bluuebunny/crossref_metadata_2025 huggingface dataset:
Field dependence of T2* contrast in human substantia nigra
Authors: Brammerloh Malte , Kirilina Evgeniya , Sibgatulin Renat , Herrmann Karl-Heinz , Reinert Tilo , Jäger Carsten , Pelicon Primož , Pine Kerrin , Vavpetič Primož , Deistung Andreas , Morawski Markus , Reichenbach Jürgen , Weiskopf Nikolaus
Published: August 2023

MRI holds high promise to diagnose Parkinson’s disease (PD) at clinical field strength B0. However, it remains unclear which B0 optimizes T2* contrast in substantia nigra, which provides high diagnostic accuracy. We used quantitative MRI at B0=1.5T-9.4T, MR microscopy, and histochemistry to characterize the field dependence of the major contributors to R2* (1/T2*): dopaminergic neurons, ferritin, and myelin. R2* maps were similar at B0=3T-9.4T, and all contributions scaled approximately linearly with B0. Hence, the contrast mechanisms are similar across currently available MRI field strengths in vivo, which informs the design of novel PD biomarkers.
Mechanisms of relaxation in blood - Nuclear magnetic resonance dispersion profile of rat’s blood, plasma, and red cells at different temperatures
Authors: Mekhfi Mohsine , Labbé Aimé , Kereselidze Dimitri , Selingue Erwan , Broche Lionel , Rollet Anne-Laure , Poirier-quinot Marie
Published: August 2023

Measuring whole blood relaxation time is as a reliable diagnosis tool. Usually, one compartmental model is used to fit data, which seems a very simplistic approach considering the complexity of blood. The aim of this work is to test the validity of this assumption by studying the relaxation rate of whole blood, plasma and red blood cells (rbc) of rats at different temperatures. The whole blood is well described by a two-compartment approach, one corresponding to plasma and another for red blood cells. Once frozen, there is only one relaxation rate population, which is considered to be the rbc population.
Interferometric, Hybrid, and Weighted $$$B_1^+$$$ Mapping for Expedited RF Calibration of Parallel Transmit Ultrahigh-Field MRI
Authors: Bosch Dario , Müller Fabian , Scheffler Klaus
Published: August 2023

With an increasing number of transmit channels, faster methods for acquiring $$$B_1^+$$$ maps on pTx MRI systems grow in importance. We compared different interferometry modes for accurate absolute $$$B_1^+$$$ mapping using satTFL. We also introduced weighted hybrid $$$B_1^+$$$ mapping as an attempt to improve hybrid $$$B_1^+$$$ mapping. In this, a second absolute $$$B_1^+$$$ map was introduced as an attempt to further shorten measurement duration while keeping acceptable accuracy. From the tested interferometry modes, phase-cycling performed best in both absolute and weighted mapping. Weighted hybrid mapping exceeded conventional hybrid mapping substantially and could therefore be sufficiently accurate for many applications.
Improved B1+- and resonance offset-robust slice-selective inversion pulses
Authors: Graf Christina , Berrington Adam , Soellradl Martin , Rund Armin , Stollberger Rudolf
Published: August 2023

In this work, an optimal control framework and its application for the development and improvement of $$$B_1^+-$$$ and $$$\Delta B_0-$$$robust, slice-selective inversion pulses is introduced. The optimized RF pulse shows superior performance compared to adiabatic, state of the art pulses through simulations, phantom experiments, and in vivo measurements. Measurements on a 3T MR system revealed improved slice-profile quality of the optimized pulse, especially for low $$$B_1^+$$$ and high $$$\Delta B_0$$$. Since the performance is independent of the field strength, its application in ultrahigh-field spectroscopy seems straightforward.
Comprehensive brainstem imaging using MT, QSM and DTI for atypical parkinsonism diagnosis
Authors: Seada Samy Abo , van der Eerden Anke , Boon Agnita , Hernandez-Tamames Juan
Published: August 2023

Differentiating atypical parkinsonism (AP) from idiopathic Parkinson’s disease (PD) remains a challenge in clinical practice. Based on a recent review on differentiating atypical parkinsonisms using MRI, we developed a dedicated MRI protocol including magnetization transfer (MT), quantitative susceptibility mapping (QSM) and diffusion tensor imaging (DTI) for improving diagnosis. Using pilot data from a healthy volunteer, we show how the assessment of important structures (substantia nigra and locus coeruleus) can be improved using a comprehensive combination of MRI techniques.
Assessment of Lumbar Nerve Root Changes in Disc Herniation Using Ultrashort Echo Time Magnetization Transfer (UTE-MT) Imaging
Authors: Liu Jin , Feng Jia-Xin , Liao Jian-Wei , Li Wei , Chen Xiao-Jun , Yao Lin , Huang Pan-Hui , Qian Long , Ma Ya-Jun , Li Shao-Lin
Published: August 2023

Ultrashort echo time magnetization transfer (UTE-MT) imaging can quantify macromolecular content changes in tissues. This study aims to investigate the feasibility of UTE-MT ratio (UTE-MTR) in assessment of lumbar nerve root changes due to disc herniation. T2 mapping and diffusion tensor imaging (DTI) were also employed for comparison. Our results demonstrated that the UTE-MTR is able to detect nerve root changes due to disc herniation and it has a better performance than T2 mapping and DTI imaging in differentiation of disc herniation and non-disc herniation.
Quantitative Evaluation Of Potential L5/S1 Spinal Nerve Degeneration In LSTV With Bertolotti's Syndrome By Diffusion Tensor Imaging
Authors: Yin Shi , Dou Weiqiang , Ding Hongyuan
Published: August 2023

This study aims to investigate if quantitative MR diffusion tensor imaging (DTI) technology can be applied to quantitatively evaluate the potential L5/S1 spinal nerve degeneration in patients with lumbosacral transitional vertebrae. By quantitative evaluating 52 patients, we found the L5/S1 spinal nerves' DTI FA values showed lower in type Ⅱ-Ⅳ LSTV cases while the nerves run through the bony articulation between the vertebra and sacrum. Therefore , quantitative MR DTI has a good performance for quantitative diagnosis of LSTV with Bertolotti's syndrome.
The value of Intravoxel Incoherent Motion in Differentiating Renal Tumors with Low Signal Intensities on T2-weighted MR image
Authors: Liu Jinghong , Liu Ailian
Published: August 2023

Clear cell carcinoma of kidney usually presents with high signal intensity on T2WI imaging, while some clear cell carcinoma presents with low signal intensity on T2WI imaging.Other rare renal tumors, such as papillary renal cell carcinoma and lipid-deficient angiomyolipoma, are characterized by low signal intensity on T2WI. Intravoxel incoherent motion (IVIM) is a model built on the basis of DWI, reflecting the structural changes and physiological state of cells from the microscopic level. Our objectivie si to evaluate the feasibility of the IVIM in differentiating renal tumors with low signal intensities on T2WI.
Improving SNR in deuterium metabolic imaging: A comparison of methods
Authors: Montrazi Elton , Martinho Ricardo , Bao Qingjia , Sasson Keren , Agemy Lilach , Scherz Avigdor , Frydman Lucio
Published: August 2023

Deuterium metabolic imaging (DMI) is a promising approach to study tumor metabolism. Still, DMI’s signal-to-noise ratio (SNR) is limited because of 2H’s low Larmor frequency, coupled to the low concentrations of DMI’s targets. We recently proposed a multi-echo balanced steady-state free precession (ME-bSSFP) method increasing DMI’s SNR, but still find it lacking in some aspects. This work assesses simple apodization, Compressed Sensing Multiplicative (CoSeM) and Block-matching/3D filtering (BM3D) denoising methods for improving DMI’s results. The ability of the latter denoising methods to enhance sensitivity without blurring resolution, is evidenced by pancreatic cancer studies carried at 15.2T.
Phosphorus MR Spectroscopy of Healthy Human Spleen
Authors: Weis Jan , Jafar Maysam , Liss Per
Published: August 2023

Phosphorous spectra of healthy spleen are useful for studies of splenic malignancies and benign causes of splenomegaly. The main challenge is the relatively small size of the normal spleen and the large distance between human spleen and surface coil. The purpose of this study was to investigate whether it is possible to acquire phosphorous spectra of healthy spleen using single-voxel ISIS sequence on a 3T scanner. We demonstrate that the proposed spectroscopy of human spleen is feasible in a clinically acceptable acquisition time and that transmitter excitation profile and chemical shift displacement errors need to be taken into consideration
MP-PCA and Low-rank noise-reduction in 1H-FID-MRSI data in the rat brain at 14.1T
Authors: Alves Brayan , Simicic Dunja , Mosso Jessie , Jelescu Ileana , Cudalbu Cristina , Klauser Antoine
Published: August 2023

1H-MRSI is highly challenging and the constant appetite for higher spatial resolution leads to increased search for post-processing methods aiming to reduce the noise variance in 1H-MRSI. The aim of the present study was to implement and test the feasibility of two noise-reduction techniques on preclinical 14.1T fast 1H-FID-MRSI datasets: the MP-PCA based denoising and the low-rank TGV reconstruction. Our results are promising showing an enormous potential of the two noise-reduction techniques towards novel and fast MRSI developments. Further studies will be performed to evaluate if the “apparent” increase in spectral SNR translates in true lower uncertainty in metabolite concentrations.
Pulse design for joint optimization of semisolid saturation and free water rotation
Authors: Leitão David , Tomi-Tricot Raphael , Bridgen Pip , Wilkinson Tom , Liebig Patrick , Gumbrecht Rene , Ritter Dieter , Giles Sharon , Baburamani Ana , Hajnal Joseph , Malik Shaihan
Published: August 2023

In MT imaging, particularly at ultra-high field, results can be influenced by spatial variations in both (1) on-resonance flip angle and (2) RF saturation specified by B1rms including on- and off-resonance contributions. Conventional pulse design with parallel transmission focuses on homogenizing flip angle (α) distributions but does not explicitly account for B1rms distribution.

In this work we propose a generalized pulse design framework that considers both α and B1rms and apply it to achieve uniform excitation and saturation at the same time. Performance is confirmed in phantom experiments at 7T, resulting in more uniform MTR compared to conventionally-designed pulses.
Correlation between GABA+ levels in mPFC and topological characters of EEG functional connectivity network during light sleep in young adults
Authors: Zhao Sihui , Liu Yanting , Gao Yanan , Yu bing , Mark Mikkelsen , Steve Hui , Richard Edden , Zhang Chen
Published: August 2023

The aim of our study is to explore the relationship between GABA levels of medial prefrontal cortex （mPFC）and the topological characters of cerebral EEG functional connectivity network in young adults during sleep using Hadamard Encoding and Reconstruction of Mega-Edited Spectroscopy (HERMES) method. Synchronous EEG-MRS data were acquired from 37 young adults. GABA+ level in mPFC and the global topological characters of the EEG functional connectivity network were calculated. The results demonstrated a significant negative correlation between global efficiency of EEG functional connectivity network in delta bandand and GABA+ levels in mPFC during N2 sleep stage.
Structural and functional changes of the cerebellum in patients with Parkinson's disease: a VBM and rs-fMRI study
Authors: Cheng xiu , Wang jun , Zhang pengfei , Zhang jing , Ai kai , Hu wanjun
Published: August 2023

To investigate the structural and functional alterations of cerebellum in patients with Parkinson's disease (PD) using voxel-based morphometry and resting-state functional MRI. We analyzed alterations gray matter volume (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF) in the cerebellum of PD patients. Furthermore, the correlation analysis between GMV, ALFF, ReHo values and clinical scale scores was performed. Our results showed that the structure and function of the cerebellum of PD patients are significantly different from healthy controls (HC), and these changes are significantly correlated with clinical scales scores, which suggested that the cerebellum plays an important role in PD.
Parkinson’s disease state modulates the effect of nigral iron deposition on the large-scale brain networks.
Authors: Wen Jiaqi , Guan Xiaojun , Guo Tao , Wu Jingjing , Bai Xueqin , Zhou Cheng , Wu Haoting , Liu Xiaocao , Chen Jingwen , Cao Zhengye , Zhang Yong , Gu Luyan , Pu Jiali , Zhang Baorong , Zhang Minming , Xu Xiaojun
Published: August 2023

In Parkinson’s disease (PD), nigral iron deposition exacerbates a-synuclein aggregation. In our study, we divided PD and normal controls (NC) into high iron group and normal iron group according to the median of nigral magnetic susceptibility of NC, respectively. ICA method was applied to separate brain large-scale networks. The PD*iron interaction effect on brain functional networks were investigated by mixed effect analysis. We found that PD disease status specifically moderates the effect of nigral iron deposition on the function of some regions in BGN and VN, which partially mediates the relationship between nigral iron deposition and disease severity.
Inhomogeneous Magnetization Transfer (ihMT) Helps to Detect Multiple Sclerosis Plaques in The Spinal Cord.
Authors: Kurosawa Ryuna , Yokota Hajime , Yoda Takafumi , Sada Takayuki , Matsumoto Koji , Namiki Takashi , Yoneyama Masami , Gilbert Guillaume , Masuda Yoshitada , Uno Takashi
Published: August 2023

Demyelination assessment with MRI for multiple sclerosis (MS) is a reliable biomarker for monitoring disease progression. Recently, inhomogeneous magnetization transfer (ihMT) combined sequencing has been developed for myelin-specific imaging. The purpose of this study was to evaluate ihMT in delineating MS lesions in the spinal cord by comparing the conventional imaging methods. The lesion-to-white matter contrast-to-noise ratio (CNR) on ihMT was significantly higher than the other methods. The qualitative analysis revealed clarity of lesion detection, but false positives were a concern. Our results in MS patients suggest that ihMT may be a helpful sequence for lesion detection.
Can MAP-MRI model be used for advance prediction of Grade II/III diffuse glioma genetics?
Authors: Wang Peng , Gao Yang , Wu Qiong , He Jinlong , Xie Shenghui , Wang Shaoyu , Zhang Huapeng
Published: August 2023

Although surgery is still the most effective treatment for diffuse glioma, patients with unresectable primary, recurrent, or multicentric illness have few options. In some cases, genotyping predictions may be useful for targeted therapy. We performed pretreatment MRI scans and genetic sequencing of tumor tissue, as well as correlation analysis, to see if essential molecular genetic events linked with diffuse glioma may be predicted in advance and noninvasively. The findings revealed that the MAP-MRI model can reliably predict tumor genotyping with high robustness and diagnostic validity, implying that it could be useful in the development of more standardized treatment.
Using graph convolutional network modeling to characterize functional network disruption in individuals with major depressive disorder
Authors: Qin Kun , Lei Du , Zhu Ziyu , Gong Qiyong
Published: August 2023

Few previous studies considered brain network architecture when establishing machine learning models to identify major depressive disorder (MDD). Based on a large, multi-site dataset including 1586 participants, this study aimed to use novel graph convolution network (GCN) to distinguish MDD patients from controls, identify MDD subtypes and characterize related network disruption. We found that GCN enabled excellent classification performance of over 80% accuracy. Besides, shared and distinct disrupted network patterns were identified in first-episode drug-naive and recurrent patients. These findings support the feasibility and effectiveness of network-based GCN classier, illustrating the utility of GCN for detecting disrupted network topology.
Altered macroscale neurovascular coupling in vascular cognitive impairment
Authors: Ruan Zhao , Liu Weiyin
Published: August 2023

This study aims to integrate psychological behavior, clinical biochemistry and other indicators, and use multi-mode MRI technology to explore specific imaging indicators of VCIND neurovascular coupling (NVC). NVC analysis and CBF/ ALFF ratio calculation were performed to investigate the neurovascular coupling changes and clinical significance of LVCI, SVCI and HC. Regardless of the level of the whole brain or brain regions, we have found neurovascular uncoupling in VCIND patients compared with healthy controls. These findings will be helpful in screening patients with VCIND, and has important theoretical and clinical significance in preventing and delaying the development of dementia.
Quantifying the Stiffness of Peritrigonal Terminal Zones in Preschool Children by Diffusion Imaging-based Virtual MRI Elastography
Authors: Zhang Na , Li Xianjun , Liu Congcong , Ge Yao , Feng Yuying , Bai Pengxuan , Wang Miaomiao , Yang Jian
Published: August 2023

The high signal intensity on T2-weighted images in terminal zones (TZ) mainly associated with lower maturational degree. We hypothesized that the stiffness in these regions may be different from typical developing children without TZ. Virtual stiffness of brain can be measured safely with virtual magnetic resonance elastography (vMRE). Therefore, this study tried to use vMRE to investigate differences between children with and without TZ. Results demonstrated that virtual stiffness of TZ was lower than controls, while higher than periventricular leukomalacia. These suggest that vMRE may provide additional information for evaluating brain maturation and injury.
Diagnostic performance of ADC and CBV imaging intersecting MRS for identifying molecular status in adult gliomas
Authors: Li Shuang , Su Xiaorui , Yue Qiang
Published: August 2023

Preoperative identification of IDH and 1p/19q codeletion could help clinical doctors make the optimal therapy plan. Although, there were few diagnostic studies could provide quantitative cutoff values of ADC and/or CBVfor identifying genogroup of gliomas. In this study, we calculated histogram metrics of ADC and CBV based on core tumor and used these metrics intersection MRS to establish diagnostic models to identify IDH mutant station and 1p/19q codeletion in turn. The main results showed that histogram metrics of ADC and CBV were powerful for identifying molecular status in adult gliomas. And MRS concentrations could improve diagnostic performance in both models.
Thalamic Plasticity in Brains with Glioma Investigated with Discrete Wavelet Transformation Analysis of Resting-state BOLD Fluctuations
Authors: Cai Siqi , Shi Zhifeng , Jiang Chunxiang , Zhou Shihui , Zhang* Lijuan
Published: August 2023

Thalamic plasticity plays an important role in the functional remodeling in brains with glioma. This study investigated the frequency-specific functional alteration of the thalami in the context of gliomas with discrete wavelet transformation and wavelet-energy. Brains with glioma in the left hemisphere featured with amplified inter-thalamus energy deviation for BOLD signals at 15.63-250mHz irrespective of the malignant grades, as compared with healthy controls. Similar analysis revealed no energy changes for the right brain gliomas. These findings suggest a differential thalamic plasticity that is specific to the tumor laterality, and may leverage innovation in the treatment of glioma involving neuromodulation.
Deep Learning with Anatomical Attention Mechanism for Distinguishing Parkinson’s Disease from Normal Controls in MR imaging
Authors: Wang Yida , He Naying , Wang Chenglong , Li Yan , Jin Zhijia , Zhao Xiance , Haacke Ewart Mark , Yan Fuhua , Yang Guang
Published: August 2023

We proposed an automatic cascaded framework based on deep learning to segment deep brain nuclei and distinguish Parkinson’s disease from normal controls using quantitative susceptibility mapping (QSM) images. A 3D CA-Net model integrating channel attention, spatial attention and scale attention module was utilized to segment 5 brain nuclei from QSM and T1W data. Then, the QSM images and the segmented brain nuclei ROIs were fed into the SE-ResNeXt50 with anatomical attention mechanism to get the predicted PD probability. The proposed method provided good interpretability and achieved AUC values of 0.97 and 0.90 on training and testing cohort, respectively.
Altered intrinsic functional connectivity across nine brain networks in early stages of idiopathic Parkinson’s disease
Authors: Shih Yao-Chia , Seow Pohchoo , Septian Hartono , Thomas Welton , Lee Weiling , Kuek Aeden Zi Cheng , Chong Say Lee , Ng Samuel Yong Ern , Chia Nicole Shuang Yu , Tan Eng-King , Tan Louis CS , Chan Ling-Ling
Published: August 2023

Parkinson’s disease (PD) is a common neurodegenerative disease. Besides motor deficits, autonomic and cognitive dysfunctions might be caused by global abnormalities beyond the dopaminergic system. We performed resting-state fMRI to measure functional connectivity between the central autonomic network and eight other critical resting networks in both early PD and healthy control groups. Using general linear models, we identified functional impairments in the inter- and intra-network connections in relation to various brain functions. These findings could shed light on the neural mechanisms behind the complex clinical manifestations evident even in the early stages of PD.
Linked brain connectivity patterns with psychopathological and cognitive phenotypes in drug-naïve first-episode schizophrenia
Authors: Sun Hui , Zhang Wenjing , Yang Chengmin , Gong Qiyong , Lui Su
Published: August 2023

Schizophrenia is characterized by abnormal functional integration between distinct brain regions but whether a common deficit in functional connectivity in relation to both clinical symptoms and cognitive impairments would present in drug-naïve first-episode patients remains elusive. A connectome-wise analysis on resting-state functional MRI in never-treated patients with first-episode schizophrenia. Using the principal component analysis, we found a trans-symptomatic pattern of functional connectivity associated with both psychopathological and cognitive manifestations in never-treated first-episode schizophrenia characterized as the dysconnections involving frontal and visual cortices, suggesting a core deficit of brain functional connectivity that might underpin the psychopathology of schizophrenia.
The disrupted subcortical functional gradient in schizophrenia and the normalization effects of antipsychotic treatment
Authors: YANG CHENGMIN , ZHANG WENJING , LIU JIAJUN , YANG ZHIPENG , LUI SU
Published: August 2023

To characterize the connectome gradient changes of subcortical system in drug-naive first-episode schizophrenia and the longitudinal treatment effect, we calculated the functional gradient and conducted the group comparisons. The principal gradient of subcortex demonstrated the fundamental functional segregation differences between patients at baseline and healthy controls, and the longitudinal analyses indicated that the treatment would gradually normalize the altered gradients with significant improvement of symptoms. This study provided the new perspective on the abnormal subcortical hierarchy organization in schizophrenia and its longitudinal gradient changes could be sensitive to reflect the antipsychotic treatment effect.
White matter fiber-specific alterations in bipolar disorder: a fixel-based analysis
Authors: Magioncalda Paola , Yeh Chun-Hung , Lin Hsiang-Yuan , Tseng Rung-Yu , Amore Mario , Martino Matteo
Published: August 2023

The recent unified model of the pathophysiology of bipolar disorder (BD) proposed that micro/macrostructural disturbance in limbic white matter (WM) fibers is important in the pathophysiological mechanism of BD. To gain more insights into this model, preprocessed diffusion MRI data of 67 BD and 125 healthy participants were analyzed using fixel-based analysis. We found a reduction of fiber density and/or cross-section of tracts, including the fornix and cingulum bundle that are core elements of the limbic system. These findings robustly support an association of BD with a specific spatial pattern of WM alterations.
The Trajectory of Knee Structures Before The Onset of Rheumatoid Arthritis: A 4-Year Longitudinal Magnetic Resonance Imaging Study
Authors: Zhong Qiaoling , Zhang Xintao , Zhang Zhongping , Zhang Xiaodong
Published: August 2023

The knee joint is one of the most commonly affected large joint in rheumatoid arthritis (RA). Its progression often causes joint destruction and deformity. The cartilage injury, bone marrow lesions and synovitis scores of the knees at baseline, P-1 (1 year prior to P0), and P0 (time of onset of RA) were evaluated using the MOAKS score. The generalized estimation equation (GEE) was used to compare the MR scores of knee joints at three time points to observe the longitudinal changes. The changes of bone marrow lesions and synovitis scores in knee joints were significant before the occurrence of RA.
Fibre-specific white matter alterations in recovered COVID-19 patients
Authors: Shen Yu , Bai Yan , Zhang Xianchang , Wu Yaping , Zhang Menghuan , Wang Meiyun
Published: August 2023

The brain fibre-specific changes in patients who recovered from Coronavirus Disease 2019 (COVID-19) for one year but still had anosmia (reCOVID19_ano) deserves to be investigated. This study used fixel based analysis (FBA), which is a novel diffusion MRI post-processing technique that enables fibre tract-specific statistical analysis, to investigate the white matter alterations in reCOVID19_ano. The results revealed that the intra-axonal volume in reCOVID19_ano was significantly increased in several fibre tracts. We speculate that impaired fibre tracts may recover gradually in a compensatory mechanism after one year recovery in reCOVID19_ano patients.
The performance of pretreatment MR-based radiomics in RHES combined chemoradiotherapy response prediction in nasopharyngeal carcinoma.
Authors: Huang Lixuan , Yang Zongxiang , Ren Hao , Tang Cheng , Zhang Huiting , Song Yang , Long Liling
Published: August 2023

This study is to investigate a MRI radiomics model based on pre-treatment texture features to explore its application value in predicting the efficacy of recombinant human endostatin(RHES) combined concurrent chemoradiotherapy for nasopharyngeal carcinoma. The results showed that the AUC and the accuracy of radiomics-clinics combine model and radiomics model for response assessment in nasopharyngeal carcinoma(NPC) was higher than clinics model. These suggest that pretreatment MRI based radiomics could predict RHES combined concurrent chemoradiotherapy response in NPC, its accuracy was better than clinics model.
Combined 7T CEST/MRS imaging to predict tumor metabolism in glioma
Authors: Yuan Yifan , Yue Qi , Zou Xiang , Guo Yu , Chu Ying-Hua , Hsu Yi-Cheng , Liebig Patrick , Yu Wenwen , Wang He , Chen Liang , Mao Ying
Published: August 2023

Magnetic resonance imaging has been applied in intraoperative neuro-navigation and irradiation guidance in glioma diagnosis. The contrast-enhanced MRI or peritumor edema on T2w image is not precise enough to delineate tumor infiltration. MR spectroscopy (MRS) and chemical exchange saturation transfer (CEST) have been used to evaluate tumor metabolism. Studies showed that amino acid PET surpassed conventional MR imaging for tumor delineation. Here, we explored the correlation between MRS and CEST at 7T and chose PET as gold standard to investigate multimodal MR imaging for glioma metabolic characteristics and tumor extent. An exemplary case with stereotactic biopsy proof was shown.
Three-dimension Amide Proton Transfer Imaging for Predicting the Treatment Response of Nasopharyngeal Carcinoma
Authors: Liu Wenguang , Pei Yigang , Xie Simin , Wang Xiao , Bai Yu , Zhou Gaofeng , Liu Weiyin , Li Wenzheng
Published: August 2023

To predict the treatment response for NPC patients is very important. This study aimed to explore the diagnostic performance of 3D APT imaging on predicting the treatment response of NPC patients. A total of 40 patients and 14 healthy volunteers were identified in this study. Result show that the APT and MT values have good and excellent intra- and inter-observer agreement. It is significant difference for MT values between residual and non-residual group. The result suggests that the pre-treatment MT values can be used to predict treatment response of NPC with chemoradiotherapy, and better than the APT and ADC value.
Real-time MRI for assessment of patients with esophageal hiatal hernia: a feasibility research
Authors: Wu Chao , Zhang Peng , Zhang Chen , Li Yajun , Sun Haoran
Published: August 2023

The purpose of this study was to observe the swallowing process of hiatal hernia patients using real-time magnetic resonance imaging (MRI) and to evaluate the transport of contrast agents through the gastroesophageal junction and the induction of sliding hernia during Valsalva. Results showed that hiatal hernia was detected in all patients enrolled in the study. Therefore, real-time MRI imaging of sliding hiatal hernia has great potential for clinical application.
Assessment of lumbra osteoporosis using MRI fat content quantitative technology：comparison with QCT
Authors: Huang Chumin , Zeng Zisan , Zhang Huiting
Published: August 2023

The purpose of this study is to explore the feasibility of magnetic resonance imaging (MRI) 3D multi-echo-Dixon (ME-Dixon) and T2-corrected multi-echo single-voxel (HISTO) spectroscopy sequences to evaluate osteoporosis by comparison with quantitative computed tomography (QCT). The results show that the proton density fat fraction (PDFF) values of bone marrow measured by these two MRI methods have high and significantly negative correlation with bone mineral density (BMD) values measured by QCT at lumbar.
Developing a comprehensive whole body MR protocol and model generation pipeline for children
Authors: Kumar* Haribalan , Green* Robby , Holdsworth Samantha , Cornfeld Daniel , Condron Paul , Kwon Eryn , Emsden Taylor , Choisne Julie , Besier Thor , Fernandez Justin , Gilbert Kat , Nash Martyn , Safaei Soroush , Talou Gonzalo Maso , Taylor Davidson , Rolfe Luke , McHugh Lucy , Smith Graham , Potter Leigh , Tawhai Merryn , Burrowes Kelly , Clark Alys , Shan Jiantao , Soltani Elias , Hogarth Erana , Murphy Rinki , McGeown Josh , Carman Laura , Wang Alan , Tayebi Maryam , Mirjalili Ali , Cleland-Pottie Grace , Osanlouy Mahyar , Shim Vickie , Maller Jerome , Ropiha Reweti , Wilson Graham
Published: August 2023

Approaches to magnetic resonance (MR) image acquisition and computational modelling often exist in silo. The application of computational modelling to paediatric data is in its infancy. This collaborative study addresses this gap for multiple organ systems. State-of-the art MR imaging sequences were selected and refined to provide imaging data for the creation of subject-specific geometric models. The MR protocol and modelling outputs will underpin a longitudinal paediatric study set in Aotearoa New Zealand, generating normative data in healthy children, and identifying early biomarkers of pathological processes. This will enable the development of new personalised, predictive, and preventative models of care.
MVPA using the hyperaligned 7T-BOLD signals revealed that the initial decrease contains finer information to decode facial expressions
Authors: Tanaka Toshiko , Okamoto Naohiro , Kida Ikuhiro , Haruno Masahiko
Published: August 2023

Previous studies suggested that the initial decrease in the BOLD signal reflects primary neuronal activity more than the later hemodynamic positive peak responses. We applied the hyper-alignment algorithm to 7T-BOLD timeseries during the facial expression discrimination task. and conducted the MVPA using the aligned data. We found decoding accuracies in the amygdala and superior temporal sulcus at 2 s after the face onset were significantly beyond baseline and the voxels contributing to the decoding accuracy displayed decreasing pattern in hemodynamics response, revealing that the initial decrease in 7T-BOLD signals contains finer information than thought previously.
Deep Learning-based Generative Adversarial Registration NETwork (GARNET) for Hepatocellular Carcinoma Segmentation: Multi-center Study
Authors: Yu Hang , Zheng Rencheng , Chen Weibo , Li Ruokun , Shi Huazheng , Wang Chengyan , Wang He
Published: August 2023

This study proposed a deep learning-based generative adversarial registration network (GARNET) for multi-contrast liver image registration and evaluated its value for hepatocellular carcinoma (HCC) segmentation. We used generative adversarial net (GAN) to synthesize images from diffusion-weighted imaging (DWI) to dynamic contrast-enhanced (DCE) and then applied for deformable registration on the synthesized DCE images. A total of 607 cirrhosis patients from 5 centers (401 HCC patients) were included in this study. We compared the proposed method with symmetric image normalization (SyN) registration and VoxelMorph. Experimental results demonstrated that GARNET improved the registration performances significantly and yielded better segmentation of HCC lesions.
Unsupervised Domain Adaptation via CycleGAN for knee joint Segmentation in MR Images
Authors: LI Siyue , Khan Sheheryar , XIAO Fan , ZHAO Shutian , ZHONG Junru , Cahill Dόnal , Griffith James , CHEN Weitian
Published: August 2023

Knee joint tissues segmentation is necessary for quantitative analysis of musculoskeletal diseases like knee osteoarthritis. Three-dimensional Fast Spin Echo (3D FSE) imaging is a potential MRI technique for routine clinical knee imaging. Thus, segmentation based on 3D FSE has valuable clinical application. However, the conventional deep learning-based segmentation requires manually annotating 3D knee images which is time-consuming. In this work, we proposed a domain adaption-based unsupervised approach for cartilage and meniscus segmentation on 3D FSE images without the need for annotating images. We demonstrated that the proposed method improved the quality of segmentation.
A Model-based Neural Network for shear modulus estimation of MRE
Authors: Wang Runke , Chen Yu , Qiu Suhao , Feng Yuan
Published: August 2023

Algorithms providing accurate estimation of shear modulus and identification of tissue boundary are always desired for magnetic resonance elastography (MRE). In this study, we proposed a model-based neural network (MNN) embedding classic direct inversion (DI) and local frequency estimation (LFE). Convolution layers with Inception-like structure were applied for preprocessing, while postprocessing was implemented with a U-net structure. Additionally, DI and LFE algorithms were encapsulated as layers transforming wave images to shear modulus maps. The network performance was tested using a phantom with an inclusion. Compared with conventional algorithms, MNN provided modulus estimation with 5-fold higher contrast-to-noise ratio with clear boundaries.
A traveling-wave expansion based subspace search (TWESS) for shear modulus estimation using magnetic resonance elastography
Authors: Ma Shengyuan , Feng Yuan
Published: August 2023

We proposed a traveling-wave expansion based subspace search (TWESS) algorithm for modulus estimation of MRE. Based on a traveling wave decomposition model, we explore the orthogonal characteristics of the signal subspace and the noise subspace. Eigenvalue decomposition of the covariance matrix of the wave data were used to search the wavenumber and retrieve the local modulus. Results showed the proposed method could provide better delineation of the inclusion boundaries, even when signal-to-noise ratio of the image was low.
Ultrafast water-fat separation using deep learning-based single-shot MRI
Authors: Chen Xinran , Wang Wei , Huang Jianpan , Wu Jian , Chen Lin , Cai Congbo , Cai Shuhui , Chen Zhong
Published: August 2023

Water-fat separation is a powerful tool in diagnosing many diseases and many efforts have been made to reduce the scan time. Spatiotemporally encoded (SPEN) single-shot MRI, as an emerging ultrafast MRI method, can accomplish the fastest water-fat separation since only one shot is required. However, the SPEN water/fat images obtained by the state-of-the art methods still have some shortcomings. Here, a deep learning approach based on U-Net was proposed to obtain SPEN water/fat images simultaneously with improved spatial resolution, better fidelity and reduced reconstruction time. The efficiency of our method is demonstrated by numerical simulations, and in vivo rat experiments.
Helmholtz Decomposition-Based Method for EPT with Approximation of Unmeasurable Magnetic Field Components Using Homogeneous Simulation Model
Authors: Eda Naohiro , Fushimi Motofumi , Nara Takaaki
Published: August 2023

We previously reported a method for magnetic resonance electrical properties tomography (MREPT) based on Helmholtz decomposition at ISMRM 2021. However, the method causes a reconstruction error due to the assumption that the unmeasurable components of the magnetic field are zero. This paper extends our previous method by approximating the unmeasurable components using a homogeneous simulation model that has the same geometry as the object to be examined and has homogeneous electrical properties (EPs). The efficacy of the proposed method was validated through numerical simulations.
High Accuracy Heartbeat Detection with 433MHz CW-Doppler Radar for MRI Application
Authors: Wu Yuxin , Pauly John , Scott Greig
Published: August 2023

This work assesses heartbeat detection by continuous-wave (CW) Doppler radar using low and high carrier frequencies of 433MHz and 5GHz as options for non-contact vitals sensing in MRI. The experimental results show that using the amplitude of received complex signals in low frequency 433MHz-detection can perform as well as 5GHz-detection due to near field interactions within a 20cm range, with similar heartbeat detection efficacy.
Actively Shielded Two-channel Transverse MRI Gradient Coil Numerical Design Using Discrete Wire Method
Authors: Kassahun Haile , Alsharafi Sadeq , Badawi Ahmed , El-Sharkawy AbdEl-Monem
Published: August 2023

A two-channel, self-shielded, cylindrical, transverse gradient coil is numerically designed. The four quadrants of both the inner and outer cylinders were each divided into two sections. All symmetric inner sections of the primary and corresponding shielding coil turns are assigned to the first channel where the outer enclosing sections belong to the second channel. Quasi-elliptic curves are used for coil tracks design. Achieving a comparable target gradient field, the DC dissipated power of a two-channel coil is lower compared to a conventional coil designed with similar dimensions and number of turns by at least 20%, thereby reducing ohmic losses.
Hippocampal subfield-specific alterations in post-stroke dementia with subcortical lesion
Authors: Wu Yihan , Cai Huaying , Ni Linhui , Han Guocan , Zhao Zhiyong , Wu Dan
Published: August 2023

The present study aimed to explore functional and structural alterations in hippocampus and its subfields in post-stroke dementia (PSD). We collected resting-state fMRI and DTI data from 24 PSD patients, 36 post-stroke nondemented (PSND) patients and 21 normal controls (NC). Comparisons between groups found that PSD patients showed subfield-specific changes in the microstructures of hippocampus compared with the other two groups. Moreover, we not only found more PSD-related changes of functional connectivity with cortical regions in the subfields than entire hippocampus, but also revealed the different contributions of subfields on the connectivity changes of entire hippocampus.
Comparison of different T2 fitting models in renal tissue relaxometry
Authors: Zhao Wan-Ting , Herrmann Karl-Heinz , Krämer Martin , Güllmar Daniel , Reichenbach Jürgen , Hoerr Verena
Published: August 2023

While relaxation rate estimation substantially varies on the chosen fitting method, a tissue-specific T2 fitting scheme for the kidney is lacking. The current study aims to compare multiple T2 fitting methods, including square signal and mono-exponential with constant offsets, in high SNR and low SNR scenarios from identical data points. We compare standard deviations for fitting robustness and RMSE for the goodness of fit. Our finding suggests a mono-exponential with constant offsets is the most suitable method, for it yielded the lowest RMSE both in high and low SNR.
Using amide proton transfer-weighted (APTw) MRI to detect severity and predict outcome after traumatic brain injury (TBI) in rats
Authors: Dong Yinfeng , Gu Yanting , Lu Jianhua , Wan Jieru , Jiang Shanshan , Koehler Raymond , Zhou Jinyuan
Published: August 2023

After TBI, secondary injury severity is difficult to determine. The objective of this study was to investigate the capacity of noninvasive APTw MRI to assess TBI injury in different brain regions and predict long-term neurobehavior outcomes. Fifty-five male and female rats were subjected to a controlled cortical impact with one of three different impactor depths to produce different degrees of TBI, and scanned on a 4.7 T horizontal bore animal imager. Our results suggest that APTw imaging can be used for detecting the level of inflammation and as a potential predictor of long-term outcomes from TBI.
Clinical DIADEM: Distortion-Free High-Resolution Diffusion-Weighted Imaging of the Brain.
Authors: In Myung-Ho , Campeau Norbert , Trzasko Joshua , Kang Daehun , Welker Kirk , Huston John , Shu Yunhong , Bernstein Matt
Published: August 2023

Echo-planar based diffusion-weighted imaging (DWI) of the brain is prone to local image distortion which can lead to misdiagnosis or nondiagnostic image quality in areas prone to susceptibility effects. A novel distortion-free imaging scheme, termed DIADEM (Distortion-free Imaging: A Double Encoding Method) was recently introduced and optimized for brain imaging on a high-performance experimental Compact 3T system. In this study, we fully implement the DIADEM DWI technique on two 510-k cleared, whole-body 3T scanners and explore the clinical feasibility for its use in routine clinical practice.
Normalization of conductivity maps to support identification of pathologic areas
Authors: Katscher Ulrich , Tha Khin
Published: August 2023

Electrical tissue conductivity is an emerging quantitative diagnostic parameter, particularly for oncology. Conductivity typically increases with tumor malignancy, however, high conductivity per se is no indication for abnormal tissue, since many tissue types are highly conductive without being abnormal. An empirical rule correlates tissue conductivity with tissue water content. One possibility to analyze abnormality of tissue is thus to compare conductivity as measured with conductivity as expected from water content. The obtained difference yielding “normalized” conductivity might serve as a more direct measure of tissue abnormality. This study presents this concept using pathologic and healthy in vivo example cases.
A deep learning diffusion MRI registration method using joint whole-brain and tract-specific information
Authors: Zhang Fan , Wells William , O'Donnell Lauren
Published: August 2023

We present a novel deep learning method, DDMReg, for accurate dMRI registration. In dMRI registration, the goal is to align brain anatomical structures while ensuring local fiber orientations consistency with the underlying white matter anatomy. DDMReg is an unsupervised method for deformable dMRI registration, without the need of non-rigidly pre-registered images and the corresponding deformation field as ground truth. We propose a novel registration architecture that leverages not only whole-brain information but also tract-specific fiber orientation information. We perform comparisons with four state-of-the-art methods on several independently acquired datasets. Experimental results show that DDMReg obtains highly improved registration performance.
Iron and Myelin Content in Multiple Sclerosis Lesions using Magnetic Susceptibility Source Separation
Authors: Rahmanzadeh Reza , Lu Po-Jui , Shin Hyeong-Geol , Weigel Matthias , Nguyen Thanh , Wang Yi , La Rosa Francesco , Cuadra Meritxell Bach , Radue Ernst-Wilhelm , Kuhle Jens , Kappos Ludwig , Lee Jongho , Granziera Cristina
Published: August 2023

Most multiple sclerosis (MS) white matter lesions (WMLs) appears hyperintense in quantitative susceptibility mapping (QSM). In the present study, we investigated the comparative contribution of myelin loss and iron deposit to QSM hyperintensity using a susceptibility source separation algorithm disentangling QSM- positive and QSM-negative susceptibility sources. Our results show that in most MS WMLs, demyelination is the source of QSM hyperintensity.
An 8-Channel Shielded Transceiver Coil for Carotid Artery imaging at 7T
Authors: Yazdanbakhsh Pedram , Couch Marcus , Gilbert Kyle , Derhovagimian Johnny , Hoge Richard
Published: August 2023

An 8-channel shielded transmit/receive RF array has been designed and fabricated for imaging the carotid arteries at 7T. The array, similar to that presented in Ref. [1], consists of four overlapping surface loops per side. In addition to the Ref. [1], we have also added two RF shields per side with DC blocking capacitors to mitigate eddy currents. To ensure robust safety of the 7T pTx coil, local SAR matrices, and the commensurate virtual observation points (VOPs), were calculated for online SAR supervision [2,3]. Finally, the phase and amplitude of each channel have been optimized to achieve maximum B1+ homogeneity.
Improving fMRI acquisition using single-shot EPTI with distortion-free high-SNR high-CNR multi-echo imaging
Authors: Wang Fuyixue , Dong Zijing , Chen Jingyuan , Setsompop Kawin , Polimeni Jonathan , Wald Lawrence
Published: August 2023

This work aims to address the limitations of EPI and improve fMRI acquisition by developing a single-shot EPTI method, to provide fast distortion-free imaging, with significantly improved tSNR, CNR, robustness to motion, reduced signal dropout, and multi-echo capability for denoising/analysis. The single-shot acquisition is enabled by the newly-designed k-t encoding to provide stronger correlation for improved reconstruction. Results show ss-EPTI achieves: i) 30% higher tSNR efficiency than EPI and 70% higher than 3-shot EPTI; ii) 50% higher CNR than EPI (visual-task); iii) distortion-free fMRI with improved robustness to motion; iv) effective signal dropout reduction; and v) effective non-BOLD variation separation.
Fat-Compensated T1 Mapping of Non-Alcoholic Fatty Liver Disease with MPRAGE and MP2RAGE
Authors: Duffy Andrew , Costa Andreu , Clarke Sharon , Stueck Ashley , McLeod Magnus , Rioux James
Published: August 2023

Fat is a confounding factor in the use of T1 measurements as a non-invasive method of assessing non-alcoholic fatty liver disease. A Dixon-based water/fat separation was used to produce T1 maps based on the separated water signal in MPRAGE and MP2RAGE sequences. A correlation inconsistent with biophysical processes was observed between uncorrected MP2RAGE T1 values and fibrosis stage, but using the fat compensated T1 values corrects the correlation. The same effect was seen to a lesser extent with MPRAGE T1 values. Further investigation and validation with a larger cohort may provide a more reliable biomarker of liver fibrosis within NAFLD.
High-Resolution Half-Spoke and Full-Spoke 4D Lung MRI with Golden-Angle 3D Radial Acquisition and Motion-Resolved Sparse Reconstruction
Authors: Wu Can , Krishnamoorthy Guruprasad , Subashi Ergys , Yu Victoria , Otazo Ricardo
Published: August 2023

This work aims to develop high-resolution 4D lung MRI with golden-angle 3D radial (kooshball) acquisition and motion-resolved sparse reconstruction. The golden-angle radial k-space lines were continuously acquired during free-breathing and retrospectively binned to multiple respiratory phases with respect to the respiratory signal obtained from a built-in motion-sensing camera. The sparsity along the respiratory motion dimension was exploited using compressed sensing reconstruction to suppress artifacts and improve SNR. The feasibility of half-spoke ultrashort echo time (UTE) and full-spoke 4D lung MRI was demonstrated on healthy volunteers on a clinical 3T MRI scanner.