bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiplex network analysis reveals disrupted brain processing speed in children with prenatal alcohol exposure
Authors: Liang Xiaoyun , Yeh Chun-Hung , Anderson Peter
Published: August 2023

In this study, we applied a method that integrates dynamic functional connectivity using the multiplex network approach to enhance the sensitivity to subtle alterations of functional connectivity on participants subject to PAE. Our results demonstrated its capability in characterizing subtle brain network changes in children with low-moderate PAE. The lower values of the PAE T1-T3 group indicates that the information processing speed could have been compromised due to PAE. In line with literature, the distinct findings between male and female groups revealed that PAE may induce gender-dependent brain disruptions and males are more susceptible to PAE.
The structure-function coupling of aging brain
Authors: Zhang Hui , Cao Peng , Mak Henry , Hui Edward
Published: August 2023

We aim to investigate the effect of aging, sex, years of education, total cognition, and the disease burden of small vessel disease, the most cause of vascular dementia, on not only the coupling of the entire brain, but also the coupling of intra and inter-functional networks. We have demonstrated varying effect of sex, years of education and total cognition on global and intra/inter-network couplings.
Thalamus regulates emotional performance in different pathways with CSVD involved
Authors: Wang Bei , Guo Cen , Wang He , Han Yan , Chu Ying-Hua
Published: August 2023

With the help of 7T Imaging, we investigated the association between the thalamic anterior vascularization patterns and emotions, including depression and anxiety. Cerebral small vessel diseases were considered as a risk factor for emotional performance. The thalamic anterior vascularization pattern was found association with depression and anxiety in subjects without CSVD burden. In the CSVD group, the thalamic volume and cortex thickness in pars triangularis, rostral middle frontal and superior frontal were found significantly correlated with both HAMD and HAMA test scores. It suggests the pathway of the thalamus regulating emotion changes with the development of CSVD.
Functional Imaging of Body Image Distortion In Anorexia Nervosa: Overweight vs. Underweight
Authors: Aydos Yagmur Karakus , Dovencioglu Dicle , Oguz Kader Karlı , Ozdemir Pınar , Kızılkan Melis Pehlivanturk , Kanbur Nuray , Unal Dilek , Nalbant Kevser , Cuhadaroglu Fusun Cetin , Akdemir Devrim
Published: August 2023

Body image disorder is the core symptom of Anorexia Nervosa (AN). Our research focuses on a group of adolescent patients diagnosed with AN to investigate neurobiological aspects of body image distortion, comparing the results with healthy control (HC) and major depression (MD) groups. We planned a block-design task in fMRI by using participants' original and distorted overweight and underweight images. We applied General Linear Models (GLM) for whole-brain analyses and examined correlations of the findings with behavioral data. As a result, AN patients differentiated when evaluating their underweight images. However, all adolescents had similar activations for overweight conditions.
Application of quantitative magnetic resonance imaging in the diagnosis of autism in children
Authors: Tang Shilong , Nie Lisa
Published: August 2023

Purpose: To explore the application of quantitative magnetic resonance imaging in the diagnosis of autism in children. Methods: All the children were scanned using head MRI conventional sequences, 3D-T1,DKI, ESWAN and 3D-pcASL sequences. The QSM, CBF and brain microstructure of each brain area were compared between the groups, and correlations were analyzed. Results: The frontal lobe, temporal lobe and hippocampal regions may be the first areas to show microstructural changes in autistic children . Conclusion: Quantitative magnetic resonance imaging can shows the abnormal changes of brain microstructural in children with autism .
Modelling the Brain Functional Difference of Movie Watching and Resting State with Autoencoder
Authors: Sun Yifei , Calamante Fernando , Lv Jinglei
Published: August 2023

The human brain is a complex dynamic system. Understanding the functional difference of the brain between the resting state and performing tasks helps to decipher the functional brain architecture. In this work, we trained an autoencoder to optimally reconstruct the resting state fMRI (rs-fMRI) data of 50 subjects, and this model was subsequently used to reconstruct the movie watching fMRI (mw-fMRI) data of the same subjects. We have compared the reconstruction error between movie watching and resting state, and significant regional functional differences were found.
Head and Neck DWI: Comparison of Image Quality and Diagnostic Performance among FASE and EPI Sequences with and without DLR
Authors: Ikeda Hirotaka , Ohno Yoshiharu , Yamamoto Kaori , Murayama Kazuhiro , Ikedo Masato , Yui Masao , Hanamatsu Satomu , Takeda Saki , Iwase Akiyoshi , Obama Yuki , Ueda Takahiro , Nagata Hiroyuki , Toyama Hiroshi
Published: August 2023

No major studies have been reported for assessing the utility of DWI obtained by Fast Advanced Spin-Echo (FASE) with Deep Learning Reconstruction (DLR) for head and neck MR. We hypothesized that DWI obtained by FASE with DLR could improve the image quality with less deformation and better diagnostic performance as compared with DWI obtained by Echo-Planar Imaging (EPI) in head and neck MR. The purpose of this study was to compare the capability of DWI obtained by FASE and EPI sequences with and without DLR for image quality and diagnostic performance on DWI in patients suspected head and neck tumors.
Quantitatively Assessing Longitudinal Alteration of Shear Stiffness in Neonatal Punctate White Matter Lesions based on Virtual Elastography
Authors: Liu Congcong , Wang Miaomiao , Li Xianjun , Ge Yao , Yang Jian
Published: August 2023

Punctate white matter lesions (PWMLs) were currently common white matter injuries, with incidence of 20-30% and associated with adverse neurological development. Longitudinal alteration of PWMLs was less researched which might be related to pathology. Therefore, this study aimed to assess alterations of PWMLs virtual shear stiffness in neonates via DKI-based virtual elastography. We found that virtual shear stiffness of PWMLs was higher than contemporaneous white matter at neonatal periods and did not change obviously with age, while virtual shear stiffness of normal white matter was increased with age. Virtual elastography might be a potential method to identify differently nosological PWMLs.
Fixel-Based Analysis of White Matter Degeneration in Patients with Huntington Disease
Authors: Tsai Chih-Chien , Oh Sher Li , Chen Chiung-Mei , Wu Yih-Ru , Hernandez Maria Valdes , Cheng Jur-Shan , Chen Yao-Liang , Wu Yi-Ming , Lin Yu-Chun , Wang Jiun-Jie
Published: August 2023

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington Disease. Fixel-based analysis (FBA) has recently emerged as a useful fiber-specific tool for examining white matter structure, which could be an important contributor to the pathogenesis of Huntington’s disease. Therefore, we investigate the utility of FBA as a biomarker for disease progression. Our findings indicated the reductions in FBA occurs in major white matter tracts, which was closely co-localized with the regions of increased diffusivity in basal ganglia. FBA analysis is effective in studying white matter tractography and fiber changes in Huntington’s Disease.
Tract-specific association of myelin water fraction with cognitive decline and motor dysfunction in Parkinson’s disease
Authors: Hartono Septian , Ong Tiet Gan , Lee Weiling , Kuek Zi Cheng , Chen Celeste , Lee Kuan Jin , Lee Jongho , Tan Eng King , Chan Ling Ling
Published: August 2023

We found associations between tract-specific myelin water fraction and cognitive decline, and motor dysfunction in patients with Parkinson’s disease (PD). Myelin water fractions (MWF) in the anterior corona radiata and posterior thalamic radiations were associated with cognitive decline in PD whilst those in the superior and posterior corona radiata, posterior limb of internal capsule and corticospinal tract were associated with moderate to severe motor dysfunction in PD. Our results suggest that MWF has potential utility as an objective imaging biomarker to monitor longitudinal changes in target WM tracts relevant to motor and cognitive dysfunction in PD neurodegeneration.
The ratio of T1-Weighted to T2-Weighted Signal Intensity and IDH mutation in glioma
Authors: Sanada Takahiro , Yamamoto Shota , Sato Hirotaka , Sakai Mio , Saito Masato , Mitsui Nobuyuki , Hiroshima Satoru , Anei Ryogo , Kanemura Yonehiro , Nakanishi Katsuyuki , Kishima Haruhiko , Kinoshita Manabu
Published: August 2023

The authors investigated the correlation of the ratio of T1WI to T2WI signal intensity (rT1/T2) and IDH mutation status in lower-grade gliomas (LrGG). An exploratory study was conducted to determine an ideal cut-off of rT1/T2 for predicting IDH-mutation, followed by a validation study using two different cohorts. Mean rT1/T of IDH-wild type LrGG was higher than IDH-mutant and significantly predicted IDH mutation in the exploratory cohort. The domestic cohort validated this result, but the accuracy in the TCIA / TCGA cohort declined. The cause of this decline should be further investigated.
Radiomics analysis of neurite orientation dispersion and density imaging: differentiation between glioblastoma and solitary brain metastasis
Authors: Zhao Guohua , Zhang Huiting , Gao Eryuan , Gao Ankang , Ma Xiaoyue , Bai Jie , Yan Xu , Yang Guang , Lin Yusong , Cheng Jingliang
Published: August 2023

Differentiation of glioblastomas and solitary brain metastases is clinically crucial for the prescription of patient management and assessment of prognosis. However, indistinguishable signs between two tumors on routine MRI leads to a high misdiagnosis rate. Neurite orientation dispersion and density imaging (NODDI) can not only estimate the intricacy of neurites in vivo but also provide data to illuminate pathology. We developed a series of radiomics models of NODDI parameter maps, routine MRI, combined routine MRI, and combined NODDI parameter maps to compare their performance in the identification of two tumors. Finally, the combined NODDI radiomics model obtained the best performance.
Microstructural Deviation in Parkinson’s Disease and Multiple System Atrophy Detected by Spatial Normative Models
Authors: Chen Chang-Le , Kuo Ming-Che , Tai Chun-Hwei , Hsu Yung-Chin , Wu Ruey-Meei , Tseng Wen-Yih
Published: August 2023

By applying spatial normative models based on a population-based cohort, we can quantify the microstructural deviation of white matter in patients with Parkinson’s disease (PD) and multiple system atrophy (MSA). We found that microstructural deviation of the frontal aslant tracts, cerebrospinal tracts, and parts of corpus callosum was more profound in MSA compared to that in PD. Also, the uncinate fasciculi were the common degenerative marker in these two diseases. Moreover, the microstructural deviation of WM tracts may reflect the association with the disease-related daily functional deficit in MSA and the timing of disease onset in PD.
Disrupted white matter network of brain structural connectomes in bipolar disorder patients revealed by q-ball imaging
Authors: Lin Pei-Ti , Tseng Huai-Hsuan , Chen Po See , Weng Jun-Cheng
Published: August 2023

Bipolar disorder (BD) is a major psychiatric disorder associated with structural and functional brain alterations and cognitive deficits. This study used q-ball imaging and graph theoretical analysis to investigate both neurological structural change and network alterations between BD patients and healthy controls. The results showed the alterations in several brain regions including the corpus callosum and cingulate gyrus, which are associated with executive, cognitive, emotional function, and memory. We found the BD group demonstrated higher global integrity than the HC group, but they remained small-world properties. It indicated that white matter integrity and network alterations were associated with bipolar disorder.
Cerebellar atrophy in Major Depressive Disorder
Authors: Rawat Vishwa , Tyagi Ritu , Hans Gagan , sharan Pratap , Kumaran S Senthil , Sharma Uma
Published: August 2023

Present study investigated volumetric changes in the brain of Indian patients suffering from Major Depressive Disorder (MDD) using Magnetic Resonance Imaging (MRI). These patients were seen to have significantly reduced brain and cerebellar volumes. Volume of caudate, putamen and globus pallidus were seen to be reduced but no significant changes were seen in hippocampus and amygdala. Volume of cerebellum and lobule VI of cerebellum was also reduced. Our results suggest that cerebellum as well as VI lobule of cerebellum may be associated with MDD.
Quantification of bone marrow component change using chemical shift-encoded MRI in Ankylosing Spondylitis patients in different stages
Authors: Ma Liping , Qian Long , Zeng Zhibin , Sheng Cuiyun , Wang Yang , Li Gen , Wu Gaoyun
Published: August 2023

Quantification of fat fraction (FF) and R2* in areas of bone marrow edema (BME) and fat metaplasia in different stages Ankylosing Spondylitis (AS). 75 AS in 3 different stage (early acute group, late acute group, stable group), 42 BME and 39 fat metaplasia were detected. Difference of FF, R2* in BME and fat metaplasia in different stages were compared and relationship between FF and R2* were analyzed. Result showed R2* in fat metaplasia, but not in BME, is significantly negative with FF. FF and R2* measurements can quantitatively analyze bone marrow component change in AS.
The diagnostic value of dynamic contrast enhancement (DCE-MR) and ZOOmitDWI quantitative parameters for the activity of sacroiliac arthritis
Authors: Zhu Qingqing , Liu Mengxiao
Published: August 2023

The purpose of this study was to evaluate the relationship between magnetic resonance dynamic contrast-enhanced imaging and quantitative parameters of the ZOOMit-DWI technique and the activity of sacroiliac arthritis. Dynamic enhanced MRI microvascular permeability parameters can visually reflect the microcirculatory perfusion status of the subchondral bone marrow region of the sacroiliac joint, and its diagnostic efficacy is better than DWI-ADC. Sacral Ktrans values and sacral iAUC values are highly correlated with ASDAS-CRP scores, which can be used as important quantitative indicators for assessing the inflammatory activity of the sacroiliac joint.
Acceleration of 3D Ankle Joint T2WI-SPAIR Images with Compressed SENSE to display the anterior talofibular ligament
Authors: ZHANG Xiaoyan , MA Peiqi , YUAN Yushan , WANG Zhongqiu , Peng Bin , YUE Xiuzheng
Published: August 2023

Compressed SENSE(CS) is a new techonolgy that can be effective accelerat 3D acquisitions and reduce scan times.In this study ,we discuss the value of the compressed sensing technology’s three-dimensional MR to display the anterior talofibular ligament (ATFL), and compare the impact of different acceleration factors on imaging. We find that when the acceleration factor(AF) of CS is six, scan times was reduced by 60 percent without significant degradation of image quality.
Intravoxel incoherent motion imaging of masticatory muscles in patients with head and neck cancer
Authors: Lin Chia-Wei , Cheng Kai-Lun , Lu Hsueh-Ju , Chou Ying-Hsiang , Tyan Yeu-Sheng , Tsai Ping-Huei
Published: August 2023

Head and Neck Cancer (HNC) is one of the most common cancers worldwide. Although skeletal muscle depletion or muscle dysfunction is associated with cancer progression, changes in masticatory muscle diffusion and perfusion in HNC are still unclear. This study aims to assess the masticatory muscle perfusion and diffusion in HNC using intravoxel incoherent motion (IVIM) imaging. Our preliminary result indicated the normalized D* values in masticatory muscles were significantly lower in HNC patients than that in controls, suggesting the possibility of reduced masticatory muscle perfusion in HNC.
Applicable diagnostic model for detecting patients with mental disorders with magnetic resonance imaging
Authors: Zhang Wenjing , Yang Chengmin , Cao Zehong , Shi Feng , Lui Su
Published: August 2023

To yield clinical utility in mental disorder identification individually, we used a multiple instance learning-based method to construct a digital model based on clinical MRI scans for automated detection of patients with psychiatric disorders. An accuracy of 84% was achieved in the primary dataset with 19453 subjects, and 76% in external dataset with 600 subjects. A higher sensitivity was achieved in identifying high-risk subjects than self-scaled questionnaires (71.1% vs 22.2%) in 148 prospectively recruited college students. With a complete workflow of development and validation, the constructed model is more practical to be translated in high-risk subject screening among vulnerable populations.
Machine learning–based prediction of post-concussive working memory decline: a 1-year fMRI prospective study
Authors: Li Yi-Tien , Chen Yung-Chieh , Chen Yung-Li , Kuo Duen-Pang , Chen Cheng-Yu
Published: August 2023

The objective of this study is to construct a framework for precise individualized prediction of post-concussive cognitive outcomes based on the early fMRI and neuropsychological biomarkers assessed at baseline to facilitate early therapeutic intervention and individualized rehabilitation strategies. Satisfactory predictions can be achieved for patients whose WM function did not recover after 3 months (accuracy = 87.5%), 6 months (accuracy = 83.3%), and 1 year (accuracy = 83.3%). The results prove the feasibility of using machine learning–based approaches to reveal predictive biomarkers related to poor post-concussive cognitive outcomes.
The value of multi-parametric magnetic resonance imaging in evaluating renal fibrosis
Authors: Hua Chenchen , Qiu Lu , Zhou Leting , Zhuang Yi , Xu Bin , Wang Liang , Xu Min , Jiang Haoxiang
Published: August 2023

Chronic kidney disease (CKD) is chronic progressive renal parenchymal damage caused by multiple factors. Evaluation of the degree of renal interstitial fibrosis (IF) is of great importance in treatment and prognosis prediction. Herein, we use multi-parametric magnetic resonance imaging (mpMRI) to assess renal IF noninvasively with intention to identify the optimal MRI biomarkers for clinical application. Our results show that multi-parameter prediction model using cortical longitudinal relaxation time (cT1) and cortical true diffusion coefficient (cDt) can effectively assess the degree of renal IF and support clinical diagnosis, treatment strategy and risk stratification in CKD patients.
Infarct core estimation with ADC: A retrospective study
Authors: Dong Yingying , Luo Yu , Wang Mingming , Tao Quan , Wang He
Published: August 2023

According to a large amount of emergency and follow-up data, we propose an optimized threshold of the apparent diffusion coefficient to identify the ischemic core with fair accuracy, which is crucial for the decision of the treatment scheme and operation mode.
Comparison of Ultrashort Echo Time MRI with High-Resolution CT for the Assessment of Idiopathic Pulmonary Fibrosis
Authors: Yang Xiaoyan , Liu Min , An Jing , Benkert Thomas , Dai Huaping , Wang Chen
Published: August 2023

This study investigated the feasibility of ultrashort echo time (UTE)-MRI to evaluate the radiologic findings of idiopathic pulmonary fibrosis, using high resolution CT (HRCT) as the reference standard. UTE-MRI is inferior to HRCT in identifying the details of lung parenchyma. The results suggest that UTE-MRI is equivalent to HRCT. In addition, inter-method agreement between UTE-MRI and HRCT were equal to inter- and intra-observer agreement for UTE-MRI for evaluating disease findings. Moreover, performance analyses demonstrated that UTE-MRI efficacy for detecting radiologic findings of pulmonary fibrosis, such as reticulation, traction bronchiectasis, and honeycombing were similar to that of HRCT.
The Effect of Implant for Lumbar Assessment in Simultaneous TOF PET/MR: A Preliminary Report
Authors: Hung Wei-Min , Gu Ching-Wei , Huang Guo-Shu , Shieh Charng-Chyi , Li Chia-Wei , Chen Yen-Chang , Hsu Yi-Chih
Published: August 2023

This study focused on the accuracy of standardized uptake value (SUV) reconstructed using the corrected MR attenuation correction (MRAC) images with time-of-flight (TOF) information by PET in patients with metallic implants. We compared the SUV of both paraspinal and psoas muscles in patients with and without implant for TOF reconstructed PET images. In the result, there was no significance in the SUV measurements obtained from MRAC between no-implant and with-implant patients. And therefore, our study demonstrated that SUVs measured from TOF PET/MR of lumbar implant indicated good reliability and robust of MRAC.
Amide proton transfer and diffusion kurtosis imaging technology in differentiation stage Ia endometrial carcinoma and endometrial polyp
Authors: Tian Shifeng , Liu Ailian , Ma Changjun , Chen Lihua , Wang Nan , Lin Liangjie , Wang Jiazheng , Wu Zhigang
Published: August 2023

Endometrial polyps (EP) is a common disease of uterine body, with a prevalence rate of about 8~25% in female population. Its clinical symptoms can be like those of endometrial carcinoma (EC), with vaginal bleeding, but there are obvious differences in prognosis and treatment between them. The purpose of this study is to investigate the value of differential diagnosis for staging Ia EC and EP by using amide proton transfer (APT) and diffusion kurtosis imaging (DKI). It shows that APT and DKI can be used to distinguish between stage Ia EC and EP. effectively and quantitatively
The value of DKI technique in the study of brain Microstructural damage and Cognitive function in patients with OSAHS
Authors: Zhang Ning , Peng Kun , Xiao Ailian , Guo Jinxia
Published: August 2023

Obstructive sleep apnea hypopnea syndrome (OSAHS) can lead to cognitive dysfunction, and in severe cases, it may develop into dementia. Early, timely and accurate diagnosis is of great significance to delay the progression of the disease, improve the quality of life and improve the prognosis. Diffusion kurtosis imaging (DKI) based on non-Gaussian model to characterize the diffusion of water is regarded as a more sensitive technology to explore the microstructural tissue changes in compare with diffusion tensor imaging (DTI). In this study, the mean kurtosis (MK) from DKI is used to assess the possible abnormality of brain regions in white and gray matter in moderate and severe OSAHS patients. And the correlation between MK values and cognitive function changes was also analyzed. The MK was found to be associated with changes in 9 brain regions including right postcentral gyrus gray matter, parietal lobe gray matter, insular gray matter, left precentral gyrus white matter, frontal lobe white matter and bilateral cingulate gyrus, left occipital lobe gray matter, and well correlated with attention, delayed recall, which can be helpful for understanding of the potential mechanism for neurocognitive function impairment and doing the evaluation.
Harmonization of multi-site DTI and NODDI data using the combined association test
Authors: Saito Yuya , Kamagata Koji , Maikusa Norihide , Andica Christina , Uchida Wataru , Nozaki Hayato , Owaki Mana , Hagiwara Akifumi , Fujita Shohei , Akashi Toshiaki , Wada Akihiko , Koike Shinsuke , Hori Masaaki , Aoki Shigeki
Published: August 2023

When analyzing multi-site diffusion MRI (dMRI) data, metrics should be harmonized to remove the site effect. In this study, we applied the combined association test (ComBat), which uses regression of covariates with an empirical Bayes framework, for diffusion metrics based on diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). The results showed that ComBat can harmonize site-related effects in DTI and NODDI metrics based on multi-site dMRI while preserving subject biological information, such as sex differences and correlation with age. Thus, ComBat could be applied in large multi-site studies to identify subtle white matter changes.
Robust MR image quality assessment algorithm irrespective of the quality of reference images
Authors: Ikushima Yoichiro , Tokurei Shogo , Tarewaki Hiroyuki , Morishita Junji , Yabuuchi Hidetake
Published: August 2023

The QEMDIM, a no-reference image quality assessment (IQA) algorithm, calculates the quality scores based on the quality difference between an image and reference images. Therefore, scores can be affected by the quality of the reference images. We modified the QEMDIM by changing the scoring method to compensate for this drawback. Brain MR images of various qualities were scored by subjective IQA (our gold standard), QEMDIM, and the modified algorithm. Modified scores showed a higher correlation with subjective IQA scores than the QEMDIM scores, using reference images of varied qualities. Our modified algorithm would be more clinically advantageous than the QEMDIM.
Accurate Prostate Segmentation in MR Images Guided by Semantic Flow
Authors: Osman Yousuf Babiker M. , Li Cheng , Xue Zhenzhen , Zheng Hairong , Wang Shanshan
Published: August 2023

To enlarge the receptive field, downsampling is frequently utilized in deep learning (DL) models. Consequently, there exists one common issue for DL-based image segmentation – the misalignment between high-resolution features and high-semantic features. To this end, decoding or upsampling has been proposed and promising performances have been achieved. However, upsamling without explicit pixel-wise localization guidance may introduce errors. To address this issue, we propose a semantic flow-guided prostate segmentation method. By guiding the upsampling process with semantic flow calculated from both high-resolution and high-semantic features, more accurate segmentation results are generated.
WRIST CARTILAGE SEGMENTATION USING U-NET CONVOLUTIONAL NEURAL NETWORKS ENRICHED WITH ATTENTION LAYERS
Authors: Vladimirov Nikita , Brui Ekaterina , Levchuk Anatoliy , Efimtsev Aleksandr , Bendahan David
Published: August 2023

Detection of cartilage loss is crucial for the diagnosis of osteo- and rheumatoid arthritis. An automatic tool for wrist cartilage segmentation may be of high interest as the corresponding manual procedure is tedious. U-Net is a convolution neural network, which has been largely used for biomedical images, but its performance in segmenting wrist cartilage images is modest. Here, we assessed whether adding attention layers to U-Net architecture would improve the segmentation performance. A truncated version of U-Net with attention layers showed the best performance(3D DSC - 0.811), as well as in the accuracy of cartilage cross-section measurements (bias - 6.4 mm2).
A combined deep learning and radiomics model predicts Ki-67 expression in HCC using MRI and multifrequency MR elastography
Authors: Hu Xumei , Li Ruokun , Zhou Jiahao , Guo Jing , Sack Ingolf , Chen Weibo , Wang He , Yan Fuhua , Wang Chengyan
Published: August 2023

In this study, a combined deep learning and radiomics (DLR) approach using six different network architectures was tested and compared for the prediction of high Ki-67 expressions in patients with hepatocellular carcinoma (HCC). The model was based primarily on data from MRI and tomoelastography, a multifrequency MR elastography technique. Xception delivered the best performance and recognized seven prominent features among which four were obtained from tomoelastography. Our findings demonstrated that biomechanical properties, especially viscosity and the fluid behavior of the tumor, are crucial imaging features that are important for imaging-based cancer diagnostics.
Water- fat separated MR Fingerprinting (MRF) with simultaneous B1+ and B0 estimation
Authors: Xu Jinmin , Liu Huafeng , Ye HuiHui
Published: August 2023

A novel water-fat separated MRF approach was proposed to minimize the known biases introduced by the B1+, B0 and water and fat partial volume. By incorporating the water-fat separation approach in the framework, the dictionary size could be greatly reduced with the known B0 and FF map. Multiple maps of parameters including B1+, B0, FF and T1 and T2* of water and fat can be acquired within 14s for one slice.
A dual-nuclei 1H/23Na knee coil for high-resolution 1H and 23Na MR imaging at 7T
Authors: yang xing , Liu Xin , du feng , Li Nan , Zheng Hairong , Li Ye
Published: August 2023

An ideal MRI study for early osteoarthritis should provide both structure imaging and functional imaging, which can show early morphologic degenerative changes and physiology changes of the cartilage. Most of previous dual-nuclei coils pushed the limits of non-proton nuclei sensitivity at the expense of 1H performance. To get high performance imaging for both nuclei, a novel dual-nuclei 1H/23Na coil array was developed. The bench test results show that all coils were sufficiently matched and decoupled, and the interference between sodium coils and proton coils was nearly negligible, thus can be expected to get high-resolution 1H imaging and quantitative 23Na imaging.
An 8-element torso RF coil array for the Australian inline MRI-Linac: Initial imaging results
Authors: Li Mingyan , Weber Ewald , Waddington David , Shan Shanshan , Liu Paul , Dong Bin , Freakley Craig , Crozier Stuart , Liu Feng
Published: August 2023

The hybrid MRI-Linac system demands dedicated radiolucent imaging coils to visualise and track tumours without interfering the Linac beams. A radiolucent whole-body transceive RF coil for the Australian inline MRI-Linac system has been previously developed and produced images with good quality. Recently, an 8-element torso RF coil array was manufactured to provide better SNR with fast imaging capability, which will facilitate real-time tumour tracking during radiotherapy. Initial imaging results acquired from the 1.0 T Australian MRI-Linac system on a phantom and a volunteer demonstrate the potential benefits of such a torso coil array for MRI-guided radiotherapies.
Combining High Permittivity Pads with Periodic Passive Components in RF Coil Design at 7T
Authors: Chen Haiwei , Xiong Zhuang , Guo Lei , Zhang Xiaotong , Liu Feng
Published: August 2023

Periodic passive components (PPC) such as metamaterials can improve SAR efficiency and B1 penetration. However, due to the shorter RF wavelength in MRI, the performance of PPC is confined by the limited number of unit cells. In this work, a novel PPC structure has been proposed to combine with a high permittivity pad (HPP), so a larger number of unit cells can be used. The designed structure is excited by a dipole coil and compared with the case when a single HPP is used. It is observed that more than 50% SAR reduction can be achieved.
Multichannel MRI receive coil based on artificial material
Authors: Koreshin Eugene , Burov Denis , Seregin Pavel
Published: August 2023

Metamaterials and metasurfaces, in particular, are gaining increasing popularity in recent years. One of the novel applications of metasurfaces are receive coils for magnetic resonance imaging. The major drawback of using such structures is the lack of parallel MRI capabilities due to the single-channel acquisition regime. In this work, we will demonstrate that it is possible to design a multichannel metasurface.
Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation
Authors: Ikemitsu Natsuki , Kanazawa Yuki , Haga Akihiro , Hayashi Hiroaki , Matsumoto Yuki , Harada Masafumi
Published: August 2023

To classify healthy subjects or patients with Alzheimer's disease (AD) using three-dimensional T1w data, we developed a machine learning system which can capture morphology features and determine atrophy of brain tissue in early-stage AD. Deep learning, a support vector machine (SVM), and 3D convolutional neural networks (3DCNN) were performed. The accuracies of SVM and deep learning based on volume values were comparable and greatly exceeded the accuracy of 3DCNN. It was found that atrophic features were more considerable than morphological features in early-stage AD.
MRI assessment of placental oxygenation changes in response to maternal hyperoxygenation in a sheep model of human pregnancy
Authors: Flouri Dimitra , Darby Jack , Holman Stacey , Williams Georgia , Ourselin Sebastien , David Anna , Morrison Janna , Melbourne Andrew
Published: August 2023

Abnormalities of placenta development and function may result in fetal growth restriction (FGR). Advances in MRI technology enable estimation of quantitative indices that reflect tissue diffusivity and oxygenation. We investigated the physiological impact of maternal hyperoxygenation on the placenta pregnant sheep. We applied a multi-compartment MRI signal model to measure the changes in oxygenation caused by changes in maternal blood oxygen level. The expected increase in feto-placental blood relaxation and feto-placental oxygen saturation with maternal hyperoxygenation was observed. Results suggested that diffusion and relaxation-based MRI is sensitive to acute changes in maternal and feto-placental oxygen level.
Phase-Based T2 Mapping for Assessment of Liver Fibrosis in a Porcine Model
Authors: Navaratna Ruvini , Tamada Daiki , Periyasamy Sarvesh , Meudt Jennifer , Laeseke Paul , Shanmuganayagam Dhanansayan , Reeder Scott , Pirasteh Ali
Published: August 2023

Fibrosis is the sequela of and the most important outcome predictor in chronic liver disease. MRI T2 mapping can provide safe and noninvasive detection/staging of liver fibrosis. However, current T2 mapping techniques suffer from prolonged acquisition times, prohibiting widespread clinical utilization. To address this unmet need, we evaluated the feasibility of a whole-liver, single-breath-hold, phase-based T2 mapping technique to assess liver fibrosis in a human-sized porcine model of liver fibrosis. We demonstrated a strong correlation between our phase-based liver T2 values and liver uptake of the fibroblast activation protein inhibitor on PET as well as the reference spin-echo T2 estimates.
Radial Maxwell correction for real-time phase-contrast MRI using spoke clustering
Authors: Kollmeier Jost , Frahm Jens
Published: August 2023

In undersampled radial phase-contrast imaging, Maxwell terms can vary for individual radial projections (spokes). Integrated into a model-based image reconstruction, a computationally expensive spoke-by-spoke correction has been proposed, for which the reconstruction times scale with the number of spokes per frame. To make this approach practical for large numbers of spokes, this work proposes to use k-means clustering of Maxwell terms in the spoke dimension and thereby reduce the computational costs of the model-based image reconstruction for phase-contrast MRI with radial Maxwell correction.
Applying the single shell 3-Tissue method to investigate long-term degeneration of the visual system following hemidisconnection surgery
Authors: Lacerda Luis , Liasis Alki , Handley Sian , Tisdall Martin , Cross Helen , Vargha-khadem Faraneh , Clark Chris
Published: August 2023

There is a need to map microstructural changes over long time periods and develop/apply methods that work with legacy data. In this study, we applied the novel single shell 3-Tissue method to data from a cohort of 4 patients who were scanned 20-years following childhood hemidisconnection surgery and presented degeneration of the visual system. We believe this study suggests that diffusion MRI can be used to monitor the integrity of the visual system following hemispherectomy and if extended to larger cohorts and a greater number of time-points, provide a clearer picture of the natural history of visual system degeneration.
Numerical approach to quantify MR imaging artifacts at metallic orthopedic implants at 1.5T, 3T, and 7T
Authors: Spronk Tobias , Kraff Oliver , Schaefers Gregor , Quick Harald
Published: August 2023

This study evaluates a numerical approach to simulate artifacts due to presence of orthopedic metallic implants in the MR environment. Further to previously published studies, the numerical approach is validated by comparing simulations and measurements of orthopedic implants at three different field strengths (1.5T, 3T, and 7T). Artifact simulations and measurements of the implants show high correlation at all field strengths. The method potentially can be applied to improve the artifacts testing procedure for medical implants according to ASTM F2119. Additionally, the influence of different imaging parameters (echo time and bandwidth) on the artifact size is quantified via numerical simulations.
The effect of primed intravenous infusion of magnetic resonance contrast agent on diffusion tensor imaging in vivo
Authors: Lapin Norman , Wen Xiaodong , Wansapura Janaka
Published: August 2023

The challenge of conducting diffusion tensor imaging in the presence of systemic contrast agent has been noted clinically. Here, we investigate primed infusion as a means of stabilizing contrast enhancement in the mouse brain during image acquisition. Our results show that with infusion-sustained contrast enhancement, fractional anisotropy (FA) was significantly elevated in whole brain and corpus callosum ROIs, but not in hippocampus ROI. Contrast enhancement significantly increased tractography metric of relative mean fiber-track length in corpus callosum versus hippocampus. Thus, contrast enhancement may have a preferential effect on anisotropic brain regions and could potentially be applied to amplify FA selectively.
In vivo validation and quantification of non-susceptibility frequency contrast obtained with DEEPOLE QUASAR
Authors: Jochmann Thomas , Haueisen Jens , Jakimovski Dejan , Zivadinov Robert , Schweser Ferdinand
Published: August 2023

Sources of MRI phase contrast include magnetic susceptibility, chemical exchange, and tissue microstructure. The novel DEEPOLE QUASAR method disentangles frequency sources and yields separate maps for magnetic susceptibility and non-susceptibility frequency shifts.

In this work, we validated the method in vivo and performed the first quantitative study of non-susceptibility frequency in the human brain. We found substantial non-susceptibility contributions in WM and GM. The quantification of non-susceptibility in the human brain provides new ground for theories on the origins of frequency contrast.
iDREAM: T1-bias compensated DREAM B1+ mapping using adiabatic inversion pulses
Authors: Nehrke Kay , Börnert Peter
Published: August 2023

A refinement of the DREAM B1+ mapping technique is presented, that removes the potential T1-bias from the B1+ maps. It is based on a phase cycling scheme including adiabatic inversion pulses and improves the B1+ mapping accuracy and reliability and extends the dynamic working range of the DREAM approach. The method has been successfully validated on phantoms and in vivo on the brain at 3T.
Functional and structural connectomes of subthalamic nucleus subregions in living humans using 7 Tesla MRI
Authors: Gomar Maria Garcia , Singh Kavita , Cauzzo Simone , Bianciardi Marta
Published: August 2023

The subthalamic nucleus (STh) plays a crucial role in the basal ganglia movement-related circuit and it is involved in movement disorders such as Parkinson’s disease, dystonia, and chorea, among others. Its study in living humans is challenging due to limited resolution and contrast in conventional MRI. Previous work developed an in-vivo atlas of two STh subregions based on their fractional anisotropy properties. With the goal of characterizing their function and connectivity, in the present study, we evaluated the functional and structural connectivity of these STh subregions using 7 Tesla MRI and tested their preferential connectivity towards associative or motor regions.
Temporal evolution of the cortical-depth profiles of BOLD fMRI response
Authors: Blazejewska Anna , Gomez Daniel , Polimeni Jonathan
Published: August 2023

The gradient-echo BOLD fMRI signal demonstrates greatest changes with activation near large draining veins which results in cortical-depth activation profiles that increase linearly with depth from the white to pial surface. However, due to the sparsity of pial vessels these profiles are likely to vary across cortical locations depending on proximity to vessels. We investigated the temporal evolution and spatial variability of the cortical-depth profiles of the BOLD response within human visual cortex and demonstrated that the response is initially strongest in the mid-cortical depths and in time becomes dominated by the large veins at the pial-surface.
Multi-Site Normative Modeling and Hierarchical Bayesian Analysis of DKI metrics in Carriers of 16p11.2 Copy Number Variants
Authors: Villalon-Reina Julio , Moreau Clara , Nir Talia , Jahanshad Neda , Consortium Simons Variation in Individuals Project , Maillard Anne , Romascano David , Draganski Bodgan , Lippé Sarah , Bearden Carrie , Thompson Paul , Jacquemont Sebastien
Published: August 2023

We used Hierarchical Bayesian Regression (HBR) to create a normative model of age-effects on Diffusion Kurtosis Imaging (DKI) measures of the white matter. DKI maps from more than 1,300 healthy subjects (3-78 years) from six sites and eight scanners were used to estimate the normative model across the lifespan enabling the multi-site data integration with HBR. 16p11.2 deletions and duplications showed “mirror effects” on diffusion kurtosis metrics.
Structural abnormalities in olfactory brain regions in early Parkinson’s disease (PD) patients measured by high resolution MRI at 7T
Authors: Paez Adrian , Rajan Suraj , Pantelyat Alex , Rosenthal Liana , Faria Andreia , Miao Xinyuan , Dawson Ted , van Zijl Peter , Kamath Vidyulata , Hua Jun
Published: August 2023

We demonstrate significant structural abnormalities in the OB, primary and secondary olfactory brain regions in early PD patients measured by high resolution MRI at 7T. The MRI measures showed significant correlations with behavioral olfactory deficits in the participants.
Metabolic Abnormalities in Bipolar Disorder Observed in the Putamen and Cerebellar Vermis with 7T MRS
Authors: Magnotta Vincent , Xu Jia , Fiedorowicz Jess , Williams Aislinn , Shaffer Joseph , Christensen Gary , Long Jeffrey , Taylor Eric , Sathyaputri Leela , Richards Jenny , Harmata Gail , Wemmie John
Published: August 2023

This study used 31P and 1H MRS to study brain metabolic differences in bipolar disorder. Data from 64 participants with BD and 42 controls was acquired from the right putamen and cerebellar vermis were acquired at 7T. The study observed reduced pHi in support of prior work that has proposed mitochondrial dysfunction in BD where there is an impaired ability to utilize pyruvate in oxidative phosphorylation. A shift from oxidative phosphorylation toward glycolytic energy production likely increases lactate acid, CO2 levels, and free protons resulting in tissue acidosis. This shift in energy production may also lead to increased glutathione.
Brain functional connectivity in schizophrenia: disrupted network dynamics revealed by fMRI
Authors: Farinha Miguel , Amado Conceição , Cabral Joana
Published: August 2023

We investigate differences between the dynamic exploration of resting-state functional connectivity (FC) states using fMRI data from 71 schizophrenia (SZ) patients and 74 healthy controls (HCs) by employing the Leading Eigenvector Dynamics Analysis (LEiDA) method to provide potential biomarkers of this disorder. We found a reduced ability of SZ patients to access and remain in a state of global BOLD phase coherence. Functionally meaningful states presented increased occurrence, limiting probability and altered dynamic transitions in SZ patients. These findings expose pronounced differences between SZ patients and HCs - supporting and developing current knowledge regarding disrupted brain dynamics in schizophrenia.
Evaluation of the efficacy of a Deep Learning-based Reconstruction in the Connectomic Deep Brain Stimulation
Authors: Choi Ki Sueng , Figee Martijn , Lebel Robert , Fung Maggie , Banerjee Suchandrima , Maybeg Helen , Shin Jaemin
Published: August 2023

The connectomic DBS approach, stimulation tractographically defined white mater pathways, has been successfully employed in functional neurosurgery, and it demonstrated the feasibility of clinical utility. However, this approach is limited in the clinical environment due to low SNR and various artifacts of DWI. The recent development of deep learning-based MR reconstruction allows us to improve SNR and reduce artifacts. This study evaluated the DL reconstruction method in the field of connectomic DBS using deterministic and probabilistic tractography. Tractography results from DL reconstruction show higher sensitivity for delineating WM pathways in specific DBS targets.
Associations between vascular health and brain stiffness
Authors: Murphy Matthew , Vemuri Prashanthi , Senjem Matthew , Jack Clifford , Ehman Richard , Huston John
Published: August 2023

Vascular health is a predictor of cognitive outcomes, but the relationship between the two remains incompletely understood. Here we tested the hypothesis that brain stiffness is significantly associated with vascular health as assessed by white matter hyperintensity (WMH) load and the presence of systemic risk factors. Through voxel-wise mapping, WMH was associated with decreased stiffness in periventricular regions, while systemic risk factors were associated with widespread, lower-amplitude stiffness decreases. Examining the partial correlations between stiffness, WMH and vascular risk factors, stiffness was significantly associated with both measures, while WMH and vascular risk were not significantly correlated after controlling for stiffness.
Lung perfusion at 0.55T using ASL: Feasibility and Initial Results
Authors: Zhao Ziwei , Lee Nam , Cui Sophia , Nayak Krishna
Published: August 2023

Lung perfusion is challenging because of the complex anatomy and pulsatile blood flow. At 1.5T and 3T, a major challenge is the low signal from parenchyma due to the short T2*. Here, we demonstrate feasibility of lung ASL perfusion imaging on a high-performance 0.55T system. Experiments were performed using FAIR labeling with snapshot bSSFP imaging and quantified using Buxton’s GKM. In four healthy volunteers, pulmonary blood flow (PBF) ranges from 0.62 to 0.99 ml-blood/ml-tissue/min, which are within the expected range (0.51 to 1.52 ml/ml/min) and agree with the total average PBF estimated by a phase contrast method.
Probing Liver Microstructure in-vivo Using Diffusion-Relaxation Correlation Spectroscopic Imaging (DR-CSI)
Authors: Kim Daeun , Lee Brian , Chen Junzhou , King Kevin , Haldar Justin , Terrault Norah , Fan Zhaoyang
Published: August 2023

Diffusion-relaxation correlation spectroscopic imaging (DR-CSI) is an advanced microstructure imaging approach that can resolve sub-voxel tissue compartments and quantify their fractions. In this work, we investigated the feasibility of DR-CSI with an optimized experiment design for in-vivo liver imaging. Our study showed that DR-CSI can measure multiple sub-voxel compartments in the liver and provide consistent component fraction maps in healthy livers. An initial test on a subject with chronic hepatitis B also demonstrated the potential of DR-CSI to identify and characterize pathological changes in liver parenchyma. Further studies on variable liver diseases are underway.
Intra-rectal gel suppression effectiveness on rectal cancer MR diffusion-weighted images
Authors: Lawrence Edward , Kim David
Published: August 2023

Retrospective evaluation of intra-rectal gel suppression on DWI from 60 rectal MRIs. The DWI, including b1000, computed synthetic b1500, and ADC maps were evaluated by 2 radiologists independently using a 5 point Likert scale with scores of 4-5 considered fully diagnostic. The median suppression score was significantly greater than 3 for both readers (p<0.05) with fully diagnostic suppression achieved in 57/60 (95.0%) and 53/60 (88.3%) cases for reader 1 and 2, respectively. No study was given a score of 1 or 2 by either reader. These results suggest that gel does not impede reader evaluation for tumor restriction at DWI.