bluuebunny/crossref_metadata_2025 huggingface dataset:
Should We Harmonize or Denoise in Diffusion MRI?
Authors: Ades-Aron Benjamin , Coelho Santiago , Veraart Jelle , Shepherd Timothy , Novikov Dmitry , Fieremans Els
Published: August 2024

To address the ongoing reproducibility crisis in quantitative diffusion MRI (dMRI), efforts are underway to harmonize and improve precision of diffusion parameter estimation. Using inter- and intra-scanner test-retest higher order dMRI, we compare the reproducibility of two popular harmonization methods, ComBat and linear-RISH, to that of denoising using MPPCA on complex-valued dMRI. We find that denoising combined with harmonization improves voxel-wise test-retest ICC by up to 60% compared to harmonization alone. Using dMRI at different voxel sizes, we find that denoising reduces the bias due to varying noise floors more accurately than harmonization. Denoising appears essential to harmonize dMRI datasets.
Chronic liver disease: The role of multiple diffusion-weighted models using the Bayesian shrinkage method for liver fibrosis assessment
Authors: Huang Jiqing , Leporq Benjamin , Beuf Olivier , Ratiney Hélène
Published: August 2024

Liver fibrosis is one of the leading features in chronic liver disease (CLD) since it conditions the prognosis and guides the treatment strategy. In this work, estimated parameters from various diffusion-weighted MRI models fitted by the Bayesian method were analyzed for the relationship with liver fibrosis through spearman’s correlation and t-test. Four parameters (Ds, σ, D*_F, Dapp) were selected for fibrosis classification and achieved the best result based on the decision tree. Our result suggested that the statistical model and a hybrid IVIM-DKI model are promising models and confirmed the confounding effect of fat for diffusivity to assess liver fibrosis.
Application of machine learning with Tract-Based Spatial Statistics in the diagnosis of pediatric autism
Authors: He Xiongpeng , Zhang Xiaoan , Zhao Xin , Sun Yongbin , Geng Pengfei , Wang Kaiyu
Published: August 2024

Early and accurate diagnosis of pediatric autism was difficult for clinicians, which hindered the timely treatment of patients. This study aimed to explore the applicability of machine learning models of diffusion kurtosis imaging (DKI) based on Tract-Based Spatial Statistics to diagnose pediatric autism. Results showed that DKI parameter was potential for differentiating early autism from the normal. And the machine learning models can be used for early detection of pediatric autism with high accuracy and sensitivity.
Restricted Water Diffusion in the Renal Cortex is Associated with Early Developmental Factors and Elevated Urinary Cytokines in Preadolescents
Authors: Michael Navin , Lu Liangjian , Ooi Delicia Shu Qin , Chan Chang-Yien , Thirumugan Kashthuri , Sadananthan Suresh Anand , Prasad Pottumarthi V. , Fortier Marielle , Loy See Ling , Hian Tan Kok , Yap Fabian , Chong Yap Seng , Godfrey Keith , Gluckman Peter , Eriksson Johan G. , Lee Yung Seng , Moritz Karen , Chan Shiao-Yng , Wlodek Mary , Velan S. Sendhil
Published: August 2024

Developmental factors that impair nephrogenesis can increase risk for chronic kidney disease (CKD). The early stages of CKD are characterized by an increased infiltration of inflammatory cells into the renal interstitium, which can restrict the molecular diffusion of water. We found that maternal gestational diabetes and preterm birth were associated with 2-fold and 4-fold higher risk of having restricted water diffusion (IVIM diffusion coefficient < 10th centile) in the renal cortex of preadolescents, respectively. Preadolescents with restricted diffusion had elevated urinary pro-inflammatory, chemotactic and pro-fibrotic cytokines, without elevations in blood markers of systemic inflammation, which was suggestive of renal inflammation.
Development of an MR Imaging Protocol for Ex-Vivo Assessment of Deceased Donor Human Kidneys
Authors: Daniel Alexander , Fawaz Sarah , Charles Philip , Elzawahry Mohamed , Grove Jane , Long David , Hunter James , Kaisar Maria , Francis Susan
Published: August 2024

Kidney transplantation is the preferred treatment for end-stage kidney disease. Donor kidney viability is currently assessed using donor age, medical history, and serum creatinine, but these have limited predictive power. As part of a study to determine if MRI can be used as an alternative, more accurate, measurement of donor kidney viability, we outline a multiparametric MRI protocol (high resolution structural scans, relaxometry (T1, T2 and T2*) mapping, susceptibility-weighted-imaging (SWI), diffusion-weighted imaging (DWI), and magnetisation transfer ratio (MTR)) to study human whole kidneys that have been declined as transplants. MRI measures will be integrated with 3D-histology and tissue proteomics datasets.
Assessment of Donor Kidney Storage Using a Porcine Model
Authors: Daniel Alexander , Elzawahry Mohamed , Charles Philip , Fawaz Sarah , Kaisar Maria , Hunter James , Francis Susan
Published: August 2024

Here, we investigate in a porcine model how MR parameters change as donor kidneys are cold stored, by studying the effect of temperature, cold ischaemia time and compare static cold storage (SCS) with hypothermic machine perfusion (HMP). Variation in relaxometry measurements with temperature has been modelled allowing the comparison of in-vivo and ex-vivo datasets, especially important when considering T1 measurements. The effects of cold ischemia time on relaxometry measures have also been quantified allowing this confounding factor to be accounted for in larger studies of human deceased donor organs. Susceptibility Weighted Imaging observed blood products in an SCS porcine kidney.
The Value of 4D Flow MRI Combined with Precontrast T1 mapping Model in Identifying High-risk Varices of Cirrhosis Patients
Authors: Li Xiaohuan , Wei Zhou , Chen Zhiyuan , Zhou Dongjing , Zhang Shuping , Huang Ruhang , Wu Yunzhu , Liu* Yupin
Published: August 2024

Noninvasive identification of high-risk varices (HRV) in cirrhosis patients is of significantly value because it could help avoid some unnecessary upper gastrointestinal endoscopy and repeat in a short time to evaluate the efficiency of non-selective beta blockers therapy. This study aims to evaluate the value of 4D flow MRI combined with precontrast T1 in identifying HRV. Our results indicated that the model including SMV forward volume, SMV maximum blood flow, precontrast liver T1 mapping, and precontrast spleen T1 mapping could effectively identify HRV of cirrhosis patients.
Association between angioarchitecture and flow parameters in ruptured and unruptured arteriovenous malformation: a pilot study by 4D flow MR
Authors: Wang Yuting , Wei Haining , Cheng Meixiong , Wang Yishuang , Wu Yunzhu , Fu Mingzhu , Li Rui
Published: August 2024

The hemodynamics of cerebral AVM likely vary with lesion angioarchitecture and the rupture status, which couldn’t be reflected by morphology-based imaging. In this pilot study, 9 patients with AVM had their complicated feeding/draining patterns visualized by 4D-flow MR. AVM tend to have heterogeneous hemodynamics even with the same Spetzler-Martin grade or similar angioarchitecture. It tends to have smaller flow of the feeding artery after rupture. AVM with deep vein drainage tends to have diffused nidus and higher wall shear stress adjacent to the nidus. Higher flow of the feeding artery was associated with higher dynamic pressure and larger nidus volume.
Interval Changes in 4D Flow-Derived Hemodynamic Parameters Stratify Type B Aortic Dissection Patients and Correlate with 2D Through-Plane Flow
Authors: Engel Josh , Kilinc Ozden , Baraboo Justin , Weiss Elizabeth , Mehta Christopher , Hoel Andrew , Malaisrie S. Chris , Markl Michael , Allen Bradley
Published: August 2024

We investigated whether changes in 4D flow-derived hemodynamic parameters stratified type B aortic dissection patients and sought to validate a 4D flow-derived 2D planar false lumen flow method. Patient scans with baseline and follow-up 4D flow at least 120 days apart were manually segmented into true and false lumens. Voxel-wise parametric maps and 2D forward and reverse flow in the descending aorta were calculated. Changes in voxel-wise hemodynamic parameters significantly correlated with aortic growth rate, with changes in false lumen reverse flow as the most robust parameter. 2D planar flow correlated with voxel-wise flow, but not aortic growth.
Ventricular flow analysis and its Association with cadiac function and structure of hypertrophic cardiomyopathy: 4D flow CMR study
Authors: Chen Yuying , Peng Yang , Feng Yu , Yuan Jun , Peng Lin , Wang Mengzhu , Jin Ning
Published: August 2024

This study aimed to investigate the potential of ventricular flow parameters derived from four‑dimensional (4D) flow cardiovascular magnetic resonance (CMR) to accurately support assessment of hypertrophic cardiomyopathy (HCM). Our results show that reduced left ventricular (LV) residual volume was associated with LV dysfunction. Higher LV retained inflow and lower delayed ejection inflow were observed in obstructive HCM patients. Flow components and kinetic energy correlated significantly with LV functional and remodelling CMR parameters. These findings suggest that 4D flow CMR may be potential method to explain the relationship between hemodynamic and pathophysiological changes in HCM.
Quantitative Mitral Valvular Regurgitation Hemodynamics Analysis Using 4D flow MRI and Echocardiography: Characteristics of Flow Momentum
Authors: Lee Jeesoo , Aratikatla Adarsh , Wu Erik , Safder Taimur , Ayuba Gloria , Thomas James , Markl Michael
Published: August 2024

Quantitative hemodynamic assessment of mitral valvular regurgitation (MVR) is critical for evaluating severity of the disease, but has been challenging with conventional echocardiographic and cardiac MRI techniques. 4D flow MRI is a promising tool that enables direct retrospective quantification of MVR hemodynamics. This study proposes a regurgitant flow momentum as a novel and reliable fluid dynamic parameter for MVR assessment using 4D flow MRI. The conservation characteristics of MVR jet flow momentum and its relationship with LA enlargement were investigated in 44 patients using 4D flow MRI and echocardiography.
Whole-brain, gray and white matter time-locked functional signal changes with simple tasks and model-free analysis
Authors: Schilling Kurt , Li Muwei , Rheault Francois , Gao Yurui , Cai Leon , Zhao Yu , Zu Zhongliang , Ding Zhaohua , Anderson Adam , Landman Bennett , Gore John
Published: August 2024

Recent studies have revealed that blood oxygenation-level dependent (BOLD) signal changes correlate with task timings throughout a majority of the cortex, challenging the idea of sparse and localized brain functions, and highlighting the pervasiveness of potential false negative fMRI findings. However, these studies have focused on gray matter only. We extend the analysis to white matter and find widespread BOLD signal changes in both white and gray matter, challenging the idea of sparse functional localization, but also the prevailing wisdom of treating white matter BOLD signals as artefacts to be removed.
Intravascular Shifted fMRI Contrast for Visual Stimulations at 3 Tesla Using DANTE-Prepared Dual-Echo EPI
Authors: Li Linqing , Chai Yuhui , Derbyshire Andy , Bandettini Peter
Published: August 2024

By using dual-echo DANTE-EPI for functional visual stimulation studies, the contrast of fractions of intravascular signal to total signal change can be generated. We show an intravascular shifted (IVS) contrast can provide simultaneous visualization of intra-extra vascular contrast under different frequencies of visual stimulations at 3T.
Cerebrovascular reactivity mapping using breath-hold BOLD-fMRI: comparison of signal models when using voxelwise lag optimization
Authors: Domingos Catarina , Esteves Inês , Fouto Ana R. , Ruiz-Tagle Amparo , Caetano Gina , Figueiredo Patrícia
Published: August 2024

We investigate the best modeling approach for mapping cerebrovascular reactivity (CVR) using voxelwise lag optimization. We considered two types of regressors (Block, PetCO2), three convolution models (no convolution, single gamma, double gamma), and a variable haemodynamic delay. We found that the CVR values obtained when using the PetCO2 signal without convolution, or convolved with a single gamma, are better than those obtained with the canonical HRF (double gamma, time-to-peak = 6s), while convolution with a canonical HRF remains the best option when using a Block design.
Cerebrovascular reactivity mapping using intermittent breath modulation: temporal resolution dependence and comparisons with CO2 inhalation
Authors: Hu Beini , Donaldson Lori , Joshi Parimal , Kartchner Lincoln , Akar Sara , Liu Peiying
Published: August 2024

Cerebrovascular reactivity (CVR) is typically measured using a carbon dioxide (CO2) stimulus combined with BOLD fMRI. However, this requires considerable subject cooperation. Although resting-state BOLD fMRI has shown its potential to generate CVR maps, the CVR results could be unreliable due to little fluctuation in some subjects’ spontaneous breathing. A new method utilizing intermittent breath modulation requires no gas-inhalation and presents higher sensitivity than resting-state CVR mapping. In this study, we investigated the effect of temporal resolution on CVR mapping obtained from breath modulation BOLD data. Our results showed that good CVR quality can be achieved with TR of 0.72s.
Slope of the spectrum of low-frequency BOLD signal relation to the connectivity strength
Authors: Nakamura Kazuhiro , Kinoshita Toshibumi
Published: August 2024

For the valuation of BOLD fluctuations, we have investigated the slope of the spectrum (SLOPE) to exclude the respiratory and heartrate fluctuation. Functional connectivity (ROI to ROI) was evaluated by Conn v19.b software. The SLOPE was evaluated in the frequency range of 0.01 – 0.1Hz. Maximum connectivity in each ROI correlated well with the value of SLOPE, but the mean connectivity did not. Therefore, it will be possible to evaluate the strength of connectivity of rs-fMRI by evaluating SLOPE.
Correlation of NAAG level in the bilateral medial prefrontal cortex with nicotine dependence score in adult cigarette smokers
Authors: Lin Liangjie , Yu Miaomiao , Xu Ke , Xu Man , Ren Jianxin , Niu Xiaoyu , Gao Xinyu , Zhang Mengzhe , Yang Zhengui , Dang Jinghan , Tao Qiuying , Han Shaoqiang , Wang Weijian , Cheng Jingliang , zhang yong
Published: August 2024

Smoking can cause cancer, heart disease, stroke, lung diseases, diabetes, and chronic obstructive pulmonary disease including emphysema and chronic bronchitis. Our study aims to explore the correlation between neurotransmitter levels in the medial prefrontal cortex of patients with nicotine addiction (NA) using the J-edited 1H MRS technique. Results showed that the N-acetylaspartylglutamate (NAAG) level in medial prefrontal of nicotine addicts was significantly correlated with the score of Fagerstrom Test for Nicotine Dependence, suggesting that the metabolism of NAAG may play a key role in nicotine dependence patients.
Super-Resolution Reconstruction of CEST images for human brain at 3T based on deep learning
Authors: Wu Sirui , Chen WenXuan , Chen Yibing , Li Zhongsen , Song Xiaolei
Published: August 2024

CEST MRI suffers from the low resolution, leading to the disability to image small structures. We proposed a new optimization process adapting the CEST data form. Based on deep learning, our optimization flow is unfolded into an unrolled network for super resolution, termed as SC-Net. Besides, we introduced ROI-based normalization loss to guarantee quantitation accuracy. Results showed that SC-Net could reconstruct high-resolution image series and quantitative maps (PSNR = 44.27dB, CNR APTw = 41.79dB), when down sampling rate = 8. And the ROI-based normalization loss could calibrate errors. In conclusion, SC-Net has the potential to image small regions and acceleration.
Investigation of deep learning reconstruction in MR imaging of pancreatic space occupying lesions
Authors: Zhang Meng , Ye Zheng , Zhang Bo , Zhang Miaoqi , Li Zhenlin
Published: August 2024

At present, the resolution of magnetic resonance image is still limited to the detection of pancreatic space occupying lesions. In this work, quantitative and qualitative analysis of pancreatic images of T1WI and DWI with built-in DL Recon was carried out. The results showed that the images obtained by the sequence with built-in DL Recon were better than the original images in terms of SNR, CNR and subjective scores. It is confirmed that deep learning reconstruction can improve image resolution and has potential in the detection of space occupying lesions in pancreas.
Deep Learning Reconstruction of Dynamic Free-breathing Fetal Heart MRI to Improve Clinical Pipeline
Authors: Prokopenko Denis , Rueckert Daniel , Hajnal Joseph
Published: August 2024

Dynamic free-breathing fetal heart MRI requires high spatial and temporal resolution, which could be reconstructed by kt-SENSE from undersampled data guided by priors of the same anatomy. Doubled acquisition time and uncontrolled fetal motion between the 2 acquisitions affects the data quality for reconstruction. We explored an alternative deep learning approach using a 3D U-Net based model with time-averaged skip connection and data consistency. Assessment of the model set a baseline for prior preconstruction and underlines important pitfalls that will drive further improvements to achieve optimal reconstruction quality.
Uncertainty Estimation for Deep Learning-Based Enhancement of Undersampled Dual-Echo Steady-State Knee MRI
Authors: Deb Ashmita , Shih Shu-Fu , Zhang Zhaohuan , Wu Holden
Published: August 2024

Deep learning (DL) based image enhancement of undersampled 3D dual-echo steady-state knee MRI can achieve faster computation times compared to compressed sensing reconstruction. However, it is hard to interpret how DL models work. This introduces the risk of DL-enhanced images containing inaccuracies without the user’s knowledge and thus confounding diagnosis. This work aimed to calculate pixel-wise uncertainty maps for DL-enhanced images by incorporating Monte Carlo Dropout into a 2D UNET to estimate epistemic uncertainty. Analysis showed that the DL-enhanced images achieved good image quality and the spatial uncertainty maps reflected errors, compared to reference images.
Accelerated MRI using Dual-domain Transformer-Based Reconstruction and Learning-based Undersampling
Authors: Hong Guan Qiu , Morley William , Wan Matthew , Wei Yuan Tao , Su Yang , Cheng Hai-Ling
Published: August 2024

Deep learning architectures such as Convolutional Neural Networks (CNNs) are widely used alongside fixed k-space undersampling for reconstructing highly undersampled MRI k-space data. However, CNN-based architectures may perform sub-optimally due to their limited ability to capture long range dependencies, and fixed undersampling patterns may not be amenable to optimal reconstruction. We propose dual-domain (image and k-space), transformer-based reconstruction architectures paired with learning-based undersampling to reconstruct undersampled k-space data. Experimental results demonstrate improved reconstruction quality compared to CNN-based (UNet) architecture across 5x to 100x acceleration factors; dual domain outperformed single domain reconstructions.
MRI Denoising with a Non-Blind Deep Complex-Valued Convolutional Neural Network
Authors: Dou Quan , Wang Zhixing , Feng Xue , Meyer Craig
Published: August 2024

Signal-to-noise ratio is crucial for MR image analysis. In this work, we proposed a non-blind complex-valued convolutional neural network for MRI denoising. Compared to existing denoising methods, the proposed method shows better performance on handling noise at different levels and on spatially variant noise.
Deep Learning Reconstruction in MRI: Comparison of Image Quality in Patients With Hepatic Malignancy
Authors: Tan Yuqi , Ye Zheng , Zhang Miaoqi , Zhang Bo , Li Zhenlin
Published: August 2024

Improving image resolution by denoising is an important research goal in MRI reconstruction. An emerging technique, deep learning reconstruction (DLR), has shown great potential in MRI denoising. In this study, we included 37 patients with pathologically diagnosed hepatic malignancy, and compared the image quality of DLR and original reconstruction regarding dual echo T1 weighted sequence, diffusion weighted imaging (DWI) and fat-suppressed T1 weighted gadolinium-enhancement. It was shown that DLR significantly improved the image quality by reducing background noise, thus making hepatic malignancy more conspicuous.
A Two-Stage Super-Resolution (TSSR) CEST Model Using Deep-Learning Reconstruction
Authors: Chen Wenxuan , Wu Sirui , Song Xiaolei
Published: August 2024

CEST is an important source of new contrast in MRI. However, it is time-consuming to obtain high-resolution CEST images. We proposed a deep learning based Two-Stage Super-Resolution (TSSR) model for CEST images. Compared with conventional SISR or MFSR models, TSSR model can effectively utilize the correlations among slices and those among saturation offsets for CEST images. We acquired brain CEST images on 14 volunteers using a 3T clinical MR scanner. Initial results suggested that the proposed TSSR model outperformed other methods for all the evaluation indicators. Our work showed the potential in reconstruction of high-resolution CEST images from low-resolution ones.
Alterations in cerebral metabolism from wakefulness to non-REM sleep
Authors: Xu Jing , Langham Michael , Rao Hengyi , Nabbout Marianne , Caporale Alessandra , Barclay Alexander , Detre John , Wehrli Felix
Published: August 2024

Sleep is fundamental to human health and function. Cerebral metabolism and blood supply are key physiological parameters of brain function, but the manner in which they change during different sleep stages is still largely unknown. In this study, we collected wakefulness and sleep data with concurrent EEG-MRI. We measured CBF, SvO2 and CMRO2 with radial OxFlow MRI. Our data show that CMRO2 is lower during non-REM sleep than during wakefulness and declines progressively as sleep stages become deeper. CBF decreases during non-REM sleep compared with wakefulness, while SvO2 gradually increases from wakefulness to slow wave sleep.
Self-Calibrated Subspace Reconstruction using Temporally Local Matrix Completion for Multidimensional MR Fingerprinting
Authors: Qiu Zhilang , Hu Siyuan , Zhao Walter , Sakaie Ken , Griswold Mark , Jones Derek , Ma Dan
Published: August 2024

We propose a new reconstruction method, named self-calibrated subspace reconstruction, for multidimensional MR fingerprinting (mdMRF), in order to correct the artifacts due to inter-shot (segment) magnitude and phase variations, without the need for extra navigator or calibration data. Different options for utilizing the low-rank property and the signal structure of mdMRF data are investigated and the optimal scheme is determined. Such that aliasing-free high-resolution image reconstruction and high-quality quantification, can be achieved.
Readout-segmented EPI using 2D spatially-selective RF excitation pulses for DWI with reduced FOV
Authors: Liu Wei , Benkert Thomas , Weiland Elisabeth
Published: August 2024

In this work, we propose to further minimize the distortion and T2* blurring in DWI by the combination of readout-segmented EPI and 2D spatially-selective RF excitation. We demonstrate its application to DWI of the temporal lobe and the uterus. The experimental results based on volunteer scans show substantial distortion reduction in the proposed method, compared to the conventional 2DRF based single-shot EPI with reduced FOV.
Unpaired Super-Resolution for Anisotropic MRI using a Gradient Mapping Adversarial Loss
Authors: Pascale Michele , Muthurangu Vivek , Tordera Javier , Steeden Jennifer
Published: August 2024

We present a novel approach to synthesise high-resolution isotropic 3D abdominal MR images, from anisotropic 3D images in an unpaired fashion. Using a modified CycleGAN architecture with a novel gradient mapping loss, we leverage disjoint patches from the high-resolution (in-plane) data of an anisotropic volume to enforce the network generator to increase the resolution of the low-resolution (through-plane) slices. This will enable accelerated whole-abdomen scanning with high-resolution isotropic images within short breath-hold times.
Age-related changes in normal adult pancreatic parenchyma: multiparametric MR imaging evaluation
Authors: Kanki Akihiko , Fukukura Yoshihiko , Sotozono Hidemitsu , Maeba Kiyoka , Higaki Atsushi , Yamamoto Akira , Tamada Tsutomu
Published: August 2024

We evaluated relationships of age and gender with shifted apparent diffusion coefficient (sADC), proton density fat fraction (PDFF), T1 relaxation time, and pancreas size using 3-T MRI. sADC increased and anterior-posterior diameter decreased with age, while T1 relaxation time and PDFF showed no correlations with age. These results would offer beneficial information regarding pancreatic imaging.
Impact of genotype on pancreatic iron overload and impaired glucose metabolism in thalassemia major.
Authors: Meloni Antonella , Pistoia Laura , Positano Vincenzo , Schicchi Nicolò , Restaino Gennaro , Barbuto Luigi , Riva Ada , Peritore Giuseppe , Tedesco Letizia , Ermini Angela , Visceglie Domenico , Bosi Costanza , Sanna Paola Maria Grazia , Cademartiri Filippo
Published: August 2024

On the basis of the type of gene mutation, three groups of patients with thalassemia major were identified: homozygotes β+, compound heterozygotes β+/β° and homozygotes β°. β0β0 patients were more likely to have pancreatic iron overload than both β+β+ patients and β0β+patients and had a double risk of alterations of glucose metabolism compared to β+β+ patients. Our findings support the knowledge of the different genotypic groups in the clinical management of β-TM patients.
Cardiac magnetic resonance in survivors of critical illness: myocardial fibrosis and dysfunction are associated with acute kidney injury
Authors: Isaak Alexander , Pomareda Isabel , Mesropyan Narine , Kravchenko Dmitrij , Bischoff Leon , Kuetting Daniel , Attenberger Ulrike , Zimmer Sebastian , Schewe Jens-Christian , Kreyer Stefan , Luetkens Julian
Published: August 2024

In this prospective study, cardiac magnetic resonance (CMR) was performed in 48 intensive care unit (ICU) survivors of acute critical illness without prior known cardiac disease. CMR revealed previously unrecognized functional abnormalities, including reduced left ventricular ejection fraction and impaired strain values, as well as evidence of focal and diffuse myocardial fibrosis represented by positive late gadolinium enhancement lesions and elevated myocardial T1 mapping and ECV. Findings were more pronounced in ICU survivors who had experienced acute kidney injury. Unrecognized fibrotic and functional myocardial alterations may be a correlate of physical impairment in post-intensive care syndrome.
Accelerated 3D free-breathing cardiac T2 mapping with tiny golden-angle hybrid trajectory and tyGRASP
Authors: Hu Jiaojiao , Zhou Jiantai , Cui Wei , Ji Yang , Nguchu Benedictor , Wang Yanming , Zhang Yong , Qiu Bensheng
Published: August 2024

Cardiac diseases are characterized by complex 3D pathological structures, 3D cardiac T2 mapping can be used as a promising tool to describe different pathologies. However, 3D T2 mapping requires a long acquisition time, which makes scanning more sensitive to motion, especially for high spatial resolution imaging. In our study, we aim to develop an accelerated and robust 3D cardiac T2 mapping technique by combining bSSFP-based hybrid radial-cartesian sampling with tiny Golden angle RAdial Sparse Parallel (tyGRASP) MRI at 3 T. The results showed that our method can generate precise T2 values with an average scan time of 6.1±1.0 min.
Default Mode Network is Not Related to Similarly Vigilance Dependent Slow Rhythms
Authors: Sharghi Vahid Khalilzad , Maltbie Eric , Pan Wen-Ju , Keilholz Shella , Gopinath Kaundinya
Published: August 2024

Several studies point to brain slow rhythms as the basis of rsfMRI signal. We recently reported that only vigilance/arousal dependent components of fMRI signal that are not specific to brain function networks (BFNs) decrease after suppression of slow rhythms, while BFNs increase in apparent strength. Default mode network (DMN) is a BFN that exhibits similar dependence on vigilance as slow rhythms. In this study, we examined the effects of slow rhythm suppression on the integrity of DMN. Our results show that DMN is not related to these rhythms and behaves just like other BFNs upon their suppression.
Adaptive Deep Learning MR Image Enhancement with Property Constrained Unrolled Network
Authors: Zhou Zechen , Chamberlain Ryan , Gulaka Praveen , Gong Enhao , Zaharchuk Greg , Shankaranarayanan Ajit
Published: August 2024

An unrolled network with explicit MR image degradation modeling and physical property constraints, termed PGDNet, is proposed for adaptive image denoising and deblurring. Preliminary evaluation demonstrated that PGDNet can achieve similar/superior image quality enhancement compared to the conventional task-specific networks, and can outperform others in joint denoising and deblurring tasks. PGDNet provides a promising solution for adaptive MR image denoising and deblurring to restore the image quality of accelerated clinical MR scans.
Deep Learning Reconstruction for 4-fold Accelerated 2DFSE Imaging: optimization of variable density undersampling
Authors: Carl Michael , Brada Rafi , Mazor Nir , Litwiller Daniel , Fung Maggie
Published: August 2024

In this work we use variable-density prospective undersampling of the phase-encode k-space lines (ky) in 2D fast spin-echo (2DFSE) followed by deep learning (DL) reconstruction. We were able to achieve an acceleration of R=4 while maintaining high image quality.
Quantitative evaluation of denoising algorithms without noise-free ground-truth data
Authors: Pfaff Laura , Wagner Fabian , Hossbach Julian , Preuhs Elisabeth , Nickel Dominik , Wuerfl Tobias , Maier Andreas
Published: August 2024

In MRI, the quantitative evaluation of denoising methods is often limited due to the lack of noise-free ground-truth data. We show how to still approximate the quality metrics mean squared error (MSE) and peak signal-to-noise-ratio (PSNR) without access to ground-truth data by using Stein’s unbiased risk estimator (SURE). The proposed method can be employed to evaluate learning- and non-learning-based denoising approaches, assuming an additive Gaussian noise model with known distribution. Our experiments further reveal that the accuracy of our evaluation method increases with the number of test samples available.
Intervertebral disc’s quantitative measurements from synthetic MR correlates with its degeneration and bone marrow fat fraction
Authors: Yuan Xiaochun , Li Ze , Fu Min , Wei Xiaochen , Chen Junrong
Published: August 2024

The conventional Pfirrmann grading currently used to assess the degree of disc degeneration is a semi-quantitative assessment criterion. And the relationship between vertebral body bone marrow fat and disc degeneration needs further clarification. In this study, quantitative synthetic MR technique as well as fat quantification MR technique are used to investigate relationship between imaging markers and degeneration levels. Results indicates intervertebral discs’ quantitative T2, T1 and PD values are significantly different among Pfirrmann grading groups. Significant negative correlations are found between Pfirrmann grading and quantitative values. T1 and PD values have weak correlation with bone marrow fat fraction.
Time-dependent diffusion in healthy adult human thigh muscle in a clinically feasible acquisition
Authors: McDowell Amy , Feiweier Thorsten , Doherty Carolynne , Wastling Stephen , Hall Matt , Clark Chris , Yousry Tarek , Reilly Mary , Thornton John
Published: August 2024

Muscle fibres are larger than axons with a complex hierarchical internal structure causing a decrease in the diffusion coefficient with diffusion time. Acquisition of larger field-of-view thigh-level images is challenged by increased distortion, higher B0 inhomogeneity, incomplete fat saturation and longer acquisition times. We optimised a protocol to study the time-dependence of diffusion indices in healthy human thigh muscle in a clinically feasible scan time. MD and FA showed strong time dependence but slight disparities from previous work in the calf, possibly due to differences in the musculature of the thigh, male/female ratio, or changes in the acquisition with optimisation.
Feasibility of Automated Segmentation of 3D Shoulder Muscle Volume via Deep Learning for Rotator Cuff Repair Patients
Authors: Yang Mingrui , Jun Bong-Jae , Owings Tammy , Polster Joshua , Winalski Carl , Derwin Kathleen , Ricchetti Eric , Li Xiaojuan
Published: August 2024

It has been shown that muscle volume and fat fraction play significant roles in musculoskeletal disorder diagnosis and prognosis. Reliable clinical tools for their evaluation, however, are currently missing. One hurdle is the challenging and laborious manual segmentation process on MR images. We proposed here a deep learning based automated tool for 3D shoulder muscle volume segmentation and achieved accurate segmentation results on clinical MR images from rotator cuff repair patients. The proposed model can be a valuable tool for shoulder muscle volume quantification and subsequent fat fraction analysis to further understand their association with clinical outcomes following shoulder procedures.
Quiet Lumbar Spine MR Imaging: Preliminary Study with Different Noise Reduction Factors
Authors: Shen Jiageng , Liu Ailian , Song Qingwei , Zhang Shuheng , Li Guobin
Published: August 2024

To evaluate the clinical value of quiet T1WI and T2WI sequences in lumbar spine imaging with different noise reduction factors (RFs).
Preliminary SNR comparison between the 11.7T Iseult RF coil and its twin coil at 7T
Authors: Amadon Alexis , Gras Vincent , Chazel Edouard , Gapais Paul-François , Mauconduit Franck , Vignaud Alexandre , Boulant Nicolas , Luong Michel
Published: August 2024

The Iseult coil, developed for MRI of the human brain at 11.7T, was presented at last year’s ISMRM meeting. Here we show SNR phantom measurements in comparison with the Avanti2 coil, a replica of the Iseult coil tuned at 300 MHz (for 7T). We derive a new power dependence of the SNR vs B0.
Exploration of the shielded-coaxial-cable coil as transceive array element for 9.4T MRI
Authors: Costa Giovanni , Paulides Margarethus , Zivkovic Irena
Published: August 2024

The recently proposed shielded-coaxial-cable (SCC) coils are intrinsically highly decoupled elements. Their suitability in multichannel transceiver arrays at ultra-high field was successfully demonstrated in 7T arrays. In this work, we investigated the single element and array properties of SCC coils at 9.4T. We simulated the SCC element and compared its properties (B1+, SAR) with those of a conventional loop coil. Subsequently, we fabricated eight SCC coils and investigated their coupling properties when placed in various configurations. SCCs at 400MHz provided similar B1+ and SAR efficiency, but generated ~25% less SAR10g,max. SCC performed well in different array configurations.
Effects of spatial resolution on brain tissue displacement estimates based on DENSE MRI at 7T
Authors: Strom Amelia , Reese Timothy , Dong Zijing , Ashenagar Baarbod , Lewis Laura , Polimeni Jonathan
Published: August 2024

Displacement Encoding with Stimulated Echoes (DENSE) MRI was used to estimate pons and midbrain tissue displacement over the cardiac cycle at 2-mm, 3-mm, and 4-mm isotropic spatial resolutions in individual subjects at 7T. Displacement estimates were largest at 2-mm resolution and matched previous reports of peak brainstem displacement over the cardiac cycle. Smaller estimates at lower resolution may be due to partial volume effects from the surrounding tissue or CSF.
Interleaved multinuclear Na+-H+-CEST-EPI metabolic MRI for simultaneously quantifying salinity and acidity
Authors: Wang Chencai , Zhong Xiaodong , Kolkovsky Alfredo , Oshima Sonoko , Khairnar Saneel , Ellingson Benjamin
Published: August 2024

Extensive evidence suggests abnormal metabolism, sodium homeostasis, and tumor acidity are interconnected and play critical roles in brain tumor formation, progression, seizure activity, treatment resistance, and immune suppression. While Na+ and advanced H+ -based MRI techniques can provide this information, Na+ and H+ images are traditionally acquired sequentially, resulting in a total scan time exceeding what is clinically reasonable. In the current study, we demonstrate utility of a new interleaved sodium gradient echo and proton-based pH-sensitive amine chemical exchange saturation transfer echoplanar imaging (Na+-GRE/H+-CEST-EPI) sequence in 15 minutes, making it feasible to study patients with brain tumors.
Signal-to-noise Ratio Enhancement of 31P Magnetic Resonance Spectroscopy using a Pre-trained Deep Learning Model
Authors: Jeon Yeong-Jae , Nam Kyung Min , Bhogal Alex , Baek Hyeon-Man
Published: August 2024

We demonstrate the feasibility of a novel denoising approach utilizing a pretrained deep learning model with multiscale local polynomial smoothing for single voxel 31P MRS data in the mice brain at 9.4T. We evaluated the low-rank denoising, one of the popular methods and the proposed method using LCModel to compare their performance. Both methods resulted in improved signal-to-noise ratio and decreased uncertainty (Cramer-Rao Lower Bounds). In this work, the suggested method outperformed in signal-to-noise ratio enhancement.
Comparison and combination of CT and MRI radiomics for early prediction of pathological response to neoadjuvant chemotherapy in gastric cancer
Authors: Li Jing , Yin Hongkun , Guo Jinxia , Qu Jinrong
Published: August 2024

To compare and combine CT and multi-parametric MRI (mp-MRI) radiomics for early prediction of pathologic response to neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC). The CT radiomics model, mp-MRI radiomics model and the combined nomogram were all associated with pathologic response. The multi-modal nomogram containing both CT and MRI radiomics scores exhibited added predictive ability and was linked to patients’ outcome. The CT and MRI radiomics model exhibited equivalent capability. This study proposed a multi-modal radiomics nomogram by incroperating concurrent CT and MRI images, which presents favorable efficacy in predicting treatment response to NAC in LAGC.
Multiparametric MRI for Staging of Bowel Inflammatory Activity in Crohn's Disease with IVIM and DCE-MRI: A Preliminary Study
Authors: Zhu Jianguo , Mao Liangqiang , Li Yan , Dou Weiqiang , Pylypenko Dmytro
Published: August 2024

In summary, our findings suggested that the combination of IVIM and DCE-MRI can be used to accurately stage CD lesions activity. However, we must acknowledge that further investigation area is warranted to validate this preliminary finding.
Clinical value of DWI combined with APT in differentiating rectal cancer from non-rectal cancer
Authors: Niu Yaxin , Lei Xiaoyan , Zhang Li , Tang Min , Ai Kai
Published: August 2024

We aimed to explore the diagnostic value of amide proton transfer-weighted (APTw) imaging combined with diffusion-weighted imaging (DWI) in differentiating rectal cancer from non-rectal cancer. The result showed that, compared with APTw or DWI (AUC=0.846 and 0.854, respectively), the highest diagnostic efficacy (AUC=0.967) was acquired using APTw combined with apparent diffusion coefficient (ADC) values.
Free-breathing, ECG-Free, Myocardial T1 Mapping: Initial Feasibility Experiments of Cardiac MR Multitasking on GE Systems
Authors: Mao Xianglun , Lee Hsu-Lei , Eyre Katerina , Delso Gaspar , Li Debiao , Christodoulou Anthony , Friedrich Matthias , Salerno Michael , Janich Martin
Published: August 2024

Quantitative imaging biomarkers such as T1 are promising for assessing focal and diffuse myocardial pathologies across different sites and scanners. However, the lack of reliable T1 mapping methods across different scanner platforms reduces patient access to robust quantitative imaging. CMR Multitasking has shown promise for non-ECG and free-breathing quantitative imaging in the heart, primarily at 3T. This work is an initial feasibility study implementing the CMR Multitasking on GE 1.5T MR scanners. Radial trajectories, self-gating/training data, and the CMR Multitasking framework together provided co-registered T1 and cine maps in a 1-min, free-breathing, non-ECG CMR scan.
Improved 3T Adiabatic T2-Prep for Cardiac T2-Mapping
Authors: Beyers Ronald , Denney Thomas
Published: August 2024

Cardiac T2-mapping allows quantifying myocardial edema resulting from events, such as, acute myocardial infarction, myocarditis and tako-tsubo cardiomyopathy. Many T2-mapping sequences exist in literature, however, most have design shortcuts that degrade their consistency, accuracy and prognostic value. We previously reported our sequence that T2-maps at end-systole (ES) for maximum wall thickness, minimized artifacts, and had four-point T2 curve-fits3. Here we present an improved 3T T2prep with four adiabatic pulses to eliminate prep inhomogeneity. This new 3T T2-mapping sequence produces T2maps at ES within 22 seconds breath hold. Pre-testing on phantoms and validation on healthy human volunteers demonstrated superior results.
MRI relaxometry mapping of hearts extracted post-mortem from acute COVID-19 patients
Authors: Ibrahim El-Sayed , Puzyrenko Andrii , Benjamin Ivor
Published: August 2024

Cardiac MRI is capable of myocardial tissue characterization using parametric mapping techniques such as T1 and T2 mappings, which are sensitive for detecting diffuse inflammation, fibrosis and edema. These techniques seem adequate for the detection of myocardial changes in COVID-19. In this study, we demonstrated the use of ex vivo MRI mapping techniques for noninvasive myocardial tissue characterization in COVID-19 patients and compared the MRI results to findings from autopsy reports. The proposed approach would allow for better understanding of COVID-19 pathophysiological effects on the myocardium through longitudinal studies that could be conducted without the need for invasive endomyocardial biopsy.
Relation of N-Terminal Pro–B-Type Natriuretic Peptide to Native T1 at Cardiac MRI
Authors: Zhang Rui , Guo Jianxin , Chen Lihong , Zhu Yi , Hao Yanhui , Ai Kai
Published: August 2024

The purpose of this study was to explore the relationship and closeness between N-Terminal pro–B-Type natriuretic peptide (NT-proBNP) and native T1, so as to predict the occurrence of heart failure(HF). This retrospective study included 43 participants. Native T1 value were measured on T1 mapping images. The result reflects native T1 values correlated positively with NT-proBNP, and had high sensitivity and specificity. Native T1 has high predictive performance for HF.
Cardiac magnetic resonance native T1 mapping assessed different CKD stages, a polit study
Authors: Chen Yating , Tian Di , Zhang Jingyu , Li Zhiyong
Published: August 2024

Chronic kidney disease (CKD) is a condition in which kidney damage or decreased kidney function persists for more than three months. Moreover, toxins inhibit myocardium leads to myocardial dysfunction and heart failure. T1 mapping, also known as longitudinal relaxation time quantitative imaging technology, is a new cardiac magnetic resonance (CMR) scanning technology, which can quantitatively evaluate myocardial T1 time and reflect changes in myocardial fibrosis. The purpose of this study is to analyze the difference and correlation between T1 value and CKD stage.
A preliminary comparison of multi-echo GraSE and T2 preparation-based myocardium T2 mapping
Authors: Wu Yang , Sun Peng , Wu Zhigang , Zhang Xiaoxiao , Zhang Jing , Wang Jiazheng
Published: August 2024

T2 mapping is a quantitative technique for measuring T2 in tissues, which is gaining popularity in the MR community, particularly for the detection of cardiac edema. There are several representative T2 mapping methods, including GraSE and T2 preparation-based schemes. However, there is still a lack of clinical experience with these T2 mapping methods. In this study, we tentatively compared the GraSE-based and T2 preparation-based methods for myocardium imaging.
Evaluation of right ventricular myocardial microcirculation in diabetes patients by using optimized intravoxel incoherent motion imaging
Authors: Li Shilan , Tao Jiahuan , Zhang Jing , Ai Kai , Liu Jiantao
Published: August 2024

Intra-voxel incoherent motion imaging (IVIM) can noninvasively and quantitatively evaluate myocardial microcirculation. At present, some scholars have demonstrated that IVIM can observe left ventricular myocardial microcirculation. However, due to the thickness of the right ventricular wall, IVIM imaging is difficult to assess it. This study proposed an optimized navigator-based and free-breathing acquisition scheme for cardiac IVIM. The results found that right ventricular myocardial microcirculation was impaired, pseudo-diffusion coefficient (Dfast) were significantly lower than healthy volunteers. It is helpful to monitor cardiovascular risk and evaluate prognosis.
Aquaporin4 inhibitor alters the apparent diffusion coefficients in mouse brain
Authors: Tsurugizawa Tomokazu , Pham Cuong , Just Anna , Le Gac Benjamin , Li Dongdong , Cauli Bruno , Komaki Yuji
Published: August 2024

The glymphatic system seems to be involved to protect the brain pathologies like Alzheimer’s disease, by the clearance of brain waste1. A previous study showed the apparent diffusion coefficients (ADC) in several brain regions were increased by aquaporin 4 (AQP4) inhibitor2. However, the time course of ADC change has not been investigated. In this study, we showed the time course of ADC change in multiple mouse brain regions following injection of the TGN020 and the effect of TGN020 on volume-dependent intrinsic optical signals in brain slices.
Revealing signatures of demyelination and axonal loss in white matter extra-axonal space using time dependent diffusion
Authors: Coronado-Leija Ricardo , Lee Hong-Hsi , Fieremans Els , Novikov Dmitry
Published: August 2024

In this work, we relate a specific feature of brain microstructure, the axon packing correlation length $$$l_c$$$, with parameters of time-dependent diffusion $$$D(t)$$$ obtained from Monte Carlo simulations. We observe that diffusion correlation length estimated from $$$D(t)$$$ shows good correspondence with $$$l_c$$$ estimated from geometries of packed disks with several densities, simple models for axon loss and demyelination, as well as for realistic substrates obtained from segmented electron microscopy.
Multidimensional diffusion MRI for monitoring radiotherapy response in human prostate cancer xenografts in mice: A longitudinal pilot study
Authors: Szczepankiewicz Filip , Safi Marcella , Ceberg Crister , Gottschalk Michael , Sereti Evangelia , Bjartell Anders , Timmermand Oskar Vilhelmsson , Knutsson Linda , Strand Sven-Erik , Strand Joanna
Published: August 2024

We use multidimensional diffusion MRI to monitor longitudinal effect of external radiotherapy in human prostate cancers in mice. The measured dimensions are “diffusion time” and “shape of the b-tensor,” enabling a probe of tissue heterogeneity, microscopic anisotropy and restriction sizes. We show that the diffusivity is highly time dependent in all tumors, and that it is significantly altered by radiotherapy, already within 1-15 days of treatment. The largest effect is seen for the diffusivity and its time dependence, but the isotropic diffusional variance is also impacted. Throughout, histology is used qualitatively to provide plausible interpretations to the observations.