bluuebunny/crossref_metadata_2025 huggingface dataset:
Altered dynamic cerebral perfusion during recovery in right hemisphere subcortical stroke
Authors: Miao Peifang , Wang Caihong , Wei Ying , Cheng Jingliang , Wang Kaiyu
Published: August 2023

To quantify cerebral blood flow (CBF) dynamic evolution and the relationship with clinical outcomes during recovery in right subcortical stroke patients,ASL and neurological examinations were performed repeatedly in 25 patients at 4 time points and 26 healthy controls (HCs) once.One-way Within-Subjects ANOVA and two sample test,pearson correlation analyses were performed.Compared with HCs, patients displayed continuous crossed cerebellar diaschisis.Increased CBF of contralesional sensorimotor cortex in the subacute and chronic are vital for recovery.Patients showed dynamic changes of CBF in contralesional cerebellum superior and occipital lobe,which were negatively correlated with memory.Findings provide a theoretical basis for functional impairment and recovery after stroke.
In vivo preliminary assessment of knee cartilage degeneration by Quantitative Ultrashort Echo Time MRI
Authors: Su Xiaolian , Tang Guangyu , Wu Pu-Yeh
Published: August 2023

Recent advances in UTE-MRI techniques development allow for quantitative measurements of tissues with very short T2. However, in vivo experiments are needed to extend its application in clinical practice. In this in vivo study, we found that both UTE-MTR and UTE-adiabatic-T1rho values indicated a moderate correlation with MOAKS Grading. Meanwhile, both of them had moderate diagnostic efficacy for the mild cartilage degeneration (MOAKS = 1). These findings suggested that quantitative UTE-MRI techniques have a great potential as imaging biomarkers for early OA diagnosis in clinic.
MIXTURE-DOSMA: Initial clinical research of a comprehensive and multi-parametric quantitative 3D knee MR exam in patients with knee joint pain.
Authors: Sakai Takayuki , Kwon Jihun , Yoneyama Masami , Murayama Daichi , Lu Quin , Desai Arjun , Chaudhari Akshay S , Miyati Tosiaki , Ochi Shigehiro , Watanabe Atsuya
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 into a Deep-learning, Open-Source Medical Analysis (DOSMA) framework for deep learning-powered musculoskeletal MR image and evaluated its clinical usefulness in patients with knee joint pain. We show that the combination of MIXTURE and DOSMA enables a comprehensive whole knee MR exam including 3D isotropic submillimeter imaging, T2- and T1ρ-mapping, and standardized image analysis. The clinical insight MIXTURE-DOSMA brings is demonstrated.
Reversible Changes in knee articular cartilage after half marathon: an MRI T2* study in heathy amateur runners
Authors: Zhang Yanjing , Zhang Li , Yao Wanzhen , Dai Siyu , Shu Dingbo , Ding Jianping , Liu Mengxiao
Published: August 2023

This research investigated the difference in T2* value of knee cartilage between amateur runners and non-exercisers, and examined the trends in the T2* value of knee cartilage in amateur runners before and after a half marathon. The results showed that the T2* value in lateral femorotibial joint of amateur runners was lower than non-exercisers. And the T2* value increased significantly after half-marathon running, and returned to the baseline level after 3 days. This indicates that long-term running may be beneficial to joint health; the effect of a half-marathon exercise on cartilage is reversible.
Quantifications of Relative Cerebral Blood Volume and MRS metabolites in Aging Collapsin Response Mediator Protein 1 Gene Knockout Mice
Authors: Hung Tzu-Ming , Huang Sheng-Min , Tsai Yun-Chieh , Chin Ting-Yu , Peng Hsu-Hsia
Published: August 2023

Aging and collapsin response mediator protein 1 (CRMP-1) gene knockout (KO) mice may exhibit neural disorganization in hippocampus and demonstrate memory and spatial learning dysfunction. The purpose of this study was to quantify relative cerebral blood volume (rCBV) and MRS metabolites in hippocampus in wild type and aging CRMP-1 KO mice. There was no significant difference of rCBV value between the two groups. In comparison with wild type (WT) mice, KO mice possessed significant lower Glx/t-Cr level in hippocampus, illustrating the altered neural transmission function in aging CRMP-1 KO mice.
Design and Construction of an 8-channel transceiver coil array for Rat imaging at 9.4T
Authors: Du Feng , Li Nan , Yang Xing , Zhang Baogui , Zhang Xiaoliang , Liu Xin , Zheng Hairong , Li Ye
Published: August 2023

The development of RF coils for the ultrahigh-field(UHF) MRI system is greatly significant for biomedical research as it determines imaging performance. In this work，an 8-channel transceiver array was designed and constructed for UHF MRI at 9.4 T to take full advantage of the benefits provided by higher field strengths. The phantom and in vivo studies were performed on preclinical 9.4 T MRI system to verify the proposed tansceiver performance. The results proved the ability of the proposed 8-channel transceiver array to obtain high signal-to-noise ratio (SNR) and high-spatial resolution MR images at 9.4T and indicated the potentiality for UHF MRIapplications.
Comparison of TGSE-BLADE, RESOLVE and SS-EPI for diffusion weighted imaging after cerebral aneurysmal clipping
Authors: Okuchi Sachi , Fushimi Yasutaka , Nakajima Satoshi , Sakata Akihiko , Hinoda Takuya , Otani Sayo , Sakurama Azusa , Wicaksono Krishna , Tagawa Hiroshi , Wang Yang , Ikeda Satoshi , Zhou Kun , Nakamoto Yuji
Published: August 2023

TGSE-BLADE DWI has been reported to reduce geometric distortion and susceptibility artifacts. However, it is unknown whether it reduces the clip-induced artifacts and improves image quality in patients after cerebral aneurysmal clipping. We compared the distortion and the artifacts between SS-EPI, RESOLVE, and TGSE-BLADE DWI in healthy volunteers and patients with a cerebral aneurysmal clip. TGSE-BLADE DWI has the best image quality regarding distortion and artifacts, especially at air-bone interfaces and near metal clips, which suggests that TGSE-BLADE DWI is a promising method for evaluating lesions at air-bone interfaces and scanning the patients with a clip.
Feasibility of non-invasive IDEAL-IQ MR imaging in assessment the correlation of fat fraction and hepatosomatic index in two in vivo fish species
Authors: Liu Dong , pan lei , Liu Weixin , Zhu Wenzhen
Published: August 2023

Fish is widely consumed as one of the main sources of animal food and plays a key role in the ecological processes in aquatic ecosystems. Of particular importance to assess the effects of aquatic pollution on the development and health of fish are organ somatic indices (HSI) and physiological indices (e.g. lipid deposition). Traditional assessment of somatic indices and lipid deposition is invasive and required to sacrifice examined animals. The present study was designed to assess HSI and lipid deposition in intraperitoneal tissues and livers of two fish species using a rapid, accurate and noninvasive magnetic resonance imaging method.
Assessment of intra-tumoral heterogeneity of prostate cancer using Intravoxel Incoherent Motion (IVIM)
Authors: Tadimalla Sirisha , Wang Yu-Feng , Sun Yu , Goodwin Jonathan , Rai Robba , Foster Sheryl , Haworth Annette
Published: August 2023

Mapping the intra-tumoral heterogeneity of perfusion before and after treatment offers the opportunity to identify hypoxic regions in the tumour and predict recurrent disease. Intravoxel Incoherent Motion (IVIM) parametric maps were obtained in patients with prostate cancer before and after radiation therapy. IVIM shows potential for the assessment of intra-tumoral heterogeneity of perfusion in prostate cancer.
HPA hyperactivity leads to time dependent alterations in serum metabolomics and inflammatory profile of closed head injured rats
Authors: Arora Palkin , Trivedi Richa , Singh Kavita , Kumari Megha
Published: August 2023

Closed head injury (CHI) can lead to both neurological disabilities and systemic alterations through HPA axis activation. A dysregulated HPA function allows relocation of energy substrates and alterations in metabolic pathways and systemic inflammation. Assessment of time-dependent changes in serum metabolites and inflammatory markers showed unique pattern between mild and moderate injured rats. These alterations were found to be associated with HPA hyperactivity with increased serum corticosterone levels and hypothalamic microglial activation post mild and moderate TBI. The study suggests an important relation between HPA axis induced changes in systemic metabolomics.
A preliminary study of real-time imaging for MR guided vascular intervention and image quality assessment
Authors: liu kunkun , Dai Weibin , Peng Yueyou , Shi Tianfeng , Liu Tingting , Song Ningning , Jiang Yueluan , Kang Yunhui , Meng Yanfeng
Published: August 2023

This study conducted a preliminary phantom study of MRI-guided vascular intervention, and evaluated the image quality of MR real-time sequences for MR compatible guidewire and balloon imaging with a 3D printed aorta phantom in a 3T MRI scanner. The results showed that the two real-time imaging sequences have sufficient guiding ability to guide the guidewire and balloon to the expected position. After comprehensive evaluation, it was concluded that the FLASH sequence was better than the True FISP sequence.
Learned Subspace Model Enables Ultrafast Neonatal Brain MR Imaging
Authors: Ke Ziwen , Guan Yue , Li Yudu , Zhang Yunpeng , Wang Tianyao , Meng Ziyu , Zhao Ting , Hu Yujie , Liu Ruihao , Zhuang Huixiang , Liang Zhi-Pei , Li Yao
Published: August 2023

Fast imaging is essential in neonatal brain MRI. Deep learning-based methods can provide high acceleration rates but their performance is instable when limited training data are available. Subspace model-based approach could reduce the dimensionality of imaging and improve reconstruction stability. This work presents a novel method to integrate neonate-specific subspace model and model-driven deep learning, making stable and ultrafast neonatal MR imaging possible. The feasibility and potential of the proposed method have been demonstrated using in vivo data from four medical centers, producing very encouraging results. With further development, the proposed method may provide an effective tool for neonatal imaging.
A Deep Unrolled Network for Reconstruction of Real-time Interventional MRI with Multi-coil Radial Sampling
Authors: He Zhao , Zhu Ya-Nan , He Yuchen , Chen Yu , Qiu Suhao , Kong Linghan , Zhang Xiaoqun , Feng Yuan
Published: August 2023

Interventional MRI (i-MRI) needs fast data acquisition and image reconstruction. We have shown that a Low-rank and Sparsity decomposition with Framelet transform model with Primal dual fixed point optimization (LSFP) could satisfy the reconstruction of real-time i-MRI. In this study, we unrolled the LSFP into a deep neural network, dubbed LSFP-Net, with multi-coil golden-angle radial sampling. Simulation results showed that LSFP-Net outperformed the state-of-the-art methods, and a phantom experiment demonstrated its potential for real-time i-MRI.
Coil Sensitivity Specific Optimization of Wave Encoding Gradient Trajectory for High Acceleration and Low Slew Rate
Authors: Su Shi , Yi Zheyuan , Zhao Yujiao , Xiao Linfang , Huang Ziming , Hu Jiahao , Zhang Junhao , Lau Vick , Man Christopher , Leong Alex , Wu Ed
Published: August 2023

Wave encoding offers high acceleration in parallel imaging by exploring the coil sensitivity variations in the readout dimension. However, typically preset wave gradients (i.e., sinusoidal trajectory) have never been optimized for specific receiver array coil, thus intrinsically limiting the maximum acceleration factor. We propose to optimize the gradient trajectory in a coil sensitivity specific manner by minimizing the squared L2-norm of off-diagonal elements in encoding correlation matrix. To guarantee an allowed maximum gradient slew rate, a bandlimited constraint is also introduced in optimization. This procedure leads to significant improvements in g-factor map and artifact reduction, especially at very high acceleration.
Accelerated Propeller FSE-DWI with Locally Low Rank Regularized Reconstruction
Authors: Yarach Uten , Saekho Suwit , Wantanajittikul Kittichai , Angkurawaranon Salita , Madla Chakri , Hanprasertpong Charuk , Sangpin Prapatsorn
Published: August 2023

Propeller FSE-DWI has been a method of choice in particular for Cholesteatoma. However, its natures such as prolong scan time, low signal-to-noise ratio (SNR), and phase variations among the blades have been challenging. Parallel imaging technique can be applied to reduce scan time, but phase estimation/correction is often compromised due to g-factor noise penalty. In this work, we develop an iterative reconstruction with locally low rank (LLR) regularization to maximize quality of propeller FSE-DWI images. As a result, LLR enable improving SNR up to SENSE factor of 4 compared to images obtained by vendor’s provided reconstruction engine.
SSTN: Self-supervised Triple-Network with Multi-scale Dilated-Convolution for Fast MRI Reconstruction
Authors: Sun Yuekai , Lv Jun , Chen Weibo , Wang He , Wang Chengyan
Published: August 2023

To solve the problem that fully-sampled reference data is difficult to acquire, we proposed a self-supervised triple-network (SSTN) for fast MRI reconstruction. Each pipeline of SSTN is composed of multiple parallel ISTA-Net blocks which consists of different scales dilated convolution layers. The results demonstrated that the proposed SSTN can generate better quality reconstructions than competing methods at high acceleration rates.
Low field multi-contrast MRI denoising using robust PCA
Authors: Ye Xinyu , Lian Yuan , Luo Hai , Wu Ziyue , Guo Hua
Published: August 2023

Owing to hardware advancements, a resurgence of interest has emerged in low field MRI systems recently. However, the intrinsic low signal to noise ratio (SNR) due to the low magnetic field strength has hindered the acquisition of high-resolution images on low field MRI systems. Here we propose a non-local robust PCA-based method to jointly denoise multi-contrast images acquired on a 0.5 T MRI system. In-vivo brain data are used to test the proposed method. The results show that the proposed method outperforms BM3D and BM4D denoising methods.
Exploring the AE model in predicting the prognosis of chemo-radiotherapy for cervical cancer based on clinical and radiomics’ features
Authors: Liu Miao , Wang Qi , Shi Gaofeng , Yang Li , Shi Qinglei
Published: August 2023

In this study, through optimizing data enhancement, data normalization, dimension reduction and feature screening schemes, an auto encoder (AE) based on clinical and radiomics features of ADC map was established and demonstrated high value in predicting the prognosis of locally advanced cervical cancer LACC in concurrent chemo-radiotherapy.
Multi-shot multi-b-value diffusion-weighted imaging using EPI with keyhole and locally low-rank reconstruction
Authors: Tang Xin , Hu Chenxi
Published: August 2023

A multi-b-value DWI imaging method based on multi-shot EPIK with continuously changing b values and Locally Low-Rank (LLR) constraint is proposed. The multi-shot EPIK acquisition improves resolution of multi-b-value DWI, and acquisition of the central k-space in every b-value bypasses the need for careful initialization. The LLR constrained problem is solved by a newly developed ADMM algorithm with robust performance. Preliminary data in healthy subjects showed that the proposed method outperforms LLR-POCS and SPA-LLR for reconstruction at high undersampling rates.
Language related cerebrum cerebellum pathway in human: a diffusion imaging‐based tractography study
Authors: Yin Hu , Zong Fangrong , Deng Xiaofeng , Zhao Jizong
Published: August 2023

Cerebellum has been proved to play an important role in no motor language function. The aims of this study including: building a new tractography atlas for cerebrum cerebellum pathway base on human connectome project (HCP) datasets which can be used in any study focused on these white matters. Some special tracking strategies were employed in the tracking process. The new tractography atlas was saved including a total of 11 tract templates and performed well in 30 healthy subjects. Both diffusion metrics and shape analysis metrics of these tracts were obtained.
Diffusion-weighted MRI evaluation of kidney tumor: Comparison of small field-of-view and conventional EPI techniques
Authors: Hu Junjiao , Zhang Huiting , Guo Hu , Benkert Thomas , Jiang Shan , Situ Weijun , Liu Jun
Published: August 2023

Image quality and apparent diffusion coefficient (ADC) values of conventional single-shot spin-echo echo-planar imaging (SS-EPI) and prototype small field-of-view EPI (Zoomit_EPI) diffusion-weighted imaging in kidney tumor were compared. Results showed that Zoomit_EPI had better image quality, including fewer distortion artifacts and blurring (p < 0.01), and clearer edges of the lesions. ADC value of Zoomit_EPI had a good correlation with those of SS-EPI (R2 = 0.91), but Zoomit_EPI had significantly larger ADC than SS_EPI with 80.4*10-6 mm2/s.
Pseudo-3D whole-brain ultra-thin-slice diffusion-weighted imaging of the brain utilizing deep learning constrained Compressed SENSE
Authors: Yoneyama Masami , Yoshida Takashige , Peeters Johannes , Kwon Jihun , Katsumata Yasutomo , Van Cauteren Marc
Published: August 2023

Deep learning constrained Compressed SENSE reconstruction (CS-AI) achieves significant improvement of image quality of whole-brain, ultra-thin-slice, high-resolution pseudo-3D diffusion imaging using single-shot EPI or single-shot TSE acquisition, compared with conventional SENSE and CS DWI.
QSM from the raw phase using an end-to-end neural network
Authors: Gao Yang , Xiong Zhuang , Fazlollahi Amir , Nestor Peter , Vegh Viktor , Pike G. Bruce , Crozier Stuart , Liu Feng , Sun Hongfu
Published: August 2023

Deep learning frameworks are emerging methods for solving QSM problems these days. However, most previous deep neural networks designed for QSM requires phase unwrapping and background field removal preprocessing procedures. This work presents a novel end-to-end network, namely Lap-Unet, for instant QSM and tissue field mapping from the raw phase in a single run. Comparative results find that the proposed method resulted in more accurate and robust reconstructions than previously established single- and multi-step methods, particularly for QSM of intracranial hemorrhages, which has been challenging due to fast signal decays.
Evaluation of k-space uniformity and blade number-optimized (K-B-optimized) binning method for abdominal 4D-DW-Propeller-EPI
Authors: Wang Lu , Li Tian , Cai Jing , Liang Liyuan , Chang Hing-Chiu
Published: August 2023

Four-dimensional diffusion-weighted imaging (4D-DWI) attracts lots of attention in MRI-guided radiotherapy since it can provide functional information and better delineate the tumor. However, the previously reported 4D-DW-Propeller-EPI technique used amplitude data binning with continuous interval to sort the blade data that might lead to non-uniform distribution of k-space sampling, therefore being suboptimal for subsequent Propeller-EPI reconstruction. Thus, we propose a new (K-B-optimized) binning method to consider the requirement of propeller reconstruction during the sorting of blade data, thereby improving the k-space distribution. Simulation and in-vivo studies demonstrated that the new binning method can improve the data quality of 4D-DW-Propeller-EPI.
Characteristics of three factors that influence the diffusion signal with PGSTE and OGSE
Authors: Oshiro Hinako , Hata Junichi , Nakashima Daisuke , Haga Yawara , Hayashi Naoya , Yoshimaru Daisuke , Hagiya Kei , Okano Hideyuki
Published: August 2023

We investigated the characteristics of diffusion quantification values in a restricted structure with a capillary phantom in PGSTE and OGSE. Smaller structure sizes require shorter diffusion times for structure estimation. In OGSE, we observed a transition of diffusion coefficients under 10 ms for capillary sizes from 6-12 μm, but no differences for those from 25-100 μm. Moreover, it was necessary to consider the temperature dependence of the diffusion measurement at low temperatures. We developed a system to measure the effects on diffusion quantification values at three phases of different temperatures, structure sizes, and diffusion times.
Discriminating Rectal Cancer Grades using Restriction Spectrum Imaging
Authors: Xiong Zhongyan , Geng Zhijun , Lian Shanshan , Yin Shaohan , Xu Guixiao , Zhang Yunfei , Dai Yongming , Zhao Jing , Ma Lidi , Liu Xin , Zheng Hairong , Xie Chuanmiao , Zou Chao
Published: August 2023

Restriction spectrum imaging (RSI) is a novel diffusion model that captures the distinct diffusion behavior of tumors. It separates water diffusion into several microscopic compartments. The restricted compartment correlating to the tumor cellularity is expected to be a potential indicator of rectal cancer aggressiveness. To assess the ability of RSI model for rectal tumor grading, we applied a three-compartment RSI model to DWI images of patients with different histopathological grades of rectal cancer. The RSI model demonstrated its ability to discriminate the rectal cancer of low and high grades, and the results outperforms the traditional ADC model and DKI model.
Intra-hippocampal fiber tracking and connectome from submillimeter DTI of the human hippocampus in vivo and ex vivo
Authors: Ma Yixin , Truong Trong-Kha , Bruce Iain , Badea Alexandra , Davis Simon , Yeh Chun-Hung , Petrella Jeffrey , Song Allen
Published: August 2023

The hippocampus plays an essential role in memory; the impairment in intra-hippocampal connectivity could result in memory loss in neurodegenerative dementias. We generate intra-hippocampal fiber tracts and connectomes from submillimeter isotropic DTI images for repeated scans from the same subjects and across different subjects. We characterize the fiber orientations and connectivity across hippocampal subfields by registering all in vivo scans onto the population template and we compare these results with those from an ex vivo human brain sample. This method can assess intra-hippocampal connectivity in vivo, which could be potentially used to diagnose neurodegenerative diseases.
High dynamicity of cortical depth-dependent connectivity states
Authors: Pais-Roldan Patricia , Ramkiran Shukti , Yun Seong Dae , Shah Jon
Published: August 2023

We assessed resting-state fMRI acquired with high spatial resolution with a dynamic functional connectivity analysis involving multiple cortical ROIs and depths. Two states relevant to the normalized global laminar connectivity were identified in healthy volunteers (superficial vs. deep layer connectivity predominance). Mean laminar connectivity states were much more dynamic than the states identified in a routine ROI-based dynamic connectivity analysis, suggesting the potential of high-spatial-resolution fMRI to reveal time-varying features in the human brain.
Cardiac Quantitative Susceptibility Mapping for Mitral Annular Calcium: Validation using Quantitative Calcium Scoring on Computed Tomography
Authors: Villar-Calle Pablo , Li Jiahao , Saffioti Alice , Johannesen Justin , Tak Katherine , Meier Rachel , Kim Jiwon , Truong Quynh , Wang Yi , Spincemaille Pascal , Weinsaft Jonathan
Published: August 2023

This study tested cardiac MRI cardiac quantitative susceptibility mapping (QSM) for measurement of mitral annular calcification (MAC) using the reference of computed tomography (CT). QSM entailed a free-breathing ECG-triggered multi-echo 3D GRE sequence with diaphragmatic navigation via ECG-gating (1D respiratory navigator, 4mm window, acquisition time ~7 minutes, navigator efficiency 36%, spatial resolution 1.5×1.5×5mm3). Among 24 patients undergoing MRI and CT (mean 3.9±3.4 months), annular susceptibility decreased stepwise (p<0.001) and R2* increased (p<0.05) among patients stratified by CT mitral annular calcium score. Both QSM (AUC=0.950, p=0.005) and R2* (AUC=0.938, p=0.007) yielded excellent diagnostic performance for advanced mitral annular calcification on CT.
A NOVEL OPEN-SOURCE CARDIAC SEGMENTATION FRAMEWORK FOR CINE MRI
Authors: León Manuel A. , Salas Rodrigo , Uribe Sergio , Sotelo Julio
Published: August 2023

Cardiac contour delineation currently presents several proposals for automatic segmentation in short-axis MRI. However, most of them have drawbacks such as low accuracy with images from other MRI scanners, lack of description of the algorithms, and difficult access for clinical or research use. For this reason, we present VENTSEG, a deep learning framework for cardiac segmentation implemented in Matlab and Python. Our dice coefficient results segmenting images from the CNN validation set are 85.55% and 96.17% on anonymized clinical data. These results demonstrate the generalization of the framework on multidomain images.
Myocardial stress field from combined CMR and FEM in ALL survivors
Authors: Ghafarinatanzi Mehdi
Published: August 2023

The objective of this study is to investigate the myocardial 3D strain stress field of the patient-specific left ventricles in children with acute lymphoblastic leukemia (ALL) after treatment. The virtual field-finite element approach is applied to the 3D mesh generated tetrahedral for each patient-specific geometry over the cardiac cycle. The results illustrate the difference in distribution stress and displacement field for each LV subject.
Neural style transfer: Applications in cardiac MR image registration
Authors: Turgut Alper , Van Houten Matthew , Wang Junyu , Feng Xue , Salerno Michael
Published: August 2023

Contrast-enhanced cardiac magnetic resonance (CMR) stress perfusion imaging shows excellent utility in evaluating coronary artery disease1. Registering perfusion CMR image series is difficult due to the varying image contrast. Neural style transfer is a deep learning method used to transfer the “style” of one domain to another while preserving the content. Two neural style transfer networks were implemented in Python using TensorFlow and PyTorch. Training of each network was done using three, slice matched patient profiles and cine-like perfusion images were generated and registered. This method is compared to a KL-transform based registration approach.
Identification of Hemodynamic Biomarkers for Bicuspid Aortic Valve induced Aortic Dilation using Machine Learning
Authors: Franco Pamela , Sotelo Julio , Guala Andrea , Dux-Santoy Lydia , Evangelista Arturo , Rodríguez-Palomares José , Mery Domingo , Salas Rodrigo , Uribe Sergio
Published: August 2023

Several studies have demonstrated the existence of altered hemodynamics in bicuspid aortic valve (BAV) patients. The objective of this study was to identify which hemodynamic parameters allow an accurate classification between BAV patients with dilated and non-dilated ascending aorta using machine learning (ML) algorithms.
On the evaluation of different variants of diffusion-weighted double-echo steady-state (dwDESS) sequences
Authors: Katscher Ulrich , Steinhorst Bjoern , Meineke Jakob , Keupp Jochen
Published: August 2023

Double-echo steady-state (DESS) sequences are a promising candidate for diffusion weighted imaging (DWI) free of geometric distortions. The design of diffusion-weighted DESS (dwDESS) sequences allows waveform variations for the diffusion weighting gradient GD. While dwDESS sequences were originally introduced with unipolar GD, also bipolar or higher order GD are possible. A balanced GD (i.e., with nulling zeroth momentum) typically necessitates a spoiler gradient to suppress banding artefacts, which additionally increases the degrees of freedom in the design of dwDESS sequences. This study explores different dwDESS sequence variants according to predefined optimization criteria.
Accelerating phase-cycled bSSFP using sparsity across the phase-cycling dimension
Authors: van Rijssel Michael , van den Berg Cornelis , Noordman Stan , van Lier Astrid
Published: August 2023

Banding artifacts in balanced steady state free precession images can be resolved by applying radiofrequency phase cycling. Unfortunately, the scan time increases linearly with the amount of phase cycles acquired, hindering clinical adoption of this sequence. We aimed to reduce the amount of phase cycles that need to be acquired by employing a signal model in an iterative reconstruction. Preliminary validation of this algorithm was performed in-silico and in a phantom. Results show excellent agreement in-silico (relative mean absolute error, RMAE, 0.0045%) and in phantom tubes with T1 and T2 values in the physiological range (RMAE 3-4%).
Prediction of new diffusion MRI data is feasible using robust machine learning algorithms for multi-shell HARDI in a clinical setting
Authors: Murray Cayden , Oladosu Olayinka , Zhang Yunyan
Published: August 2023

High Angular Resolution Diffusion Imaging (HARDI) is a promising method for the analysis of microstructural changes. However, HARDI acquisition is time-consuming and therefore impractical in clinical settings. We developed 2 neural networks for predicting non-acquired diffusion datasets based on diffusion MRI: Multi-layer Perceptron (MLP) and Convolutional Neural Network (CNN). Through systemic training and evaluation with healthy public data and local MS patient MRI, we found that both the MLP and CNN models could predict high b-value from low b-value data that allowed the assessment of Neurite Orientation Dispersion and Density Imaging (NODDI) outcomes. Neural networks can make NODDI clinically viable.
A mesh-based CNN for the evaluation of MR RF-induced heating of complex-shaped passive implants
Authors: Chang Jiajun , Zheng Jianfeng , Guo Ran , Lan Qianlong , Thakore Mayur , Kainz Wolfgang , Chen Ji
Published: August 2023

In this research, a convolutional neural network (CNN) model is developed to predict the RF-induced heating for several tibia plate systems. One thousand four hundred and sixteen device configurations were developed, and the peak 1g-average SAR values were extracted. A subset of the data was used as training set and simulation meshes were used as the input of the CNN model. Results showed a quick network convergence and high correlation. The network also had a low absolute and percentage error level. This demonstrates that one can potentially use CNN model to predict the RF-induced heating of plate systems.
Evaluation of 3D Tailored Excitation Sequences on the MRI Safety Assessment of Transvenous Implantable Pacemaker, ICD or CRT System
Authors: Feng Kevin , Jiang Ruoli , Sison Shiloh
Published: August 2023

A 3D tailored excitation sequence at 3T was found to have peak RF simultaneous with gradient slewing. The exposure levels generated by this sequence were determined and impact to the transvenous implantable pacemakers, implantable Cardioverter Defibrillators (ICDs) and Cardiac Resynchronization Therapy (CRT) systems safety evaluation of RF and gradient voltages was assessed. It is demonstrated that the combined RF and gradient level is expected to be covered by the separate RF and gradient test level required by ISO/CD 10974, and the bandwidth of the 3D sequence is well within the frequency ranged specified in ISO/CD 10974.
Harmonization of Cortical Thickness Measurements Throughout the Human Lifespan
Authors: Ahmad Sahar , Nan Fang , Wu Ye , Wu Zhengwang , Lin Weili , Wang Li , Li Gang , Wu Di , Yap Pew-Thian
Published: August 2023

Pooling and integrating diverse imaging data across multiple sites is key to big data analytics in neuroimaging. Data amassed from multiple studies are inevitably heterogeneous due to differences in scanners, acquisition protocols, and post-acquisition image processing pipelines, substantially complicating downstream analyses. Here, we present a harmonization technique for multi-site large-scale longitudinal and cross-sectional data. We demonstrate the utility of our method in removing non-biological variability in cortical thickness measurements of individuals from birth to 100 years of age.
Assessment of human brain pyruvate oxidation using functional hyperpolarized 13C MRS
Authors: Zaidi Maheen , Thomas Binu , Ma Junjie , Pena Salvador , Chen Jun , Ratnaker James , Malloy Craig , Bartnik-Olson Brenda , Park Jae Mo
Published: August 2023

[13C]Bicarbonate production from hyperpolarized [1-13C]pyruvate in the brain is directly related to pyruvate oxidation and, thus serves a potential biomarker of brain function. In this study, we assessed time-wise bicarbonate production in the visual cortex during activation with minimal perturbation of its precursors, pyruvate and lactate, using a multichannel 13C receive array, a spectral-spatial RF pulse that fully excites bicarbonate signals, and dynamic 13C MRS. The real-time changes of bicarbonate production in response to visual stimuli were observed in healthy volunteers.
Discovery of two novel deep gray matter brain iron networks through an Independent Component Analysis of Quantitative Susceptibility Maps
Authors: Reeves Jack , Bergsland Niels , Jakimovski Dejan , Salman Fahad , Damm Juliane , Meineke Nicklas , Dwyer Michael , Zivadinov Robert , Schweser Ferdinand
Published: August 2023

Magnetic resonance imaging (MRI) studies have shown age and neurological disease affect iron concentrations in the deep gray matter (DGM). However, it is unknown whether iron accumulation occurs independently across DGM regions or in inter-regional patterns, i.e. “iron networks”. Here, we identified two highly reproducible, inter-regional DGM iron networks by applying independent component analysis (ICA) to quantitative susceptibility maps (QSM) from healthy volunteers. Areas of network overlap had relatively high iron concentrations and each network was related to separate environmental variables, indicating they have independent mechanisms of iron change. Our results advance the understanding of brain iron physiology.
Unsupervised learning with multi-parametric diffusion MRI to detect brain injury in concussed athletes
Authors: Muftuler L. Tugan , Meier Timothy , McCrea Michael
Published: August 2023

Despite high prevalence of concussion in contact sports, there is still a lack of reliable, unbiased biomarkers of brain injury and recovery following sport-related concussion. The changes in imaging biomarkers after concussion are generally subtle such that signs of abnormalities are detected only in group analyses with large cohorts. Although diffusion MRI techniques show promise, detecting injury in individual subjects is still a challenge. The goal of this project is to identify potential signatures of brain injury in an individual subject with concussion using an unsupervised learning method using parameters derived from diffusion kurtosis imaging (DKI).
Systemic inflammation alters brain blood flow and R2*: An in-vivo 9.4T MRI animal study
Authors: Shafqat Qandeel , Wu Ying , Hamilton A. Max , Hashem Mada , Dunn Jeff
Published: August 2023

Systemic inflammation is linked to a range of neurological diseases. Reductions in cerebral blood flow (CBF) and the presence of brain hypoxia have been detected in animal models of inflammation and in multiple sclerosis, a disease with significant inflammation. Reduced CBF combined with hypoxia could exacerbate damage in neuroinflammatory conditions. To study this link, we used in-vivo 9.4T MRI to quantify CBF and R2*, a marker of deoxyhemoglobin, following systemic inflammation induced by bacterial lipopolysaccharide. We found reduced CBF and increased R2* in 4 regions, including the cortex and hippocampus—indicating that inflammation is accompanied by hypoxia and reduced CBF.
INTRACRANIAL EFFECTS OF ARTIFICIAL GRAVITY: A 3T MRI STUDY
Authors: Kramer Larry , Hasan Khader , Zhang Xu , Macias Brandon , Marshall-Goebel Karina , Laurie Steven , Bershad Eric
Published: August 2023

Headward fluid shift is a natural consequence of working in microgravity. It is theorized to be the cause of changes in brain morphology and the development of optic nerve pathology in astronauts. This study looked at the application of artificial gravity in the form of short-arm centrifugation at 0.3g as a potential countermeasure in 24 healthy volunteers over a 60 day period. Headward fluid shift was simulated using a head down tilt bed rest model. Both continuous and intermittent artificial gravity for 30 minutes per day failed to show any benefit on intracranial changes associated with chronic headward fluid shift.
Is T2 a biomarker of inflammation in normal appearing gray matter: Maybe!
Authors: Shafqat Qandeel , Tariq Rehman , Muhammed Rania , Wu Ying , Dunn Jeff
Published: August 2023

With the reduction in use of gadolinium enhanced MRI for assessment of neuroinflammation, it is important to identify new non-invasive biomarkers of brain inflammation, as well as to understand the link between inflammation induced pathology and MRI. We used quantitative T2, behaviour and histology to study gray matter in an LPS mouse model of inflammation. There was a significant reduction in T2, along with behaviour and histological markers indicating inflammation. Although T2 appears useful as biomarker for inflammation, it may be that the precision needed will make it difficult to implement in patients.
A Multi-Sequence, Interleaved MRI-DMI Protocol for Human Brain
Authors: Liu Yanning , De Feyter Henk , Fulbright Robert , McIntyre Scott , Nixon Terence , de Graaf Robin
Published: August 2023

Deuterium Metabolic Imaging (DMI) is an emerging method to spatially map metabolism in vivo. To enhance the time efficiency of a combined MRI-DMI protocol, interleaved MRI-DMI acquisitions were developed for multiple clinical MRI sequences. The protocol includes four MRIs that are commonly used in neurological MRI exams, namely FLAIR, T2W, SWI and T1W MP-RAGE, with DMI acquisition in parallel, acquired in 28 minutes. We demonstrate the performance of the interleaved MRI-DMI protocol on healthy human brain and discuss the guiding principles as well as limitations of extending other MRI sequences with DMI using the presented interleaving strategy.
Velocity to Pressure Mapping in Stenotic Pulsatile Flows with an Encode-Decoder Deep Network
Authors: Nath Ruponti , Kazemi Amirkhosro , Stoddard Marcus , Amini Amir
Published: August 2023

We propose a novel deep learning based approach to estimate pressure drop inside a stenotic valve from 4D Flow MRI velocities. A neural network architecture learns the relationship of three directional velocities and predicts pressure as output. The network was tested on real 4D flow MRI data of aortic valvular flow both in-vitro and in vivo. Estimated in-vitro pressure drop by proposed method shows (3-5)% relative pressure drop error with corresponding CFD pressure. Estimated In-vivo pressure drop was also compared with doppler Echocardiography and simplified and modified Bernoulli at peak systole timepoints in 10 patients with aortic stenosis.
Assessment of arterial pulsatility of cerebral perforating arteries using 7T high-resolution dual-VENC phase-contrast MRI
Authors: Tang Jianing , Ma Samantha , Yan Lirong
Published: August 2023

A dual VENC strategy was applied in 2D high-resolution phase-contrast MRI to improve the sensitivity of arterial pulsatility measurement in cerebral perforating arteries at 7T. Compared to a single VENC of 40cm/s, significant increase in the number of detected perforators was observed using a dual-VENC approach with VENC of 20cm/s and 40cm/s. Reproducibility of arterial pulsatility measurement in perforating arteries was evaluated in test-retest experiments. Good agreement was achieved between test-retest pulsatility measurements.
Validation of Qp/Qs quantification based on 4D flow MRI: effects of scan acceleration techniques
Authors: Fujiwara Takashi , Englund Erin , Moghari Mehdi , Fonseca Brian , Browne Lorna , Barker Alex
Published: August 2023

The ratio of pulmonary to systemic blood flow (Qp/Qs) is a clinically important index to estimate the existence and amount of cardiovascular shunt flow and to determine the need for surgical intervention for congenital heart disease patients. Accelerated 4D flow MRI is capable of measuring Qp/Qs in a single acquisition, but its accuracy and reliability are not well established. We compared conventional 2D phase-contrast MRI and two 4D flow MRI acquisitions with different acceleration techniques to investigate accuracy of Qp/Qs quantification with accelerated 4D flow in adult healthy volunteers (N=10). Consequently, we found no statistical differences in Qp/Qs.
Potential regulation of cerebral blood flow by the basal forebrain
Authors: Zhang Zongpai , Riley Elizabeth , Anderson Adam , DeRosa Eve , Dai Weiying
Published: August 2023

The basal forebrain (BF) has a known regulatory role in the cholinergic vasodilatory system, increasing cerebral blood flow (CBF) in the cerebral cortex using animal studies. However, parallel human studies have never been performed. Thirty-three young adults and 27 older adults were tested for the aged-related changes in arterial transit time (ATT) and CBF, which were measured using arterial spin labeling (ASL). We observed the age-related CBF and ATT changes in the basal forebrain and other brain regions, which provide a foundation for investigating the regulatory role of the basal forebrain on the cholinergic vasodilatory system.
Mapping the Age Effect on Cortical Arterial Arrival Time and Perfusion using multi-delay pCASL
Authors: Sun Yutong , Chang Paul , Chen J. Jean
Published: August 2023

Multi-delay arterial spin labeling (ASL) has made it possible to non-invasively quantify cerebral hemodynamic changes in aging, including cerebral blood flow (CBF) and arterial arrival time (ATT). However, limited numbers of studies exist to focus on the spatial heterogeneity of age effects on both CBF and ATT. In this study, we map the relationships between age, CBF and ATT on the cerebral cortex using multi-delay pseudo-continuous ASL (pCASL) data from the Human Connectome Project in Aging.
Volumetric Renal Perfusion Imaging with pCASL – Comparison of 3D TSE and 3D GraSE Readout
Authors: Zhou Limin , Wang Yiming , Madhuranthakam Ananth
Published: August 2023

Recent consensus recommended SE-EPI as the preferred readout for 2D single-slice renal perfusion imaging using pCASL. Compared to single-slice 2D acquisition, 3D acquisitions can achieve higher SNR, larger slice coverage, and optimal background suppression in similar scan times. In this study, we compared 3D GRASE, the recommended 3D readout for brain perfusion imaging, with an optimized 3D TSE readout using Cartesian acquisition with spiral profile reordering and Variable Density Sampling (VD-CASPR) in 4 healthy volunteers for volumetric renal perfusion imaging. Results showed that 3D pCASL with TSE VD-CASPR is more robust and has higher SNR than 3D pCASL with GRASE.
Improving Spatial Resolution of Brain and Renal ASL MR Images using 3D Cartesian TSE and Compressed SENSE Reconstruction
Authors: Wang Yiming , Zhou Limin , Pinho Marco , Pedrosa Ivan , Maldjian Joseph , Madhuranthakam Ananth
Published: August 2023

Arterial spin labeled (ASL) MRI is often acquired at reduced spatial resolution due to lower signal to noise (SNR), although higher spatial resolution within clinically feasible scan times is desired. In this study, we applied Compressed Sensing–Sensitivity Encoding (CS-SENSE) to 3D Cartesian TSE with Variable Density (VD) sampling to achieve higher spatial resolution ASL-MRI without prolonging acquisition time. Perfusion images acquired with CS-SENSE showed good SNR and image quality in both brains and kidneys, without introducing bias to perfusion quantification. This may be particularly useful to measure perfusion changes in small-sized lesions in both brains and kidneys.
Customized whole-brain covering GRASE in multi-delay pCASL for distinct contrasts and adequate SNRs in hemodynamic parameter mappings
Authors: Hu Yichen , Wei Qing , Zhou Zhongyang , Hu Junpu , Xie Jun , Xu Jian
Published: August 2023

We report that manipulation of GRASE readout with SORT view-ordering in multi-delay ASL on either gradient echo trains for adjusted spatial resolutions or FSE train for modulated T2-blurring can significantly alter the perfusion hemodynamic parameter mapping contrasts among tissues and among cerebral lobes under different pathways of blood circulation, and can meanwhile regulate the SNRs of the maps. Among the performed GRASE designs, the readout with moderate spatial resolution and segmented kz is recommended for sharp GM/WM contrasts in CBF and ATT maps in conjunction with distinct contrast between anterior and posterior circulations in the ATT map, with adequate SNRs.
Blood-brain barrier permeability in response to caffeine challenge
Authors: Lin Zixuan , Jiang Dengrong , Liu Peiying , Moghekar Abhay , Lu Hanzhang
Published: August 2023

Caffeine is known to alter brain physiology by acting as an adenosine antagonist, but its effect on the BBB permeability to water is not fully elucidated. In this study, we utilized water-extraction-with-phase-contrast-arterial-spin-tagging (WEPCAST) MRI to investigate the change of BBB permeability after caffeine challenge in young healthy adults. Results showed that after caffeine ingestion, water extraction across BBB increased as global cerebral blood flow decreased, while the BBB permeability to water remained unchanged, indicating a relative stable BBB function in response to caffeine challenge, which can be important for normal brain function.
Imaging Ascending Thoracic Aortic Aneurysm Wall Stretch: A Comparison to Biaxial Mechanical Testing
Authors: Dong Huiming , Haraldsson Henrik , Leach Joseph , Zhou Ang , Ballweber Megan , Zhu Chengcheng , Xuan Yue , Wang Zhongjie , Hope Michael , Ge Liang , Epstein Frederick , Saloner David , Tseng Elaine , Mitsouras Dimitrios
Published: August 2023

Ascending thoracic aortic aneurysm (aTAA) can result in life-threatening rupture or dissection. Displacement encoding with stimulated echoes (DENSE) is a non-invasive phase-contrast MRI technique that can measure aTAA wall deformation during the cardiac cycle. This study investigated DENSE-derived aTAA wall stretch in patients and found that the ratio between aTAA stretch and descending aorta stretch was different in patients who met surgical repair criteria from those who did not. Moreover, mechanical properties of aTAA specimens from patients who underwent surgery correlated significantly with in vivo DENSE measurements. Our findings suggest DENSE as a potential imaging marker for understanding aTAA progression.
Radial perfusion cardiac magnetic resonance imaging using deep learning image reconstruction.
Authors: Assana Salah , Morales Manuel , Nakata Kei , Sai Eiryu , Amyar Amine , Haji-Valizadeh Hassan , Nezafat Reza
Published: August 2023

Myocardial perfusion assessment using cardiac MRI allows non-invasive assessment of myocardial ischemia. In myocardial perfusion sequence, imaging is collected after a saturation pulse. An alternative approach based on steady-state imaging with radial sampling has been recently proposed. However, image reconstruction using compressed sensing in steady-state myocardial perfusion remains long and clinically not feasible. In this study, we sought to develop a deep learning-based image reconstruction platform for myocardial perfusion imaging.
Resting-state based Cerebrovascular Reactivity (CVR) mapping at high spatial resolutions
Authors: Kartchner Lincoln , Jiang Dengrong , Joshi Parimal , Xu Cuimei , Lu Hanzhang , Liu Peiying
Published: August 2023

Cerebrovascular reactivity (CVR) is typically assessed with a carbon dioxide (CO2) stimulus combined with BOLD fMRI. Recently, resting-state BOLD fMRI has been shown capable of generating CVR maps, providing a potential for broader CVR applications in neuroimaging studies. However, prior RS-CVR studies have primarily been performed at a spatial resolution of 3-4mm3 voxel sizes. It remains unknown whether RS-CVR can also be obtained at high-resolution without major degradation in image quality. In this study, we investigated the feasibility of high-resolution CVR mapping based on resting-state fMRI data. Our results showed good CVR quality can be obtained at 2-3mm3 voxel sizes.