vandana , Wei Catherine , Karimi Zahra , Kuperman Joshua , Dale Anders , Pisano Etta , Rakow-Penner Rebecca
Published: August 2023

Diffusion weighted imaging (DWI) holds great potential in improving specificity of findings detected on contrast enhanced breast MRI. Restriction spectrum imaging (RSI), an advanced diffusion imaging model, has potential in discriminating between malignant and fibroglandular breast tissue. In this abstract, we evaluate RSI’s performance in differentiating malignant from benign lesions in a prospective study performed on a breast screening population. All lesions were biopsy proven. The breast RSI model allowed discrimination between malignant, high-risk and low-risk benign lesions and healthy fibroglandular tissue.
Sodium Breast Imaging of Ductal Carcinomas at 3 T
Authors: Kaggie Joshua , Baxter Gabrielle , McLean Mary , Woitek Ramona , Gallagher Ferdia , James Andrew , Kennerley Aneurin , Schulte Rolf , Brackenbury William , Gilbert Fiona
Published: August 2023

Sodium (23Na)-MRI was performed using a dual-tuned bilateral 23Na/1H breast coil on seven patients with ductal carcinoma, one patient with lobular carcinoma, and ten normal volunteers. Several patients had [23Na] measurements that were 2-3 times higher than the mean normal fibroglandular [23Na] measurements. There were no strong correlations between 23Na-MRI and either DCE or DWI measurements in the patients. These measurements suggest that [23Na] may provide an additional physiological imaging mechanism of breast cancer.
Minimum number of scans for magic angle directional imaging based on a priori anatomical information
Authors: Lanz Harry , Chappell Karyn , Ristic Mihailo
Published: August 2023

By exploiting the field-dependent anisotropy of collagen, valuable clinical information can be obtained, such as fibre tractography. We investigated the use of a priori anatomical knowledge such as scout scan, using both simulations and experimentally acquired images. We conclude that only 3 scanning directions may be sufficient for robust analysis, instead of 9 or more in the case when no such information is used. The method is also compatible with low SNR values associated with low-field MRI.
A Beamforming-Based Coil Combination Method to Reduce Streaking Artifacts and Preserve Phase Fidelity in Radial MRI
Authors: Shih Shu-Fu , Wu Holden
Published: August 2023

Radial acquisition can be sensitive to hardware imperfections such as gradient non-linearity and B0 field inhomogeneity. This usually becomes accentuated in areas more distant to the isocenter and can lead to streaking artifacts even when nominally fulfilling Nyquist criteria. Previous work demonstrated beamforming-based methods for radial streaking reduction, but did not explicitly consider phase and did not evaluate the artifact-suppression performance on phase explicitly. In this work, we developed a new beamforming formulation based on minimum-variance distortionless response (MVDR) that can suppress streaking artifact while preserving accurate phase information
BPE XD-GRASP: Using GROG-BPE for improved respiratory motion compensation in dynamic contrast enhanced golden-angle radial MRI
Authors: Bilal Yumna , Aslam Ibtisam , Siddiqui Muhammad , Omer Hammad
Published: August 2023

This work aims at incorporating the GROG facilitated Bunch Phase Encoding (BPE) in XD-GRASP reconstruction framework for improved motion compensation in free-breathing Dynamic Contrast Enhanced golden-angle radial MRI data. In the proposed method, the inherent randomness and added redundancy in the BPE data, is exploited by the Compressed Sensing (CS) algorithm resulting in images with higher quality and improved mitigation of respiratory motion artifacts as compared to the conventionally used XD-GRASP method.
Reproducibility of IVIM Quantification Across Diffusion Gradient Waveforms using Pseudo-Diffusion and Physical IVIM Signal Models
Authors: Simchick Gregory , Hernando Diego
Published: August 2023

The intravoxel incoherent motion (IVIM) DWI signal has been shown to depend on both b-value and the first motion moment (M1). However, traditional pseudo-diffusion IVIM signal models only include b-value dependence. In this work, monopolar and 2D (b-M1) IVIM acquisitions were acquired using diffusion gradient waveforms with different maximum amplitudes to emulate different gradient hardware. From each acquisition, IVIM estimates were obtained by fitting pseudo-diffusion and physical (M1 dependent) IVIM signal models. Estimated IVIM parameters were compared across acquisitions. Reproducible physical IVIM estimates were obtained using 2D IVIM-DWI acquisitions, while pseudo-diffusion IVIM estimates obtained using monopolar acquisitions demonstrated poor reproducibility.
EPIFANI: an ultrafast T1, B1 and magnetization mapping technique
Authors: Zampini Marco , Sijbers Jan , Verhoye Marleen , Garipov Ruslan
Published: August 2023

Quantitative MRI still struggles to be used in clinical practice due to long acquisition times. We introduce EPIFANI, an ultrafast B1-corrected T1 mapping technique which uses EPI images acquired in two successive repetition times and a parametric map fit used in VAFI. Both a single-shot and a multi-shot version of EPIFANI were tested on phantoms and in vivo and report accurate T1 values.
Susceptibility weighted imaging using Stack of Spiral trajectories
Authors: Chao Tzu-Cheng , Pipe James
Published: August 2023

A new strategy to acquire Susceptibility Weighted Imaging was proposed with Stack of Spiral trajectories to reduce scan time while maintaining adequate SNR. Spiral encoding offers acceleration in scan speed by six times compared to conventional Cartesian methods, with similar SNR, resolution, and image quality. Due to its improved SNR efficiency, the proposed method has the potential to facilitate lesion detection with higher resolution SWI in a reasonable scan time.
2D (b-M1) Data Sampling and Blood Velocity Standard Deviation Distribution Fitting for Repeatable Tri-exponential IVIM Quantification
Authors: Simchick Gregory , Geng Ruiqi , Hernando Diego
Published: August 2023

There is growing evidence of tri-exponential IVIM-DWI signal behavior in the liver. However, tri-exponential estimates often suffer from the instability associated with separating three decaying signal components sampled along a single dimension (i.e., b-value). In this work, standard monopolar and noise-optimized 2D (b-M1) data sampling schemes were acquired. From each acquisition, tri-exponential ROI-based fitting and a blood velocity standard deviation distribution (BVD) fitting method were performed. The estimated tri-exponential parameters were compared across acquisitions and fitting methods. Repeatable tri-exponential IVIM estimates were obtained using the 2D data sampling combined with BVD fitting. A new, physical tri-exponential model is also proposed.
Inter-scanner reproducibility and variability assessment of advanced liver diffusion MRI metrics
Authors: Grussu Francesco , Bernatowicz Kinga , Barba Ignasi , Palombo Marco , Corral Juan Francisco , Vidorreta Marta , Merino Xavier , Mast Richard , Roson Núria , Calvo‐Malvar Nahúm , Amores Manuel Escobar , Garcia-Bennett Josep , Perez-Lopez Raquel
Published: August 2023

Innovative liver Diffusion-Weighted (DW) MRI aims to increase sensitivity and biological specificity of routine DW imaging, but may feature lower reproducibility due to longer scan times and acquisition of highly DW images. We assess inter-scanner reproducibility and variability of metrics from two novel approaches, T2-Intra-Voxel Incoherent Motion-Kurtosis (T2-IVIM-Kurtosis) and Diffusion-Relaxation Hepatic Imaging via Generalised Assessment of DiffusiOn Simulations (DR-HIGADOS), in two 1.5T scanners (Siemens Avanto; Philips Ingenia). Both methods are reproducible across scanners. Cellularity, intra-cellular diffusivity and vascular fraction show the highest measurement variability, implying that larger cohorts may be required in studies that focus on these indices.
Sensitivity comparison of probabilistic and deterministic DTI tractography for robust characterization of arm skeletal muscle geometry
Authors: Joshi Divya , Dewald Julius , Ingo Carson
Published: August 2023

The robustness of probabilistic versus deterministic DTI tractography in characterization of skeletal muscle structure is not yet established. We investigated the sensitivity to turning angle when probabilistic and deterministic methods were used to estimate fascicle lengths and fractional anisotropy in the arm’s biceps muscle (n=8). Results produced with deterministic methods were highly sensitive to the turning angle, but those produced with probabilistic methods were not. Furthermore, the recommended angle in probabilistic methods yielded findings consistent with ground truth measurements, while the turning angle in deterministic methods needed to be altered from the recommended value to achieve similar results.
Brain Extracellular Free Water Correlates with MRSI Biomarkers of Neuro-inflammation in the Brain of HIV Clade-C Infected Individuals
Authors: Salan Teddy , Vyas Sameer , Aggarwal Deepika , Singh Paramjeet , Govind Varan
Published: August 2023

Free water (FW) imaging is a diffusion-weighted MRI technique that differentiates extracellular from intracellular water compartments. Increased FW fraction is generally associated with neuroinflammation. However, establishment of a direct link between FW and biomarkers of neuroinflammation in human studies is not feasible. In this work, we use MRSI to find correlations between FW and metabolic biomarkers of inflammation in HIV infected individuals. Our results show that FW had the most significant positive correlations with myo-inositol, a strong biomarker of gliosis and inflammation. This corroborates previous findings that elevated FW can be interpreted as a sign of inflammation in the brain.
Metabolic Changes Immediately Following Sequential Motor Learning: an MRS-fMRI Study
Authors: Geiger Yasmin , Weiss Tali , Volovick Osnat , Aharon Inbar , Maaravi-Hesseg Rinatia , Karni Avi
Published: August 2023

Sequential finger tapping (SFT) is a model for motor learning. The initial phase of SFT manifests in changes to behavior, neuronal activation (BOLD) and metabolic concentrations. The metabolic changes and correlations to BOLD and behavioral changes during SFT are still poorly understood. Here we analyze these bilateral changes at the motor cortex using BOLD‑fMRI and 1H-MRS. We show a significant hemispheric‑dependent correlation between changes in GABA+ and behavior, which do not correlate with the BOLD signal. Additionally, GABA+ basal levels differ between hemispheres.
Increased Iron Deposition in Gray Matter Nuclei in Patients with Intracranial Artery Stenosis Evaluated by Quantitative Susceptibility Mapping
Authors: Mao Huimin , Dou Weiqiang , Wang Xinyi , Chen Kunjian , Guo Yu
Published: August 2023

This study aimed to use quantitative susceptibility mapping (QSM) to systematically investigate iron content changes of gray matter (GM) nuclei in patients with long-term anterior circulation artery stenosis (ACAS) and posterior circulation artery stenosis (PCAS). The differences of iron-related susceptibility in GM nuclei, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus, substantia nigra (SN), red nucleus and dentate nucleus (DN) were explored in 25 ACAS and 25 PCAS patients. Compared with healthy controls, mean susceptibility of bilateral PU, GP, and SN in ACAS and PCAS patients, and of extra bilateral DN in PCAS patients were significantly increased.
Fatty Acid Composition MRI of Human Epicardial Adipose Tissue
Authors: Echols Jack , Shah Soham , Epstein Frederick
Published: August 2023

Epicardial adipose tissue (EAT) fatty acid composition (FAC) plays an important role in coronary vascular inflammation due to obesity and diabetes. We show for the first time the feasibility of quantifying human EAT FAC using radial multi-echo gradient-echo MRI with IDEAL mapping. This method may enable further investigations into the relationship between EAT fatty acid composition and cardiovascular disease.
Brain iron deposition in patients with unilateral middle cerebral artery stenosis: an in vivo quantitative susceptibility mapping study
Authors: Mao Huimin , Dou Weiqiang , Wang Xinyi , Chen Kunjian , Guo Yu
Published: August 2023

The main purpose was to quantitatively evaluate iron alterations in gray matter (GM) nucleus of patients with unilateral middle cerebral artery stenosis (MCAS)-related ischemic stroke using quantitative susceptibility mapping (QSM). Forty-six unilateral MCAS patients and thirty-eight healthy controls underwent QSM examination. Iron-related susceptibility of GM nucleus, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus, substantia nigra (SN), red nucleus, and dentate nucleus were assessed. Compared with healthy controls, PU, GP, and SN regions at lesion side presented significantly increased susceptibility in patients, indicating that abnormal iron metabolism may present in the brain after ischemic stroke.
MULTI-CONTRAST ATHEROSCLEROSIS CHARACTERIZATION (MATCH) AND MULTI-SEQUENCE MRI IN QUANTIFYING CAROTID PLAQUE COMPOSITION
Authors: Kassem Mohamed , Boswijk Ellen , van der Pol Jochem , Moonen Rik , Bucerius Jan , Mess Werner , van Oostenbrugge Robert , Fan Zhaoyang , Kooi M
Published: August 2023

Multi-contrast Atherosclerosis Characterization (MATCH) was developed to quantify of carotid atherosclerotic plaque composition within 5 minutes’ scan time. Twenty symptomatic patients with ≥2 mm carotid plaque underwent 3.0 Tesla conventional multi-sequence and MATCH MRI. Excellent agreement was obtained for scoring a Lipid-rich necrotic core (LRNC) intraplaque hemorrhage (IPH) on the MATCH images while fair for calcifications. No significant differences between MATCH and multi-sequence MRI were found in volume of LRNC, IPH and calcifications. We demonstrated excellent agreement between MATCH and multi-sequence MRI for the identification and quantification of LRNC and IPH within significant shorter time.
THE ASSOCIATION BETWEEN PLAQUE SURFACE DISRUPTION AND FIBROUS CAP STATUS AT BASELINE AND VOLUME CHANGE OF INTRAPLAQUE HEMORRHAGE OVER TWO YEARS
Authors: Kassem Mohamed , Gorissen Tahnee , AlBenwan Mohamed , van Dam-Nolen Dianne , Liem Madieke , van der Geest Rob , Hendrikse Jeroen , Mess Werner Werner , Nederkoorn Paul , Bos Daniel , Nelemans Patty , van Oostenbrugge Robert , Kooi M
Published: August 2023

The factors that contribute to intraplaque hemorrhage (IPH) development within the carotid atherosclerotic plaque are incompletely understood. Previously, we demonstrated that IPH is associated with a thin/ruptured fibrous cap (TRFC) and disruption of the plaque surface on in a cross-sectional study. Baseline and 2 year’s follow-up carotid MR images of 110 patients from the Plaque at Risk (PARISK) study were analyzed. IPH volume change in TRFC at baseline was significant different (p=0.04) than thick fibrous cap group. Baseline IPH volumes are larger in patients with TRFC and disrupted plaque surface, but didn’t increase during the follow-up.
Late feature fusion and GAN-based augmentation for generalizable cardiac MRI segmentation
Authors: Khalil Yasmina Al , Amirrajab Sina , Lorenz Cristian , Weese Jürgen , Pluim Josien , Breeuwer Marcel
Published: August 2023

While recent deep-learning-based approaches in automatic cardiac magnetic resonance image segmentation have shown great promise to alleviate the need for manual segmentation, most are not applicable to realistic clinical scenarios. This is largely due to training on mainly homogeneous datasets, without variation in acquisition parameters and pathology. In this work, we develop a model applicable in multi-center, multi-disease, and multi-view settings, where we combine heart region detection, augmentation through synthesis and multi-fusion segmentation to address various aspects of segmenting heterogeneous cardiac data. Our experiments demonstrate competitive results in both short-axis and long-axis MR images, without physically acquiring more training data.
Transfer Learning in Ultrahigh Field (7T) Cardiac MRI – Automatic Left Ventricular Segmentation in a Porcine Animal Model
Authors: Kollmann Alena , Lohr David , Ankenbrand Markus , Bille Maya , Terekhov Maxim , Hock Michael , Elabyad Ibrahim , Reiter Theresa , Schnitter Florian , Bauer Wolfgang , Hofmann Ulrich , Schreiber Laura
Published: August 2023

Cardiac magnetic resonance (CMR) is considered the gold standard for evaluating cardiac function. Tools for automatic segmentation already exist in the clinical context. To bring the benefits of automatic segmentation to preclinical research, we use a deep learning based model. We demonstrate that for training small data sets with parameters deviating from the clinical situation (high resolution images of porcine hearts acquired at 7T in this case) are sufficient to achieve good correlation with manual segmentation. We obtain DICE-scores of 0.87 (LV) and 0.85 (myocardium) and find high agreement of the calculated functional parameters (Pearson‘s r between 0.95 and 0.99).
Hippocampal subfield neurofunctional alterations in chronic insomnia
Authors: Yang Yang , Li Yong , Zhao Linwei , Chen Hong , Fan Xiaoping , Yan Gaowu
Published: August 2023

This study investigated the patterns of volume changes across neurofunctionally distinct hippocampal subfields in patients with chronic insomnia. The results suggested that L1 and R2 atrophy increased the risk of developing chronic insomnia approximately 3-fold, and negative emotion positively acted on the causal path of insomnia severity leading to R1 atrophy. In addition, we developed a practical and visual nomogram of individual competing risks for predicting chronic insomnia risk with high accurate predictive power based on these hippocampal subfields. Neurofunctional hippocampal subfield atrophy was a risk factor leading to chronic insomnia, contributing to understand of the etiology of insomnia.
DWI of cholesteatomas: An initial assessment based on RESOLVE and SPEN MRI
Authors: Otikovs Martins , Anaby Debbie , Shrot Shai , Nissan Noam , Frydman Lucio
Published: August 2023

Cholesteatomas are destructive lesions growing in the middle ear, in need of periodic assessments. Diffusion weighted imaging (DWI) at 3T provides clear contrast of these growths, facilitating their detection. However, the close presence of air-tissue interfaces within the ear channel results in geometric distortions that have led to adoption of non-EPI based methods for these high field evaluations. Herein we present results from initial DWI experiments performed for imaging cholesteatomas, which point out the value of Spatiotemporal Encoding (SPEN) DWI methods as promising alternatives to retrieve high-contrast, high-definition images.
The origins of BOLD signal fluctuations in non-gas-inhalation CVR mapping: an fMRI-EEG study
Authors: Joshi Parimal , Zhang Yi , Hou Xirui , Xu Cuimei , Bottomley Paul , Lu Hanzhang , Liu Peiying
Published: August 2023

Cerebrovascular reactivity (CVR) is typically measured with hypercapnic challenges, which require considerable subject cooperation. Recent CVR mapping approaches using resting-state BOLD data are promising, but their sensitivity is low in subjects with minimal spontaneous changes in breathing pattern. Performed in conjunction with resting-state BOLD scans, intermittent breath modulation enhances variations in breathing pattern while requiring minimal subject compliance, and is a promising tool for CVR mapping without gas inhalation. Here we conducted simultaneous fMRI-EEG experiments to investigate origins of the global BOLD signal fluctuations during intermittent breath modulation, to verify the validity of this new approach.
Attenuation Correction in PET/MRI Pediatric Treated Brain Tumors: a Preliminary Comparison between the ZTE and Atlas Techniques
Authors: Scifo Paola , Fallanca Federico , Barbera Maurizio , Savi Annarita , Bettinardi Valentino , Neri Ilaria , Gattuso Giovanna , Massimino Maura , Verderio Paolo , Pizzamiglio Sara , Falini Andrea , Gianolli Luigi , Spreafico Filippo , Picchio Maria , Baldoli Cristina
Published: August 2023

A preliminary comparison between the two Atlas and ZTE attenuation correction methodologies in a group of pediatric patients with brain tumors is presented. The differences of the two ACmaps and PET images were calculated and the PET parameters were compared. Our results show that using ZTE or Atlas to generate ACmaps modifies the SUVs, but the differences in values are very small. Moreover, when metallic artefacts occur, both ZTE and Atlas show loss of signals but ACmapsAtlas has smaller artefacts.
Evaluating b-value combinations on IVIM-DKI analysis with parametric reconstruction method in pancreatic carcinoma: A digital phantom study
Authors: Malagi Archana , Kandasamy Devasenathipathy , Khare Kedar , Calamante Fernando , Sharma Raju , Mehndiratta Amit
Published: August 2023

Optimization of b-values in IVIM-DKI is required for parameter estimation accuracy. IVIM-DKI model with Total Variation correction approach was employed in this study, which avoids abrupt changes in parameter values and eliminates non-physiological heterogeneity in maps. In pancreatic cancer, different b-value combinations were used: 4,6,8,10, and 13b-values. In terms of accurate parameter estimations and comparable qualitative maps, 8-13 b-values exhibited a similar trend; in contrast, 4b-values indicated inaccurate and noisy maps. 8b-values can be employed in pancreatic cancer with a constrained technique for a shorter acquisition process and reduced noise in parameter maps at low SNR.
Improving the biocompatibility of parahydrogen hyperpolarized [1-13C]pyruvate
Authors: Reineri Francesca , Bondar Oksana , Carrera Carla , Cavallari Eleonora , Cerutti Erika , Di Matteo Ginevra , Aime Silvio
Published: August 2023

ParaHydrogen Induced Polarization is a hyperpolarization method much less technically demanding and affordable than d-DNP. The Side Arm Hydrogenation method allowed to obtain hyperpolarized [1-13C]pyruvate that can be used for metabolic studies, but concerns about the safety and bio-compatibility of the final aqueous solution of the HP products may be present, due to organic solvents and metal complex. In this work, a method to remove all the traces of toxic solvents and metal complex from the final product will be presented, together with the 13C-MR images obtained using the metabolite thus hyperpolarized.
In situ evidence of radiation trapping limiting Rb polarization in common SEOP setups
Authors: Kelley Michele , Branca Rosa
Published: August 2023

To increase the 129Xe polarization for emerging biomedical applications, the Rb polarization on which the 129Xe directly depends must be first optimized. Radiation trapping is a form of Rb depolarization thought to be quenched by the N2 added to SEOP gas mixtures. Here we use absorption spectroscopy to measure the Rb density, optical spectroscopy to monitor the fraction of Rb atoms involved in radiation trapping, and field cycling to measure the Rb polarization. We find that radiation trapping is still present during spin-exchange optical pumping and appears to limit the achievable Rb polarization.
Assessment of treatment efficacy in T-cell acute lymphoblastic leukemia models with Hyperpolarized MR and NMR metabolomics
Authors: Enriquez Jose , Baran Natalia , Pudakalakatti Shivanand , Konopleva Marina , Bhattacharya Pratip
Published: August 2023

Metabolic reprogramming is one of the key hallmarks in acquiring aggressive phenotype and chemoresistance in many cancers including T-cell acute lymphoblastic leukemia (T-ALL). To combat chemoresistance, we treated patient-derived xenografts with two metabolic drugs that target two different pathways for T-ALL: IACS-010759, a Complex I inhibitor for OXPHOS pathway and AZD3965, a monocarboxylate transporter-1 (MCT1) inhibitor. Hyperpolarized metabolic imaging in vivo and NMR metabolomics ex vivo was utilized to observe the difference in metabolism with single treatment and in combination. Our results demonstrate that metabolic intervention utilizing OXPHOS blockade can be potentiated by targeting the MCT1 transporter.
Random Matrix Theory reconstruction for T1 quantification on a field-cycling scanner for B0 ranging between 2-200mT
Authors: Lemberskiy Gregory , Mallikourti Vasiliki , Novikov Dmitry , Broche Lionel
Published: August 2023

We showcase high SNR T1 maps over a range of low field strengths on a stroke patient imaged using a field-cycling imaging scanner (FCI), an MR system capable of varying B0 over 2 orders of magnitude. Images from this scanner are denoised using Random Matrix Theory (RMT), leveraging the redundancy over multiple inversion times and field strengths to increase the baseline SNR by 3-fold. Following RMT denoising, we observe the T1 dispersion effect indicating a deviation of R1 frequency dependence from the BPP theory.
In Vivo T1 Mapping of Neonatal Brain Tissue at 64mT
Authors: Padormo Francesco , Cawley Paul , Dillon Louise , Hughes Emer , Almalbis Jennifer , Robinson Joanna , Maggioni Alessandra , Cromb Daniel , Price Anthony , Consortium UNITY , Arlinghaus Lori , Hu Houchun , Williams Steve , Malik Shaihan , Counsell Serena , Rutherford Mary , Arichi Tomoki , Edwards A. David , Hajnal Joseph
Published: August 2023

A promising application of ultra-low field portable MRI is neonatal imaging. In this work we show that neonatal brain T1 mapping is viable at 64mT utilising the Hyperfine Swoop portable MRI system.
Accelerating Ultra-Low Field MRI with Compressed Sensing
Authors: Waddington David , Shimron Efrat , Hindley Nicholas , Koonjoo Neha , Rosen Matthew
Published: August 2023

Portable MRI scanners that operate at very low magnetic fields are increasingly being deployed in clinical settings. However, the intrinsic low signal-to-noise (SNR) ratio of these low-field MRI scanners often necessitates many signal averages, and therefore excessively long acquisition times. Here we propose to improve SNR through optimized k-space undersampling and Compressed Sensing reconstruction. We demonstrate this approach for 6.5 mT ultra-low-field MRI using: (1) retrospective-subsampling experiments with 2x to 4x acceleration; (2) prospectively-subsampled data acquired from a human brain phantom with a 6.5mT MRI. The results exhibit a higher SNR than the traditional averaging method, without increasing scan time.
Strong non-BOLD Effect of EPI Gradient Switching Sounds on Voxel Intensities Both Inside and Outside Rat Cranium
Authors: Prichard James , Patz Samuel
Published: August 2023

Echoplanar images of rat head with and without blocking of external ear canals revealed large voxel intensity changes outside as well as inside the cranium. These are probably mechanical effects of vibrational energy originating in the tympanic membrane and coupled to other tissue compartments of the head through the auditory ossicles, basilar membrane, and cochlear round window. They are so large that even slight variations in them may distort magnetic resonance imaging measurements of neural activity and water diffusion. Awareness of that possibility may inform measures to remove or compensate for it.
Remapping of functional connectivity with optogenetic locus coeruleus activation in rats
Authors: Anumba Nmachi , Kelberman Michael , Smith Corrie , Pan Wen Ju , Clavijo G Perrin , Weinshenker David , Keilholz Shella
Published: August 2023

High tonic (3-5 Hz) locus coeruleus (LC) activity drives anxiety-like behaviors and the stress response via its dense afferents and receptor distribution profile. Previous studies have utilized DREADD stimulation to understand the global effects of elevating LC activity, but lacked temporal and patterned control of stimulation. Here, we combined optogenetic stimulation of the LC (5 Hz) with functional magnetic resonance imaging to better understand global changes in functional connectivity as a result of high tonic LC activity. We found that LC stimulation at 5 Hz resulted in a shift toward increased connectivity in ChR2 injected animals compared to mCherry controls.
Humanized mouse brain biomarkers through transcriptomic conversion
Authors: Vrooman Roël , Homberg Judith , Grandjean Joanes
Published: August 2023

Since the translation of data between species remains subjective, our goal is to develop a data-driven tool to perform this translation based on the expression patterns of homologous genes. For this, human and mouse fMRI data, which was manually matched based on spatial homology between co-activation patterns, was modelled as a linear addition of gene expression maps. Weighting factors were then used to estimate synthetic brain states based on homologous genes. When comparing the synthetic brain states to their matched biological state, they showed higher correlation than compared to mismatched states, showing the effectiveness of the translational tool.
Multimodal BOLD and CBV MRI for artifact correction in fluorescence recordings
Authors: Lambers Henriette , Wachsmuth Lydia , Faber Cornelius
Published: August 2023

Combining fMRI and fluorescence recordings has become an important tool for neuroimaging. However, hemodynamic changes lead to artifacts in fluorescence recordings, since blood absorbs fluorescence light. We investigated the hemodynamic artifact in functional and pharmacological MRI and fluorescence measurements and present an MRI-based correction method. In both stimulation and lactate injection experiments, hemodynamic artifacts in FRET recordings occurred. These artifacts cannot be removed effectively using a standard (purely optical) correction method. An MRI-based correction presented in this work eliminates the artifact while the expected fluorescence signal changes persist.
Layer-specific microsimulation of S2 cortex revealed distinct functional microcircuits in non-human primate brain
Authors: Yang Pai-Feng , Wang Feng , Reed Jamie , Yang Zhangyan , Gore John , Chen Li Min
Published: August 2023

Intracortical microstimulation is one of the most common techniques used to activate cortical functional networks and probe causal connections. This study investigates whether BOLD signals can detect layer-specific functional circuit responses to electrical brain stimulation. We delivered electrical current to different layers of secondary somatosensory cortex (S2) and detected layer-specific BOLD activations. Effective functional connectivity analysis revealed different networks to different layers of S2 cortex.
Evidence for an intercollicular auditory push/pull mechanism revealed by BOLD fMRI
Authors: Severo Frederico , Valente Mafalda , Shemesh Noam
Published: August 2023

The role of the rodent inferior colliculus (IC) in binaural integration is of great interest especially for sound localization and processing of interaural level difference (ILD). Yet, many IC underlying mechanisms remain unclear. Here, we find evidence for a push/pull mechanism in IC, with contralateral (positive BOLD) activity exerting dominance over ipsilateral (negative BOLD) activity, possibly as means of a sound localization/lateralization.
Automated cardiac bi-ventricular segmentation and motion analysis in a monocrotaline rat model of pulmonary hypertension
Authors: Niglas Marili , Baxan Nicoleta , Ashek Ali , Zhao Lin , Duan Jinming , O'Regan Declan , Dawes Timothy , Bai Wenjia , Zhao Lan
Published: August 2023

Multiple cardiac AI-based image processing pipelines exist for clinical application, yet the equivalent is lacking for rodents. We utilized a fully convolutional network combined with 3D-atlas registration to auto-segment cine images from pulmonary hypertension (PH) rats and produce 3D contraction maps. The auto-segmentations were equivalent to manual (Dice overall >0.7). The volumetric parameters did not differ between methods, except a minor underestimation for RVESV in PH rat (8.2%). 3D contraction maps indicated moderately increased basal wall motion at early (adaptive) stage followed by a 36% reduction at later (maladaptive) stage of PH. This regional motion remodelling correlates with PAH patients.
Deep learning-based Automatic Analysis for Free-breathing High-resolution Spiral Real-time Cardiac Cine Imaging at 3T
Authors: Awad Marina , Wang Junyu , Feng Xue , Zhou Ruixi , Salerno Michael
Published: August 2023

Cardiac real-time cine imaging is useful for patients who cannot hold their breath or have irregular heart rhythms. Free breathing high-resolution real-time cardiac cine images are acquired efficiently using spiral acquisitions, and rapidly reconstructed using our DESIRE framework. However, quantifying the EF from free-breathing real-time imaging is limited by the lack of an EKG signal to define the cardiac cycle, and through-plane cardiac motion resulting from free-breathing. We developed a DL-based segmentation technique to determine the end-expiratory phase and determine end-systole and end-diastole on a slice by slice basis to accurately quantify EF from spiral real-time cardiac cine imaging.
Feasibility of machine learning for cardiovascular function analysis in patients with repaired tetralogy of Fallot
Authors: Thompson Elizabeth , Bhattaru Abhijit , Vu Phuong , Donnelly Elizabeth , Goldmuntz Elizabeth , Fogel Mark , Witschey Walter
Published: August 2023

Tetralogy of Fallot (ToF) is a congenital heart disease that is typically repaired with surgery early in life, but right ventricular remodeling results in adverse events for many patients. This preliminary analysis of 8 patients investigated the feasibility of training a convolutional neural network to segment the right and left ventricles from 2-dimensional cardiovascular magnetic resonance images, resulting in Dice scores ranging from 0.73-0.91 for the left ventricular blood pool, left ventricular myocardium, and right ventricular blood pool. Machine learning shows promise to enable large-scale longitudinal studies of ToF.
Improving multimodal imaging with an MR-compatible EEG net: the R-Net-MR-IT
Authors: Fultz Nina , Jeong Hongbae , Williams Stephanie , Gomez Daniel , Setzer Beverly , Warbrick Tracy , Jaschke Manfred , Bonmassar Giorgio , Lewis Laura
Published: August 2023

EEG provides valuable clinical information, but EEG nets produce artifacts in MRI and CT images, preventing these modalities from being combined in typical clinical practice. We tested whether a new MR-compatible EEG net, called the R-Net-MR-IT, could produce high-quality clinical and research images. We assessed image quality in CT and MR images on a phantom with a conventional net, R-Net-MR-IT, and with no net. We then performed the same comparison in humans, as well as fMRI scans. Our results show that the R-Net-MR-IT enables acquisition of high quality CT and MR images, with minimal artifact from EEG hardware.
Development of Non-Rectangular Excitation Pulses for Improved kZ Fidelity in Super-Resolution T2-Weighted Spin-Echo MRI
Authors: Borisch Eric , Florea Alexandru , Grimm Roger , Kawashima Akira , Riederer Stephen
Published: August 2023

Results from continuing investigation of non-rectangular slice excitation profiles with the goal of providing improved results when used to reconstruct overlapping-slice 2D acquisitions leveraging knowledge of the slice profile are presented. A simulation of the excitation/acquisition process and accompanying reconstruction has been developed to aid the exploration of non-traditional slice profiles and their impact on the final reconstruction quality.
Characterization of SNR for radial spin echo imaging
Authors: Stern Neta , Block Kai T , Solomon Chen , Blumenfeld-Katzir Tamar , Ben-Eliezer Noam
Published: August 2023

To optimize the use of radial spin-echo sequences, SNR characterization for relevant T1 and T2 ranges is required. In this work, we studied the interplay between the number of excitations (Nexc) and the turbo factor (NTF - number of echoes within each TR) on the SNR of images acquired using the RAISE (RAdIal Spin Echo) sequence. SNR was evaluated for phantom and in-vivo images. Phantom analysis focused on SNR per T1 and T2 ranges appropriate for known gray and white matter relaxation times. Selected parameter sets were later used for in vivo scans for qualitative evaluation.
Comparison of Imaging Methods for Fast Whole-Body MRI Screening
Authors: Rea Marc , Barrett Alex , Romaniuk Christopher
Published: August 2023

Improvements in image quality and scan time coupled with AI reading of images, is enabling the possibility of quickly screening all patients who attend MRI for malignant tumours. This research explores the imaging and clinical requirements for such a programme, and reports on the ability of various sequences and patient configurations to meet those requirements.
MR image enhancement using a multi-task neural network trained using only synthetic data
Authors: Blansit Kevin , Hu Zhehao , Zaharchuk Greg , Gong Enhao , Datta Keshav
Published: August 2023

Faster MRI scans can be achieved by acquiring low resolution images or low SNR images and enhancing them to standard-of-care using deep learning techniques. However, to achieve clinical diagnostic quality images, this requires a large number of paired clinical datasets to train the model. Here we show that a multi-task deep convolutional neural network (DCNN) trained using only simulated motion artifact, low SNR, and low resolution images is capable of improving the quality of clinically acquired images from motion corrupted and accelerated sequences.
Paired CycleGAN-based Cross Vendor Harmonization
Authors: Yoon Joonhyeok , Ji Sooyeon , Choi Eun-Jung , Jeong Hwihun , Lee Jongho
Published: August 2023

CycleGAN shows good performance with harmonization task. However, generative models have risk of structure modification. we proposed a cross-vendor harmonization model with paired CycleGAN based architecture for both high performance and structural consistency. We acquired 4 in-vivo dataset from Siemens and Philips scanner. For algorithm, we adapted CycleGAN for generation model, and we utilized L1 loss from pix2pix and patchGAN discriminator for structural consistency. Evaluations were performed both quantitatively and qualitatively. To quantitative evaluation, we assessed means of structural similarity index measure (SSIM). Proposed model shows better results compared to CycleGAN architecture.