bluuebunny/crossref_metadata_2025 huggingface dataset:
Diffusion of 129Xe in the lung: airspace size heterogeneity and airway connectivity assessed by filter exchange imaging
Authors: Kern Agilo , Gutberlet Marcel , Hohlfeld Jens , Wacker Frank , Vogel-Claussen Jens
Published: August 2024

A filter exchange imaging (FEXI) sequence was developed for studying dynamic changes of apparent diffusion coefficient (ADC) in hyperpolarized 129Xe MRI, thereby probing heterogeneity and connectivity of lung airspaces. The sequence was tested in healthy volunteers and patients of chronic obstructive pulmonary disease (COPD). An initial reduction of ADC after filter application was observed in all subjects. Relative reduction and recovery rate tended to be increased in COPD. Weak/moderate correlations of initial reduction and recovery rate with ADC before filter application were observed. 129Xe FEXI lung MRI is feasible and derived quantities may be useful for disease phenotyping in COPD.
Introduction of a Digital Lung Model for Validation and Refinement of Functional Lung Imaging Methods
Authors: Voskrebenzev Andreas , Gutberlet Marcel , Klimeš Filip , Wacker Frank , Vogel-Claussen Jens
Published: August 2024

Functional lung imaging with proton MRI based on acquisition of free-breathing image-time-series gained interest during the last years, as it offers potential for ventilation / perfusion measurements without requirement for high patient compliance or administration of contrast agents. Since these methods rely on indirect surrogate measurements, validation with more direct techniques (e.g. hyperpolarized MRI), is required, which is elaborate, costly and limited. In this study a framework for a digital lung model, including artificial pathologies, is introduced and tested for different ventilation and perfusion measurements. Using the proposed method important differences were found between the methods regarding ventilation defect detection.
Feasibility study of using Zero TE Sequence to evaluate pulmonary lesions: compared with CT examination
Authors: xiaoyan wang , yan zhang
Published: August 2024

Pulmonary MRI zero-echo time (ZTE) and MRI conventional sequences were compared with thoracic computed tomography (CT) to evaluate the lesions. All participants in the study underwent chest CT, ZTE, T2-TSE, T2-HASTE, and T1-VIBE scans. ZTE can be used as a supplementary examination of CT imaging. ZTE combined with T2WI can improve the detection rate and display performance of pulmonary nodules
The application of REACT based on CS-AI for abdominal vessel imaging in kidney-pancreas transplantation and diabetic nephropathy patients
Authors: Wang Hongbin , Liu Wenyun , Zhang Lei , Wang Zhuo , Qiu Ying , Sun Yuejiao , Guo Dandan , Zhu Yi
Published: August 2024

Patients with diabetic nephropathy and terminal renal insufficiency and those requiring combined kidney-pancreas transplantation should avoid using gadolinium-based contrast agents MR Angiography due to its potential nephrotoxicity. Compressed SENSE (CS) Artificial Intelligence (CS-AI) reconstructed Relaxation-Enhanced Angiography without Contrast and Triggering (REACT) sequence provides a simultaneous depiction of abdominal arterial and venous vessels. This study aims to improve the image quality of REACT sequence with CS-AI and further quantitatively evaluate the image quality in patients with diabetic nephropathy, and CS-AI reconstructed REACT sequence was first applied to image transplanted renal arteries in patients with combined kidney-pancreas transplantation.
Non-enhanced Multi-contrast 3D Whole-heart MRI for Assessment of Reperfusion Injury in Patients with Acute Myocardial Infarction
Authors: Liu Xin , Liang Lu , An Jing , Zhang Chen , Kunze Karl-Philipp , Neji Radhouene , Botnar René , Prieto Claudia , Yang Qi
Published: August 2024

Bright- and black-blood MRI sequences provide multi-contrast information for myocardial assessment in patients with acute ST-segment-elevation myocardial infarction (STEMI). A free-breathing 3D whole-heart bright-blood and black-blood phase sensitive (BOOST) inversion recovery sequence has been recently proposed for a simultaneous multi-contrast high-quality depiction of cardiac and vascular structures without contrast agent injection. In this study, we applied this sequence to visualize reperfusion injury in 10 patients with STEMI. Good agreement in microvascular obstruction (MVO) and intramyocardial hemorrhage (IMH) visualization was observed between the proposed approach and traditional 2D imaging methods in patients, promising potential integration into clinical treatment workflow.
Assessing Myocardial Microvascular Reactivity with a Novel MRI Blood-Pool Imaging Approach
Authors: Loai Sadi , Qiang Beiping , Laflamme Michael , Cheng Hai-Ling Margaret
Published: August 2024

Coronary microvascular dysfunction is driven by vascular inflammation and can go undetected for years. Current imaging diagnostics lack the ability to quantify microvascular vasomodulation, a potential biomarker for cardiac diseases dominated by microvascular disease. We propose a novel MRI approach that utilizes elevated carbon dioxide and a blood-pool contrast agent to quantify changes in microvascular blood volume. Our results confirmed hypercapnia caused strong vasodilation within female myocardium but no response in males. Transitioning from hypercapnia to room air elicited strong vasoconstriction in both sexes. This technology will be valuable for early detection of microvascular dysfunction in various diseases.
Fractal Analysis of Left Ventricular Trabeculae in HFpEF Patients with Multivessel Coronary Artery Disease
Authors: Gu Zi-Yi , Chen Wei-Bo , Wang Yong-Yi , Wu Lian-Ming
Published: August 2024

HFpEF patients with multivessel CAD have changes in myocardial trabecular complexity. The left ventricular FD obtained with fractal analysis can reflect the complexity of myocardial trabecular and has an independent predictive value for the diagnosis of HFpEF in patients with multivessel CAD. Including FD into the diagnostic model can help improve the diagnosis.
A clinical application of deep learning reconstructed LGE combined with coronary calcification scoring in coronary artery disease
Authors: Lu Xuefang , Yan Yuchen , Liu Weiyin , Liu Changsheng , Gong Wei , Wang Yan , Peng Zhoufeng , Quan Guangnan , Zha Yunfei
Published: August 2024

Preclinical disease is primarily assessed through the coronary artery calcium score (CACS) and used for risk assessment, screening CACS is a reliable indicator for the assessment of coronary artery disease in our study, FWHM analysis of PSMDEDL and PSMDEO showed moderate correlation between the percentage of enhancement area and CACS, beneficial for check-up with less imaging time and low radiation screening. This finding should be further validated in a larger sample size. Moreover, threshold techniques such as 2SD to 5SD were sensitive to signal intensity and should be concerned for analysis on deep-learning reconstructed images, especially missing detection rate.
Comparison of 17 machine-learning models derived from LGE-MRI for predicting reverse LV remodeling in patients with STEMI
Authors: Cui Jianing , Li Tao , Yue Xiuzheng , Huang Sicong , Kang Yun , Yan Fei
Published: August 2024

Radiomics is an emerging quantitative imaging method that could extract mineable high-dimensional data from medical images. We investigate the suitable models and signiﬁcant radiomics features of LGE images in participants with STEMI and assess their value in predicting r-LVR. We chose 17 classification models to analyze all the adiomics features of LGE images in participants with STEMI. Our study found that the model of extra tree classifier was manifested relatively high AUC value in predicting r-LVR. The wavelet-HHH_gldm_SmallDependenceLowGrayLevelEmphasis was relatively strong predictor of r-LVR.
Magnetic resonance multitasking T1 mapping in atrial fibrillation
Authors: Zhao Chengchen , Jin Chunna , He Xiaopeng , Meng Simin , Liu Qi , Zhang Zhongqi , Sun Jianzhong , Xiang Meixiang
Published: August 2024

CMR multitasking T1 mapping, a recently proposed free-breathing, non-ECG technique, was evaluated in atrial fibrillation patients. It demonstrated good image quality, differentiated patients from healthy participants, and correlated with important cardiac function biomarkers. It is a promising T1 mapping tool in atrial fibrillation patients.
Can Radiomics Identify Severe Right Ventricular Dilation in Patients with Repaired Tetralogy of Fallot by LV Cardiac Magnetic Resonance Images?
Authors: Peng Jo-Hua , Wu Ming-Ting , Pan Nai-Yu , Huang Teng-Yi , Liu Yi-Jui , Weng Ken-Pen , Peng Hsu-Hsia
Published: August 2024

Radiomics analysis of cardiac magnetic resonance (CMR) may provide new insights into the quantitative analysis of cardiac imaging by extracting many computational quantitative metrics. This study aimed to develop a radiomics-based classification model by left ventricular (LV) CMR images to identify repaired tetralogy of Fallot (rTOF) patients with severe right ventricular (RV) dilation. In our results, the AUC were 0.81 and 0.91 for LV radiomics and LV radiomics+LV indices models, respectively. The extracted features underlined the LV intracardiac flow alteration due to RV dilation and the potential LV remodeling in rTOF patients with severe RV dilation.
Ultra-high Moment Gold-coated Iron Particles Allows for Longitudinal Time-lapse MRI of Individual Stem Cells in the Brain
Authors: Pothayee Nikorn , Dodd Stephen , Liu Li , Zabow Gary , Koretsky Alan
Published: August 2024

In this study, gold coated microfabricated gold-coated iron particles are used for in vitro and in vivo labeling of immune cell and neural precursors, respectively for MRI. These particles have a pure iron core and protective layer of gold and exhibit extremely high magnetic moment relative to more commonly used, chemically synthesized, iron-oxide based particles. Following in situ labeling of neural precursor cells, we show that the migration of a large pool of individual cells can be visualized in time-lapse and longitudinal MRI.
Monitoring triple negative breast cancer therapy against lncRNA MANCR with MT218, a targeted MRMI contrast agent
Authors: Nicolescu Calin , Sun Da , Gao Songqi , Lu Zheng-Rong
Published: August 2024

Developing new molecular targeted therapies for triple negative breast cancer remains an obstacle. MANCR is a long noncoding RNA overexpressed in TNBC that sustains aggressive breast cancer growth. Silencing its expression with siRNA nanoparticles suppresses tumor growth, and treatment efficacy can be assessed by MRMI with a targeted contrast agent, MT218. Reduction in contrast-to-noise ratio following treatment confirmed effectiveness of siRNA therapy and allowed regular monitoring of tumor inhibition. RNA therapy shows promise as a new approach for treating aggressive breast cancer, and MRMI with the targeted contrast agent is a non-invasive imaging tool for TNBC detection and therapeutic surveillance.
Deep Learning-based Flexible Echo Time Dual-Echo Water-Fat Separation
Authors: Wu Yan , Li Zhitao , Alley Marcus , Wen Zhifei , Zhong Zheng , Zhang Fan , Pauly John , Vasanawala Shreyas
Published: August 2024

We designed a deep learning-based dual-echo water-fat separation method with capability to support flexible echo times. A densely connected hierarchical network was employed, where input included dual-echo images and echo times, and ground truth images were produced using the projected power method. The model was trained and tested using 78 contrast enhanced image sets acquired with optimal echo times, and further validated on 15 non-contrast enhanced image sets obtained with different imaging parameter values. The proposed water-fat separation method has demonstrated high accuracy when dual-echo images were acquired with optimal or non-optimal echo times.
Free-breathing T1ρ Quantification in the Pancreas
Authors: Ehler Hannah , Clarke Sharon , Williams Geoff , Rioux James
Published: August 2024

T1ρ quantification in the pancreas is largely unexplored due to the difficulty of compensating for breathing motion. In this study we demonstrate a free-breathing T1ρ technique for use in the abdomen which is able to quantify T1ρ in the pancreas without respiratory gating, through the use of golden-angle radial sampling. The technique was validated in phantoms and tested in three healthy volunteers. T1ρ values in the liver and spleen agreed with recent literature, while differences in T1ρ values in the pancreas may be related to the use of free breathing instead of respiratory gating.
Trading Streamlines in Tractography using Autoencoders (TINTA)
Authors: Legarreta Jon Haitz , Petit Laurent , Jodoin Pierre-Marc , Descoteaux Maxime
Published: August 2024

Current tractography methods have a limited ability to accurately reconstruct the long-range brain white matter fiber pathways. Local orientation propagation methods provide tractograms with a non-negligible amount of implausible streamlines. In this work, we propose an artificial intelligence model to recover long-range white matter tracks that are potentially missed in conventional streamline propagation. Our method uses the generative ability of an autoencoder to propose new, plausible streamlines that are subsequently exchanged, according to a given similarity index, with the implausible streamlines in a given tractogram. This allows to potentially improve the reliability of the reconstructed fiber pathways.
Image Quality and Quantitative Analysis of abbreviated IVIM Brain MRI With Deep Learning–Based Reconstruction
Authors: Li Qiongge , Yin Yayan , Lu Jie
Published: August 2024

Deep learning-based reconstruction may improve the image signal to noise ratio without impacting the image contrasts. Intravoxel incoherent motion (IVIM) often require multiple b values with multiple averages that give rise to prolonged scan time. In this work, deep learning reconstruction is used to reduce the overall IVIM scan time. Based on qualitative and quantitative analysis, deep learning reconstruction may significantly improve the results of IVIM and make an abbreviated IVIM feasible.
Predicting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning
Authors: Liu Li , Zhang Yue , Zhang Nan , Xiao Feng , Chen Jing , Ma Lin
Published: August 2024

In this study, we proposed a promising method to distinguish the double expression lymphoma (DEL) from the non-double expression lymphoma (non-DEL) in primary central nervous system lymphoma (PCNSL) by using multiparametric MRI-based machine learning. The results showed that clinical characteristics and MR imaging features had no significant differences in distinguishing DEL from non-DEL. However, radiomics features could differentiate the two status and the best model in this study was SVMlinear with the combined four sequence group (AUCmean = 0.89±0.04). So multiparametric MRI based machine learning is promising in predicting DEL status in PCNSL.
Convolutional Neural Network based Stack-of-Star Imaging with Noise and Artifacts Removal
Authors: Wang Xinzeng , Lee Yedaun , Lee Joonsung , Mandava Sagar , Cashen Ty , Zhu Xucheng , Guidon Arnaud
Published: August 2024

Stack of Star acquisition is one of the most frequently used non-Cartesian k-space sampling methods due to its fast speed and robustness to motion. To further reduce the scan time or increase the temporal resolution, Stack of Star is often down-sampled with fewer spokes and advanced sampling patterns, such as golden angle acquisition. However, this makes Stack of Star prone to noise and streak artifacts, limiting the in-plane resolution and degrading diagnostic quality. In this work, we evaluated a deep-learning based stack-of-star method for free-breathing abdominal imaging and it shows improved diagnostic quality.
Sex Difference of Hippocampal Subfields in First-episode Drug-naive Patients with Major Depressive Disorder
Authors: Tang Mengyue , Zhang Lianqing , Zhou Zilin , Cao Lingxiao , Gao Yingxue , Li Hailong , Hu Xinyue , Liang Kaili , Bao Weijie , Wang Yingying , Kuang Weihong , Gong Qiyong , Huang Xiaoqi
Published: August 2024

We investigated hippocampal subfields volumes in a relatively large sample of first-episode drug-naive MDD and explored sex-related effects. We used Freesurfer software to segment the hippocampus with longitudinal axis and transverse axis automatically. We found there were different alterations of hippocampus along different axis. The sex-independent decreased volume of hippocampal and its subregions along the longitudinal, while the sex specific alteration only detected in the subfields along the transverse axis. These current findings may interpretate the hippocampus appears to have functional segregation along the different axis, which may contribute to developing new diagnostic and mechanism of sex difference for MDD.
Evaluation of different multi-echo combinations on objective depression prognosis in an emotional face-matching task
Authors: Pilmeyer Jesper , Lamerichs Rolf , Ramsaransing Faroeq , Breeuwer Marcel , Zinger Svitlana
Published: August 2024

Objective prognosis of major depressive disorder (MDD) based on functional MRI (fMRI) biomarkers remains problematic due an abundance of physiological and motion confounders. Multi-echo imaging enhances the BOLD sensitivity while reducing signal loss. Here, we evaluate the effect of different multi-echo combinations on MDD symptom improvement prediction in an emotional face-matching fMRI task. We demonstrate improved signal quality and activation contrast for multi-echo combinations in the amygdala and hippocampus and predict 3-months and 6-months MDD symptom improvement with 91% and 87% accuracy, respectively. These results highlight the benefits of novel multi-echo acquisitions for prognosis in psychiatric disorders.
The Hippocampus-Amygdala Complex Show Altered Structural Covariance Properties in Never-treated Patients with First-Episode Depression
Authors: Zhang Lianqing , Hu Xinyue , Tang Mengyue , Qiu Hui , Hu Yongbo , Gao Yingxue , Li Hailong , Kuang Weihong , Huang Xiaoqi
Published: August 2024

The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder. By constructing a network based on the volumetric covariation among subfields/subregions within the hippocampus-amygdala complex, we found the topologic properties within localized network of the hippocampus-amygdala complex were disrupted in never-treated patients with first-episode depression. The current study provided the first evidence of atypical structural covariance network within the hippocampus-amygdala complex in patients with early stage of MDD, which could be a potential biomarker in the future psychoradiological practices.
Glymphatic system dysfunction in patients with major depressive disorder
Authors: Yang Shanshan , Lin Xuecong , Wen Junyan , Cui Wei , Qian Long , Cui Weiwei , Wu Ziqi , Hu Peiqian , Yang Liyang , Wen Ge
Published: August 2024

Major depressive disorder (MDD) is a severe mental sickness. Yet, its neural mechanisms remain unclear. The present study aimed to analyze the different degrees of glymphatic system activity between patients with MDD and healthy controls using diffusion tension imaging (DTI) along the perivascular space (DTI-ALPS). The results showed that the patients with MDD had glymphatic system dysfunction, which increases anxiety. Thus, the ALPS index is expected to be a biomarker for monitoring changes in glymphatic system function in MDD patients.
Effect of acute ketamine on vigilance measured by multi-echo fMRI in treatment resistant major depression
Authors: Evans Jennifer , Zarate Carlos
Published: August 2024

We investigate vigilance changes during intravenous ketamine administration in patients with treatment resistant major depression using an fMRI arousal template. There is a significant decrease in the average vigilance index after ketamine infusion as compared to placebo. The fMRI based vigilance index shows promise in detecting the rapid onset of ketamine administration effects.
Predictive diagnosis of Major Depressive Disorder using integrated NMR based metabolomics and logistic regression model approach
Authors: Tyagi Ritu , Rawat Vishwa , Hans Gagan , sharan Pratap , Kumaran S Senthil , Sharma Uma
Published: August 2024

The current diagnosis for Major Depressive disorder (MDD) is dependent on symptomatic clusters and resulting high error rates. The study identifies a panel of biomarkers using 1H NMR spectroscopy and logistic regression prediction modelling. The VIP score of >1.5 and S-plot based on OPLS-DA depicted 4 significant metabolites (phosphocreatine, phosphocholine, glycerophosphocholine and glutamine) indicating abnormalities in energy and lipid metabolism. Phosphocreatine showed the highest AUC of 0.875 with 90% sensitivity and specificity, while with a combination of 4 metabolites, the AUC increased to 0.927 with 96.3% sensitivity and 87.5% specificity, which may act as a supplementary diagnostic tool for MDD.
Altered Structural Connectivity Of Thalamocortical Connections in Major Depressive Disorder: A 7T Study
Authors: Qadi Ameen Al , Verma Gaurav , Murrough James , Balchandani Priti
Published: August 2024

This study investigated the structural integrity of thalamic nuclei and their white matter connections in the brains of patients with Major Depressive Disorder (MDD) to help elucidate MDD etiology using diffusion tractography and structural MRI at 7T. Group differences were found with decreased FA and increased MD, RD, and AD in the tracts of multiple nuclei in the MDD cohort compared to controls. There were no significant differences in the average volumes of the nuclei between groups. These results suggest aberrant axonal integrity in multiple pathways responsible for visual & auditory processing, motor function, and emotional response networks.
Quantitative Study of Brain Iron Deposition in Major Depression Disorder
Authors: Zhou Bo , Liang Wenjia , Sun Chenxi , Wang Wenjun , Dou Weiqiang , Pylypenko Dmytro , Hou Huimin , Wang Bao
Published: August 2024

The occurrence of depression may be related to the accumulation of iron in the brain. T1-weighted images were linearly registered into the QSM space, and then six regions of interest (ROIs) were obtained using the automated segmentation pipeline. Susceptibility values of major depression disorder (MDD) and healthy control (HC) groups were compared using the two-sided Student's t-test. The susceptibility of the left amygdala and right putamen in MDD patients were significantly increased, and positively correlated with the severity of depression and insomnia, respectively. The increased iron in the left amygdala may be a new biomarker for MDD.
Resting-state brain functional connectome disruptions in social anxiety disorder
Authors: Zhang Xun , Gong Qiyong
Published: August 2024

Social anxiety disorder (SAD) is a prevalent disabling psychiatric condition, for which the underlying neurobiological mechanisms remain poorly understood. Herein, we used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra- and inter-network functional network connectivity (FNC), as well as their associations with clinical characteristics and their potential diagnostic value. As a result, we observed widespread intra-/inter-network FNC abnormalities among high-order and primary perceptual RSNs in SAD, which were correlated to the symptom severity and illness duration, and allowed individual classification of SAD versus healthy controls with significant accuracy.
Scaling nuFFT Memory-Overhead Down to Zero: Computational Trade-Offs and Memory-Efficient PICS-Reconstructions with BART
Authors: Blumenthal Moritz , Holme H. Christian M. , Uecker Martin
Published: August 2024

We propose a new decomposition of the nuFFT algorithm, allowing for a zero-memory-overhead implementation of the (adjoint-)nuFFT. With one grid-sized buffer, the decomposition allows for a memory efficient nuFFT with negligible computational overhead compared to a two-fold oversampled conventional nuFFT - to the prize of less efficient parallelization on many-threads CPU systems. We reduce memory requirements of 3D non-Cartesian PICS-reconstructions in BART by a factor up to ten, allowing for GPU acceleration of reconstructions with eight coils and matrix size 256x256x256 on a 4GB consumer-level GPU.
A k-space insight of aliasing effects and their removal of SPEN MRI
Authors: Zhong Sijie , Chen Minjia , Dai Ke , Chen Hao , Frydman Lucio , Zhang Zhiyong
Published: August 2024

The reconstruction theory of Spatio-temporal encoding MRI is not complete at present. Aliasing artifacts in SPEN MRI reconstructions can be traced to image contributions corresponding to high-frequency k-space signals. The k-space picture provides the spatial displacements, phase offsets and linear amplitude modulations associated to these artifacts, as well as routes to removing these from the reconstruction results. These new ways to estimate the artifact priors were applied to reduce SPEN reconstruction artifacts on simulated, phantom and human brain MRI data.
MUSIC-MRI: unleash the resolving power of k-space beyond the Fourier transform
Authors: Sun Dongbiao , Zhuo Yan , Chen Lin , Zhang Zihao
Published: August 2024

Modern MRI reconstructs images by performing Fourier transform (FT) on k-space to decompose the signal on an orthogonal basis composed of trigonometric functions. We are inspired by the problem of estimating the Direction of Arrival in radar theory and propose a novel route for MRI reconstruction based on multiple signal classification (MUSIC). MUSIC-MRI overcomes the sidelobe problem of FT and significantly promotes the actual resolution in the meaning of full width at half maximum (FWHM). Our phantom experiments show that the FWHMs are 0.45mm by MUSIC-MRI and 1.50mm by FT, while the nominal resolution of the k-space data is 0.94mm.
Accelerating Multi-Contrast Imaging Near Metallic Implants with Variable Resolution Sampling and Joint Reconstruction
Authors: Mickevicius Nikolai , Nencka Andrew , Koch Kevin
Published: August 2024

In multi-spectral imaging near metallic implants, redundant information is present in neighboring spectral bins and contrasts due to the overlapping and smooth spectral profiles. This redundancy is exploited here to reduce scan time when multiple image contrasts are desired.
SENSE factor optimization for 2D RF based Reduced Field of View DWI on Cardiac at 3.0T
Authors: Wu Yang , Sun Peng , Wu Zhigang , Zhang Xiaoxiao , Zhang Jing , Wang Jiazheng
Published: August 2024

Diffusion MRI delivers unique information about the heart without the use of external contrast agents, Because of B0 inhomogeneity within the thorax and short transverse relaxation durations, which cause substantial distortion and signal loss, it has proven technically problematic. DWI with Zoom imaging with 2D RF pulse (iZoom) could significantly minimize distortion, but it is still vulnerable to field inhomogeneity when it is big. iZoom with SENSE could reduce distortion and signal loss even further. An in vivo research on volunteers with various SENSE factors revealed that combining iZoom with SENSE considerably improves visual quality.
Compensation for Sporadic Motion in MR Thermometry Though a Hybrid Augmented Multi-Baseline and Near-Referenceless Approach
Authors: Akbulatov Arthur , Wong Suzanne , Macsemchuk Craig , Headrick Andrew , Drake James , Waspe Adam
Published: August 2024

Magnetic resonance-guided high-intensity focused ultrasound (MRgHIFU) treatments are limited by motion artifacts introduced into MR thermometry calculations by large sporadic motions. A hybrid principal component analysis and projection onto dipole fields (PCA-PDF) motion compensation algorithm was expanded upon to include predicted motion using image augmentation techniques. When tested on MR images from a gelatin phantom being translated in the coronal plane, the improved PCA-PDF algorithm yielded a temperature standard deviation of 0.4 ± 0.1 °C, which is a 3.7 ± 0.1 °C reduction from an unmodified PCA-PDF approach, indicating that thermometry artifacts induced by motion were significantly reduced.
Estimating transcytolemmal water exchange from the Kärger model using a Bayesian method in a rat model of ischemic stroke
Authors: Ba Ruicheng , Ma Yuhui , Liu Kuiyuan , Zheng Tianshu , Li Haotian , Li Chen , Wang Xiaoli , Wu Dan
Published: August 2024

Transcytolemal water exchange can be estimated using diffusion-time-dependent diffusion kurtosis imaging acquired at long diffusion times. However, dMRI signals acquired at long diffusion times using STEAM sequences are typically noisy, and fitting of the nonlinear kurtosis model and the Kärger model accumulates fitting errors. Here, we proposed a Bayesian method for estimating transcytolemal exchange time from the Kärger model and compared accuracy and robustness with conventional least square fitting method in both simulated data and rat brain data in a model of transient middle cerebral artery occlusion. Results indicated improved fitting accuracy and robustness against noise using the Bayesian approach.
Image normalization can improve the effectiveness of radiomics model based on multiscale structural MRI for diagnosing MDD and StD in adolescents
Authors: Ma Huan , Ding Yingying , Yang Jianzhong , Li Kun , Zhang Dafu , Zhang Xiaoyong , Zhang Zhongping
Published: August 2024

We developed a radiomics classifier for MDD and StD in adolescents with multiscale structural MRI after normalization, and it had the best performance and was superior to the classifier based on conventional image indicators and unnormalized radiomics features. The AUC, sensitivity, and accuracy for discriminating MDD and HC, MDD and StD, StD and HC were 0.928, 89.2% and 90.5%, 0.821, 73.0% and 80.8%, 0.836%, 82.4% and 79.7% respectively. The high discriminant radiomics features of cuneiform lobe and cerebellum (lobule ⅵ, ⅶ-b and ⅹ, 4/5 area of cerebellar vermis) played a key role in the pathophysiological mechanism of MDD and StD.
Functional and structural brain alterations in autism spectrum disorder: A multimodal meta-analysis of neuroimaging studies
Authors: Guo Zixuan , Yan Hong , Tang Xinyue , Qian long , Wang Ying
Published: August 2024

Numerous neuroimaging studies conducted have shown functional and structural brain alterations in patients with ASD. We conducted a whole-brain voxel-wise meta-analysis to summarize previous inconsistent results by using Seed-based d Mapping software. In the present multimodal meta-analysis, functional and structural alterations in specific regions were found, which provide new insights into the quest for a neuroimaging-based marker for ASD.
Low-Loss Switches for Multinuclear MRI/S Using Stimuli-Responsive Polymer Materials
Authors: Valle Edith , Tasmim Seelay , McDougall Mary , Ware Taylor
Published: August 2024

The development of highly sensitive multinuclear RF coils for MRI/S is challenging because most current multi-tuning techniques involve the addition of lossy components. Although it is possible to optimize for a particular nucleus, usually non-1H, multinuclear coils have lower SNR than their single-tuned counterparts. We investigate a novel switching system that uses stimuli-responsive materials. The coils with the proposed switching method had a decrease of <26% in Q when compared to single-tuned coils. As a result, we demonstrated a promising alternative to traditional switching techniques.
A Low-complexity Approach to Decouple Dual-tuned RF Coil Elements in Multinuclear Receive Array Coils
Authors: Sun Chenhao , Bauer Courtney , Hou Jue , Wright Steven
Published: August 2024

This study proposes a novel low-complexity decoupling approach for multi-nuclei receive array coil design. Instead of using narrowband LC networks and isolation preamplifiers, a preamplifier with high input impedance can be used to decouple receive coils while maintaining most SNR. A broadband impedance matching network consist of LCC multi-tuned circuit and transformer was developed to interface the coil with a high Z preamplifier. The proposed setup has achieved more than 15dB of decoupling over a range of 25MHz. The prototype simultaneously yielded 73.6% and 91.9% of SNR at 2H and 23Na when compared to the conventional single-tuned preamplifier decoupling methods.
A 16-Channel Proton/Sodium Transmit/Receive Array Design for 7 Tesla Head Imaging
Authors: Wu Menglu , Clément Jérémie , Vliem Jules , Leitão David , Tomi-Tricot Raphael , Ipek Özlem
Published: August 2024

7T MRI has great potential to enhance the sensitivity to 23Na, allowing access to functional and anatomical information when combined with proton imaging. We introduce an RF coil design of a 16-channel Tx/Rx head array composed of eight proton dipoles and eight overlapping sodium loops for 7T. The initial results were acquired on phantoms with comparable performance for both nuclei, and a 40% B1+ gain was reported in sodium channels against the commercial coil. All elements were well-decoupled (-7.2dB to -36dB) without implementation of multiple layers or RF shield, paving the way for future simultaneous 1H/23Na MRI acquisition at 7T.
Repeatability of ProMyoT1: an open-source inversion recovery myocardial T1 mapping sequence for fast prototyping
Authors: Gaspar Andreia , Silva Nuno , Ferreira António , Nunes Rita
Published: August 2024

The open-source method Prototype of Myocardial T1 mapping (ProMyoT1) created with Pulseq was tested in vivo in healthy subjects to evaluate its repeatability and compare its performance with that of the clinical MOLLI method. ProMyoT1 provided myocardium T1 values similar to those obtained with MOLLI. The precision was better for MOLLI, but the repeatability measures (Coefficient of Variation and Repeatability Coefficient) were similar in both methods. The developed ProMyoT1 method was shown to be reliable and should improve the accessibility to T1 mapping, while also enabling fast sequence prototyping so that further improvements can easily be tested.
Inter-site variability observed in R1 maps of the brain generated from two-point inversion-recovery MRI
Authors: Heo Stella , Rowley Christopher , Tardif Christine , Bock Nicholas
Published: August 2024

The longitudinal relaxation rate (R1) is deemed to be a suitable quantitative imaging metric for multi-site investigations as it describes a quantitative property of the tissue that can be measured, reproduced, and compared across sites when differences in hardware and acquisition settings are accounted for. Here, we present inter- and intra-vendor variability observed in whole-brain R1 maps generated from two-point inversion-recovery MRI data after accounting for variations in pulse sequences and B1+ field maps. We posit that this inter-site variability may be due to differential intensity scaling applied at acquisition and suggest a potential correction method using site-specific scaling factors.
Test-Retest Repeatability of Smart BrainQuant (STAGE) of the healthy brain at 1.5T
Authors: Ling Yuting , Zhang Jianjun , Xiang Jiangwei , Wang Yu , Miao Zhenzhuang , Zhang Xingxing , Liang Xiaoyun , Huang Feng
Published: August 2024

Smart BrainQuant, adapted from strategically acquired gradient echo (STAGE) method, is capable to provide 10 multi-contrast and multi-quantitative images with high image quality in 4:21 minutes at 1.5T. A preclinical validation work was introduced in this study with the aim to assess the test-retest repeatability of T1, proton spin density (PSD), susceptibility, and R2* by recruiting 18 healthy volunteers. Coefficient of variation of T1, PSD, and R2* ranged from 3.3% to 4.1%. Bland-Altman demonstrated that the line of equality is in the 95% confidence interval (CI) of the mean difference for the four maps.
Phantom T1rho and T2 relaxation times demonstrate good repeatability across sequences and scanner position
Authors: Vainberg Yael , Mazzoli Valentina , Kogan Feliks
Published: August 2024

T2 and T1rho repeatability is essential for evaluating the small changes that occur during early osteoarthritis disease progression. In this study, we acquired phantom data on T2 and T1rho relaxation times across 6 time points as well as 3 distinct locations along the scanner for T2/T1rho 3D MAPSS and 3D qDESS with varying resolution for T2 mapping. We observed repeatability of the 4 quantitative MRI sequences that were well within the QIBA benchmark for phantom scans of 4-5%. Further, our data suggests that phantom positioning within the scanner bore did not affect repeatability or quantitative values.
Quantification of Hemosiderin Deposition in Hemophilic Arthropathy Using Ultrashort Echo Time Quantitative Susceptibility Mapping (UTE-QSM)
Authors: Sedaghat Sam , Luck James , von Drygalski Annette , Ball Scott , Shin Soo Hyun , Fu Eddie , Chang Eric , Du Jiang , Jang Hyungseok
Published: August 2024

We investigated the quantitative capability of the UTE-QSM technique in the assessment of hemosiderin compared to histology. UTE-QSM and histology were performed in knee synovium tissues from hemophilia patients to visualize hemosiderin. The susceptibility maps from UTE-QSM showed a visually high similarity to the corresponding histological findings for all tissues. There was a significant difference in tissues with low and high iron load (p<0.001) in UTE-QSM. The susceptibility values on UTE-QSM showed a significant strong positive correlation to the blue signal in histology (R=0.908; p<0.001). We showed that UTE-QSM has excellent performance for detecting and quantifying hemosiderin in HA.
Cardiac Magnetic Resonance Feature Tracking for Detection of Acute Cardiac Allograft Rejection after Heart Transplantation
Authors: Li Yunling , Yang Kai , Chen Xiuyu , Lian Jianxiu , Sun Yong , Zhao Shihua
Published: August 2024

Acute cardiac allograft rejection is a major cause of morbidity and mortality after heart transplantation. Reliable non-invasive diagnostic techniques for acute cardiac allograft rejection (ACAR) are unavailable. Cardiac magnetic resonance feature tracking can detect global functional changes in the longitudinal, radial, and circumferential directions during the early stages of graft rejection. We found that cardiac magnetic resonance feature tracking (CMR-FT)-derived global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS) are safe, noninvasive, and gadolinium contrast-free parameters for ACAR diagnosis. CMR-FT may provide a method that can reduce the dependency on invasive EMBs after heart transplantation.
DeepCardioPlanner: Deep Learning-based tool for automatic CMR planning
Authors: Osório Pedro , Henningsson Markus , Herrero Alberto , Nunes Rita , Correia Teresa
Published: August 2024

Cardiac Magnetic Resonance (CMR) is a powerful technique which can be used to perform a comprehensive cardiac examination. However, its adoption is often limited to specialised centres, in part due to the need for highly trained operators to perform the complex procedures of determining the 4 standard cardiac planes: 2-, 3-, 4-chamber and short axis views. To automate view planning, a deep learning-based tool (DeepCardioPlanner) has been proposed to regress the view defining vectors from a rapidly acquired 3D image. It successfully takes advantage of multi-objective learning to allow accurate, fast and reproducible view prescriptions without any operator input.
EMPIRE: Elastographic Magnetization Prepared Imaging with Rapid Encoding
Authors: Cerjanic Alex , Diano Alexa , McGarry Matthew , Johnson Curtis
Published: August 2024

This study demonstrates the use of magnetization preparation for MR elastography in combination with a 3D GRE stack of spirals pulse sequence. By decoupling the motion encoding from the readouts, rapid encoding strategies, such as 3D GRE, can be used. MRE images, displacement, and inverted elastograms are obtained on in vivo human brain. 3D GRE readouts with EMPIRE motion encoding can acquire a complete MRE dataset 33% faster than 2D SE-EPI with similar parallel imaging acceleration factors.
New biomaterial for 3D cell modeling and NMR analysis: low signal interference and high diffusion for robust metabolic studies in-vitro
Authors: Gómez Alba Herrero , Azagra Marc , Rius Irene Marco
Published: August 2024

Due to its non-invasive nature, NMR has become a pillar as a diagnostic technique, as well as a support for biochemical assays and disease tracking both in vivo and in-vitro. However, due to its magnetic susceptibility, some of the materials used for tissue engineering and 3D cell modeling are incompatible with the technique, interfering with data acquisition and reducing its applications in-vitro. We developed a cryogel that could help bridge this gap between NMR and tissue engineering.
Multi-orientation ZOOMit diffusion-weighted imaging in the preoperative T staging of gastric cancer
Authors: Xu Wei-Yue , Li Qiong , Hou Ya-Jun , Hsu Yi-Cheng , Benkert Thomas , Zhang Yu-Dong , Liu Xi-Sheng
Published: August 2024

Magnetic resonance imaging has been demonstrated to be a useful tool in the preoperative diagnosis of gastric cancer. With improved imaging quality and flexible imaging orientation, ZOOMit diffusion-weighted imaging (DWI) is attracting attention in gastric tumor imaging. The stomach is a hollow organ with variable morphology. Thus, multi-orientation ZOOMit DWI imaging provides a complete view of the lesion compared with axial DWI, thus leading to more accurate preoperative staging in treatment strategy determination.
Soft-Tissue Sarcomas demonstrate Fractional Anisotropy in Diffusion Tensor Imaging and Fractional Anisotropy Values Change After Treatment
Authors: Thrussell Imogen , Winfield Jessica , Usman Sadiq , Newman Jennifer , Hopkinson Georgina , Zaidi Shane , Miah Aisha , Messiou Christina , Blackledge Matthew
Published: August 2024

In previous studies average values of Apparent Diffusion Coefficient (ADC) have been shown to change significantly after radiotherapy in Soft-Tissue Sarcomas (STS). In this study we evaluate the Fractional Anisotropy (FA) of STS before and after treatment and demonstrate that (i) tumours can exhibit significant diffusion anisotropy, and (ii) changes in FA are inversely correlated with ADC change. Diffusion-Tensor Imaging (DTI) may therefore provide important microstructural information when interpreting change in STS after radiotherapy, and that diffusion anisotropy should be accounted for when optimising diffusion-weighted imaging (DWI) protocols for STS.
Does MADI Detect Temporal Brain Metabolic Activity Changes?
Authors: Pike Martin , Li Xin , Baetscher Eric , Barbara Thomas , Sammi Manoj , Stevens Alexander , Springer Charles
Published: August 2024

Metabolic Activity Diffusion Imaging [MADI] maps on-going sodium pump metabolic flux. Here, we investigate the question as to whether MADI can detect temporal changes of this activity in sequential acquisitions from the healthy human brain.
Evaluating different k-space undersampling schemes with iterative and deep learning image reconstruction for fast multi-parameter mapping
Authors: Podranski Kornelius , Pine Kerrin , Colnaghi Timoteo , Marek Andreas , Scheibe Patrick , Scherf Nico , Weiskopf Nikolaus
Published: August 2024

Approaches for accelerating multi-echo gradient echo (ME-GRE) acquisitions as a basis for multi-parameter mapping (MPM) were explored. Fully sampled ME-GRE data were retrospectively undersampled to equispaced Cartesian, CAIPIRINHA and Poisson disc patterns. Echoes were jointly reconstructed with the iterative ENLIVE algorithm and the machine learning/artificial intelligence adapted DeepcomplexMRI (DCMRI) approach. The approaches result in comparable peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), but show different types and different levels of artifacts. The DCMRI approach promises fast reconstruction and flexibility in the choice of undersampling patterns for ME-GRE imaging in the future.
Static and Dynamic Alteration of Intrinsic Brain Activity might improve MRI-negative Temporal Lobe Epilepsy Diagnosis and Lateralization
Authors: ru song cheng , liang cheng jing
Published: August 2024

We comprehensively explored the potential intrinsic brain activity (IBA) abnormalities affected by MRI-negative temporal lobe epilepsy (TLE) based on six temporal dynamic indicators (dALFF, dfALFF, dReHo, dDC, dGSCorr, dVMHC) and their corresponding static indicators, the results revealed that the abnormally activated brain regions overlap markedly, including ①decreased fALFF, Reho, DC, VMHC, dfALFF, dReHo in the temporal neocortex with ipsilateral superiority. ②decreased dGSCorr and dVMHC in the occipital lobe. Moreover, many IBA indicators significantly correlated with the epilepsy duration or cognitive scale scores. The dDC, fALFF and DC showed significant discrimination ability. The ReHo and fALFF demonstrated lateralization significance.
Quantitative Comparison of 1.5T and 3.0T 1H Magnetic Resonance Spectroscopy for Temporal Lobe Epilepsy
Authors: Qu Biao , Tan Hejuan , Xiao Min , Liu Dongbao , Wang Shijin , Zhang Yiwen , Chen Runhan , Zheng Gaofeng , Yang Yonggui , Yan Gen , Qu Xiaobo
Published: August 2024

The study explored the diagnostic utility of different field strengths for the temporal lobe epilepsy (TLE) with 1H magnetic resonance spectroscopy (1H-MRS) which could be utilized to examine the concentrations of related metabolites. Four ratios of brain metabolites, including NAA/Cr, NAA/Cho, NAA/(Cho+Cr) and Cho/Cr were introduced to four control experiments with the Mann-Whitney U Test, the power analysis and the Paired T-Test adopted. Results suggested that 1.5T and 3.0T scanners might have comparable potential in distinguishing TLEs from HCs when 1H-MRS was used to identify patients with TLE.
Gradient Non-Linearity Calibration for Improved Spatial Position Accuracy with a High-Performance Gradient Using a Fiducial Phantom
Authors: Abad Nastaren , Fiveland Eric , Lee Seung-Kyun , Hua Yihe , Tao Shengzhen , Trazasko Joshua , Bernstein Matt , Foo Thomas
Published: August 2024

Spatial encoding in MR-systems is subject to gradient non-linearity. If ignored or inadequately calibrated during system install, non-linear gradient fields manifest as spatial distortions impacting image quality, diminish accuracy for applications requiring MR guided intervention and introduce systematic errors in quantitative imaging such as diffusion MRI. High-performance, high-efficiency gradient systems, such as MAGNUS, require accurate calibration for imaging precision. In this study, a fiducial phantom was utilized to characterize and correct for residual distortions after standard gradient calibrations. Results highlight that distortion due to gradient non-linearity can be successfully reduced by phantom-based calibration for improved accuracy inline with QC metrics.
UV-Curable Hydrogels for Quantitative T1/T2 in Slice Phantoms
Authors: Tung Szu Ting , Huey Jolene , Lustig Michael , Arias Ana , Flynn Anita
Published: August 2024

We developed a high-volume, low error UV-curable hydrogel formation process that can target specific T1 and T2 parameters. Our process relies on the polymerization of water-soluble photoinitiator TPO-Lithium in acrylamide (monomer), polyethylene-glycol-diacrylate (crosslinker), de-ionized (DI) water, and paramagnetic ions. We characterize the linearizing effect of varying paramagnetic ion concentrations in determining T1 and T2 values, and present an application to construct a quantitative anatomy-mimicking brain slice phantom containing UV gels.