bluuebunny/crossref_metadata_2025 huggingface dataset:
XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI Reconstruction
Authors: Zhou Yirong , Qian Chen , Guo Yi , Wang Zi , Wang Jian , Qu Biao , Guo Di , You Yongfu , Qu Xiaobo
Published: August 2023

Machine learning and artificial intelligence have shown remarkable performance in accelerated magnetic resonance imaging (MRI). Cloud computing technologies have great advantages in building an easily accessible platform to deploy advanced algorithms. In this work, we develop a high-performance medical intelligence cloud computing platform (XCloud-pFISTA) to reconstruct MRI images from undersampled k-space data. Two state-of-the-art approaches of the Projected Fast Iterative Soft-Thresholding Algorithm (pFISTA) family have been successfully implemented on the cloud. This work can be considered as a good example of cloud-based medical image reconstruction and may benefit the future development of integrated reconstruction and online diagnosis system.
Rapid 3D MR cholangiopancreatography in a breath-hold using deep learning constrained Compressed SENSE reconstruction
Authors: Zhang Yu , Xia Chunchao , Zhang Xiaoyong , Li Zhenlin
Published: August 2023

In this work, we aimed to use a deep learning based Compressed SENSE reconstruction algorithm, presented here as Artificial Intelligence Compressed-SENSE (AI-CS), to improve image quality of 3D magnetic resonance cholangiopancreatography (MRCP) in a breath hold (BH). The results demonstrated that AI-CS BH MRCP can enable improved image quality and show great visibility of small ductal structures than other previous methods.
Multi-Adaptive Convolutional Neural Network Reconstruction (MA-CNNR) for Parallel Imaging at 1.5T Brain Images
Authors: Kaneko Yukio , Suzuki Atsuro , Amemiya Tomoki , Ishihara Chizue , Bito Yoshitaka , Shirai Toru
Published: August 2023

Recently, deep learning techniques for high-speed or high-quality imaging in MRI have been reported. However, deep learning techniques for the inhomogeneous spatial distribution of noise caused by parallel imaging have not been fully established. In this study, “Multi-Adaptive Convolutional Neural Network Reconstruction (MA-CNNR)” has been investigated. A noisy image was segmented into four regions by g-factor map, and different optimized CNNs were selected for each region. A denoised image was generated by combining the four denoised regions. The denoising effect was evaluated for 1.5T brain images, and it was confirmed that MA-CNNR can reduce the inhomogeneous noise in parallel imaging.
Accelerate Pulmonary Hyperpolarized Gas MRI with Multi-Task Learning
Authors: Li Zimeng , Xiao Sa , Wang Cheng , Ye Chaohui , Zhou Xin
Published: August 2023

Hyperpolarized gas MRI is a non-invasive and non-radiation imaging modality that can provide lung structure and function information. However, the problem of long imaging time limits its clinical application. Deep learning-based methods have shown great potential to accelerate MRI. In this work, we proposed a multi-task network to perform pulmonary hyperpolarized gas MRI reconstruction and lung region segmentation simultaneously, which allows sharing representations between two tasks. The results show that the proposed multi-task network has better reconstruction performance, stronger robustness and fewer model parameters than the comparison method.
Susceptibility Weighted MRI for Predicting Critical Developmental Regulatory S100 Proteins in Meningiomas at 3T
Authors: Azamat Sena , Buz-Yaluğ Buse , Baş Abdullah , Ozcan Alpay , Danyeli Ayça Ersen , Tan Kubra , Can Ozge , Pamir Necmettin , Dinçer Alp , Ozduman Koray , Ozturk-Isik Esin
Published: August 2023

Meningiomas are the most common primary intracranial tumors in adults. S100 protein expression (S100+) in meningiomas is a marker of neural crest origin. Eighty-four patients with preoperative MRI were included in this IRB approved study. The whole tumor volumes were segmented from FLAIR, followed by co-registration onto SWI. Supervised machine and deep learning methods were employed to categorize meningiomas into S100+ and S100- groups based on SWI histogram values. Ensemble bagged trees resulted in an accuracy of 85.7% (sensitivity=87.0 % and specificity=84.4 %), while a Resnet 50 architecture had 70.5% accuracy (sensitivity=80%, specificity=57.1%) for predicting S100 protein expression in meningiomas.
Vascular Heterogeneity Model-based Deep Learning Reconstruction for High-Definition Dynamic Contrast Enhanced MRI
Authors: Nguyen Nhan , Park Joon Sik , Choi Seung , Yoo Roh-Eul , Park Jaeseok
Published: August 2023

To take characterization of various vascular contrast dynamics into account, in this work we propose a novel, vascular heterogeneity model based deep learning reconstruction from highly undersampled data for high-definition whole brain DCE MRI. To this end, we introduce a new, vascular contrast dynamics (VCD) weighted deep attention neural network (VACAN) consisting of: 1) a vascular adaptive attention 3D U-Net, 2) a multilayered non-negative matrix factorization (NMF) layer, and 3) a data consistency layer. Experimental studies are performed using highly undersampled patient data to validate the effectiveness of the proposed VACAN against conventional 3D U-Net.
Accelerated VCC-Wave MR Imaging Using Deep Generative Models
Authors: Liu Congcong , Cui Zhuoxu , Qiu Zhilang , Li Haoxiang , Guo Yifan , Cao Chentao , Liu Xin , Zheng Hairong , Liang Dong , Wang Haifeng
Published: August 2023

CSM or kernel needs to be estimated in conventional parallel image, which is very time-consuming and the estimation process may be inaccurate. Here, wave coding model based on virtual conjugate coil using deep generative modes (WV-DGM) is proposed for the virtual conjugate coil (VCC) extended model based on wave coding. WV-DGM combined with deep DGM without training can realize advantages of wave encoding and introduce extra phase to reduce the ill-condition of the model via VCC. The results in vivo demonstrated that WV-DGM can achieve better quality compared with conventional SENSE while 10x times used to estimate CSM is reduced.
Calibrationless Reconstruction of Uniformly Undersampled
Multi-channel MR data with Deep learning Estimation of ESPIRiT Maps
Authors: Zhang Junhao , Yi Zheyuan , Zhao Yujiao , Xiao Linfang , Hu Jiahao , Man Christopher , Zhao Yujiao , Wu Ed
Published: August 2023

Conventional ESPIRiT reconstruction requires accurate estimation of ESPIRiT maps from autocalibration samples or signals but acquiring such autocalibration signals takes time and may not be straightforward in some situations. This study aims to deploy deep learning to directly estimate ESPIRiT maps from uniformly undersampled multi-channel 2D MR data that contain no autocalibration signals. Results show that the estimated ESPIRiT maps could be reliably obtained and they could be used for ESPIRiT and SENSE reconstruction with high acceleration.
Comparison of multi-echo MRS and radial TSE sequences in patients with HCC
Authors: li Chenhui , Long Liling , Zhang Huiting , Han Fei
Published: August 2023

Multi-echo MRS (HISTO) and a novel radial TSE (RadTSE) sequence were compared in patients with hepatic cellular cancer (HCC). Results showed that T2 from RadTSE with fat saturation had a good consistency with that from HISTO. The difference in T2 between RadTSE without and with FS showed excellent correlation with fat fraction from HISTO. Radial TSE and multi-echo MRS sequences may have similar value in terms of quantitative imaging of the liver.
3D diffusion MRI with Twin-navigator-based GRASE for comparison of fiber-tracking using 2D and 3D sequences in human whole brain
Authors: Li Haotian , Hsu Yi-Cheng , Zu Tao , Sun Yi , Zhang Yi , Wu Dan
Published: August 2023

3D pulse sequences enable high-resolution acquisition with high SNR and ideal slice profiles, which however, is particularly difficult for diffusion MRI (dMRI) due to the additional phase errors from diffusion encoding. Here we proposed a twin-navigator based 3D diffusion-weighted gradient spin-echo (DW-GRASE) sequence to correct the phase errors between shots for human whole-brain acquisition. Moreover, we tested whether acquisitions may impact the fiber-tracking results by comparing the 3D-GRASE with 2D-EPI using the fixel-based analysis, which indicated a significant difference between the 3D and 2D sequences in several microstructural parameters of the long cerebrospinal tract and splenium of corpus callous.
Improved fat suppression in diffusion MRI using eddy current compensation gradient
Authors: Liu Wei , Koehler Michael , Carinci Flavio , Kettinger Adam , Feiweier Thorsten , Zhou Kun , Zeller Mario
Published: August 2023

In this work, we propose to compensate the residual eddy current field caused by diffusion gradients at the time when chemically selective fat suppression gets applied with an additional gradient applied after the EPI readout. Using an analytic solution, the amplitude of the eddy currents can be cancelled under certain assumptions. The experimental results based on a volunteer scan demonstrate improved fat suppression in diffusion MRI with the proposed method.
Banding artifacts reduction for brachial plexus (BP) imaging Using RF phase cycling balanced FFE technique combined with compressed SENSE
Authors: Wu Qiaoling , Hu Geli
Published: August 2023

Banding artifacts are frequently observed in brachial plexus imaging, particularly within the spinal canal, with the balanced FFE sequence (b-FFE) at 3.0T due to increased influence of higher magnetic field inhomogeneity compared with clinical 1.5T. In this work we propose using a RF phase cycling technique with b-FFE (namely b-FFE-XD) to reduce the banding artifacts in clinical. This design RF phase limits the intravoxel dephasing of scan object voxels, therefore the artifacts caused by field inhomogeneity decrease. Meanwhile, the compressed SENSE technique was adopted to reduce the scan time. Results demonstrated successful removal of banding artifacts with the proposed technique.
High efficient Bloch simulation of MRI sequences based on deep learning
Authors: Huang Haitao , Yang Qinqin , Wu Zhigang , Bao Jianfeng , Cheng Jingliang , Cai Shuhui , Cai Congbo
Published: August 2023

To overcome the difficulty of obtaining a large number of real training samples, the utilization of synthetic training samples based on Bloch simulation has become more and more popular in deep learning based MRI reconstruction. However, a large amount of Bloch simulation is usually very time-consuming even with the help of GPU. In this study, a simulation network that receives sequence parameters and contrast templates, was proposed to simulate MR images from different imaging sequences. The reliability and flexibility of the proposed method were verified by distortion correction for GRE-EPI images and T2 maps obtained with overlapping-echo detachment planar imaging.
Transformer based Self-supervised learning for content-based image retrieval
Authors: Anand Deepa , Bhushan Chitresh , Shanbhag Dattesh
Published: August 2023

Diversity in training data encompassing variety of patient conditions is a recipe for the success of medical models based on DL. Ensuring diverse patient conditions is often impeded by the necessity to manually identify and include such cases, which is time-consuming and expensive. Here we propose a method of retrieving images similar to a handful of example images based on features learnt using self-supervised learning. We demonstrate the features learnt using SSL on transformer based networks are excellent feature learners which not only eliminates the need for annotation but enable accurate KNN based image retrieval matching the desired patient conditions.
High-quality Reconstruction of Volumetric Diffusion Kurtosis Metrics via Residual Learning Network and Perceptual Loss
Authors: Feng Min , Tong Qiqi , Li Yingying , Dong Bo , Zhong JIanhui , He Hongjian
Published: August 2023

This study proposed a novel 3D residual network to learn end-to-end reconstruction from as few as eight DWIs to volumetric DKI parameters. The weighted loss function combining perceptual loss is utilized, which helps the network capture in-depth feature of DKI parameters. The results show that our method achieves superior performance over state-of-the-art methods for providing accurate DKI parameters as well as preserves rich textural details and improves the visual quality of reconstructions.
Rapid reconstruction of Blip up-down circular EPI (BUDA-cEPI) for distortion-free dMRI using an Unrolled Network with U-Net as Priors
Authors: Yarach Uten , Chatnuntawech Itthi , Liao Congyu , Teerapittayanon Surat , Iyer Siddharth Srinivasan , Kim Tae Hyung , Cho Jaejin , Bilgic Berkin , Hu Yuxin , Hargreaves Brian , Setsompop Kawin
Published: August 2023

Blip-up and Blip-down EPI (BUDA) is a rapid, distortion-free imaging method for diffusion-imaging and quantitative-imaging. Recently, we developed BUDA-circular-EPI (BUDA-cEPI) to shorten the readout-train and reduce T2* blurring for high-resolution applications. In this work, we further improve encoding efficiency of BUDA-cEPI by leveraging partial-Fourier in both phase-encode and readout directions, where complimentary conjugate k-space information from the blip-up and blip-down EPI-shots and S-LORAKS constraint are used to effectively fill-out missing k-space. While effective, S-LORAKS is computationally expensive. To enable clinical deployment, we also proposed a machine-learning reconstruction derived from RUN-UP (unrolled K-I network) that accelerates reconstruction by >300x.
Echo time optimization for in-vivo measurement of unsaturated lipid protons using J-difference-edited MRS.
Authors: Lin Dingyi , Hsu Yi-Cheng , Li Hong , Zhou Jiaqiang , Zheng Fenping , Wang Min
Published: August 2023

In this study, J-difference editing was applied to unsaturated lipid protons. Density-matrix simulations were devised to demonstrate the TE-dependent signal evolution of J-coupled protons. Phantom and in-vivo experiments on human muscles were performed to verify the simulation results. The optimal TE was determined as 45 ms with the signals gain of 148.03% for allylic and 2.37% for diallylic groups on phantom and 160.16% for allylic and 13.22% for diallylic groups on human muscles, when compared to TE of 70 ms. This edited-MRS protocol allows robust quantification of unsaturated lipid composition in-vivo and investigation on lipid metabolism in future.
A Feasibility Study of 0.055T MRI for Neuroimaging and Comparison with Clinical 3T MRI
Authors: Leong Alex T. L. , Liu Yilong , Zhao Yujiao , Xiao Linfang , Mak Henry K. F. , Anderson Tsang , Lau Gary K. K. , Leung Gilberto K. K. , Wu Ed X.
Published: August 2023

Magnetic resonance imaging is a key diagnostic tool in modern healthcare, yet its accessibility is low with the vast majority of clinical MRI scanners being placed in highly specialized radiology departments, large centralized imaging centers, and housed on ground floors of hospitals and clinics. In this study, we deployed our recently developed 0.055T brain ultra-low-field MRI scanner to demonstrate preliminary feasibility in diagnosing tumor and stroke cases with direct comparisons to 3T clinical MRI results. The development of such ULF MRI technologies will enable patient-centric and site-agnostic MRI scanners to fulfill the unmet clinical needs across various global healthcare sites.
Preliminary Study of the Uncertainty for RF-induced Heating Assessment of Subcutaneous and Partially Implanted Devices during MRI Exposure
Authors: Yao Aiping , Ma Minjuan , Pei Yunfeng , Tang Longjun
Published: August 2023

This work intends to provide a preliminary evaluation of the uncertainty produced by current Tier 3 approach during the assessment of subcutaneous and partially implanted devices. The transfer function of a 600 mm long DBS and guidance wire for Interventional MRI are derived under homogeneous and heterogeneous tissue environments, respectively. The resulting power deposition using different transfer function are evaluated and compared. The results show that using current Tier 3 approach may lead to potential large underestimation of the power deposition for subcutaneous and partially implanted devices, methods which can overcome or reduce these uncertainty are needed.
Evaluation of Cerebral Blood Flow and BBB Water Exchange in an Aged African American Cohort
Authors: Ojogho Brandon , Abdolahi Farzan , Shao Xingfeng , Ma Samantha , Zhao Chenyang , Jann Kay , Jiang Xuejuan , Wang Danny
Published: August 2023

This study evaluated CBF and BBB water exchange rate (kw) measured by diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) in a cohort of aged African American individuals. The results showed decreasing CBF and kw with age, and higher CBF in females. Both CBF and kw were correlated with picture sequence memory test score. CBF was negatively correlated with white matter hyperintensities (WMH), free water (FW) and peak skeletonized mean diffusivity (PSMD), although age accounted for these correlations. These findings suggest the potential for CBF and kw as biomarkers of cerebral small vessel disease.
The influence of fat in the estimation of strain from tagged MR images
Authors: Mella Hernán , Uribe Sergio
Published: August 2023

In this work, we investigated the influence of fat in the estimation of strain from tagged MR images. The results showed that in a static phantom with sharp and smooth fat fractions, the estimated strain is influenced by the bandwidth of the bandpass filter, the tagging period, and the fat fraction.
Spin-lock dispersion imaging detects changes in the intrinsic susceptibility microstructure of brain induced by oxygen
Authors: zu zhongliang , Adelnia Fatemeh , Harkins Kevin , Wang Feng , Gore John
Published: August 2023

Previous research has shown that spin-lock imaging with low locking amplitude can quantify the spatial characteristics of intrinsic susceptibility gradients in tissues which likely reflect vascular microstructure. We evaluated the capability of spin-lock dispersion imaging with weak locking fields to detect vasoconstriction in rat brains under oxygen challenges.
Dynamic MTRasym in GlucoCEST MRI using modified DGE
Authors: Kaneblai Gustavo , Otaduy Maria Concepcion , Franca Regis , Costa Frederico , Figueiredo Eduardo , Doring Thomas , Blois Marcelo , Leite Claudia , Cerri Giovanni , Miyoshi Mitsuharu
Published: August 2023

A new method to create B0 corrected dynamic MTRasym glucoCEST maps during glucose administration and uptake without the need of acquiring a full Z-Spectrum with small changes in DGE. Results observed in 3T.
Water-Fat Separation from Dual-Echo Dixon Imaging Using Deep Learning
Authors: Wu Yan , Alley Marc , Datta Keshav , Li Zhitao , Sandino Christopher , Wen Zhifei , Lustig Michael , Pauly John , Vasanawala Shreyas
Published: August 2023

We design a data-driven method to generate water/fat images from dual-echo complex Dixon images, aimed at near-instant water-fat separation with high robustness. A hierarchical convolutional neural network is employed, where ground truth images are obtained using a binary quadratic optimization approach. With IRB approval and informed consent, 9281 image sets are collected from 30 pediatric patients to train and test networks, with the application of six-fold cross validation. In addition to high fidelity and significantly reduced processing time, the predicted images are superior to the ground truth in mitigation of water/fat swaps and correction of artifacts introduced by metallic implants.
Accelerated MRI of epicardial adipose tissue fatty acid composition in mice using a compressed-sensing and dictionary-based reconstruction
Authors: Shah Soham , Epstein Fred
Published: August 2023

Epicardial adipose tissue (EAT) and its fatty acid composition (FAC) have been implicated in numerous cardiovascular diseases as saturated fatty acids are known to promote inflammation. FAC MRI techniques, while prominent, have not been applied to EAT due to extended scan times, thus, image acceleration is essential. Here, we demonstrate compressed sensing with a signal model-based dictionary (CS-DICT) to reconstruct psuedo-random undersampled images. Using CS-DICT, we achieve rate-3 acceleration while maintaining accurate EAT FAC maps and estimations in obese mice. These methods facilitate the application of FAC MRI to the EAT.
Cardiac and Respiratory-Resolved Image Reconstruction with the Beat Pilot Tone
Authors: Lamar-Bruno Kathryn , Anand Suma , Lustig Michael
Published: August 2023

We have previously proposed Beat Pilot Tone (BPT), a motion sensing method using ultra-high-frequency RF and preamplifier intermodulation. BPT uses ultra-high-frequencies, which provides greater sensitivity to motion compared to the Pilot Tone (PT). In this work, we use the motion estimates from the BPT to reconstruct respiratory and cardiac-resolved images and compare them to motion-resolved images obtained using PT, respiratory bellows, and electrocardiogram (ECG) data. We show that BPT provides comparable image quality to conventional motion sensing for respiratory and cardiac motion.
High-Performance 0.55T Supports Contrast-Optimal SMS bSSFP Cardiac Imaging
Authors: Tian Ye , Cui Sophia , Lim Yongwan , Lee Nam , Zhao Ziwei , Nayak Krishna
Published: August 2023

Balanced steady-state free precession (bSSFP) cardiac cine MRI at 1.5T and 3T is routinely used for cardiac function assessment. Simultaneous multi-slice (SMS) imaging significantly reduces the number of required breath holds, but is typically performed with suboptimal flip angles (FA) due to SAR constraints and banding artifacts, both of which are significantly relaxed at 0.55T. In this work, we demonstrate blipped-CAIPI bSSFP cine imaging combined with spiral sampling for ventricular function at 0.55T with optimal FA for blood-myocardium contrast (100o-120o) at SMS factors of 2 and 3.
Pericarotid fat density was associated with carotid plaque vulnerability, especially IPH and TRFC
Authors: Yu Miao , Meng Yankai , Wang Beiru , Ge Yaqiong , Xu Kai
Published: August 2023

Inflammation play important roles in the vulnerability of atherosclerotic plaque. Pericoronary fat is associated with coronary heart disease and high-risk plaque, however the value of pericarotid fat density (PFD) remains uncertain. We evaluated the association between PFD on computed tomography angiography (CTA), with the vulnerable composition of carotid plaques. We found that the PFD was independently associated with vulnerability of carotid plaque especially for IPH and TRFC, suggesting that pericarotid fat tissue may play a key role in the occurrence of vulnerable plaques. The identification of local perivascular inflammation may help identify patients who may benefit from targeted therapy.
Wall Enhancement of Unruptured Intracranial Aneurysm on MR Imaging is Associated with Irregular Pulsation Detected by Four-dimensional CTA
Authors: Zhang Jianjian , Li Xiao , Zhu Chengcheng , Zhao Huilin
Published: August 2023

Both aneurysm wall enhancement (AWE) and irregular pulsation have been suggested as potential candidates for intracranial aneurysms (IAs) instability. No studies have explored the association between AWE and irregular pulsation. By using vessel wall MRI and four-dimensional computed tomography angiography, we found a significantly strong correlation between AWE and irregular pulsation (phi coefficient=0.569, p<0.001). IAs with irregular pulsation had much less AWE grade 0 and more AWE grade 1, 2 and 3 compared with IAs without irregular pulsation (all p<0.05). Further longitudinal studies are needed to validate the role of the two imaging markers in predicting aneurysm growth and rupture.
The influence of scanning order on whole-heart coronary MRA with multiple compressed sensing acceleration factors
Authors: su guangzong , wu yang , ma xiaojing , shuang dongsi , peng ting , li haixia , sun peng
Published: August 2023

Compressed sensing (CS) is a novel magnetic resonance imaging technique to accelerate scanning under the premise of ensuring image quality. Whole-heart coronary MRA with CS technique can assess coronary artery lesions. However, the image quality is still sensitive to many factors. In this study, we demonstrated that there were statistical differences in parts of image quality with different scan orders when using CS AF of 6, where the scanning at the late stage of examinations showed high image quality. It might be the optimal choice to start coronary MRA scanning later in cardiac MRI practice.
Comparison of 5T and 3T MRI in patients with moyamoya disease: An initial study
Authors: Li Sirui , Tu Mengqi , Xu Dan , Han Shihong , Zhang Shuheng , Sun Wenbo , Chen Jinchao , Xu Haibo , Zhang Jianjian
Published: August 2023

In this study, a 5.0T whole body MR imaging system was used for the evaluation of moyamoya disease (MMD). Diagnostic performance of time-of-flight magnetic resonance angiography (TOF-MRA) and susceptibility-weighted imaging (SWI) were evaluated and compared between the 5T MRI scanner and a clinical 3T MRI scanner in three MMD patients. Preliminary results show that 5 T MRI might be superior to 3T MRI for the visualization of small collateral branches and micro bleeding points.
Compressed sensing improved the assessment of the corticospinal pathways in stroke brains scanned with traditional DTI
Authors: Meng Yuguang , Zhang Xiaodong
Published: August 2023

Conventional diffusion tensor imaging (DTI) has been widely used to examine white matter connectivity with neurological diseases but is limited in detecting pathways with crossing fibers. As the crossing fibers are abundant in large and complicated brains like human and non-human primate brains, the DTI tractography results may be biased substantially. In stroke research, the integrity of corticospinal tract (CST) plays a critical role in assessing the motor function. In this study, a compressed sensing technique was explored to improve the CST delineation with conventional DTI, and the feasibility was evaluated by using a monkey model of stroke.
Pulmonary Vasculature and T2* mapping of Lung in post-COVID subjects using Free-Breathing 3D UTE
Authors: Malis Vadim , Bae Won , Kungsamutr Jirach , Zhang Xiaowei , Kassai Yoshimori , Yen Andrew , Hopkins Susan , Ohno Yoshiharu , Miyazaki Mitsue
Published: August 2023

Free-breathing 3D MRI techniques are applied to explore the impact of COVID-19 in adults. Single echo non-fat suppressed Ultra-short TE (UTE) was utilized for automatic segmentation of lung, Multi-echo UTE with fat suppression was used to obtain T2* maps, and UTE with Time-Spatial Labeling Inversion Pulse (Time-SLIP) allowed to visualize pulmonary vasculature.
High-resolution, high-contrast MRI protocol with extended delayed imaging for peritoneal mesothelioma
Authors: Medved Milica , Witmer Hunter , Dhiman Ankit , Berger Yaniv , Sherman Scott , Hindi Enal , Armato Samuel , Reiser Ingrid , Oto Aytekin , Engelmann Roger , Kindler Hedy , Oren Nisa , Harmath Carla , Turaga Kiran
Published: August 2023

Improved methods for visualizing malignant peritoneal mesothelioma are needed. A high-resolution, high-contrast MRI protocol at 3T, including multiple delayed phases, was tested in 18 patients scheduled for laparoscopy/laparotomy. Both contrast washout and ongoing uptake was observed in individual lesions, pointing to a need for imaging with both short and long post-contrast delay times for optimal sensitivity. The per-patient average uptake/washout rate was significantly correlated with the cumulative nuclear score on pathology. The tested MRI protocol is feasible and may allow for more accurate visualization of peritoneal lesions and better guidance of management options.
A simulation study of the negative impact of fat on the accuracy of T1 measurements
Authors: Li Zhitao , Vasanawala Shreyas , Feng Li
Published: August 2023

A simulation study examining the effects of fat in the accurate assessment of T1. The study looks at both the variable flip angle and Look-Locker methods, and different fat fractions and different T1 values are used in the simulation. The results indicated that while both VFA and Look-Locker methods’ accuracy are affected by fat, VFA method’s biases increases more rapidly as fat fraction goes up, and the bias for larger spin species with larger T1s are more severely impacted by the presence of fat.
Comparison of analytical BOLD-fMRI models against Two-Photon Microscopy and Monte Carlo simulations
Authors: Charest Jordan , Schwarz Pierre-Olivier , Walsh Mathieu , Genois Élie , Gagnon Louis , Desjardins Michèle
Published: August 2023

BOLD fMRI arises from a complex physiological and physical cascade of events taking place at the level of the cortical microvasculature which constitutes a medium with complex geometry. Several analytical models of the BOLD contrast have been developed but these have not been compared directly against detailed bottom-up modeling methods. Using a recent 3D modeling method based on Two-Photon Microscopy and Monte Carlo simulations, we tested the accuracy of two analytical models to predict the amplitude of the BOLD response at 1.5T, 3T, 4.7T and 7T for both gradient echo and spin echo acquisition protocols.
Intravoxel Architecture Atlases (IAA) Across the Human Lifespan
Authors: Wu Ye , Ahmad Sahar , Yap Pew-Thian
Published: August 2023

Human brain atlases integrate multifaceted features of the brain in common coordinate spaces, allowing systematic investigation of brain development and maturation. Here, we introduce a set of intravoxel architecture atlases (IAA) covering changes of tissue microstructure from birth to 100 years of age.
3D Dynamic Magnetic Resonance Imaging: A Tool for Describing Velopharyngeal Function
Authors: Gilbert Imani , Xing Fangxu , Jin Riwei , Shosted Ryan , Woo Jonghye , Sutton Bradley , Perry Jamie
Published: August 2023

Direct visualization of velopharyngeal structures and musculature during speech is best attained using 3D dynamic magnetic resonance imaging. Through innovative MR imaging and atlasing methods, we successfully describe velopharyngeal contours as represented on MR statistical atlases and individual subject images. Manual linear measurements of velum configurations during /p/ across two different speech stimuli reveal slight velar differences, reflecting major influences of neighboring speech sounds on velar movements.
Deep Learning-enabled Prostate Segmentation: Large Cohort Evaluation with Inter-Reader Variability Analysis
Authors: Liu Yongkai , Qi Miao , Surawech Chuthaporn , Zheng Haoxin , Nguyen Dan , Yang Guang , Raman Steven , Sung Kyunghyun
Published: August 2023

Whole-prostate gland (WPG) segmentation plays a significant role in prostate volume measurement, treatment, and biopsy planning. This study evaluated a previously developed automatic WPG segmentation, deep attentive neural network (DANN), on a large, continuous patient cohort to test its feasibility in a clinical setting.
A detunable multi-row self-decoupled Transmit Array for 7 T ASL and brain spinal cord Imaging
Authors: Yan Xinqiang , Zhu Yue , Lu Ming
Published: August 2023

Transmit arrays improves the transmit field homogeneity while reducing the local hot spot. Current array designs for the head are not optimized for arterial spin labeling and simultaneous brain and cervical spinal cord applications caused by the short longitudinal coverage. To approach this problem, we designed and constructed a three-row Tx array covering the whole brain and cervical spinal cords (length: 28 cm). The overall performance of the coil is good with return losses < -20 dB while having adjacent coils’ coupling averaging -25.3 dB and diagonal coil’s coupling averaging -14.6 dB. The coil’s detune circuit also worked as intended.
Self-shielded and self-decoupled transmit RF array for 7T head imaging
Authors: Yan Xinqiang , Zhu Yue , Lu Ming
Published: August 2023

Transmit (Tx) array with multiple independent coil elements is a well-recognized approach to addressing the B1 inhomogeneity and high local SAR issues at ultrahigh fields. However, Tx arrays typically have a lighter loading and more severe coil coupling. We designed a self-shielded and self-decoupled 2x8 Tx array with high inter-element isolation for 7T head imaging. Each Tx element is based on the corner-fed self-decoupled coil. Four coil elements were constructed to prove the concept is viable. The coil elements are highly decoupled (inter element response < -15 dB) while maintaining good tuning/matching characteristics (power reflection < -20 dB).
Quantitative assessment of lumbar nerve root compression using contrast-enhanced 3D-FIESTA imaging sequence
Authors: Ou Kun , Gao Hui , Liu Weiyn , Zhang Kun
Published: August 2023

Actual contact surface between the extraforaminal nerve root and the adjacent structures is commonly missing on the conventional MR scanning, possibly leading to misdiagnosis. In our study, the detection rate of nerve root compression was significantly higher on the 3D-FIESTA-C images than T2WI. The shortest distance between the extraforaminal nerve root and the disc of L4/5 and L5/S1 in the healthy group was significantly longer than that in the lumbar disc herniation (LDH) group. The spatial relationship between nerve roots and surrounding tissues could be better described using 3D-FIESTA-C sequence and was helpful for the detection of nerve root compression.
Accelerated brachial Plexus MRI using deep learning constrained compressed SENSE reconstruction
Authors: Xiao Yi , Hu Sixian , Xia Chunchao , Li Zhenlin , Zhang Xiaoyong , Ling Chuntang
Published: August 2023

This study presents an accelerated brachial Plexus MR imaging technique using deep learning constrained compressed SENSE reconstruction (CS-AI-SENSE). The results showed that CS-AI-SENSE could enable comparable diagnostic image quality to the conventional SENSE-accelerated 3D T2-TSE approaches while significantly reduced the data acquisition time, which has potential to enhance the workflow of brachial Plexus MR examinations in clinics.
Utility of advanced diffusion model in early detection of cervical spondylotic myelopathy: a comparison between DTI and NODDI
Authors: Zhang Meng-Ze , Ou-Yang Han-Qiang , Jin Dan , Wang Chun-Jie , Liu Jian-Fang , Zhao Qiang , Zhang Xian-Chang , Liu Xiao-Guang , Liu Zhong-Jun , Lang Ning , Sun Xing-Wen , Jiang Liang , Yuan Hui-Shu
Published: August 2023

This study compared the sensitivity of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to detect cervical spondylotic myelopathy (CSM) at an early stage. The results showed that NODDI-based indicators can distinguish patients with CSM without T2-weighted increased signal intensity from healthy controls during internal validation, while DTI-based indicators cannot. These findings suggest that NODDI is a promising method to detect CSM at an early stage.
High-spatial assessment of low-level permeability within normal-appearing brain tissue using dual-temporal resolution DCE-MRI
Authors: Li Ka-Loh , Lewis Daniel , Zhu Xiaoping , Cootes Timothy , Jackson Alan
Published: August 2023

Quantifying blood-brain barrier permeability in normal-appearing brain through dynamic contrast-enhanced MRI (DCE-MRI) is challenging. We evaluated a new method, which combines the hybrid first-pass Patlak-plot (FP-PP) model with a high spatiotemporal resolution DCE approach termed LEGATOS. Dual-temporal resolution DCE-MRI data in twelve patients with neurofibromatosis type II (NF2) imaged at 1.5T were analyzed, and estimates of Ktrans within normal-appearing grey matter (NAGM) and white matter (NAWM) were compared. This new method permitted high-spatial resolution assessment of low-level permeability in normal-appearing brain and in our NF2 patient cohort a significant positive correlation between tumor volume and NAGM/NAWM Ktrans values was observed.
Visible "Butterfly" of the Cervical Spinal Cord: A Pilot Study Using 3D and 2D m-FFE with Inhomogeneous Magnetization Transfer Pulse
Authors: Yoda Takafumi , Yokota Hajime , Sada Takayuki , Kurosawa Ryuna , Matsumoto Koji , Namiki Takashi , Yoneyama Masami , Gilbert Guillaume , Masuda Yoshitada , Uno Takashi
Published: August 2023

The purpose of this study is to find the parameters that provide the optimal trade-off in Signal-to-noise-ratio (SNR) and contrast-to-noise ratio (CNR) for 3D ihMT m-FFE (3D-ihMT) and to explore the feasibility of that for the segmentability of gray and white matters in the cervical spinal cord compared with 2D ihMT m-FFE (2D-ihMT). We recommend a Flip angle of 7 and TFE factor of 5 as an optimal trade-off between segmentability and artifact level, at least 16 nr repetitions are required for robust segmentation. The segmentability of 3D-ihMT could be increased to a level close to that of 2D-ihMT.
Free-water volume fraction increases nonlinearly across the lifespan in healthy human brain white matter areas
Authors: Pieciak Tomasz , París Guillem , Beck Dani , Maximov Ivan , Tristán-Vega Antonio , de Luis-García Rodrigo , Westlye Lars , Aja-Fernández Santiago
Published: August 2023

The free-water (FW) volume fraction $$$f$$$ is a sensitive diffusion MRI biomarker correlated with microstructural alterations in the human brain. This paper studies the variations in the FW volume fraction $$$f$$$ in healthy human brain white matter (WM) across the lifespan from a set of 248 female and 140 male subjects. Our study reveals positive nonlinear correlations of the volume fraction $$$f$$$ with age over the WM regions and suggests a heteroscedastic nature and age-dependent intra-region-of-interest variability of $$$f$$$ across the lifespan.
High-resolution flow-sensitive CINE imaging visualizing valve, chamber, and regurgitant flow
Authors: Shiina Isao , Nagao Michinobu , Yoneyama Masami , Goto Yasuhiro , Hamatani Yutaka , Kodaira Kazuo , Ogawa Takumi , Kato Mana , Sakai Shuji
Published: August 2023

Cardiac bSSFP CINE imaging is widely used in clinical practice for function and morphological evaluation, but we often experienced situations where it is difficult to visually evaluate blood flow and valves. TFEPI is a flow-sensitive imaging method and can be expected to evaluate blood flow and valves. In this study, we investigate the clinical usefulness of Flow sensitive CINE Imaging using TFEPI.
Left ventricular blood flow kinetic energy in Hypertensive heart disease ：A pilot study of 4D flow cardiovascular magnetic resonance
Authors: Peng Kun , Liu Yong , Hua Ting , Zhang Xianling , Zhao Xiance , Zhang Jilei , Tang Guangyu
Published: August 2023

Four-dimensional flow magnetic resonance imaging (4D-flow MRI) technique has been developed to assess intra-cavity left ventricular (LV) blood flow. Hypertensive heart disease (HHD) is a common cardiovascular disease and manifested as left ventricular hypertrophy and diastolic/systolic dysfunction. The purpose of this study was to investigate whether 4D-flow CMR kinetic energy (KE) parameters are sensitive to distinguish HHD patients from age/gender-matched healthy controls, and to access if there are significant differences in different sub-groups of LV ejection fraction. We also aimed to investigate the association of LV KE to LV function parameters and LV mass.
Assessments of hemodynamic changes in abdominal aortic aneurysm in patients using 4D EPI flow MRI
Authors: Zeng Wen , Xia Chunchao , Zhang Xiaoyong , Li Zhenlin
Published: August 2023

Four-dimensional flow MRI (4D flow MRI) plays a significant role in cardiovascular imaging, which provides new insights into the pathophysiology of disease. In this study, 4D flow with echo-planar imaging was introduced to evaluate the hemodynamic parameters of patients with abdominal aortic aneurysm, including velocity, flow and wall shear stress. We propose that 4D EPI flow can find differences of the above parameters between abdominal aortic aneurysm and normal abdominal aorta and has potential to be used for hemodynamics assessment in AAA patients.
Evaluation of cardiotoxicity in chest tumor patients receiving immune checkpoint inhibitors by cardiovascular magnetic resonance
Authors: Liu Jia , Cao Yukun , Zhu Kuikui , Yao Sheng , Yuan Mei , Kong Xiangchuang , Liu Xiaoming , Li Yumin , Cui Yue , Han Xiaoyu , Zhou Xiaoyue , Meng Rui , Shi Heshui
Published: August 2023

In our study, we conducted a prospective study to investigate the subclinical cardiotoxicity by serial cardiovascular magnetic resonance (CMR) in patients receiving immune checkpoint inhibitor (ICI). Some functional parameters and global strains of bi-ventricles revealed significant decrease at the early stage on ICI therapy, and ejection fraction as well as global strain values of both ventricles all showed a decline trend. Tissue characterization is an extra advantage of CMR technique. While in our study, parameters (T1 mapping, T2 mapping and late gadolinium enhancement) regarding tissue characterization of global myocardium showed no significant differences, compared with baseline data.
Simultaneous late-gadolinium enhancement and T1 mapping to detect diffuse myocardial fibrosis in 1K/DOCA/salt-induced mice using MP2RAGE
Authors: Zheng Gang , Li Yifang , Salimova Ekaterina , Wang Hong , Zhong Shenjun , Samuel Chrishan , de Veer Michael , Egan Gary
Published: August 2023

The detection and localization of diffuse myocardial fibrosis is for the non-invasive evaluation of therapeutic strategies in murine cardiac disease models. Cardiac late-gadolinium enhancement (LGE) and T1 mapping are two techniques for non-invasive cardiovascular magnetic resonance (CMR) imaging. This abstract demonstrates that the magnetization prepared 2 rapid acquisition gradient echo (MP2RAGE) can simultaneously acquire LGE and T1 maps for the detection of diffuse myocardial fibrosis in a 1K/DOCA/salt-induced murine model of hypertensive disease.
Detection of crossed cerebellar diaschisis in subacute ischemic stroke using 3D PCASL with two post-labeling delay time method
Authors: Lyu Yuelei , Gu Hua , Xue Yanping , Xie Lizhi , Jiang Tao , Yang Qi
Published: August 2023

This study investigated the feasibility of 3D PCASL to detect crossed cerebellar diaschisis (CCD) in patients with unilateral supratentorial subacute stroke using two PLD method and correlated the ischemic perfusion with CCD to identify the relevant imaging factors of CCD development. 3D PCASL can detect CCD in patients of supratentorial subacute stroke. Patients of supratentorial subacute stroke experience late-arriving flow while CCD+ patients suffer late arriving flow in the affected contralateral cerebellum. CCD+ patients may have a propensity towards more hemodynamic compromise and compensatory collateral flow in the cerebellum.
ATP-A safe stressor for stress perfusion cardiac magnetic resonance
Authors: Kong Huihui , An Jing , Cao Jiaxin , Tian Jinfan , Yong Jingwen , Song Xiantao , He Yi
Published: August 2023

This study investigated the side effects and safety of ATP as a stressor for stress perfusion cardiac magnetic resonance. The result showed the high safety of stress perfusion with ATP and side effects were mild and resolved shortly after receiving ATP. Furthermore, it was also observed splenic switch-off that can be used to assess stress adequacy undergoing stress-CMR with ATP.
Correlation Analysis between BOLD Delay and Cerebral Blood Flow: A Study in Moyamoya Patients
Authors: Hu Zhangxuan , Zhang Zhe , Zhai Yuanren , Qian Long , Sui Binbin , Zhang Dong
Published: August 2023

It has been shown that the BOLD delay calculated from resting-state fMRI can reveal perfusion information. In this study, the correlation between BOLD delay and CBF measured from ASL were explored. The results showed the inter-subject correlation between BOLD delay and CBF values. Meanwhile, the inter-group differences of the correlation coefficients between Moyamoya patients and healthy controls were also compared.
The impact of hemodynamic patterns and geometric features of vertebra-basilar system on atherosclerotic plaque occurrence
Authors: Shen Rui , Han Hualu , Zheng Jinmei , Qiao Huiyu , Ning Zihan , Tong Xinyu , Xue Yunjing , Zhao Xihai
Published: August 2023

This study investigated the relationship between the geometry of vertebra-basilar system and hemodynamic measurements and presence of BA plaques. We found that geometric measurements and most hemodynamic features were significantly correlated with the occurrence of BA plaque (mean curvature, r=0.368; NOR-TAWSS-NF, r=-0.312; SAR-OSI-NF, r=0.290; NOR-TAWSS-nNF, r=-0.387; NOR-OSI-nNF, r=0.440). There were significant differences in mean curvature, hemodynamic characteristics of Newtonian flow and non-Newtonian flow models between patients with and without BA plaque. Our study indicated that geometric features and non-Newtonian flow model-based hemodynamic measurements are risk factors of BA plaque.
Altered Spontaneous Brain Activity Related to Neurologic Dysfunction in Patients with Cerebral Small Vessel Disease: A resting-state study
Authors: Feng Mengmeng , Wen Hongwei , Xin Haotian , Liang Changhu , Guo Lingfei
Published: August 2023

Cerebral small vessel disease (CSVD) patients can present structural and functional abnormalities. We divided 102 subjects into three groups and obtained information about altered spontaneous brain activity using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) methods based on resting-state functional MRI. Compared with controls and the CSVD without cerebral microbleeds (CSVD-n) group, the CSVD with cerebral microbleeds (CSVD-c) group showed significantly increased ALFF/ReHo values and decreased fALFF values in some brain regions, which are correlated to abnormal clinical characteristics. These results expounded the underlying neurophysiological mechanisms in CSVD patients.
Arterial transit artifact could prognose stroke patients beyond 24 hours from last known well
Authors: Wu Di , Zhang Shun , Liu Weiyin , Zhu Wenzhen
Published: August 2023

The study aimed to assess the correlation of arterial transit artifact (ATA) with clinical outcomes and collateral circulation status in stroke patients beyond 24 hours from last known well. ATA is assessed by 3-dimentional pseudo-continuous ASL (3D-pCASL), collateral status by magnetic resonance angiography (MRA) using a grading system from 0 to 3, and clinical outcomes by 3-month modified Ranking Scale (3m-mRS). ATA was present in about half of the enrolled patients, most of whom had large artery disease. Though the correlation between ATA and the degree of collateral supply was not statistically significant, ATA could predict the favorable clinical outcomes.
Deep Learning regularized SPIRiT reconstruction accelerates joint intracranial and carotid vessel wall imaging into 3.5 minutes
Authors: Jia Sen , Cheng Jing , Cui Zhuoxu , Zhang Lei , Wang Haifeng , Liu Xin , Zheng Hairong , Zhang Hongying , Liang Dong
Published: August 2023

Deep learning regularized SPIRiT reconstruction is developed by unrolling the conventional L1-SPIRiT optimization solved by the projection onto convex sets (POCS) iteration into a multi-layer convolutional neural network. The learnable network regularization with 3D convolution improved the reconstruction accuracy and efficiency compared with the iterative L1-SPIRiT with 2D sparsity regularization in a fixed transform domain. The simplicity of POCS iteration also benefits the design complexity of the DL-SPIRiT network. The proposed DL-SPIRiT could accelerate the joint intracranial and carotid vessel wall imaging of isotropic 0.6 mm resolution by 8-fold, leading to a scan time of only 3.5 minutes.
Mapping functional connectivity and brain network changes in hypertensive using resting-state fMRI
Authors: Chuang Yu-Chen , Wu Wen-Chau , Chen Vincent Chin-Hung , Hsu Yen-Hsuan , Weng Jun-Cheng
Published: August 2023

Although understanding of the relationship between cardiovascular disease and brain dysfunction has improved significantly over the past decades, it remains unclear whether hypertension can be a potential risk factor for cognitive impairment. This study tried to use resting-state fMRI to explore the association between hypertensive (HTN) and brain function alterations. We found significant differences in the DMN subsystems in HTN group compared with control group. We also observed higher assortativity in HTN group.