bluuebunny/crossref_metadata_2025 huggingface dataset:
High resolution myocardial T1mapping with a deep learning constrained Compressed SENSE reconstruction
Authors: Yoshida Takashige , Yuda Kohei , Yoneyama Masami , Kwon Jihun , Cauteren Marc
Published: August 2023

High-resolution imaging and T1 mapping is needed to achieve useful clinical information optimally in cardiac MRI. However, prolonged acquisition time can lead to poor or non-diagnostic image quality. In this study, we investigated the use of a deep learning-based reconstruction algorithm to highly accelerate T1map acquisition for cardiac MRI. Adaptive-CS-Net, a deep neural network previously introduced at the 2019 fastMRI challenge, was expanded and integrated into the Compressed-SENSE Artificial Intelligence (CS-AI) reconstruction. The purpose of this study was to compare the image quality of high-resolution T1map between reference and accelerated methods: SENSE, Compressed-SENSE, and CS-AI.
Comparison of different denoising approaches for DCE-MRI
Authors: Wang Zejun , Wang Bao , Huang Ziyi , Liu Yingchao , Bai Ruiliang
Published: August 2023

The physiological parameters estimated from pharmacokinetic modeling of DCE-MRI are usually biased by the non-white, spatially-dependent noise. In this study, we compared several state-of-arts denoising approaches, including gaussian low pass filter (GLPF), the dynamic nonlocal mean (DNLM), the nonlocal mean based on spatiotemporal patches (NLM-ST), 2D and 3D kinetics-induced bilateral filter (KIBF). Our results reveal that the 3D KIBF can reduce the noise significantly and reserve subtle information best.
Revealing Occult Hemodynamic Signatures from the Acetazolamide-Augmented Cerebral BOLD Response
Authors: Dogra Siddhant , Wang Xiuyuan , Veraart Jelle , Gupta Alejandro , Ishida Koto , Qiu Deqiang , Dehkharghani Seena
Published: August 2023

Acetazolamide-augmented blood-oxygen-level-dependent (ACZ-BOLD MRI) provides robust estimation of cerebrovascular reactivity (CVR). Past approaches are limited to extraction of terminal CVR at arbitrarily selected times in the pharmacologic response, due to low signal-to-noise characteristics. We previously introduced a computational framework that pre-conditions the BOLD response for dynamic analysis and extraction of maximal, rather than terminal augmentation profiles, and novel hemodynamic signatures such as ACZ-BOLD time-to-maxima (Tmax). Several consistent and sometimes paradoxical patterns have emerged, the presentation of which we considered timely for this potentially novel hemodynamic neuroimaging biomarker.
Characterization of mouse cerebrovascular reactivity using task-free resting-state fMRI
Authors: Xue Yixi , Chan Russell , Wu Sarah , Tse Emily , Faiq Muneeb , Sajitha Thajunnisa , Chan Kevin
Published: August 2023

The recent development of relative cerebrovascular reactivity (rCVR) mapping derived from task-free resting-state blood-oxygenation-level-dependent fMRI resolves issues of experimental complications from hypercapnic challenge or pharmacological administrations required in conventional CVR mapping. While human clinical rCVR studies have begun, there lacks rCVR characterization in healthy adult rodents before it can be applied to preclinical models of neuropathology for translational research. This study demonstrated the feasibility of rCVR mapping using resting-state fMRI at 7 Tesla in mice. The results also revealed potential rCVR lateralization in cortical regions and heterogenous vascularization along the septotemporal axis of the hippocampus.
Cerebrovascular Reactivity Mapping using General Linear Model in Frequency Domain
Authors: Xu Botian , Vu Chau , Borzage Matthew , Wood John
Published: August 2023

Cerebrovascular reactivity (CVR), measuring the ability of vessel dilation or constriction, is an important indicator of cerebrovascular health. As a parameter describing the hemodynamic changes, CVR requires a physiological challenge as the stimulus and monitors the response of the brain metabolism. We propose a frequency-based approach, which applies general linear model (GLM) on the magnitude of the stimulus and response spectrum to avoid challenges with signal alignment and improve robustness to noise in CVR estimation.
Improve the Image Quality of Arterial Spin Labeling with Echo Planar Imaging with Compressed SENSE
Authors: Su Chunqiu , Zhao Xiance , Zhang Jilei , Hong Xunning , Lu Shanshan
Published: August 2023

Arterial spin labeling (ASL) is a non-invasive MRI perfusion technique that can quantify tissue blood flow, which is meaningful for clinical applications. However, ASL perfusion images always have a limited signal-to-noise ratio (SNR). We aimed to using the echo planar imaging with compressed SENSE (EPICS) to obtain high-quality brain ASL images. Eleven healthy subjects and four patients with intracranial infarction were enrolled, and underwent ASL imaging with and without EPICS. The results demonstrated the feasibility of EPICS to increase the quality of ASL images.
Preliminary study on plaque characteristics in young adults with symptomatic intracranial atherosclerotic stenosis
Authors: Li Ling , Zhang XiaoLing , Lei Xiaoyan , Tang Min , Yan Xuejiao , Ai Kai
Published: August 2023

This study used high-resolution magnetic resonance imaging (HRMRI) to explore plaque characteristics of young adults with symptomatic intracranial atherosclerotic stenosis (sICAS). Compared with old patients, young patients with sICAS have a smaller Maximum wall thickness and a greater ability to reconstruct, and are more prone to positive remodeling, which may cover up some patients with atherosclerotic stenosis. The results show great clinical importance for a better understanding of youth intracranial arterial plaque features and highlights the importance of HRMRI.
Effects of vascular territories on the efficiency of DANTE preparation pulse for ASL
Authors: Ishida Shota , Kimura Hirohiko , Takei Naoyuki , Fujiwara Yasuhiro , Matsuda Tsuyoshi , Kosaka Nobuyuki
Published: August 2023

This study aimed to assess whether the efficiency of DANTE, a vascular suppression in ASL, is affected by vascular territories. CBF, transit times (TT), and their rates of change were determined in nine vascular territories from the proximal to distal regions. Although CBF reduction rates were not different among the territories, TT extension rates were lower in the distal region than in other regions. No correlation was observed between TT extension and CBF reduction rates. DANTE efficiency is not affected by transit time or vascular territories. Homogenous vascular suppression effects could be obtained by DANTE-ASL.
Evaluate myocardial microcirculation in pediatric myocarditis patients with free breathing intravoxel incoherent motion MR sequence
Authors: Li Shilan , Tao Jiahuan , Zhang Jing , Ai Kai
Published: August 2023

To explore the possibility of application of free breathing intravoxel incoherent motion (IVIM) imaging in pediatric myocarditis patients, we utilized diaphragmatic navigation technique to detect heart rate and improved the probability of scanning success. Eight pediatric myocarditis patients and ten healthy volunteers were enrolled. The study confirmed that the IVIM imaging method with free breathing condition was acceptable and achievable. Besides, compared with healthy children, the microcirculation of myocarditis patients was impaired, and pseudo-diffusion coefficient (Dfast) and perfusion fraction (f) were significantly lower.
MIXTURE-DOSMA: A comprehensive and multi-parametric quantitative 3D knee MR exam in 10 minutes
Authors: Kwon Jihun , Sakai Takayuki , Yoneyama Masami , Murayama Daichi , Lu Quin , Desai Arjun , Chaudhari Akshay , Cauteren Marc
Published: August 2023

Multi-Interleaved X-prepared TSE with inTUitive RElaxometry (MIXTURE) is a recently developed 3D magnetization-prepared turbo spin-echo sequence. MIXTURE provides 3D high-resolution isotropic knee morphometry and T1ρ relaxometry in a clinically reasonable scan time. In this study, we integrated MIXTURE with the Deep Open-Source Medical Analysis (DOSMA) framework for deep learning-powered musculoskeletal MR image analysis to expand its clinical usage. By exploiting the advantage of both techniques, we show that the combination of MIXTURE and DOSMA enables a comprehensive whole knee MR exam including 3D proton density-weighted isotropic submillimeter imaging, T2- and T1ρ-mapping, and standardized image analysis techniques.
Distinction of compensated stage of liver cirrhosis in patients with chronic hepatitis B using IDEAL-IQ Magnetic Resonance Imaging
Authors: Li Hongyi , lesheng Huang , Chen Jun , Liu Weiyin , Jiang Jinghua , Cai Kaili , Liu Tianzhu , Zhang Wanchun , Tang Jiahui , Yang Kailian , Peng Se , Li Dan
Published: August 2023

The purpose was to evaluate the feasibility of IDEAL-IQ in distinction of patients with early liver cirrhosis(compensated stage). Sixty CHB patients with compensated cirrhosis conformed by liver biopsy and twenty healthy controls were recruited. FF and R2* of IDEAL-IQ sequence were analyzed between CHB compensated cirrhosis patients and volunteers. Correlations between FF and R2* and ALT, INR values were analyzed in CHB patients with compensated cirrhosis. R2* was statistically different between compensated cirrhosis patients and volunteers (p<0.01) with AUC of 0.726. The correlations between FF and ALT, INR were both fair(0.268, p=0.03 and -0.351, p<0.01).
Staging liver fibrosis through a machine learning model built from radiomics features of T2WI images
Authors: shi nannan , sun jianqing , Shan Fei , qin Yiying , yang Zecheng , chen Weibo , shi yuxin
Published: August 2023

To further develop and validate a radiomics-based model from liver T2WI images for staging liver fibrosis.
Can extracellular volume fraction assess liver fibrosis? A preliminary Gd-EOB-DTPA-enhanced MRI study
Authors: Yang Pin , Jiang YanLi , Zou Jie , Chang Miao , Zhang Jing , Ai Kai
Published: August 2023

This study evaluates the feasibility of extracellular volume fraction (ECV) in judging liver fibrosis, analyzes the interaction between ECV and liver function.The method is to calculate ECV in different degrees of liver function and compare the correlation between ECV and serum albumin. Our research shows that ECV20min had no significant difference among Child-Pugh A, Child-Pugh B and Child-Pugh C, there was a weak correlation with serum albumin. Therefore, we consider that ECV of hepatobiliary phase will not be affected by liver function when Gd-EOB-DTPA is used to evaluate liver fibrosis, it may be a reliable tool in assessing liver fibrosis.
A Novel Three-Dimensional k-Space Reconstruction Method by Spherical Fourier Transform
Authors: Shafiekhani Mojtaba , Ghodrati Vahid , Nasiraei-Moghaddam Abbas
Published: August 2023

The two- and three-dimensional radial trajectory has been widely used due to its lower sensitivity to movement and flow and also shorter acquisition time. Re-gridding, the dominant approach for radial data reconstruction, suffers from severe artifacts at high acceleration rates. This study proposes a mathematical approach based on spherical harmonics to reconstruct images in the spherical coordinates without any interpolation in the frequency domain, unlike the conventional re-gridding algorithm. The feasibility of the proposed algorithm for reconstructing the images on both 3D Shepp-Logan and brain digital phantoms was shown.
Densely-overlapped locally low-rank algorithms outperform conventional locally low-rank algorithms for accelerating parametric mapping
Authors: Hu Chenxi , Yang Fan , Tang Xin , Zhang Zhiyong , Peters Dana
Published: August 2023

The Locally Low-Rank (LLR) constraint has been increasingly used for MR acceleration. Here we compare two strategies for LLR-constrained reconstruction, namely the Non-overlapped LLR (NLLR) and the Densely-overlapped LLR (DLLR) to show their differences. The NLLR strategy has been used by a number of LLR algorithms, including the most well-known POCS algorithm. On the other hand, the DLLR strategy has not been well-recognized as a different strategy, and algorithms able to employ the strategy have only been developed recently. In this work, we show that DLLR is different and superior to NLLR by yielding faster convergence and reduced undersampling artifacts.
Image reconstruction with subspace-assisted deep learning
Authors: Guan Yue , Li Yudu , Liu Ruihao , Meng Ziyu , Li Yao , Ying Leslie , Du Yiping , Liang Zhi-Pei
Published: August 2023

Deep learning-based image reconstruction methods are often sensitive to changes in data acquisition settings (e.g., sampling pattern and number of encodings). This work proposes a novel subspace-assisted deep learning method to effectively address this problem. The proposed method uses a subspace model to capture the global dependence of image features in the training data and a deep network to learn the mapping from a linear vector space to a nonlinear manifold. Significant improvement in reconstruction accuracy and robustness by the proposed method has been demonstrated using the fastMRI dataset.
Fast and Automatic Rank Determination (ARD) via Deep Learning for Low-rank Calibrationless Reconstruction
Authors: Hu Jiahao , Yi Zheyuan , Zhao Yujiao , Man Christopher , Xiao Linfang , Lau Vick , Su Shi , Huang Ziming , Zhang Junhao , Leong Alex , Chen Fei , Wu Ed
Published: August 2023

Low-rank matrix completion has emerged as a potent reconstruction approach for calibrationless parallel imaging. However, in all existing low-rank reconstruction methods, the rank threshold must be carefully chosen slice by slice in a manual and trial-and-error manner, severely hindering the adoption of low-rank reconstruction in routine clinical applications. To tackle the problem, we proposed a fast and automatic rank determination via deep learning. It directly determines optimal rank from undersampled k-space data by exploiting coil sensitivity and finite image support. Our proposed method enables fast, automatic and robust rank determination for all existing calibrationless reconstruction using low-rank matrix completion.
Joint Sensitivity Estimation and Image Reconstruction in Parallel Imaging Using Pre-learned Subspaces of Coil Sensitivity Functions
Authors: Tang Lihong , Zhao Yibo , Li Yudu , Guo Rong , Cai Bingyang , Li Yao , Liang Zhi-Pei , Luo Jie
Published: August 2023

Accurate estimation of coil sensitivity functions is essential for SENSE-based image reconstruction. This paper presents a new method for joint estimation of coil sensitivity functions and image reconstruction from sparsely sampled k-space data without any auto-calibration data. The proposed method uses a probabilistic subspace model to capture statistical spatial distributions of a given coil system from prior scan data. The proposed method has been validated using experimental data (fastMRI dataset), producing high-quality reconstruction results from calibrationless sparse data (acceleration factor R = 8 or R = 16). The proposed method may further enhance the practical utility of parallel imaging.
Simultaneous Multi-slab DWI Reconstruction with Intrinsic Distortion Correction using Blip-up/down Acquisitions
Authors: Zhang Jieying , Liu Simin , Dai Erpeng , Ye Xinyu , Yu Yang , Zhang Yajing , Lu Jie , Guo Hua
Published: August 2023

Simultaneous multi-slab imaging (SMSlab) can achieve high-resolution DWI with high SNR efficiency, but image distortions remain a problem. Joint reconstruction of blip-up/down EPI data can correct for distortion and reduce g-factors simultaneously. This study proposed a joint reconstruction framework with intrinsic distortion correction for SMSlab. Three sampling patterns were compared in terms of levels of distortions and g-factors. According to the results, a multi-shot acquisition should be used to reduce the distortion. Combined with the controlled aliasing in parallel imaging (CAIPI) sampling pattern, it can further reduce the g-factors.
Highly Accelerated Volumetric Brain Imaging with META and Deep Learning Reconstruction
Authors: Takei Naoyuki , Lebel R , Kaushik Suryanarayanan , Fujita Shohei , Fukunaga Issei , Aoki Shigeki , Banerjee Suchandrima , Wakayama Tetsuya
Published: August 2023

We combine advanced acquisition and reconstruction techniques for highly accelerated 3D brain imaging. A hybrid acquisition called META (Mixed Echo Train Acquisition) generates 3D T1W, T2W and FLAIR contrasts simultaneously and with high SNR efficiency. A 3D deep learning reconstruction (AIR Recon DL) reduces image noise, reduces artifacts, and enhances resolution relative to conventional reconstructions, solving the trade-off between SNR, scan time, and resolution. META with the DL Recon achieved 1mm isotropic T1W, T2W and FLAIR images within 4 minutes. These combinations are well suited in high resolution volumetric brain imaging.
Performance of PROPELLER FSE T2WI in reducing metal artifacts for patients with various material porcelain fused to metal
Authors: Bian Wenjin , Niu Jinliang , Li Jianting , Wu Wenqi
Published: August 2023

The metal artifacts caused by metal copings in porcelain fused to metal (PFM) always impair MRI quality. This study aimed to compare MRI quality between common FSE T2WI with PROPELLER FSE T2WI for patients with various metal copings. Fifty-nine subjects with the most commonly used PFM were recruited and imaged at 1.5T MRI system. By comparing the image quality and artifact areas, we found PROPELLER technique was less sensitive to metal artifacts than common FSE. It can be proposed the PROPELLER FSE T2WI to be used as clinical MRI examination of oral cavity and maxillofacial part for patients with PFM.
Implementation of the QRAPMASTER sequence using a dictionary matching and quantitative evaluation of the magnetization transfer effect
Authors: Kose Katsumi , Kose Ryoichi , Terada Yasuhiko
Published: August 2023

The magnetization transfer effect of the QRAPMASTER sequence was investigated using phantom experiments and Bloch simulations. The phantom consisted of MnCl2 aqueous solution with various proton T1 values and raw chicken breast meat. T1 values of the MnCl2 solution measured using the QRAPMASTER sequence showed excellent linear relation with those measured with the standard method. However, T1 of the chicken breast sample deviated far from the linear regression line. The results suggested that the T1 values of biological samples measured by the QRAPMASTER sequence are underestimated compared to those measured by the standard method.
Ultra-Fast T1-Weighted Imaging with Wave-CAIPI MPRAGE for Clinical Pediatric Brain MR imaging: A Prospective Quantitative Assessment Study
Authors: Chen Yung-Chieh , Kuo Duen-Pang , Chen Cheng-Yu
Published: August 2023

Morphologic neuroimaging in children can be challenging and time-sensitive during routine clinical imaging workflow due to patient discomfort, susceptibility to motion, and frequent need of sedation. Our study quantitatively assessed the imaging performance of ultra-fast T1 3D magnetization-prepared rapid acquisition gradient echo (MPRAGE) using wave-controlled aliasing with parallel imaging (wave-CAIPI) sequence for accelerated pediatric brain MR imaging via whole brain wide analysis under different MR imaging parameter settings with and without contrast administration. Our results show that wave-CAIPI can deliver comparable image quality to standard MPRAGE with significantly reduced scan times with optimized imaging parameters.
Comparison of conventional and spiral TOF-MRA in clinical applications
Authors: Kang Taishan , Lin Liangjie , Wu Zhigang , Wu Jian
Published: August 2023

TOF-MRA is a routine noninvasive method that does not require intravenous contrast agents or exposure to radiation for brain artery assessment. However, artifacts are prone to appear in conventional TOF-MRA under situations of complicated blood vessels or changes in blood flow; and the display of distal arterioles is also not good. The spiral acquisition technique has been previously introduced for scan acceleration of TOF-MRA, while here we compared the performance of conventional and spiral TOF-MRA under similar scan duration. Results indicated that spiral TOF-MRA provide better quality MRA images, and may help improve the clinical diagnosis of vascular problems.
Experimental study on intracranial gadolinium deposition in rats after linear conversion to macrocyclic gadolinium contrast agent
Authors: wang xucong , chen bing , li jian , wang zhen hua , Wei Xiaocheng
Published: August 2023

To investigate the changes of intracranial gadolinium deposition in rats with linear gadolinium deposition after continuous injection of large ring gadolinium contrast agent. The intracranial gadolinium deposition in these rats increased but was relatively small. The DCN T1 value measured on MRI ensemble sequence scan images was significantly negatively correlated with gadolinium concentration in cerebellar DCN. (ALL P values were less than 0.05).
Accelerating Cerebrovascular 4D Flow by Low-Rank and Sparsity Constraints at Ultra-High Field
Authors: Zhao Xueying , Van de Moortele Pierre-Francois , Chu Ying-Hua , Wang He
Published: August 2023

Inspired by the success of low-rank and sparsity (L+S) representation in 4D flow MRI acceleration of great vessels (e.g. hearts or aortic), we managed to implement a generalized L+S reconstruction framework for cerebrovascular 4D flow at 7T. The iterative hard-thresholding approach was adopted instead of the popular used soft-thresholding method because we found soft-thresholding underestimated the reconstructed phase value while hard-thresholding well preserved the phase information. The L+S reconstructed magnitude and phase value at an acceleration factor of 10 is comparable to the fully sampled reference and represents less errors compared with other compressed sensing based approaches.
Physics-based data-augmented deep learning without fully sampled dataset for multi-coil magnetic resonance imaging
Authors: Wu Ruoyou , Hu Chen , Li Cheng , Fan Wenxin , Zheng Hairong , Wang Shanshan
Published: August 2023

Self-supervised deep learning for MR reconstruction has shown high potential in accelerating MR imaging as it doesn’t need fully sampled dataset for model training. However, the performances of the current self-supervised methods are limited as they don’t take full utilization of the available under-sampled data. We propose a physics-based data-augmented deep learning method to enable faster and more accurate parallel MR imaging. Novel augmenting losses are calculated, which can effectively constrain the model optimization with better utilization of the collected dataset. Extensive experiments are conducted, and better reconstruction results are generated by our method compared to the current state-of-the-art methods.
A Novel Variable-Density Sampling Strategy for 3D Diffusion-Tensor Imaging with 3D-MUSER and Compressed Sensing
Authors: Xu Xiaorui , Liang Liyuan , Liu Xiaoxi , Chang Hing-Chiu
Published: August 2023

3D multi-slab multi-shot diffusion-weighted EPI can enable high-resolution diffusion-tensor imaging (DTI). Furthermore, in order to avoid the slab boundary artefacts, 3D-MUSER was proposed to enable 3D phase correction for effectively reconstructing nearly whole brain 3D DTI data acquired with only a single slab. Compressed sensing (CS) was also combined with 3D-MUSER to further reduce the scan time, but the previously proposed pseudo-random sampling strategy was still suboptimal for CS reconstruction. Therefore, we propose a novel variable-density k-space sampling strategy that is compatible with 3D-MUSER and able to achieve highly-accelerated and high-quality 3D DTI by taking the full advantage of CS.
Differential association of apparent diffusion coefficient, apparent myelin water fraction, and T1w/T2w ratio in white matter and grey matter
Authors: Chen Nan-Hao , Chen Li-Ping , Hsu Chia-Wei , Yang Chin-Hua , Peng Hsu-Hsia
Published: August 2023

The purpose of this study was to evaluate the differential associations among various myelin-related indices in white matter (WM) and grey matter (GM) to comprehend the alteration of microstructural integrity in brain tissue. We calculated mean, coefficient of variance (CV), and peak probability of ADC, apparent myelin water fraction (aMWF), and T1w/T2w ratio and found differential associations among myelin-related indices in GM and WM. In conclusion, measurements of ADC, aMWF, and T1w/T2w ratio as well as their correlations can help to understand characteristics of microstructural tissue integrity in GM and WM.
Diffusion Time Dependence of SANDI Analysis using High Gradient Diffusion MRI Data
Authors: Dong Tanxin , Song Jie , Lee Hong-Hsi , Tian Qiyuan , Huang Susie Y. , Fan Qiuyun
Published: August 2023

High gradient diffusion MRI has recently been demonstrated to be useful in mapping gray matter microstructure, despite of a few caveats arising from the challenges in comprehensively modeling the complex tissue environments. One example was the assumption of impermeable membranes in the SANDI model and hence its limitation in the presence of water exchange depending on the diffusion time (Δ) used in the MR experiments. We found time-dependence in the signal decay in cortical regions for Δ=19ms~49ms, suggesting fast exchange effects, which might be the cause of the observed time-dependence of the fitting parameters using the standard SANDI model.
To Evaluate Values of Six Cancer-Related DWI Models in Predicting the Levels of HER-2 Expression in Invasive Ductal Carcinoma of the Breast
Authors: Dong Cece , Xu Qian , Wang Haiyun , Shi Gaofeng , Shi Qinglei , Yan Xu , Yang Guang
Published: August 2023

In this study, we evaluated and compared the values of quantitative parameters derived from the six DWI models in the diagnosis of HER-2 expression levels in patients with IDC of the breast, including conventional mono-exponential model, IVIM, DKI, SEM, FROC, and CTRW models. We found that the CTRW model showed higher sensitivity in the predicting HER-2 expression levels than the other models. Meanwhile, a logistic regression model was built by combining parameters of the advanced DWI models, which showed a high diagnostic performance and may potentially be used in clinical practice.
The effect of contrast agent injection in MRCP under respiratory-triggered 3D-SPACE
Authors: Jin Dayong , Li Xin , Qin Yue , Zhu Yinhu , Liu Liyao , Qian Yifan , Tian Juan , Wang Shaoyu
Published: August 2023

This study compared the image quality of MRCP before and after contrast agent injection on a 3T MRI scanner using the same respiratory-triggered 3D-SPACE sequence. Our results showed that enhancement of contrast-to-noise ratio (CNR) and background suppression will make the contour of pancreaticobiliary system more clear, which indirectly improves the imaging effect of MRCP. We performed MRCP scanning during the delayed waiting period for enhanced scans, which shortens the overall scan time for such patients. In summary, respiratory-triggered 3D-SPACE MRCP imaging with enhanced contrast injection significantly improved the imaging quality of the pancreaticobiliary duct and shorten the overall acquisition time. It is worthy of promotion and application in clinical practice.
Accuracy of fat fraction when using IDEAL-IQ with a liver nonspecific extracellular contrast agent
Authors: Huang Lesheng , Li Hong yi , Chen Jun , Liu Weiyin , Cai Kai li , Jiang Jing hua , Zhang Wan chun , Tang Jia hui , Tian Guang jun , He Tao , Yang Kai lian , Hu Meng , Zhang Dong , Li Dan
Published: August 2023

To long-term track patients with liver disease is often carried out in clinics. It is also noted that nonspecific contrast agents change the relaxation time of tissue components, but few studies focus on the strong or weak FF alteration reflected by IDEAL-IQ derived measurements acquired before and after the contrast injection. In our study, we discovered significantly altered T1 values and fat fraction but not R2* even after the non-specific contrast agent achieved balanced condition at 3 minutes later of post-injection. Therefore, the liver non-specific contrast agent had an impact on the fat fraction measurements computed by IDEAL-IQ, and the utility of IDEAL-IQ should be performed before the injection of contrast agents to ensure the accuracy of fat fraction.
Differentiation of liver benign, primary malignant and secondary malignant tumors using MR DCE and mDIXON-Quant imaging
Authors: Ren Xue , Wang Jiazheng , Lin Liangjie , Chen Lihua , Song Qingwei , Pu Renwang , Zhao Ying , Lin Tao , Xu Qihao , Liu Ailian
Published: August 2023

The quantitative MR dynamic contrast-enhanced (DCE) and mDIXON-Quant imaging were used in this study for differentiation between benign and malignant liver lesions. The combination of DCE and mDIXON-Quant showed significantly improved diagnostic efficacy between benign liver tumors and primary malignant tumors, as well as between primary and secondary malignant tumors.
Improving estimation of cell size distribution using Fourier expansion-based deconvolution for microstructural parameters mapping (FED-MPM)
Authors: Shi Diwei , Li Sisi , Wang Yishi , Chen Li , Jiang Xiaoyu , Xu Junzhong , Zheng Quanshui , Guo Hua
Published: August 2023

Cellular microstructural parameters mapping can provide quantitative information for tumor diagnosis and treatment monitoring. Particularly, voxel-wise cell size distribution may provide critical clinical biomarkers to characterize heterogeneity of tumors. Currently, MRI-cytometry may measure such a distribution, but it “blurs” the distribution peaks and prevents differentiating different cell populations with different cell sizes. In this work, we develop a new approach to improve this and hence make it more practical to distinguish different cells. Detection of T cell infiltration for assessment of early response to immunotherapy may be a potential application of this method.
A deep learning dipole inversion method for QSM of arbitrary head orientation and image resolution
Authors: Xiong Zhuang , Gao Yang , Bollmann Steffen , Sun Hongfu
Published: August 2023

Due to the intrinsic data-driven property, many existing deep learning QSM methods can only be applied to local field maps with FOV orientation and image resolution consistent with the training data. This work proposes a novel and robust deep learning approach to reconstruct QSM of arbitrary head orientation and image resolution. Experiments are conducted on both simulated and in vivo human brain data to verify the proposed approach.
B0 shimming for 7T cardiac T2*-weighted MRI in large animals: practical demands and hardware limitations.
Authors: Terekhov Maxim , Lohr David , Hock Michael , Bille Maya , Aures Julia , Elabyad Ibrahim , Schnitter Florian , Bauer Wolfgang , Hofmann Ulrich , Schreiber Laura
Published: August 2023

Cardiac MRI with T2*-contrast at 7T is of particular interest because it is highly sensitive to cardiac tissue alterations after myocardial injury. A reliable T2*-contrast quantification and usage for tissue characterization require minimization of the inhomogeneity of the B0-field in the heart. In this work, we analyzed the B0-conditions achievable in longitudinal T2* measurements in the hearts of domestic pigs which during the experiment grew from 30 to 90 kg. B0 distribution statistics were summarized for the maps of individual slices. Demands on the 7T-scanners B0-shimming hardware (up to 3rd-order spherical harmonics) were analyzed.
Multi-center evaluation of the novel Beat Sensor Cardiac triggering technology
Authors: Hayes Carmel , Huang Yan Tu , Rick Manuela , Kroeker Randall , Bacher Mario , Pan Yue , Varghese Juliet , Simonetti Orlando , Jin Ning , Davids Rachel , Chow Kelvin , Vanliedekerke Rudy , Vangelder Marieke , Dehem Johan , Gatehouse Peter , Soundarajan Raj Kumar , Wage Ricardo , Azzu Alessia , Nielles-Vallespin Sonia , Speier Peter
Published: August 2023

A multi-center evaluation of a Pilot Tone-based triggering technique using the BioMatrix Beat Sensor has been performed in healthy volunteers and patients undergoing a cardiac MRI examination. At five different sites, and two different field strengths, a wide range of MR sequences typically used in standard cardiac MRI examinations were successfully triggered using the prototype Beat Sensor Cardiac triggering technology. By including a short signal training and RF calibration step at the start of the examination, the device proved robust across a range of subjects, thereby offering an alternative means to trigger cardiac examinations without the need to attach electrodes.
A Comprehensive MR Fingerprinting Development Kit (MRFDK)
Authors: Kluge Thomas , Nittka Mathias , Kannengiesser Stephan , Koerzdoerfer Gregor , Grund Christina , Buonincontri Guido , Pang Jianing , Boyacioglu Rasim , Chen Yong , Griswold Mark
Published: August 2023

Magnetic Resonance Fingerprinting (MRF), as an approach for multi-parametric, quantitative imaging, imposes new paradigms for sequence design in terms of optimized signal encoding and dictionary matching. In this work, we present a novel comprehensive framework and tool chain for rapid and efficient MRF prototyping. Key concepts are modularization and abstraction of the MRF experiment related to spin-physics, spatial encoding, and scanner hardware.
Whole-brain high-resolution MRSI at 7T with non-Cartesian FID-ECCENTRIC in glioma patients
Authors: Klauser Antoine , Strasser Bernhard , Bogner Wolfgang , Hingerl Lukas , Schirda Claudiu , Thapa Bijaya , Cahill Daniel , Batchelor Tracy , Lazeyras Francois , Andronesi Ovidiu
Published: August 2023

MR spectroscopic imaging (MRSI) can map specific metabolic alterations of glioma brain tumors. Increasing structural details for spatial distribution of metabolites is needed to probe tumor margins and heterogeneity with higher sensitivity and specificity. Here we evaluate the performance of ECCENTRIC, a newly developed non-Cartesian compressed sense MRSI method, to realize fast and high-resolution metabolic imaging at 7T ultra-high field in glioma patients. This is expected to improve diagnosis, prognostication, planning, guidance, and response assessment of treatment in glioma patients and other brain diseases.
Optimal experimental design of MR Fingerprinting for simultaneous quantification of T1, T2, and ADC
Authors: Hu Siyuan , McGivney Debra , Griswold Mark , Ma Dan
Published: August 2023

The MRF framework has been recently investigated to estimate T1, T2 and apparent diffusion coefficient (ADC) from a single scan with b-tensor encoding schemes. However, the current human-designed experiment protocol for multi-dimensional MRF is still subject to limited measurement accuracy. Here we propose to adapt the Cramer-Rao Bounds to optimize multi-dimensional MRF scan for simultaneous quantification of relaxation and diffusion. The optimization framework explores all possible combinations of MRF sequence parameters, including flip angles, TRs, b-values, and preparation modules to seek the optimal tissue parameter encoding scheme. The optimized sequence simultaneously improves the measurement precision of T1, T2 and ADC.
LeaRning nonlineAr representatIon and projectIon for faSt constrained MRSI rEconstruction (RAIISE)
Authors: Li Yahang , Ruhm Loreen , Henning Anke , Lam Fan
Published: August 2023

We proposed here a novel method for computationally efficient reconstruction from noisy MRSI data. The proposed method is characterized by (a) a strategy that jointly learns a nonlinear low-dimensional representation of high-dimensional spectroscopic signals and a projector to recover the low-dimensional embeddings from noisy FIDs; and (b) a formulation that integrates forward encoding model, a spectral constraint from the learned representation and a complementary spatial constraint. The learned projector allows for the derivation of a highly efficient algorithm combining projected gradient descent and ADMM. The proposed method has been evaluated using simulation and in vivo data, demonstrating impressive SNR-enhancing performance.
A Deep Learning Neural Network for Quantifying Metabolite Concentrations by Multi-echo MRS
Authors: Zhang Yan , Shen Jun
Published: August 2023

Multi echo techniques such as JPRESS consist of both short and long echoes and provide more diversified information for spectral fitting than techniques based on a single echo. However, fitting multi echo data is more challenging because signals attenuate with increasing echo time due to T2 relaxation, and the macromolecule background also varies across the echoes. We present a novel neural network architecture that directly maps the time domain JPRESS input onto metabolite concentrations. The testing results show the model can successfully predict in vivo metabolite concentrations from multi-echo JPRESS data after being trained with quantum mechanics simulated spectral data.
Surface-Volume Registration Produces Atlases More Realistic than Either Surface or Volume Registration
Authors: Ahmad Sahar , Wu Zhengwang , Lin Weili , Li Gang , Wang Li , Yap Pew-Thian
Published: August 2023

We show that spatial registration by simultaneously considering both tissue contrast and cortical geometry produces brain atlases that are more reflective of individuals than registration by considering only one of the two factors alone. Registration with tissue contrast alone produces atlases with blurred cortical structures. Registration with cortical geometry alone produces surface atlases that are artificially sharp but do not reflect surface attributes of individuals.
Pathway analysis of cerebral bicarbonate production from hyperpolarized [1-13C]pyruvate
Authors: Zaidi Maheen , Chen Jun , Ma Junjie , Wen Xiaodong , Bartnik-Olson Brenda , Park Jae Mo
Published: August 2023

Detection of [13C]bicarbonate in the brain from hyperpolarized [1-13C]pyruvate provides a unique opportunity for assessing cerebral mitochondrial function in-vivo. Although decarboxylation of the labeled pyruvate occurs within the mitochondria, the metabolic path of the injected pyruvate could be complex before being transported to intracellular space. In this study, we investigated the likelihood of pyruvate being converted to lactate prior to decarboxylation.
Differentiating TCA Cycle Activity of Gray and White Matter in Human Brain at 7T Using High Resolution Dynamic Deuterium MRS Imaging with SPICE
Authors: Zhu Xiao-Hong , Wiesner Hannes , Li Yudu , Zhu Wei , Wang Tao , Li Xin , Liang Zhi-Pei , Chen Wei
Published: August 2023

The emerging deuterium MRS (DMRS) imaging (DMRSI) technology has shown great promise in studying brain glucose metabolism, TCA cycle and glycolytic activity. In particular, its potential as a clinical tool for tumor detection in brain or other organs has attracted a lot of attention. However, the temporal and spatial resolution of dynamic DMRSI is limited by its low detection sensitivity. In this study, we proved that 7T high-resolution dynamic DMRSI combined with SPICE method can not only map the Glx production rate constant, but also distinguish the TCA cycle activity level between human brain gray matter and white matter.
Rapid, high-spatial resolution in vivo diffusion MRI with joint subsampling and reconstruction in k-,q- and RF-space
Authors: Ramos-Llorden Gabriel , Bilgic Berkin , Huang Susie Y.
Published: August 2023

In this work, we accelerate the high-SNR, high-spatial resolution in vivo diffusion MRI technique gSlider by applying subsampling jointly in the k,-q, and RF-encoding space. Good reconstruction quality is achieved if complementary information from the multi-dimensional space k-,q-, and RF-space is combined in a complementary fashion and the reconstruction problem is solved jointly.
Improved Structural Neuro-MRI with Triple TSE-based Synthetic MP-RAGE
Authors: Zhang Lei , McNaughton Ryan , Jara Hernan , Kennedy David , Marable Carmen , Hua Ning , Kuban Karl , O'Shea T. Michael , Fry Rebecca
Published: August 2023

Purpose: To develop and evaluate a metal-artifact robust triple turbo-spin-echo (TSE)-based synthetic MP-RAGE method. Methods: T1, T2 and PD maps generated from triple TSE, two MP-RAGE image sets simulated by the Bloch equation, and FreeSurfer brain segmentation were performed on 44 participants at age of fifteen. Results: Reduced artifact and homogenous synthetic MP-RAGE images were produced in orthodontic brace-wearing subjects. Comparable image contrast and FreeSurfer brain segmentation results were observed between synthetic and acquired MP-RAGE in normal subjects. Conclusion: Triple TSE based synthetic MP-RAGE may enhance conventional MP-RAGE in the neuroimaging studies of orthodontic brace-wearing subjects with reduced metal artifacts.
Dynamic Changes in the Pituitary Gland and Brain Stiffness with Treatment of Idiopathic Intracranial Hypertension
Authors: Cogswell Petrice , Murphy Matthew , Bhatti Muhammad , Cutsforth-Gregory Jeremy , Huston John , Chen John
Published: August 2023

Morphological changes in the pituitary gland and brain stiffness in idiopathic intracranial hypertension (IIH) are not well understood. We evaluated the difference in pituitary height and regional brain stiffness between IIH patients and controls and how these metrics change following acute and chronic treatment. The pituitary gland is smaller in IIH patients than controls and increases in size after chronic, but not acute, treatment of raised intracranial pressure. IIH patients have a different pattern of brain stiffness than controls, including stiffer occipital lobes. Following chronic treatment, the stiffness pattern becomes more like controls, though occipital stiffness does not significantly change.
AI-based Fully Automated 4D Flow Image Reconstruction and Post-Processing Pipeline in under 10 minutes.
Authors: Berhane Haben , Scott Michael , Pathrose Ashitha , McCarthy Patrick , Malaisrie Chris , Allen Bradley , Avery Ryan , Markl Michael
Published: August 2023

4D flow MRI provides comprehensive assessment of cardiovascular hemodynamics. However, the current clinical usage of standard 4D flow MRI is hindered by long scan times and extensive, time-consuming post-processing such as eddy current corrections, noise masking, and 3D vessel segmentation. We seek to address this by developing a fully automated image reconstruction and post-processing pipeline for highly-accelerated aortic 4D flow MRI (R=5.7-10.2). The fully automated pipeline was shown to provide good-to-excellent agreement in quantitative and hemodynamic measures to conventional 4D flow MRI (GRAPPA, R=2) with manual post-processing. Additionally, the pipeline only requires <10 minutes compared to 20 minutes manually.
Can blood flow and artery patency alterations in medium-to-large arteries predict alteration in cognitive function?
Authors: Zhang Kaiyu , Chen Zhensen , Chen Li , Canton Gador , Geleri Duygu Baylam , Pimentel Kristi , Balu Niranjan , Hatsukami Thomas , Yuan Chun
Published: August 2023

Association between brain tissue level perfusion and cognitive decline has been previously documented. However, contribution of blood flow and artery patency in medium-to-large arteries and its relation to tissue level perfusion and cognition remain unclear. In this study, 3D-TOF, ASL, and SNAP, an MRA technique sensitive to slow blood flow, were acquired at baseline and 12-months follow-up. A vascular map construction software was used to measure changes in medium-to-large arterial features. Changes in SNAP artery length and branch number during follow-up were significantly associated with changes in cognitive function, while no such association was found with ASL tissue level perfusion.
Reliability of Periventricular White Matter Cerebral Blood Flow using Different ASL protocols
Authors: Sadaghiani Shokufeh , Tackett William , Tisdall M. , Detre John , Dolui Sudipto
Published: August 2023

Cerebral blood flow (CBF) in periventricular white matter (PVWM) may provide a mechanistically specific biomarker of cerebral small vessel disease. We compared the reliability of PVWM CBF obtained from arterial spin labeling MRI acquired twice separated by a week, using different protocols involving standard, long labeling duration, single and multiple inflow saturation (MIS), and level of background suppression (BS), in young healthy participants. The MIS protocol with 99% BS significantly improved the temporal signal to noise ratio of the acquisition, with a subtle improvement of intersession-reliability. Reliability of PVWM CBF was of the same order as other conventional regions of interest.
Multi-delay pCASL with optimal post-labeling delay times by incorporating ATT probability distribution improves accuracy of CBF measurement
Authors: He Yining , Zhang Zhiyuan , Shao Xingfeng , Macaulay Timothy , Yan Lirong
Published: August 2023

The accuracy of CBF measurement in multi-delay ASL relies on the design of optimal PLDs. In this study, we optimized PLDs in 3D pCASL using a previously proposed optimization framework based on the Cramer-Rao lower bound optimization by incorporating different ATT prior distributions including in-vivo Gaussian distribution and uniform distribution. Evenly spaced PLDs were also applied for comparison. Both simulation and in vivo data suggest that optimal PLDs using in vivo ATT Gaussian distribution offer the best performance in terms of the accuracy of CBF estimation.
MR measures of regional cerebral blood flow and cortical thickness are tightly linked to the proximity of large cerebral arteries
Authors: Cote Samantha , Caceres Marco Perez , Dumais Felix , Lepage Jean-Francois , Whittingstall Kevin
Published: August 2023

Using time of flight magnetic resonance angiography, we explored how local variations in cerebral arterial morphology are related to cerebral blood flow (CBF) and cortical thickness (CT). We observed a significant, negative relationship between the proximity of a region of interest to an artery and CBF and CT such that regions proximal to large arteries have higher CBF and CT. These results highlight the importance of considering underlying cerebral vasculature when studying the human brain using MRI as it can lead to significant biases in commonly employed metrics.
Contrast-free MR Angiography and Venography for Visualization of Iliac Vein Compression Syndrome in less than 10 minutes
Authors: Malis Vadim , Kungsamutr Jirach , Bae Won , Zhang Xiaowei , Kassai Yoshimori , Hsiao Albert , Lane John , Miyazaki Mitsue
Published: August 2023

Iliac vein compression syndrome, known as May-Thurner syndrome (MTS), is a condition when the right common iliac artery constrains the flow in the left common iliac vein. Currently, ultrasound and CT venography (CTV) are the imaging modalities of choice for the diagnosis. We propose a framework to visualize iliac vein and artery utilizing contrast free MR venography and MR angiography in less than 10 minutes.
Predicting penumbral tissue death using intravoxel incoherent motion MRI in a canine large vessel occlusion model
Authors: Shazeeb Mohammed Salman , King Robert , Vardar Zeynep , Kolstad Josephine , Anagnostakou Vania , Henninger Nils , Gounis Matthew
Published: August 2023

In acute ischemic stroke due to large vessel occlusion (LVO), information about the penumbral tissue can be vital in making decisions on how to treat ischemic stroke patients in the clinic. This study investigated the use of intravoxel incoherent motion (IVIM) MRI in a canine LVO model to quantify the perfusion information in penumbral tissue prior to infarction. The IVIM parameters were assessed to predict the onset of penumbral tissue death. Of the 3 IVIM parameters, f showed the best utility in predicting penumbral tissue death.
Predicting Hematoma Expansion after Spontaneous Intracranial Hemorrhage Through a Magnetic Resonance-Based Radiomics Model
Authors: Seymour Samantha , Rava Ryan , Chudzik Mitchell , Snyder Kenneth , Waqas Muhammad , Davies Jason , Levy Elad , Siddiqui Adnan , Zhang Xiaoliang , Ionita Ciprian
Published: August 2023

Intracranial hemorrhage (ICH) is bleeding within the cranium and occurs within the brain tissue, ventricles, and intracranial space. Hematoma expansion following an ICH has been related to increased mortality and morbidity inpatients. To detect ICH patients at risk, machine learning models can be used to predict whether or not hematoma expansion will occur. This study aims to assess the feasibility of machine learning prediction models using a radiomics approach. The highest sensitivity results indicated as 95% confidence intervals are 0.68 ± 0.004 and 0.72 ± 0.004, were achieved by support vector machine and logistic regression classifier models, respectively.