bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of regional differences in pH values obtained via 31P MRSI at 7T
Authors: Platek Justyna , Kroh Florian , Franke Vanessa L. , Boyd Philip S. , Weckesser Nina , Schlemmer Heinz-Peter , Paech Daniel , Ladd Mark E. , Bachert Peter , Korzowski Andreas
Published: August 2024

In this study, we analyzed pH values obtained via high-resolution 31P MRSI at 7T in different subjects and different regions of the human brain, and identified a trend towards lower pH values in the frontal region compared to other brain regions. The potential regional variation should be taken into account in cases, where only small pH changes between different tissues are expected and partial volume effects might dominate.
Distinction of True-Progression from Pseudo-progression in Glioblastomas using ML Model based on Quantitative mpMRI and Molecular Signatures
Authors: Yadav Virendra , Mohan Suyash , Agarwal Sumeet , Godoy Laiz Laura , Wang Sumei , Nasrallah MacLean P. , O’Rourke Donald M. , Bagley Stephen , Poptani Harish , Chawla Sanjeev , Singh Anup
Published: August 2024

Glioblastoma patients (n=93) exhibiting enhancing lesions within 6 months after completion of standard therapy underwent anatomical imaging, diffusion and perfusion MRI. The median values of parameters (MD, FA, CL, CP, CS and rCBV) were computed from the enhancing regions. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status was available from 75 patients. Subsequently, these patients were classified as TP (n=55) or PsP (n=20). The data were randomly split into training and testing sets. The best model for differentiating TP from PsP was obtained using quadratic SVM classifier with a training accuracy of 90.9%, cross-validation accuracy of 85.5% and testing accuracy of 85%.
A neural network to estimate the hip center of rotation for a fully-automated range of motion analysis in femoroacetabular impingement.
Authors: Montin Eros , Panozzo Daniele , Lattanzi Riccardo
Published: August 2024

We evaluated three neural network architectures for the automatic identification of the center of the femur head on 3D water-only Dixon MRI. We trained using a mixture of real and augmented data. The mean error of the best-performing network was three-time lower compared to a manual annotation and on the order of 1 voxel. We combined the network to create the first fully automated pipeline to assess the hip range of motion from 3D MR.
Reduction of Hippocampal Subfield Volumes in Treatment-Resistant Depression using ASHS: A 7-Tesla Study
Authors: Alper Judy , Verma Gaurav , Rashid Shams , Balchandani Priti
Published: August 2024

Major depressive disorder has complex pathophysiology. It is critical to understand treatment-resistant depression (TRD) specifically, as there are many patients for whom no sufficient treatment exists. In this study we assess volumetric differences in hippocampal subfields between TRD patients and healthy controls (HC) using automatic segmentation of hippocampal subfields and ultra-high field MRI. 13 TRD patients and 13 HC underwent imaging using 7-Tesla MRI. ASHS software produced automated hippocampal segmentation for volumetric analysis. Compared to HC, TRD patients showed reduced right-hemisphere CA2/3 subfield volume. Determining biomarkers for TRD pathophysiology may elucidate the underlying mechanisms of treatment-resistant depression.
White and Grey Matter Microstructure Alterations in Early Psychosis and Schizophrenia
Authors: Pavan Tommaso , Alemán-Gómez Yasser , Jenni Raoul , Cleusix Martine , Alameda Luis , Cuenod Kim Do , Conus Philippe , Klauser Paul , Hagmann Patric , Jelescu Ileana
Published: August 2024

In schizophrenia, widespread brain abnormalities are commonly reported but not the microstructure alterations. Here, we investigate brain microstructure during early psychosis and schizophrenia using DKI (in GM & WM), a clinically feasible extension of DTI, and we apply the White Matter Tract Integrity – Watson (WMTI-W, WM only) model. In WM, extensive alterations, consistent with demyelination, were found in early psychosis, while transitioning to chronic schizophrenia, microstructure changes become region-specific as indicated by the two ROI-dependent trends of disease progression found in this cohort. GM showed increased diffusivities and decreased kurtosis, but not widespread as in WM.
Deep Learning Prediction of Multi-channel ESPIRiT Maps for Calibrationless MR Image Reconstruction
Authors: Zhang Junhao , Yi Zheyuan , Zhao Yujiao , Xiao Linfang , Hu Jiahao , Lau Vick , Chen Fei , T.L.Leong Alex , Wu Ed X.
Published: August 2024

We present a U-Net based deep learning model to estimate the multi-channel ESPIRiT maps directly from uniformly-undersampled multi-channel multi-slice MR data. The model is trained with a hybrid loss function using fully-sampled multi-slice axial brain datasets from the same MR receiving coil system. The proposed model robustly predicted ESPIRiT maps from uniformly-undersampled k-space brain and cardiac MR data, yielding highly comparable performance to reconstruction using to acquired reference ESPIRiT maps. Our proposed method presents a general strategy for calibrationless parallel imaging reconstruction through learning from coil and protocol specific data.
Lightweight encoder-decoder architecture for Fat-Water separation in MRI using biophysical model-guided deep learning method
Authors: M Ganeshkumar , Kandasamy Devasenathipathy , Sharma Raju , Mehndiratta Amit
Published: August 2024

In this study, we propose a novel lightweight encoder-decoder architecture for deep learning based Fat-Water separation in multi-echo MRI data. The architecture's performance is evaluated in the biophysical model-guided deep learning-based Fat-Water separation task and compared against the widely used U-Net. This biophysical model-guided deep learning-based Fat-Water separation requires no training data and ground truths, but it involves time-consuming loss minimization for thousands of epochs. Despite having significantly fewer training parameters, the proposed architecture performed equally well in generating the Fat-Water maps compared to the U-Net. So, our proposed architecture aids in the faster generation of Fat-Water maps.
Transferable Deep Learning for Fast MR Imaging
Authors: Zhou Yuxiang , Paul Riti , Ding Pak Lun Kevin , Hu Leland , Patel Ameet , Li Baoxin
Published: August 2024

Artificial intelligence (AI) applications in the field of magnetic resonance imaging have been implemented in routine clinical practice. However, MRI still faces a practical and persistent challenge: its long acquisition time. This has led to two prominent issues in health care: high cost and poor patient experience. Long acquisition time is also a source of degraded imaging quality (e.g., motion artifacts). In the study, we propose to develop novel Deep Learning (DL) architectures combined with transfer learning capabilities to address the above challenge and apply this newly developed AI technique for image reconstruction in MRI with very fast imaging acquisition.
Radial vs. Spiral – A Comparison of Stack-of-stars and Stack-of-spirals Spatial Encoding Schemes in Multiparametric Body MRI with QTI
Authors: Pirkl Carolin , Schulte Rolf , García-Polo Pablo , Cencini Matteo , Endt Sebastian , Biagi Laura , Tosetti Michela , Menzel Marion
Published: August 2024

Highly accelerated multiparametric MRI techniques are more and more demonstrating their diagnostic potential. To achieve short scan times, these techniques rely on non-Cartesian (under-) sampling. Initially developed for MRI applications in the brain, these sequences are now also applied in body MRI. In this work, we present a phantom and in vivo study to demonstrate and evaluate the strengths and pitfalls of the two most common non-Cartesian – spiral and radial – sampling schemes for the application of rapid, free-breathing 3D T1, T2 and proton density (PD) mapping with quantitative transient-state imaging (QTI) in the prostate gland.
Machine learning for detecting sensorineural hearing loss utilizing functional imaging with a combination of static and dynamic brain features
Authors: Xu Xiao-Min , Chen Yu-Chen
Published: August 2024

Alterations of static and dynamic brain function have been found in sensorineural hearing loss (SNHL). The combination of data-driven machine learning based classifiers and multiple imaging features can identify SNHL and healthy controls automatically. The spearman rank correlation with radial basis functional kernel support vector machine (SVM) and sigmoid SVM provides promising neural biomarkers for clinical classifier of SNHL.
A simultaneous dual slice acquisition with spiral trajectory for morphological and functional lung assessment
Authors: Slawig Anne , Weng Andreas , Köstler Herbert
Published: August 2024

SElf-gated Non-Contrast-Enhanced FUnctional Lung imaging (SENCEFUL) is a well-established method to determine functional lung parameters and was already successfully combined with 3D-UTE for robust ventilation quantification. Nevertheless, the evaluation of not only ventilation, but also perfusion, requires a 2D excitation, as it is based on the inflow effect. Additionally, coverage of more than one slice within short measurement times is valuable. Here, it is shown that functional information can be obtained from two slices acquired simultaneously, thus doubling the anatomical coverage of a conventional 2D acquisition.
Remote Pneumatic Dose Administration for 129Xe MRI: Effects on Lung Inflation and Patient Experience
Authors: Church Alexander , Zhang Shou , Lu Junlan , Blanton Cody , Korzekwinski Jennifer , Mummy David , Driehuys Bastiaan
Published: August 2024

Hyperpolarized 129Xe MRI requires repeatable lung inflation volumes to ensure consistent and accurate data. Current dose administration techniques require specialized study personnel to not only properly coach the subject through the inhalation maneuver, but also to directly administer the 129Xe dose, often while leaning deep into the MRI bore. Since lung inflation directly affects imaging data, it is important to maximize the consistency of inflation volumes across imaging sessions. We propose a novel 129Xe gas administration device intended to mitigate lung inflation differences as well as allow for remote administration of doses from outside the bore.
Feasibility and Reproducibility of Ventilation and Perfusion Imaging at a 0.35 T MR-Linac in Healthy Volunteers and Lung Cancer Patients
Authors: Klaar Rabea , Rabe Moritz , Gaass Thomas , Schneider Moritz , Benlala Ilyes , Corradini Stefanie , Eze Chukwuka , Belka Claus , Landry Guillaume , Kurz Christopher , Dinkel Julien
Published: August 2024

Hybrid MR-imaging and linear accelerators for radiotherapy allow highly accurate treatment of lung cancer patients. The potential of Non-uniform Fourier Decomposition (NuFD), a non-contrast enhanced free-breathing technique that allows the assessment of lung ventilation and perfusion, was investigated in 10 healthy subjects and 2 lung cancer patients at a 0.35 T MR-Linac. Due to challenging ventilation quantification and reproducibility, two normalization strategies were proposed. Evaluation on repeated scans demonstrated clear improvement compared to uncorrected cases. First longitudinal ventilation assessment over treatment course shows promising results for the use of NuFD as treatment response monitoring tool in the clinical workflow.
Impact of Epicardial Adipose Tissue Assessed on Early Left Atrial Dysfunction in Heart Failure with Preserved Ejection Fraction
Authors: Li Yunling , Liu Shengliang , Lian Jianxiu , Wang Goukun , Gu Xia , Sun Yong , Yu Bo
Published: August 2024

Heart failure with preserved ejection fraction (HFpEF) characterized by heart diastolic dysfunction. Epicardial adipose tissue (EAT) has been speculated to play an important role in HFpEF pathophysiological processes. In present study, EAT volume was significantly increased in patients with HFpEF and patients with high risk for developing HFpEF compared with healthy controls, and it was correlated with CMR parameters indicative of diastolic dysfunction, particularly GLS and LA reservoir, conduit, and pump strains. These findings provided compelling evidence for the potential role of EAT in adverse myocardial remodeling and the pathophysiology of HFpEF.
Left Atrial Hemodynamics Assessed with 2D Real Time Phase Contrast MRI are Associated with Prior Stroke History in AF Patients
Authors: Baraboo Justin , Pradella Maurice , Maroun Anthony , Weiss Elizabeth , Dicarlo Amanda , Gunasekaran Suvai , Lee Daniel , Passman Rod , Kim Daniel , Markl Michael
Published: August 2024

2D real time phase contrast was utilized in atrial fibrillation patients with and without a prior history of stroke. To account for within patient heartbeat variability, heartbeats were aggregated within each patient according to ECG trace. Heartbeat durations (RR-intervals) were sorted from fast to slow for each patient. Three groups were formed from the tertiles of the RR-intervals (faster, regular, and slower heartbeats). Blood stasis and peak velocity were compared between the stoke subgroups for each grouping. Patients with prior stroke had significantly higher stasis which remained significant in multivariable modeling using demographic variables as well.
High-resolution, free-breathing, fat-suppressed 3D Late Gadolinium Enhancement to define atrial wall scar after atrial fibrillation ablation
Authors: Dash Rajesh , Chubb Henry , Mao Xianglun , Nikbeh Fara , Wang Pingni , Tada Yuko , Delso Gaspar , Janich Martin , Narayan Sanjiv , Ennis Daniel , Yang Phillip
Published: August 2024

Atrial fibrillation (AF) ablation procedures still face challenges to achieve durable restoration of sinus rhythm. Advanced cardiac MRI delayed enhancement can delineate atrial wall scar to aid in planning AF ablation. However, thin atrial walls demand more advanced sequence development. In this study, we report protocol optimizations for high-resolution, free-breathing, fat-suppressed 3D LGE to detect atrial wall scar. In three AF patients to date, we found progressive improvements in CNR and detailed the sequence modification that led to these improvements. Future iterations will be used to assess atrial scar in patients, pre- and post-AF ablation.
Characterization of left atrial remodelling and atrial fibrillation subtype using fractal analysis of late gadolinium enhanced MRI
Authors: Thornhill Rebecca , Kang Jessie , Nery Pablo , Redpath Calum , Birnie David , Chenier Sophie , Peña Elena
Published: August 2024

Atrial Fibrillation (AF) is a heart rhythm disorder of the left atrium (LA) that is associated with an increased risk of stroke and death. AF has been known to induce morphological changes of the LA that may be detectable with fractal analysis. The purpose of this study was to assess whether there are differences in fractal dimension of the LA based on AF severity or subtype. The paroxysmal AF groups demonstrated increased fractal dimension compared to persistent or permanent groups. LA dilatation associated with persistent or permanent AF may explain this result, but this requires validation in a larger cohort.
A MMP-Responsive Nanoplatform with Transformable Magnetic Resonance Property for Quantitative Tumor Bioimaging and Synergetic Therapy
Authors: Wang Zhongling , CHEN AN , Lu Hongwei , Zhao Xiance
Published: August 2024

We developed a novel nanoplatform-based MMP9-responsive T2–T1 switching MRI contrast agent, which can be used not only for non-invasive visualization and quantitative analysis of MMP9 activity, but also as a carrier in photothermal sensitization chemotherapy. The nanoplatform acts as a T2 contrast agent in physiological conditions ,then transform into a T1 contrast agent by MMP9 stimulus. We have demonstrated that the changes R1 and R2/R1 values are MMP9 concentration dependent in tumors. The combination of PMPSD with laser irradiation was more effective than single chemo-/photothermal therapy, and up-regulation of MMP9 in the tumor could eanhance the nanoplatform’s therapeutic effect.
In Vivo Single Voxel Relaxation-Diffusion Correlation Spectra Revealed the Microstructure of Human Brain
Authors: Wang Lixian , Okada Tomohisa , Hanakawa Takashi , Zhang Baogui , Liang Huilou , An Jing , Xue Rong , Zong Fangrong
Published: August 2024

Multidimensional MRI resolves the correlations between physical parameters and relaxation properties and has become an increasingly important protocol in biomedical engineering. It has sub-voxel resolution but most research still uses multi-voxel ROIs. In this study, we obtained the single voxel T1-D Relaxation-Diffusion correlation spectra from in vivo human brain tissue boundaries. The significant variance in these spectra might help to identify tissue microstructure at the sub-voxel resolution. Our research disclosed the feasibility of applying multidimensional MRI techniques to detect and segment the human brain.
FLAIR3Phase: a new synthetic MRI contrast for paramagnetic rim lesions detection in multiple sclerosis
Authors: Bulcke Colin Vanden , Delinte Nicolas , Macq Benoît
Published: August 2024

Chronic active multiple sclerosis (MS) lesions are visible on susceptibility-based MRI as paramagnetic rim lesions (PRL); these lesions are characterized by severe tissue damage and strongly correlate with disease severity. PRL assessment is usually performed manually on unwrapped-filtered phase images. However, PRL assessment is associated with high intra/inter-rater variability due to the poor visibility of PRL and to the lack of standardized imaging protocols/guidelines for their detection. Here, we propose a new synthetic contrast called FLAIR3Phase to augment PRL assessment workflow and to reduce rater variability.
Quantification of gray matter abnormalities in drug‑naïve major depressive disorders by synthetic MRI
Authors: Wen Junyan , Yang Shanshan , Lin Xuecong , Cui Wei , Qian Long , Chen Zhimin , Gao Liaoming , Gao Qian , Huang Weikang , Cheng Dongliang , Wen Ge
Published: August 2024

Major depressive disorder (MDD) is a common mental illness. Herein, we explored the differences in the whole-brain T1 and T2 relaxation times between drug-naïve major depressive disorder patients and healthy controls by synthetic MRI (SyMRI). The results showed altered T1 and T2 values in specific regions of the gray matter in MDD patients, which may be associated with alterations in the brain gray matter microstructure, such as excessive iron deposition. Thus, these quantitative variables may be promising imaging markers for further exploring the pathophysiological mechanisms of depression.
Abnormal dynamic function connectivity pattern in first-episode, drug-naïve adult patients with major depressive disorder
Authors: Chen Tao , He Zhongyi , Guo Qinger , Duan Jinfeng , Zhang Yong , Wang Min , Yang Hong
Published: August 2024

Objective: To explore the specific FC change patterns of MDD by combining sFC and dFC. Methods: 37 MDD and 36 matched HCs were included in this study. The differences of sFC and dFC between two groups were compared. Results: Compared to HCs, patients showed less time in the anti-correlated state between higher-order and lower-order networks and longer dwell time in the whole-brain weakly connected state. The mean dwell time of state 4 was negative correlation with the behavioral scale score in patients. Conclusions: These disrupted dFC patterns provide new clues to understanding the neuropathology of state-dependence in MDD.
Free water DTI for evaluating gray matter microstructure in major depressive disorder: A preliminary study
Authors: Lin Xuecong , Wen Junyan , Yang Shanshan , Cui Wei , Qian Long , Hao Yanyu , Gong Liya , Huang Weikang , Zhang Haijie , Wen Ge
Published: August 2024

Major depressive disorder (MDD) is a common mental disease with unclear pathophysiology. Herein, we explored the differences in the whole-brain gray matter free-water axial diffusivity (AD) and mean diffusivity (MD) values between MDD patients and healthy controls using free-water DTI. The results showed altered free-water AD and MD values in specific regions of the gray matter in MDD patients, which may be associated with alterations in the brain gray matter microstructure, such as microstructure damage or neurodegeneration. Thus, these quantitative variables could be used as valuable biomarkers that could further our understanding of the pathophysiological mechanisms of depression.
Constrained Reconstruction of White Noise (CROWN) for Strategically Acquired Gradient Echo (STAGE) Imaging
Authors: Kokeny Paul , Xu Qiuyun , Gharabaghi Sara , Sethi Sean , Liu Yu , Zhang Youmin , Liu Peng , He Naying , Yan Fuhua , Haacke E.
Published: August 2024

By using the inherent relationship between proton spin density (PSD) and T1, we propose a new image-processing approach to reduce noise called CROWN (Constrained Reconstruction of White Noise). Firstly, we established a linear relationship between these two parameters, then applied a cost function to constrain simulated Strategically Acquired Gradient Echo (STAGE) PSD map and T1 map data in the presence of noise. Secondly, we applied this approach to in vivo STAGE images to reduce noise and improve SNR without the loss of image detail. CROWN has the potential to make higher resolution or faster imaging viable with improved SNR.
Correcting motion-induced B0 shim failure at 3T CMR using a deep-learning-enabled 3D motion-resolved B0 shimming
Authors: Li Xinqi , Huang Yuheng , Guan Xingmin , Zhang Xinheng , Yoosefian Ghazal , Bi Xiaoming , Han Fei , Lee HsuLei , Christodoulou Anthony , Li Debiao , Dharmakumar Rohan , Han Hui , Yang Hsin-Jung
Published: August 2024

B0 inhomogeneity is a long-lasting issue for CMR in high-field (3T and above) scanners. B0 shimming is a standard way to improve the B0 field. However, motion-induced field inhomogeneity is an unknown factor in routine practice and compromises cardiac B0 shimming quality. Here, we proposed a motion-resolved cardiac B0 shimming strategy by acquiring motion-resolved cardiac B0 field maps and adopting a modified U-net model for precise and automatic shim field derivation. We showed that dynamic shimming could improve field homogeneity through the respiratory cycle and provide a reliable B0 field for free-breathing CMR at 3T.
Spherical harmonic shim analysis of B0 distributions in cardiac imaging planes from 921 subjects
Authors: Shang Yun , Theilenberg Sebastian , Peng Boyu , Hock Michael , Schreiber Laura , Jambawalikar Sachin , Juchem Christoph
Published: August 2024

Cardiac functional scans adopting bSSFP sequences suffer from dark band artifacts due to B0 inhomogeneity. The best remedy to mitigate this issue is through cardiac B0 shimming. A limited understanding of the B0 conditions in clinical diagnostic orientations impedes the development of an optimal B0 shim strategy in the human heart. Here we perform a theoretical analysis of spherical harmonic B0 shim at 3 T using a static global approach and slice-specific dynamic shim updating in the short-axis views of human hearts from 921 subjects as a starting point for the development of optimized cardiac B0 shim strategies.
Accelerated, Free-Breathing 3D Cardiac T1ρ Mapping Pulse Sequence with XD-GRASP Reconstruction
Authors: Gunasekaran Suvai , Hong KyungPyo , Catania Roberta , Robinson Joshua , Passman Rod , Katsaggelos Aggelos , Rigsby Cynthia , Witschey Walter , Kim Daniel
Published: August 2024

T1ρ mapping is an emerging non-contrast pulse sequence for measuring cardiac fibrosis. Unfortunately, current T1ρ techniques suffer from lack of coverage, poor spatial resolution, and long scan time. Thus, we developed an accelerated, free-breathing 3D cardiac T1ρ mapping pulse sequence using XD-GRASP reconstruction including both respiratory and contrast dimensions; additionally, view sharing and KWIC filtering were incorporated to improve spatial resolution. This sequence was tested in 8 patients undergoing clinically indicated cardiac MRI, resulting in robust image quality and T1ρ values that are in agreement with literature.
Recovering image orientation for unconventional acquisition plane with deep learning algorithm: cardiac magnetic resonance case.
Authors: Rebbah Habib , Boutelier Timothé
Published: August 2024

Deducing the orientation main view of an image from the DICOM information could be complicated especially for unconventional image plane as for cardiac MR. We explore here the feasibility of deducing the orientation of the image based on CNN approach.
A dual-flip angle bSSFP imaging method for proton resonance frequency-based thermometry
Authors: So Seohee , Park HyunWook , Seo Hyunseok
Published: August 2024

Proton resonance frequency thermometry estimates temperature change by detecting the frequency change which is proportional to that of the temperature. In this study, we propose a dual- flip angle bSSFP thermometry method that generates a high intensity signal and linear phase to the frequency shift. Two steady states of the proposed method have phase dependency on the off-resonance frequency and the phase difference between the steady states has a linear relation with the off-resonance frequency. The linear phase relation makes it possible to measure temperature change. And the acquired high intensity signal benefits temperature monitoring and guidance for thermal therapy.
Monitoring Temperature using Gradient Echo Imaging at 0.5T
Authors: Martinez Diego , Harris Chad , Wiens Curtis , Handler Will , Chronik Blaine
Published: August 2024

Gradient Echo Proton Resonant Frequency (GRE-PRF) based thermometry, a standard approach to temperature mapping, was assessed at 0.5T. Experiments were performed using a 3 slice GRE acquisition at a resolution of 2x2x5mm and an update rate of 7.7s. Phantom and in-vivo measurements of the temperature stability yielded uncertainties of 0.78°C and 1.48°C respectively. Furthermore, a cooling experiment with the phantom showed excellent agreement to temperature changes simultaneously measured with a temperature probe. All results suggest that GRE-PRF thermometry is feasible at 0.5T.
Real-time automatic temperature regulation during in-vivo MRI-guided Laser-induced Thermo-Therapy (MR-LITT)
Authors: Desclides Manon , Ozenne Valéry , Bour Pierre , Faller Thibault , Machinet Guillaume , Pierre Christophe , Chemouny Stéphane , Quesson Bruno
Published: August 2024

The presented method allows to automatically adjust laser power relying on real-time rapid volumetric MR-thermometry using the proton resonance frequency (PRF) shift technique. The laser output power is regulated every second to force temperature to follow a predefined temperature-time profile using a PID controller, taking MR-temperature data as input. The proposed temperature regulation algorithm is successfully validated in vivo in the skeletal muscle of a pig.
The link between superficial and deep white matter fibers
Authors: Chamberland Maxime , Shastin Dmitri , Jones Derek , Norris David , Schilling Kurt
Published: August 2024

Here we visualized how superficial association fiber (SAF) systems relate to deep white matter bundles. We found that various shape features can be reliably extracted from those systems. The combination of superficial white matter tractography with traditional deep white matter bundles opens possibilities to study bundle-specific SAF in health and disease.
Assessing the variability of brain diffusion MRI preprocessing pipelines using a Region-of-Interest analysis
Authors: Veraart Jelle , Winzeck Stefan , Planchuelo-Gómez Álvaro , Fricke Björn , Kornaropoulos Evgenios , Merisaari Harri , Pieciak Tomasz , Zou Yukai , Descoteaux Maxime
Published: August 2024

The lack of a standardized preprocessing pipeline is a significant source of variability that might lower the reproducibility of studies, especially across sites and with incomplete description of the preprocessing workflows. We evaluate the downstream impact of variability in preprocessing workflow by quantifying the reproducibility and variability of region-of-interest (ROI) analyses. While many pipelines achieve excellent reproducibility in most ROI, we observed a large variability in performance of preprocessing workflows to the extent that some pipelines are detrimental to the data quality and reproducibility.
Micro-anisotropy and time-dependent diffusion in the mouse brain in vivo with spherical tensor encoding and the spectral principal axis system
Authors: Lasic Samo , Just Nathalie , Budde Matthew , Lundell Henrik
Published: August 2024

Accounting for time-dependent diffusion (TDD) in tensor-valued encoding is required for unbiased assessment of microscopic anisotropy (µA). We have previously introduced the spectral principle axis system (SPAS) to find linear tensor encoding (LTE) projections of spherical tensor encoding (STE) with maximum spread of sensitivity to TDD. This can be used to simultaneously achieve unbiased µA and TDD contrasts within a single protocol. Here we present results from in vivo experiments in a mouse brain. The two independent contrasts (µA- TDD) indicate consistent variations in different brain regions.
Toolkit for capillary pseudo-diffusivity Monte Carlo simulations
Authors: Powell Elizabeth , Parker Geoff , Palombo Marco
Published: August 2024

The pseudo-diffusivity effect - arising from blood flow in capillaries - is used to characterise the diffusion-weighted MRI signal at low b-values (b<200 s/mm2) in several biophysical models. We propose here a generative model for producing vascular meshes with tunable properties - such as vessel segment radius and length, and vessel volume fraction – that are compatible with common Monte Carlo diffusion simulation frameworks. Monte Carlo simulations of pseudo-diffusivity are performed, under varying conditions, by adapting the Camino simulation toolkit to include a plug flow component to spin dynamics inside the vascular mesh; the resulting signals are validated against analytical solutions.
Single Shot Diffusion Trace Spectroscopic Imaging using Radial Echo Planar Trajectories
Authors: Saucedo Andres , Thomas M. Albert
Published: August 2024

We present the first demonstration of single shot diffusion trace spectroscopic imaging using radial echo planar k-space trajectories on a clinical 3T scanner. Conventional DW-MRS requires three separate acquisitions to compute the trace apparent diffusion coefficient (ADC), whereas the single shot technique generates a trace-weighted signal in one measurement, although this has so far only been applied in NMR and to a limited extent in DW-MRI. Our preliminary results indicate good agreement with expected trace ADC values both in phantom and in healthy brain, showing a promising approach for determining the orientation-independent trace ADC value with non-Cartesian diffusion-weighted spectroscopic imaging.
Conditional VAE for Single-Voxel MRS Data Generation
Authors: van de Sande Dennis , Amirrajab Sina , Veta Mitko , Breeuwer Marcel
Published: August 2024

We propose a conditional VAE to synthesize single-voxel MRS data. This deep learning method can be used to enrich in-vivo datasets for other machine learning applications, without using any physics-based models. Our work is a proof-of-concept study which demonstrates the potential of a cVAE for MRS data generation by using a synthetic dataset of 8,000 spectra for training. We evaluate our model by performing a linear interpolation of the latent space, which shows that spectral properties are captured in the latent space, meaning that our model can learn spectral features from the data and can generate new samples.
Estimating uncertainty in diffusion MRI models using generative deep learning
Authors: Zijlstra Frank , While Peter
Published: August 2024

Uncertainty is an important aspect of fitting quantitative models to diffusion MRI data, which is often overlooked. This study presents a method for estimating uncertainty intrinsic to a model using a generative deep learning approach (Denoising Diffusion Probabilistic Models (DDPM)). We numerically validate that the approach provides accurate uncertainty estimates, and demonstrate its use in providing signal-specific uncertainty estimates. Furthermore, we show that DDPM can be used as a fitting method that estimates uncertainty, and show both ADC and IVIM fitting on an in vivo brain scan. This shows promise for DDPM, as both an investigate tool and fitting method.
Synthetic CT generation from different MR contrast inputs and evaluation of its quantitative accuracy
Authors: Kaushik Sandeep , Cozzini Cristina , Wyatt Jonathan , McCallum Hazel , Maxwell Ross , Menze Bjoern , Wiesinger Florian
Published: August 2024

MRI to synthetic CT image conversion is a problem of interest for clinical applications such as MR-radiation therapy planning, PET/MR attenuation correction, MR bone imaging. Many methods proposed for this purpose use different MR inputs. In this work, we compare the sCT generated from different 3D MR inputs, including Zero TE (ZTE), fast spin echo (CUBE), and fast spoiled gradient echo with Dixon-type fat-water separation (LAVA-Flex), using a multi-task deep learning (DL) model. We analyze the qualitative and quantitative accuracy of the generated sCT image from each input and highlight the aspects relevant for different clinical applications.
Synthesising MRIs from CTs to Improve Stroke Treatment Using Deep Learning
Authors: Wen Grace , McNaughton Jake , Chong Ben , Shim Vickie , Fernandez Justin , Holdsworth Samantha , Wang Alan
Published: August 2024

MRI holds an important role in diagnosing brain conditions, however, many patients do not receive an MRI before their diagnosis and onset of treatment. We propose to use deep learning to generate an MRI from a patient's CT and have implemented multiple models to compare their results. Using CT/MRI pairs from 181 stroke patients, we use mutiple deep learning models to generate MRI from the CT images. The model produces high quality images and accurately translates lesions onto the target image.
Elevated glutamine levels and activation of astrocytes involved in excessive excitatory neurotransmissions in autism spectrum disorder
Authors: Matsuoka Kiwamu , Oya Masaki , Kubota Manabu , Fujino Junya , Tei Shisei , Takahata Keisuke , Tagai Kenji , Yamamoto Yasuharu , Shimada Hitoshi , Seki Chie , Itahashi Takashi , Aoki Yuta , Ohta Haruhisa , Hashimoto Ryu-ichiro , Sugihara Genichi , Obata Takayuki , Zhang Ming-Rong , Suhara Tetsuya , Nakamura Motoaki , Kato Nobumasa , Takado Yuhei , Takahashi Hidehiko , Higuchi Makoto
Published: August 2024

We conducted MRS and PET to examine if enhanced excitatory tones occur and correlate with astroglial activations and/or diminished dopaminergic suppression of astrocytic functions in autism spectrum disorder (ASD) cases. MRS revealed elevated glutamate and glutamine levels associated with astroglial activation in ASD versus control anterior cingulate cortex, while there were also inverse correlations between glutamine levels and dopamine D1 receptor availability in this area of both ASD cases and controls. Hence, dopamine transmissions may repress astroglial glutamine synthesis independently of the ASD etiology, while astroglial activation in ASD could elicit augmented glutamate synthesis and consequent excitation of neuronal tones.
Diffusion Brain Imaging in Autistic Adolescents with and without Speech Impairment
Authors: Li Yan , Lafontaine Marisa , Xu Duan , Li Yi , Demopoulos Carly
Published: August 2024

In this study, we performed diffusion weighted imaging in subjects with Autism Spectrum Disorder and typically growing controls (TDC) to compare the differences in apparent diffusion coefficient (ADC) values between the two groups and examine their relationship to speech impairment.
Relationships among brain controllability, cognition, and clinical symptoms of major depressive disorder
Authors: Li Qian , Zhao Youjin , Wang Yaxuan , Long Fenghua , Gong Qiyong , Li Fei
Published: August 2024

Major depressive disorder (MDD) showed both clinical symptoms and cognitive deficits. Prior studies have typically examined either symptoms or cognition correlated with brain measures, thus causing a paucity of stable brain markers that capture the full characteristics of MDD. Sparse canonical correlation analysis was used to assess the associations between two multi-dimensional clinical measurements (symptoms and cognition) and brain controllability of MDD. Average controllability of dorsal attention network (DAN) and visual network reached high associations with clinical variates in MDD, and altered controllability of DAN in patients could induce impairment of cognitive flexibility, and thus cause severe depressed mood.
Xenon-129 Platform for Operating a T/R Coil and Phased Array at 3T
Authors: Loew Wolfgang , Van Horne Virginia , van der Meulen Peter , Dumoulin Charles
Published: August 2024

A platform was developed for 129Xe applications allowing the use of an insertable whole-body transmit/receive coil by itself or in combination with a 129Xe phased array coil. Experiments were performed in a 3T MRI scanner without modification of the scanner’s 1H body coil. 129Xe imaging was performed with a loader phantom and a xenon Boltzmann phantom in both configurations.
DOuble tuned and DOuble matched large-size loop coil (DODO) design and evaluation for 17O MRSI and 1H MRI application at 7T
Authors: Li Xin , Zhang Guangle , Zhu Wei , Zhang Xiaoliang , Zhu Xiao-Hong , Chen Wei
Published: August 2024

Current state-of-the-art RF coils for X-nuclear MRS/MRI studies typically use two separate sets of RF coils operating at the X-nuclear and proton frequencies, respectively. Here, we introduce a new coil concept whereby large-size loop coil with split capacitors which can be simultaneously tuned and matched to 17O and 1H Larmor frequencies for 7T human imaging application. Importantly, this novel coil exhibits excellent performance in proton and X-nuclear imaging, therefore, it provides a simple RF coil solution, particularly for ultrahigh field (UHF) multinuclear brain MR imaging applications.
A multi-feed, loop-dipole approach to enhance performance of multi-channel dielectric resonator antenna arrays for human brain MRI at 7T
Authors: Wenz Daniel , Dardano Thomas
Published: August 2024

The goal of this work was to demonstrate that performance of multi-channel dielectric resonator antenna arrays for brain MRI at 7T can be substantially improved using a novel multi-feed, loop-dipole coupling mechanism. Simulations were conducted for different rectangular DRA geometries and dielectric constants. Three RF feed types were investigated: loop-only, dipole-only and loop-dipole. 16-channel, loop-dipole rectangular DRA arrays provided significant gains in B1+, SAR efficiency and SNR vs. 8-channel bow-tie antenna array. The feasibility of multi-feed, loop-dipole approach was for a 24-channel DRA array was demonstrated.
Improved diagnosis performance of CAD using single-bolus quantitative stress perfusion CMR imaging: a pilot study of reproducibility
Authors: Yang Zhaoxia , Xiang Chunlin , Liu Weiyin , Wang Haonan , Huang Lu , Xia Liming
Published: August 2024

Automated CMR perfusion maps enable quantification of MBF for detection of myocardial ischaemia rapidly within a clinical workflow. Stress perfusion CMR derived quantitative parameters had good to excellent reproducibility, as well as quantitative MPR was moderately correlated with semi-quantitative MPR. Quantitative myocardial perfusion CMR provides objective indices (MBF and MPR), which could better identify disease extent and detect coronary microvascular disease than visual interpretation.
Multicenter and multi-vendor reproducibility of T1, T2 and ADC phantom data on 1.5T and 3T MRI scanners
Authors: Caroli Anna , Pasini Siria , Vandelboe Tau , Raj Anish , Garcia-Ruiz Leyre , Strittmatter Anika , Echeverria-Chasco Rebeca , Villa Giulia , Brambilla Paolo , Hansen Esben Søvsø Szocska , Ringgaard Steffen , Zoellner Frank , Fernandez-Seara Maria , Francis Susan , Laustsen Christoffer
Published: August 2024

This multicentre study aimed at assessing multi-vendor accuracy and reproducibility of typical MR biomarkers on 3T and 1.5T scanners from 5 clinical centers. MRI acquisitions were performed using NIST protocols, on Essential System and Diffusion NIST phantoms. T1 was measured by 3-parameter fitting, while T2 and ADC by mono-exponential fitting, using PhantomViewer software. When compared with reference values, non-negligible discrepancies were found across vendors, especially for T1 and T2 measurements. Reproducibility was vendor-dependent, and higher on 3T than on 1.5T scanners. ADC and T1 showed highest reproducibility. Corrections are likely needed to account for possible temperature and scanner differences.
Longitudinal stability of brain and spinal cord structural quantitative MRI measures
Authors: Boudreau Mathieu , Karakuzu Agah , Boré Arnaud , Zelenkovski Kiril , Pinsard Basile , Alonso-Ortiz Eva , Boyle Julie , Bellec Pierre , Cohen-Adad Julien
Published: August 2024

The stability of quantitative MRI measures of microstructure in the brain and spinal cord was quantified longitudinally over three years. Six healthy subjects were scanned approximately four times per year with an structural quantitative imaging protocol (T1w, T2w, T2*w, DWI, MP2RAGE, MTsat, and B1). The intra-subject COV indicated good stability of all quantitative metrics measured in the brain (< 2.3% in WM, < 3.1% in GM). The spinal cord resulted in slightly higher COVs (3.9% - 9.5%). This work is part of a larger project, the Courtois project on neural modelling (CNeuroMod).
Low-Rank Plus Sparse Accelerated Proton Resonance Frequency Shift and T1-mapping with a Dual-Echo 3D Spiral Ultra-Short Echo Time Sequence
Authors: Chen Sheng , Wang Zhixing , Gilbo Yekaterina , Sporkin Helen , Fielden Samuel , Allen Steven , Mugler John , Miller G. , Meyer Craig
Published: August 2024

Unintended heating of the skull and nearby brain tissue during MR-guided Focused Ultrasound (MRgFUS) treatment is not standardly monitored. A method for addressing this issue, which combines variable flip angle (VFA) T1 mapping and proton resonance frequency (PRF) shift thermometry based on a dual-echo 3D spiral ultra-short echo time (UTE) acquisition, was accelerated with a low-rank plus sparse model in image reconstruction and validated using retrospectively undersampled data in vitro.
Adapted rosette trajectory for functional 2D lung imaging
Authors: Frantz Hanna , Metze Patrick , Rasche Volker
Published: August 2024

Lung MRI is a steadily evolving field of research, especially concerning the evaluation of chronic lung diseases such as cystic fibrosis or COPD. The major limitation of lung MRI is the ultrashort T2* relaxation time of lung parenchyma, which demands ultrashort echo time sequences. Sufficient SNR values in the parenchyma are crucial for clinical evaluations and the assessment of physiological parameters. This abstract presents an adapted rosette trajectory for UTE imaging, yielding higher SNR per unit time in comparison to radial UTE sampling approaches.
On the elimination of the fat saturation effect in ultrashort echo-time imaging of Achilles tendons.
Authors: Latta Peter , Juras Vladimir , Starcuk Zenon , Kojan Martin , Rektor Ivan , Szomolanyi Pavol , Trattnig Siegfried
Published: August 2024

We investigated tri‑component analysis of 2D-UTE in-vivo measurements on a clinical 3T scanner and tested its ability to eliminate the effect of fat suppression on short T2* values in Achilles tendons. We found that fat-suppressed acquisition with two-component analysis provides ratios of short-T2* to long-T2* component intensities that are substantially lower (by a factor 0.95 to 0.55) than those resulting from fat-unsuppressed acquisition and tri-component fitting. Hence it seems that the combination of 2D-UTE acquisition with tri-component analysis might contribute to further improvement of T2* estimation accuracy.
Robust assessment of macromolecular fraction in muscle with differing fat fraction using ultrashort echo time magnetization transfer modeling
Authors: Jerban Saeed , Ma Yajun , Tang Qingbo , Fu Eddie , Szeverenyi Nikolaus , Jang Hyungseok , Chung Christine , Du Jiang , Chang Eric
Published: August 2024

Magnetization transfer (MT) MR imaging can indirectly characterize the spatial distribution of the relative contents of the macromolecular and water proton pools (MMF) of skeletal muscles. Fat presence in muscle has always been a source of concern in MMF calculation where some studies have reported significant underestimation of MMF for muscles with a considerable fat fraction (FF). We investigated the impact of FF on MMF in muscle/fat phantoms using an ultrashort echo time (UTE) MT model after T1 compensation. MMF demonstrated a relatively robust value with under 5% and 20% changes for FF increases up to 30 and 45%, respectively.
Ultrashort Echo Time Magnetization Transfer Imaging of Knee Cartilage After Long-Distance Running
Authors: Zhu Dantian , Fang Yijie , Wu Wenhao , Li Shaolin , Qian Long , Ma Yajun
Published: August 2024

To assess the detection of changes in the knee cartilage of amateur marathon runners before and after long-distance running. We recruited 23 amateur marathon runners prospectively. MRI scans using UTE-MT and UTE-T2* sequences. UTE-MTR and UTE-T2* were measured for knee cartilage. The UTE-MTR values in lateral tibial plateau, central medial femoral condyle, and medial tibial plateau showed a significant decrease at 2 days post-race compared to the other two time points (P < 0.05). But no significant UTE-T2* changes were found for any cartilage subregions. UTE-MTR is a promising method for the detection of dynamic changes in knee cartilage.
Assessing the clinical value of PETRA sequence for detection of subsolid pulmonary nodules：comparison with CT
Authors: Feng Hui , Yang Li , Zhang Chen , Liu Hui , Zhang Ning , Shi Gaofeng
Published: August 2024

The PETRA technique had high sensitivity for the detection of subsolid pulmonary nodules and can accurately assess their diameter and morphologic characteristics.
Myelin Content Imaging Using Ultra-Short TE MRI with Variable Flip Angles
Authors: Jung Kwan-Jin , Larsen Ryan , Rund Laurie , Steelman Andrew
Published: August 2024

Myelin content was measured from the fast T1 relaxation component using bi-exponential T1 relaxation regression. The data was collected using UTE with variable flip angles to detect short T2 signal of myelin and to avoid magnetic susceptibility corruption by T2*-based myelin contrast methods. The estimated myelin content was influenced by CSF, which was suppressed by use of the slow T1 relaxation time. The estimated myelin content was higher in white matter than other brain regions. However, the myelin content was increased in the anterior pole and low in motor areas in this in-vivo piglet data.
A feasibility study of deep learning cardiac cine comparing image quality and volumetry with the conventional ASSET cine
Authors: Okuda Shigeo , Tsukada Ryo , Arai Manabu , Motomatsu Sari , Nozaki Atsushi , Zhu Xucheng , Jinzaki Masahiro
Published: August 2024

Accelerated cardiac cine was obtained with deep learning reconstructed technique on ten patients (DL Cine). Three series of DL Cine with different parameters were acquired, including reduction factor (RF) of 12 under free breathing (FB), RF of 12 during one breathhold (R12) and RF = 9 dividing the left ventricular short axis into two slabs during each breathhold (R9). The two readers evaluate image quality (IQ) score and measure the cardiac functional parameters and compared them with the conventional ASSET cine. Although the IQ score was smaller than ones of the conventional cine, they are clinically acceptable. We found good correlations between volumetry on the conventional and DL cine.