bluuebunny/crossref_metadata_2025 huggingface dataset:
Structure-function relationships in the human hippocampus: new insights using track-weighted dynamic functional connectivity
Authors: Dalton Marshall , Lv Jinglei , D'Souza Arkiev , Calamante Fernando
Published: August 2023

The hippocampus is a brain structure central to a broad range of cognitive functions including episodic memory. In recent years, we have developed a greater understanding of the structural and functional connectivity of the human hippocampus. Despite these advances, we lack a detailed understanding of structure-function relationships of cortico-hippocampal connectivity. We addressed this gap by combining high-quality data from the Human Connectome Project with cutting-edge fibre-tracking and track-weighted dynamic functional connectivity methods to quantitatively characterise the relationship between anatomical and functional connectivity of the human hippocampus. Our results contribute to ongoing efforts to characterise structure-function relationships of the hippocampus.
Feasibility of 3D-MENSA sequence for qualitative assessment of lumbosacral plexus nerve root in comparison with 3D-MERGE MRI
Authors: Hu Shuang , Hou BoWen , Li YiTong , Zhang Yao , Liu Weiyin , Li XiaoMing
Published: August 2023

Lumbar radiculopathy is a worldwide cause of disability. Mechanical compression of nerve root may lead to nerve inflammatory changes. Peripheral blood vessels overlapping with inflammatory changes can make radiologists confused and result misdiagnosis. To differ lesions from vessels in lumbosacral plexus nerve imaging, three-dimensional motion-sensitized driven equilibrium prepared rapid gradient echo (3D-MERGE) and three-dimensional multiecho in the steady-state acquisition (3D-MENSA) were investigated. Our study showed 3D-MENSA images showed greater nerve-to-vein CNR and CR than 3D-MERGE and the measurement repeatability of the same observer was good. Overall, 3D-MENSA sequence provided images with superior vascular suppression and offered better conspicuity of LSP.
7 T CBV fMRI reveal cortical microcircuits of bottom-up saliency in the human brain
Authors: Liu Chengwen , Liu Chen , Zhaoping Li , Zhang Peng
Published: August 2023

Using a slab-selective VASO sequence at 7 T, we investigate cortical depth-dependent CBV fMRI activity to orientation-defined saliency stimuli in early visual and parietal cortices of the human brain. Results show that the fMRI response of salient foreground bars is strongest in the superficial depth of V1, and peaks in the middle cortical depth of V2/V3 and IPS. These findings support the hypothesis that bottom-up saliency is initially created by iso-feature suppressions through lateral connections in V1 superficial layers, and then feedforward to parietal cortex to generate the attention priority map.
Laminar BOLD normalization using breath-hold challenge
Authors: Eun Seulgi , Han SoHyun , Uludaǧ Kâmil , Kim Seong-Gi
Published: August 2023

Limitations of the several developed laminar fMRI acquisition methods and pial and intra-cortical ascending vein contamination of the gradient-echo (GE) restrict the neural specificity of the depth profiles. Preserving the advantage of high sensitivity of the GE-EPI sequence, we propose a simple and intuitive model to normalize laminar BOLD with breath holding. Our normalization method increased specificity of the BOLD activation map and emphasized laminar BOLD signal changes in gray matter regions by suppressing signal changes from CSF. This approach takes into account the different vascular sensitivity across layers but may not fully account for the draining vein contamination.
Effect of caffeine on cerebral hemodynamic response: The modulation of dietary caffeine consumption
Authors: Peng Shin-Lei , Chu Lok Wang , Su Feng-Yi
Published: August 2023

The main aim of this study was to characterize the acute effect of caffeine on cerebral hemodynamic responses in participants with different caffeine consumption habits. The non-habitual group exhibited a larger degree of vasoconstriction and thus diminished the ability to dilate upon stimulation. As the vessel dilation ability has been considered as a covariate to explain variabilities in fMRI signals, our results may suggest that the suppressed BOLD response to a visual stimulation in low-caffeine-level users could be partially attributed to the decreased vascular reactivity altered by the baseline perfusion.
Correction of Gibbs ringing artifact improves visualization of epileptogenic pathology
Authors: Smith Robert , Pierre Eric , Jackson Graeme , Vaughan David
Published: August 2023

We evaluate the utility of a recently-proposed method tailored for the removal of Gibbs ringing artifacts in 3D MRI data, by applying it to high-resolution isotropic T2-weighted data acquired during the Australian Epilepsy Project (AEP) pilot. The filter is highly effective at removing this known artifact whilst preserving pathological detail. We therefore encourage its uptake in not only the radiological assessment of the Epilepsies, but any 3D imaging context where the manifestation of Gibbs ringing may be detrimental.
Characterising the Common Wiring of the Human Brain
Authors: Ho Mai , Calamante Fernando , Lv Jinglei
Published: August 2023

To compare white matter fibre tracks between individuals or within the same individual over time, a diffusion MRI tractography template is essential. Tractography template describes the location and orientation of fibre bundles that build a representative organization of human white matter. Despite numerous recent advances in methods to map human brain connectivity, tractography suffers from several limitations, including the over- and the under-representation of certain fibre populations. By integrating multimodal registration and SIFT2 quantification approach, we explore the most consistent bundles across subjects, which could help us advance our understanding of the common wiring in the human brain.
Unravel the Role of Primary Olfactory Cortices in Olfactory Processing via Optogenetic fMRI
Authors: Ma Teng , Wang Xunda , Xie Linshan , Chong Pit Shan , Cao Peng , Khong Pek-Lan , Lim Lee Wei , Wu Ed. X , Leong Alex T. L.
Published: August 2023

The anterior olfactory nucleus (AON) and the piriform cortex (Pir) are the two primary sensory cortices critical for olfaction. Although it is well documented that both cortices overlap significantly in their functions in olfactory processing, molecular and anatomical tracing studies have indicated otherwise. Consequently, our present understanding of the functions of AON and Pir in olfactory processing at the systems level remains incomplete. In this study, we employed optogenetic fMRI to interrogate the role of AON and Pir in processing olfactory inputs and beyond, and the associated long-range olfactory pathways and their spatiotemporal response properties.
Effects of Dobutamine on Neural Activity in Normal Subjects: A Exploratory Resting-State Functional MRI Study.
Authors: Liu Yawen , Ren Pengling , Zhang TingTing , Cai Linkun , Wang Hao , Yin Hongxia , Zheng Wei , Wang Yishi , Niu Haijun , Yang Zhenghan , Luo Dehong , Wang Zhenchang
Published: August 2023

To explore the alternations in spontaneous brain activities in normal subjects after dobutamine infusion, the regional homogeneity (ReHo) method was used to analyze the interregional synchronized activity of all participants. The results showed that compared with normal resting state, significantly decreased ReHo was found after dobutamine infusion in bilateral frontal lobe, while increased in left temporal lobe and right parietal lobe, suggesting that dobutamine may have an effect on functional brain activity.
Thalamic Reticular Nucleus Exerts Long-range Cross-modal Modulation on Sensory Processing Depending on Inputs?
Authors: Wang Xunda , Xie Linshan , Ma Teng , Chong Pit Shan , Lim Lee-Wei , Cao Peng , Khong Pek-Lan , Leong Alex T. L. , Wu Ed X.
Published: August 2023

Thalamic reticular nucleus (TRN) has been shown to gate sensory thalamo-cortical interactions and selectively modulate thalamic sensory information processing according to behavioral demands. However, whether TRN can exert long-range, i.e., beyond thalamus, cross-modal modulation of sensory processing remains unclear. In this fMRI study, we demonstrate that optogenetic excitation of somatosensory-specific TRN enhances cross-modal excitatory sensory inputs but suppresses cross-modal competing inputs at somatosensory cortices. Our work provides insight into how TRN differentially gate the processing of distinct cross-modal sensory information at large-scale, which may be critical for ensuring the balance between various task demands.
The value of diffusion kurtosis imaging in detecting delayed brain development of premature infants
Authors: Zhao Xin , Zhang Chunxiang , Zhang Bohao , Yan Jiayue , Guo Jinxia , Wang Kaiyu , Zhu Zitao , Zhang Xiaoan
Published: August 2023

Preterm infants are at high risk of adverse neurodevelopmental outcome. Therefore, it is necessary to find a tool to detect brain developmental abnormalities earlier. Diffusion kurtosis imaging (DKI) is considered as a more accurate technology based on a kurtosis model accounting for the variation of Gaussian distribution caused by complex cellular environments in compare with diffusion tensor imaging. The mean kurtosis (MK) in posterior limbs of the internal capsule (PLIC), anterior limb of internal capsule (ALIC), the mean diffusion (MD) in parietal white matter (PWM) were found with good diagnostic performance for abnormal brain microstructural change.
An evaluation of the caput nuclei caudati in children with autism spectrum disorder and language deficits with DKI and Synthetic MR
Authors: Sun Yongbing , Zhao Xin , Guo Jinxia , Meng Lingsong , Xuan Desheng , He Xiongpeng , Zhang Xiaoan
Published: August 2023

In this study, DKI combined with synthetic MRI of magnetic resonance imaging compilation (MAGiC) was used to assess the developmental integrity of the caput nuclei caudati of children with ASD and language deficits, and the relationship between DKI parameters and language test scores were explored.
Interpretable Meningioma Grading and Segmentation with Multiparametric Deep Learning
Authors: Jun* Yohan , Park* Yae Won , Shin Hyungseob , Shin Yejee , Lee Jeong Ryong , Han Kyunghwa , Lim Soo Mee , Lee Seung-Koo , Ahn** Sung Soo , Hwang** Dosik
Published: August 2023

Preoperative prediction of meningioma grade is important because it influences treatment planning, including surgical resection and stereotactic radiosurgery strategy. The aim of this study was to establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation. We demonstrated that the interpretable multiparametric DL grading model that combined the T2-weighted and contrast-enhanced T1-weighted images can enable fully automatic grading of meningiomas along with segmentation.
Repeatability and feasibility of amide proton transfer imaging in musculoskeletal tumors
Authors: Wen Ming , Zhang Yujin , Cui Jianling , Shen Zhiwei
Published: August 2023

Amide proton transfer (APT) imaging is a noninvasive emerging molecular MRI technique. Currently, APT was mainly used for the diagnosis, classify and recurrence prediction of head glioma. The application in other tissue such as musculoskeletal disease is limited. The feasibility and the repeatability of APT imaging in body or other tissues is necessary for its clinical practice. In this study, we explorer the scan-rescan repeatability of APT imaging in musculoskeletal (MSK) tumor on a clinical 3.0T MR scanner, and further to differentiate malignant from benign solid tumors in the study.
Feasibility Study of T2* Mapping, R2* Mapping and T1 Mapping Technology in the Quantitative Evaluation for Primary Osteoporosis of Lumbar Spine
Authors: Li Yuan , Yang Guanhua , Jing Wei , Lan Shimin , Yue Xiuzheng
Published: August 2023

The aim of this study was to investigate the feasibility of T2* mapping, R2* mapping and T1 mapping techniques for quantitative assessment of primary osteoporosis of the lumbar spine.The differences and correlation between T2* mapping, R2* mapping and T1 mapping values of patients with osteoporosis group and the normal population were analyzed. The statistical results of our data showed that the T2 values in the osteoporotic group of L3 and L5 vertebrae were greater than the normal group, and the R2* values and T1 values were less than the normal group.
Three-dimensional architecture and diffusion properties of the medial gastrocnemius muscle in human infants in vivo
Authors: Chow Brian V. Y. , Bolsterlee Bart , Morgan Catherine , Rae Caroline , Warton David I. , Novak Iona , Davies Suzanne , Lancaster Ann , Popovic Gordona C. , Rizzo Rodrigo R. N. , Rizzo Claudia Y. , Kyriagis Maria , Smith Melissa , Muling Erin , Herbert Robert D.
Published: August 2023

Diffusion tensor magnetic resonance imaging (DT-MRI) was used to investigate the three-dimensional architecture and diffusion properties of medial gastrocnemius muscles in living human infants aged 2-3 months. Mean muscle volume, physiological cross-sectional area and fascicle length in infants were 1.8%, 3.8% and 47.2% of values previously obtained in 8 adult muscles. Radial diffusivity in infant muscle was half that in adult muscle, presumably because infant muscle fibres have much smaller transverse dimensions.
Efficacy of motion-free MRI of the shoulder using Compressed SENSE MultiVane
Authors: Saruya Shinji , Yoneyama Masami , Katsumata Yasutomo , Inoue Kaiji , Kozawa Eito , Niitsu Mamoru
Published: August 2023

Combining Compressed SENSE (CS), an acceleration technique that combines with compressed sensing and SENSE, with MultiVane achieves comparable scan time to Cartesian scan and increases motion robustness while maintaining similar image quality to Cartesian scan without increasing streak artifacts. We compared this newly developed CS-MultiVane with conventional acquisition method such as routine SENSE, SENSE-MuliVane with reduction factor = 1.0 and SENSE-MuliVane with reduction factor = 1.4 in terms of the overall image quality, overall degree of artifacts and signal-to-noise ratio (SNR). In conclusion, CS-MultiVane acquisition method is feasible for MRI of the shoulder.
Differential Diagnosis of Dermatofibrosarcoma Protuberans: Clinical Values of High-resolution DCE-MRI
Authors: YU QIUYU , YANG YANG , HUANG RENJUN , LI YONGGANG , ZHOU NAIHUI , LI PING , WU PENG , TANG MENGXIAO
Published: August 2023

Dermatofibrosarcoma protuberans (DFSP) is a type of intermediately malignant cutaneous spindle cell neoplasms, which is easy to be confused with several benign ones even after needle biopsy, especially cellular fibrous histiocytoma (cFH), resulting in inadequate excision and local recurrence. We found that as a novel skin imaging technique, high-resolution (HR) DCE MRI could distinguish DFSP. The features include infiltration of surrounding fat, ill-defined margins and large quantitative parameters. Both DFSP and cFH have type-III time-signal intensity curves (TICs). In contrast, other confused lesions presented type-II-or-I TIC. The recommendation of preoperative HR-MRI could assist dermatologists to perform surgical plan more confidently.
Deep Learning for Veterinary MRI: Automated Detection of Intervertebral Disc Herniation in Pet Dogs
Authors: Deng Guoxiong , Huang Shoujin , Chen Ziran , Mei Lifeng , Li Jianzhong , Jiang Ruixiang , Xiao WenYue , Wei Dexing , Kang Yan , Lyu Mengye
Published: August 2023

The automated detection of Intervertebral disc (IVD) herniation in animal MRI may facilitate veterinary diagnosis, yet it is rarely studied due to the lack of training data and the challenges from inter-breed variations. Here, we constructed a dog spinal cord MRI dataset with bounding box annotations of herniated discs, and conducted experiments using a number of well-known deep learning models. We demonstrated that automated detection of animal IVD herniation was feasible and in general two-stage detection models such as Faster R-CNN outperformed one-stage models.
Development and validation of an MRI-based radiomics nomogram for distinguishing multiple myeloma from bone metastasis of breast cancer
Authors: Takasu Miyuki , Takeda Konagi , Kawai Saki , Tanitame Nobuko , Tamura Akihisa , Iida Makoto , Akiyama Yuji , Awai Kazuo
Published: August 2023

We established and validated the feasibility of an MRI-based radiomics nomogram to differentiate between multiple myeloma (MM) and bone metastasis of breast cancer (BC). Regions of interest were drawn for the largest bone lesion per patient on T1- and T2-weighted images of patients with MM (n = 85) and BC (n = 70) from two institutions. The machine learning model with logistic regression resulted in the best performance for differentiating MM from BC with both sequences in the test cases. Our proposed clinical radiomics analysis shows promise in differentiating MM from bone metastasis of BC.
Lower-limb fat: how it is distributed spatially and its potential in approximating whole-body fat content
Authors: Mu Xin , Lv Zhenfeng , Tian Meng , Zhang Jeff L
Published: August 2023

Fat content in lower limb is of highly clinical interest as it reflects physical activity. In this study, we quantified lower-limb fat content in a comprehensive way using a Dixon method. We found that fat content in lower limb generally decreased from pelvis to ankle. Of particular note, fat content in thigh was significantly higher than that in calf, and can potentially differentiate subjects with different body-mass index (BMI). It is also encouraging that fat content for a single cross-section at mid-thigh (30 sec scan time) approximated whole-limb fat content well, as it makes whole-body quantification in clinical setting feasible.
Multi-stage ensemble machine learning for predicting the pathology of thyroid micronodules on small-datasets high b-value thyroid DWI
Authors: Deng ChengLong , Wu BingChao , Wang QingJun , Shi QingLei , Guan Bei , Qu Dacheng , Li ChenXi , Zan DaoGuang , Chen XiaoLin , Wang YongJi
Published: August 2023

In this paper, a multi-stage ensemble learning based on the majority voting mechanism was designed to leverage the contradiction between an insufficient number of thyroid MRI and well-trained deep learning models that accurately predicted the pathology of thyroid micronodules. And its clinical applicability value was also assessed in terms of micronodule risk stratification and optimal regimen selection on high b-value (2000 s/mm2) diffusion-weighted images. Experimental results proved that our model had the capability of effectively distinguishing benign and malignant micronodules on small-dataset thyroid DWI images.
Feasibility of Integrating 7 Diffusion Models within a Single Acquisition and Their Performance Comparison in Glioma Grading
Authors: Zhou Minxiong , Zhang Huiting , Gao Ankang , Wang Shaoyu , Bai Jie , Yang Guang , Cheng Jingliang , Yan Xu
Published: August 2023

There are many advanced diffusion models available for neural and body researches, while their acquisitions are different and normally difficult to be joint applied and compared in one study. In this study, we tried to calculate 7 diffusion models, including 4 neural and 3 cancer related models, using data from one acquisition, and applied it for glioma. Two diffusion acquisition strategy were evaluated, and the performance of these models in glioma grading was also compared. The result showed that both acquisition strategies could generate high quality quantitative parameters for all models, which showed significant differences between high- and low-grade tumor.
The relationship between pubic bone and pubococcygeus muscle injury in transvaginal delivery primiparas using MRI
Authors: Zhang Cheng , Zhao Yujiao , You Cong , Shen Zhiwei , Shen Wen
Published: August 2023

As transvaginal delivery may led to bony and soft birth canal injury, this study aimed to explore the possible relationship between the pelvic bones injury and the pelvic floor support muscles injury. In this study, we found that the pubic injury with significant clinical symptom may suggest the occurrence of pubococcygeus muscle injury with hidden symptoms. With the increased severity of the pubic bone injury, the higher the rate and severity of pubococcygeus muscle injury could be detected, which could be used to guide the clinical evaluation of abnormalities and corresponding rehabilitation treatment in time.
Monitoring the response to induction therapy of multiple myeloma by diffusion weighted and mDIXON Quant whole body imaging
Authors: Sun Mengtian , Cheng Jingliang , Ren Cuiping , Ma Jie , Lin Liangjie
Published: August 2023

This study aims to investigate the value of whole-body DWIBS and mDIXON Quant imaging in monitoring the response to induction therapy of multiple myeloma focal lesions (FLs). Significant differences in the number of multiple myeloma focal lesions (FLs), the maximum diameter of FLs, ADC, FF, T2* values, ADC change rate, FF change rate and T2* change rate were observed between the deep remission group and the non-deep remission group. The FF change rate was the best discriminator of the deep remission.
Multi-Parametric MRI in Diagnosing Ovarian Endometrioma: a Feasibility Study
Authors: Wang Fang , Ding Dawei , Dou Weiqiang , Pylypenko Dmytro , Wang Qing , Yu Dexin
Published: August 2023

This study aims to investigate the feasibility of multi-parametric MRI in distinguishing endometrioma from other ovarian cystic lesions. A total of 50 patients with clinically suspected endometriosis were recruited in the study. Quantitative MRI, including T1, T2 mapping, T2* mapping and CEST, was used. A positive correlation was found between R2* and iron levels in fluid of endometrioma. The AUC of R2*, T1, T2 and MTR_asym were 0.941, 0.996, 0.980 and 0.806, respectively. Therefore, multi-parametric quantitative MRI can be considered an effective method in differentiating endometriomas from various ovarian cystic lesions.
Dynamic functional network connectivity and its association with lipid metabolism in Alzheimer’s disease
Authors: Zang Feifei , Liu Xinyi , Fan Dandan , He Cancan , Zhang Zhijun , Xie Chunming
Published: August 2023

Brain networks of Alzheimer’s disease (AD) represent the fluctuating functional connectivity with time. Using the sliding-window method, this study identified two different functional connectivity states at the large-scale network level in AD spectrum. The AD patients took more time in the tense-connected state II than the non-AD populations. Moreover, lipid metabolism-related factors affected the dynamic network connectivity across the AD spectrum populations. These results provide insights into the neural biological underpinnings of the dynamic networks reorganization for AD pathophysiology.
Automatic no-reference image quality rating metrics in DL-reconstructed image quality assessment and protocol optimization
Authors: Ge Yaan , Liu Xiaolan , Dai Qingyu , Wang Kun
Published: August 2023

This study proposed an automatic no-reference image quality rating metrics (VSS score) based on SVR model, that not requiring clinical expert labeled data, simulating human visual sense and applicable to all anatomies and contrast. The feasibility of applying this rating metrics in DL-recon integrated rapid scan protocol automatic evaluation is demonstrated. The result shows VSS score is in good correlation with visual sense to image quality and outperformed BRISQUE and PIQUE rating algorithms.
Classifier fusion improves prostate cancer detection using MP-MRI
Authors: Jamshidi Ghazaleh , Ardakani Ali Abbasian , Mofrad Farshid Babapour , Rad Hamidreza Saligheh , Ghafoori Mahyar
Published: August 2023

Multiparametric MRI (MP-MRI) has been widely used for detection of Prostate Cancer (PCa). In this study, we propose a new method using MP-MRI including T2-weighted (T2W) and dynamic contrast enhanced (DCE-) MRI for detection of PCa. 32 patients who had high prostate specific antigen (PSA) level recruited. We generated predictive models by extracting radiomics features and classifying benign and malignant lesions. The feature scores are evaluated with Relieff feature selection for each of the modalities. The fused classifier using decision template method showed the highest performance with accuracy, specificity, and sensitivity of 100.
Association between white matter hyperintensity and diabetes-related mild cognitive impairment
Authors: Nan Yashi , Zhang Jian , Ni Jianming , Wang Silun
Published: August 2023

White matter hyperintensities (WMH) features may assist detecting diabetes-related MCI. We aimed to identify the correlations between WMH and MCI in T2D using brain magnetic resonance imaging. Fifty participants, matched for age, were included. Total and regional WMH volumes were calculated using automated segmentation approach. WMH patterns were compared between groups using a voxel-wise analysis. Results show that cognitive impairment was related to a higher prevalence of regional WMH. Subcortical WMH volumes in specific brain regions. The findings suggested that the presence of WMH in specific regions rather the WMH volumes appears to be correlated with the MCI in T2D.
MS or not MS: T2-weighted image (T2WI)-based radiomics findings distinguishes MS from its mimics
Authors: He Ting , Mao Yi , Wang Yao , Wang Lei , Kuang Qinmei , Xu Jie , Ji Yuqi , He Yujie , Zhu Meimei , Zhou Fuqing
Published: August 2023

Multiple sclerosis (MS) is the most common immune-mediated disease of the central nervous system. Early identification of MS lesions and its mimics is very important to help alleviate the tension between the benefits of early diagnosis of MS and inaccurate diagnosis that can have serious health and economic consequences.The radiomics feature model based on T2-weighted images (T2WIs) has obvious clinical value and high specificity in differentiating patients with multiple sclerosis and ischemic demyelination. The high specificity of radiomic model could improve the accuracy of the 2017 McDonald diagnostic criteria for MS, by differentiating it from its mimics-- ischemic demyelination.
Fast Magnetic Resonance Imaging by Deep Learning the Sparsified Complex Data
Authors: Jin Zhaoyang , Xiang Qing-San
Published: August 2023

In this study, we exploited a sparsifying deep learning method and an inverse filtering reconstruction to obtain high quality complex MR images for under-sampled MRI data. This study allows much more flexible data representations for complex MRI data training, leading to significantly higher complex reconstruction quality for practical MRI applications.
Real-time Reconstruction for Accelerated MR Thermometry Using CRNN in MRgLITT Treatment
Authors: Pan Ziyi , Zhang Jieying , Zhang Kai , Sun Hao , Han Meng , Kuang Yawei , Dou Jiaqi , Liu Wenbo , Guo Hua
Published: August 2023

MRI-guided laser-interstitial thermal therapy (MRgLITT) is a minimally invasive therapeutic method in neurosurgery. Accelerating the data acquisition of thermometry for MRgLITT treatment is crucial in achieving high temporal-spatial resolution and large volume coverage. In this work, we suggest using the convolutional recurrent neural network (CRNN) to achieve real-time reconstruction for accelerated temperature mapping, because CRNN is capable of utilizing the temporal correlations of dynamic data to resolve aliasing artifacts. Results demonstrate that 6-fold acceleration can be achieved in MRgLITT treatment using CRNN with clinically acceptable reconstruction time and temperature measurement errors.
Quality Assessment of Pediatric Cortical Surfaces with Spherical Transformer
Authors: Cheng Jiale , Zhang Xin , Zhao Fenqiang , Wu Zhengwang , Wang Ya , Huang Ying , Lin Weili , Wang Li , Li Gang
Published: August 2023

Quality assessment of cortical surfaces, which is a crucial step and prerequisite in surface-based large-scale neuroimaging studies, aims to identify the low-quality surfaces and exclude them in the subsequent analysis. Convolutional neural network-based methods have achieved great success in image quality assessment, but they are inherently inapplicable for objects presented in non-Euclidean spaces, such as the brain cortical surfaces. To this end, we propose a transformer-based network, which describes the local information based on feature correspondences among vertices, thus enabling itself to be applied directly onto a spherical manifold. Extensive experiments on 1,860 infant cortical surfaces validated its superior performance.
Improved Parallelized Blind MR Image Denoising using Asymmetric Weighting coefficients
Authors: ITO Satoshi , YAMATO Kazuki
Published: August 2023

Parallelized blind image denoising (ParBID) is an improved CNN based denoising method in which weighted average of slice images are denoised using blind denoising CNN followed by image separation. To further improve the denoising performances, weighting coefficients (wc) of slice image averaging was examined. Negative value wc resulted in a significant change in the noise distribution, resulting in a change in the noise distribution and consequently changes the degree of noise reduction. Experimental studies showed that the PSNR was improved compared to the previous method using positive value wc at all noise levels.
Initial study of elastic modulus estimation method using deep learning in MR elastography
Authors: Aoki Takanori , Suga Mikio
Published: August 2023

MRE is a method for non-invasively and quantitatively estimating the stiffness of biological tissues. Although many estimation methods have been proposed, such as LFE, DI, and MMDI, there is a problem that both quantitativeness and spatial resolution cannot be achieved. In this study, we developed an elastic modulus estimation method by deep learning and compared its robustness to noise, quantitativeness, and spatial resolution with existing methods by numerical simulation. Compared with the conventional method (LFE), the proposed method has the same level of noise robustness, higher spatial resolution, and better quantitative performance in the case of high elastic modulus.
CoSimPy: an Open-Source Python Library for MRI RF Coil EM/Circuit Cosimulation
Authors: Zanovello Umberto , Seifert Frank , Bottauscio Oriano , Winter Lukas , Zilberti Luca , Ittermann Bernd
Published: August 2023

The Electromagnetic/Circuit cosimulation method represents an effective strategy to address those problems where a radiative structure has to interact with external supporting circuitries.This method proved to be particularly valuable for MRI RF coil design where the supporting circuitry optimisation is generally of particular concern. CoSimPy, an open-source library conceived for Electromagnetic/Circuit cosimulations, is presented. CoSimPy is written in Python following an Object-oriented programming. This improves its scalability and easily allows interested scientists to collaborate, integrating and improving the library with other methods. CoSimPy is available under https://github.com/umbertozanovello/CoSimPy together with a detailed documentation providing guidelines and examples.
Head Coil for Vertical-Field MRI using Loop/Dipole Parallel RF Coils
Authors: Otake Yosuke , Arai Koichi , Taniguchi Takeshi , Dohata Masayoshi , Shimoda Takahide , Kato Kazuyuki , Ochi Hisaaki
Published: August 2023

To improving the SNR and the g-factor in a vertical-field MRI, a multi-channel head coil has been developed. The coil consists of loop/dipole parallel RF coils (LDP) that improve the signal detection efficiency in the deep region of the subject in the vertical-field MRI. The performance of the coil was evaluated in a phantom experiment at 1.2T vertical-field MRI. The SNR and the g-factor of the coil using LDP were 1.2 and 1.2-2.9 times better than those of a conventional head coil, respectively. This technique will contribute to improve the performance of the vertical-field MRI.
Whole Spine Imaging at 5.0T Using An 8-channel Volume Transmit Coil and 48-channel Receive Array
Authors: Che Shao , Fang Fuyi , Dong Kaida , Han Shihong , Li Ye
Published: August 2023

Large field-of-view imaging of spine in ultra-high field 5.0T magnetic resonance imaging system is achieved with RF hardware design of an 8-channel volume transmit coil and a dedicated posterior spine array of 48 receive channels. The axial coverage and transmit homogeneity allow the use of refocusing pulses under specific-absorption ratio limits by safety regulations. Consequent high-resolution fast spin echo clinical images are acquired and compared with results on a commercial 3.0T scanner.
Design of ultrahigh dielectric constant uHDC helmet for 3T and its intrinsic resonance modes
Authors: Chen Xinlian , Gandji Navid P. , Sica Christopher T. , Yang Gary W. , Poshtgol Parisa Lotfi , Wiesner Hannes M , Zhu Xiao-Hong , Lanagan Michael , Chen Wei , Yang Qing X , Xin Xuegang
Published: August 2023

This investigation characterize the intrinsic resonance modes (IRM) in a helmet made from utrahigh dielectric constant (uHDC) material and their interactions with RF field produced by conventional array coils using numerical simulation. The RF field of the three lower order modes, TE, TM1 and TM2, were investigated. TM1 mode produces uniform H-field in the transverse plane inside the helmet similar to that of a birdcage coil. TM2 mode produces a strong RF field but with a large gradient. Understanding of the IRMs of large uHDC structures such as helmets provides theoretical foundation for wider applications of uHDC materials RF engineering.
A 2kW non-magnetic RF power amplifier with negative feedback for 5T MRI proton imaging
Authors: Luo Jun , Liu Shengping , Chen Jifeng , Li Ye
Published: August 2023

Parallel transmission technology has attracted much attention because of its advantages of uniform excitation and artifact correction in ultra-high field. A 2kW non-magnetic prototype RF amplifier for 5T multi-channel parallel transmission (pTx) is presented. It is equipped with analogic feedback loops and provides a high linearity up to peak output power. It maintains excellent fidelity performance even without a circulator.
Abdominal imaging at 5.0 Tesla: Preliminary results
Authors: Zheng Liyun , Yang Chun , Sheng Ruofan , Dai Yongming , Zeng Mengsu
Published: August 2023

Higher magnetic field strength leads to an increase of the SNR. On the other hand, the increase of magnetic field strength implies larger magnetic susceptibility inhomogeneities. Recently, 5.0T whole body magnetic resonance imaging system has been introduced into research and clinical settings. In this study, we evaluated the feasibility of abdominal imaging at 5T and compared the image quality and potential artifacts with 3T. Our results indicated that 5T MRI is able to acquire artifact-free anatomical images of the abdomen. Compared to 3T MRI, abdominal MRI at 5T resulted in comparable image quality and better contrast ratios.
Evidence from dual-calibrated fMRI for raised mitochondrial oxygen tension in the MS brain
Authors: Chiarelli Antonio , Patitucci Eleonora , Chandler Hannah , Tomassini Valentina , Germuska Michael , Wise Richard
Published: August 2023

Dysfunction of energy supply or usage may be present in Multiple Sclerosis. We investigated the use of a simple oxygen diffusion model to infer mitochondrial oxygen tension from dual-calibrated fMRI (dc-fMRI) data. We observed a significant reduction of grey matter CBF and CMRO2 in people with MS but no significant difference in OEF or BOLD-sensitive blood volume. Assuming no substantial tissue or vascular remodelling in MS, these results imply, within a simple flow-diffusion model of oxygen from capillaries into the tissue, an elevated partial pressure of oxygen at the mitochondria which may indicate mitochondrial dysfunction.
Glutamatergic dysfunction associated with tau depositions in Alzheimer’s disease
Authors: Matsuoka Kiwamu , Hirata Kosei , Kokubo Naomi , Tagai Kenji , Endo Hironobu , Takahata Keisuke , Shinotoh Hitoshi , Ono Maiko , Seki Chie , Kawamura Kazunori , Zhang Ming-Rong , Shimada Hitoshi , Takado Yuhei , Higuchi Makoto
Published: August 2023

Glutamatergic neurons and cingulate cortices have crucial roles in the cognitive dysfunction of Alzheimer's disease (AD). This study aimed to evaluate regional vulnerabilities of the glutamatergic system in AD at the level of the cingulate gyrus in relation to tau and amyloid-β (Aβ) depositions. Combining MRSI and PET, we found that the glutamatergic system in the posterior cingulate cortex (PCC) is vulnerable to tau deposits but not Aβ from the early stage of AD, and glutamate in the PCC region may be a marker of disease progression in AD.
Measuring changes in placental morphology using magnetic resonance imaging in a preclinical model of human pregnancy
Authors: Flouri Dimitra , Darby Jack , Holman Stacey , Perumal Sunthara , Ourselin Sebastien , David Anna , Melbourne Andrew , Morrison Janna
Published: August 2023

Abnormalities of placental development and function underlie many pathologies of pregnancy including preeclampsia and fetal growth restriction (FGR). Advances in MRI techniques provide capacity to obtain additional placental in vivo information to support clinical decision-making. Animal models are used in invasive validation studies are possible in animal models and allow for controlled experiments during pregnancy. Here, we investigated whether MRI technology could be used to study the anatomical morphology of placentae in vivo in sheep; and we characterise diffusion and perfusion properties in normal pregnancies and those complicated by induced FGR.
Effect of Inhaled Oxygen Concentration on 129Xe Chemical Shift of Red Blood Cells in Rat Brain
Authors: Friedlander Yonni , Zanette Brandon , Lindenmaier Andras , Li Daniel , Kadlecek Stephen , Santyr Giles , Kassner Andrea
Published: August 2023

Hyperpolarized 129Xe RBC chemical shift in the rat brain was measured to be higher during hypoxic ventilation than during normoxic ventilation.
Validation of non-invasive MR measurement of feto-placental oxygen saturation in a sheep model of human pregnancy
Authors: Flouri Dimitra , Darby Jack , Holman Stacey , Perumal Sunthara , Ourselin Sebastien , David Anna , Melbourne Andrew , Morrison Janna
Published: August 2023

Abnormal placental development is postulated as one of the leading causes of fetal growth restriction (FGR). Advances in MRI technology enable non-invasive measurement of fetal oxygen saturation, but not all have yet been validated. Due to the invasiveness of tests required, validation in human subjects is not possible. Preclinical models such as pregnant sheep allow invasive methods to validate MRI measurements. Here we show that multi-compartment modelling of non-invasive placental MRI can be used to estimate the oxygen saturation of feto-placental oxygenation in normal sheep pregnancy and pregnancies affected by early gestation onstet FGR.
Multi-slab 3D ECLIPSE for whole brain lipid suppressed MRSI
Authors: Kumaragamage Chathura , Brown Peter , McIntyre Scott , Nixon Terence , De Feyter Henk , de Graaf Robin
Published: August 2023

The utility of ECLIPSE, a pulsed second order gradient insert allowing elliptical localization, was previously shown to provide high axial coverage for single slab MRSI acquisitions with robust lipid suppression. In this work we extend the ECLIPSE method with multi-slab localization that provides improved coverage, for applications in 3D MRSI acquisitions. A two-slab ECLIPSE-OVS method providing > 100-fold in mean lipid suppression was developed, with improved superior-inferior coverage. Simulation results show that a four-slab ECLIPSE method, based on OVS and IVS, can provide high-quality lipid suppression with whole-brain coverage.
Characterization of the Zona incerta and Fields of Forel using QSM at 9.4T
Authors: Kumar Vinod , Scheffler Klaus , Hagberg Gisela , Grodd Wolfgang
Published: August 2023

The subthalamic structures, like the zona incerta (ZI), fields of forel (FF), subthalamic nucleus (STN), and their surrounding structures, are poorly characterized regarding anatomical imaging. Using quantitative susceptibility mapping (QSM) at ultra-high-field, iron, and myelin mapping may allow an advanced characterization. Therefore, QSM data were acquired at 9.4 Tesla in 21 subjects to characterize the para- and diamagnetic properties of the ZI, FF, and their adjacent structures. In contrast to the FF, we found a higher contribution of diamagnetic and paramagnetic sources, i.e., iron, myelin, and calcium, in the STN and ZI.
Combining navigator-based prospective and data-driven retrospective motion correction for high resolution 7T multi-slice T2W MRI.
Authors: Boer Vincent , Grande Lucilio Cordero , Pedersen Jan Ole , Prener Martin , Petersen Esben , Paulson Olaf , Andersen Mads , Opheim Giske
Published: August 2023

High-resolution multi-slice T2W imaging at ultra-high field is highly sensitive to motion due to high tissue-CSF contrast and the k-space filling pattern. In this study we investigated the combination of 3D prospective and in-plane retrospective motion correction to improve image quality. We observed that a combination of navigator based prospective and data-driven retrospective correction is able to correct most severe motion artifacts during scanning, and remove smaller residual artifacts in reconstruction.
Feature and voxel fidelity constraints improve the accuracy of direct inversion quantitative susceptibility mapping in deep gray matter
Authors: Pazmiño Jorge Campos , Fortier Véronique , Levesque Ives
Published: August 2023

We have designed a novel QSM algorithm that addresses some of the limitations of existing techniques that combine the background removal and dipole inversion steps in a single step. We propose that the solution to the direct inversion problem can be aided by an iterative k-space algorithm and the inclusion of a priori information that represents feature-based and voxel-fidelity-based constraints. The considered approach, when compared with other techniques, resulted in a more accurate depiction of the susceptibility in high susceptibility deep gray matter (dGM) structures without sacrificing performance in regions like the cortex of the brain.
Detecting longitudinal dynamic functional connectivity changes using multiband multi-echo fMRI in high school football athletes
Authors: Cohen Alexander , McCrea Michael , Wang Yang
Published: August 2023

Repetitive head impact exposure (RHIE) during contact sports may have damaging neurocognitive effects. In this study, we investigated longitudinal changes in dynamic functional connectivity (dFNC) using multiband multi-echo (MBME) fMRI in high school football players over the course of two seasons. Four recurring connectivity states were identified. A greater total number of dFNC changes were observed over two seasons compared to over the course of one season. Changes across all four states were only observed in the two-season comparison. These preliminary results suggest that RHIE may lead to accumulated effects in functional connectivity patterns.
NORDIC PCA increases tSNR in both human and mouse resting-state fMRI for potential improvements in cerebrovascular reactivity mapping
Authors: Tse Emily , Chan Russell , Wu Sarah , Xue Yixi , Liu Peiying , Moeller Steen , Chan Kevin
Published: August 2023

Cerebrovascular reactivity (CVR) reflects the response of cerebral blood vessels to vasoactive stimuli. Whole-brain relative CVR (rCVR) mapping is achieved using task-free resting-state fMRI, which resembles conventional CVR mapping using hypercapnia challenge. To optimize rCVR mapping, we apply NOise Reduction with DIstribution Corrected (NORDIC) PCA which removes thermal noise originating from the scanner and/or the subject. Results show that NORDIC-correction increases the temporal signal-to-noise ratio in both humans and mice, lowers mouse rCVR variance, and potentially improves mouse rCVR along cortical layers. Future rCVR studies investigating cerebrovascular diseases may incorporate NORDIC-correction for higher sensitivity.
Hemodynamic responses based on CBV weighted fMRI strongly correlate with single-unit neuronal action potentials across cortical layers
Authors: Zhu Wei , Cruttenden Corey , Cho Shinho , Zhu Xiao-Hong , Ugurbil Kamil , Chen Wei
Published: August 2023

The specificity of hemodynamic signals detected by functional magnetic resonance imaging (fMRI) to neuronal activity is complicated by the neurovascular coupling. To investigate the fidelity of fMRI in differentiating the neuronal activity across cortical layers, we mapped the laminar orientation preference maps in the cat visual cortex by using high-resolution cerebral blood volume weighted (wCBV) fMRI and single-unit neuronal action potential recording, respectively. The strong correlation between wCBV percent change and spike firing rate indicates that wCBV fMRI with sufficient spatial resolution could distinguish the differences of neural activities across layers but with a reduced sharpness.
Brain Structure-Function Network Hierarchy Abnormalities in Major Depressive Disorder
Authors: Jacob Yael , Morris Laurel , Rutter Sarah , Verma Gaurav , Murrough James , Balchandani Priti
Published: August 2023

Major depressive disorder (MDD) diagnosis, research, and treatment is especially challenging given that current diagnosis entirely depends on clinical symptoms, whereas the underlying brain pathology remains largely unclear. Applying a novel multilayer network analysis, considering communication within functional and structural networks as well as the interactions between them, we found aberrant centrality measures of various brain regions in MDD compared to controls that were not detected using single structural or functional connectomes. In addition, using multilayer network features as predictors in a machine learning algorithm resulted in higher predictive values compared to classification models based on single layer.
Unmethylated MGMT combined with post-CRT perfusion MRI-derived tumor burden informs overall survival in newly diagnosed glioblastoma
Authors: Prah Melissa , Connelly Jennifer , Schmainda Kathleen
Published: August 2023

As treatment response can mimic progressive tumor on standard imaging, clinical outcomes following upfront chemo-radiotherapy in newly diagnosed glioblastoma rely heavily on MGMT promoter methylation status. While MGMT is a reliable marker of outcomes, the purpose of this study was to determine if inclusion of advanced perfusion-MRI derived fractional tumor burden (FTB) volume might better inform survival outcomes. Results revealed that low FTB volume in MGMT unmethylated glioblastoma confers significant survival benefit, approaching that of MGMT methylated glioblastoma. Clinically, combining FTB with MGMT methylation status may identify patients with potentially better outcomes or for whom more aggressive approaches are warranted.
Unique Alterations in the Pattern of Iron Deposition in Deep Gray Matter Relative to White Matter Microstructure in Mild Traumatic Brain Injury
Authors: Chung Sohae , Fieremans Els , Novikov Dmitry , Amorapanth Prin , Rath Joseph , Flanagan Steven , Lui Yvonne
Published: August 2023

Primary and secondary injury are both believed to play important roles in the pathogenesis of disease after mild traumatic brain injury (MTBI). Here we investigate the relationships between white matter microstructure and deep gray matter iron deposition after MTBI, which may shed light on primary WM injuries and potential secondary changes in brain iron. Our results show different patterns of correlation between deep gray matter iron content as measured by QSM and WM microstructure as measured by diffusion MRI in MTBI compared with normal controls.
Reproducibility of Chemical Shift-Encoded MRI Fat Quantification in Liver Across Field Strengths in Patients with Iron Overload
Authors: Wang Zihan , Reeder Scott , Hernando Diego
Published: August 2023

The purpose of this study is to assess the reproducibility of CSE-MRI methods to measure proton density fat fraction (PDFF) in liver in patients with iron overload. The PDFF measurements of 31 patients with known or suspected iron overload and 10 healthy volunteers were imaged at both 1.5T and 3.0T. Patients were separated into four groups with increasing liver iron concentration (LIC). The reproducibility across field strengths was quantified within each group and reported below.