bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychophysical evaluation of radiologic vs. deep-learning based identification of multiple sclerosis brain lesions
Authors: Solomon Chen , Shmueli Omer , Blumenfeld-Katzir Tamar , Radunsky Dvir , Omer Noam , Stern Neta , Shrot Shai , Salti Moti , Greenspan Hayit , Ben-Eliezer Noam
Published: August 2023

Computer assisted detection (CAD) of pathology in MRI scans may provide higher sensitivity to tissue changes. We present rigorous comparison of CAD vs. conventional radiologic evaluation of multiple sclerosis (MS) lesions. A psychophysical experiment was performed, where radiologists and a deep neural-network were asked to detect artificial MS lesions, synthetically simulated on T2-weighted FLAIR images, and at 8 levels of severity. Odds ratio analysis indicated that the human vision is less sensitive to low-severity lesions. This suggests that CAD can improve early detection of tissue abnormalities in the brain.
Repeatability and accuracy of MR-STAT quantitative T1 and T2 measurements
Authors: van der Heide Oscar , Fuderer Miha , Liu Hongyan , van den Berg Cornelis , Sbrizzi Alessandro
Published: August 2023

MR-STAT is a quantitative MRI technique that obtains multiple tissue parameter maps (e.g. T1, T2) from a single, short scan. In this study we perform an accuracy and repeatability study of MR-STAT using a Cartesian FISP-based sequence by repeatedly scanning Eurospin gel tubes and comparing the results against reference measurements. We observe coefficients of variation between 0.5 % and 1.5 % for T1 and between 2.0 % and 7.2 % for T2. The mean relative errors as compared to the reference measurements are -1.5 % for T1 and 5.8 % for T2.
Dynamic Glucose Enhanced (DGE) CEST imaging at 3T: from phantom to patient with brain metastases
Authors: Wu Yulun , Derks Sophie , Wood Tobias , van der Veldt Astrid , Smits Marion , Warnert Esther
Published: August 2023

To develop detection of glucose contrast enhancement (GCE) with CEST for assessing brain metastases in clinical setting, here we performed a phantom study, scanned 10 healthy volunteers and one patient with brain metastases at 3T. We acquired dynamic GCE at 1.2 and 2 ppm for dynamic B0 correction and applied principle component analysis (PCA) to perform noise reduction, after which we compared the resulting GCE at both offsets. The developed pipeline resulted in GCE of ~5% in tumor and -5 to 0.05% in healthy tissues after glucose infusion.
Towards gradient perturbation correction in diffusion weighted imaging based on the gradient system transfer function
Authors: Scholten Hannah , Köstler Herbert
Published: August 2023

Eddy current induced field perturbations can cause artifacts in diffusion weighted imaging (DWI). Such perturbations may be calculated and corrected for by the gradient system transfer function (GSTF), provided the gradient system behaves linear and time-invariant. We discovered that the linearity assumption can be violated by gradients with high zeroth order moments. We therefore propose a modified measurement scheme for the GSTF including higher gradient moments to better approximate their behavior. Our approach substantially reduces errors in the predicted gradient time courses. We may thus enable the application of GSTF-based correction methods to DWI in the future.
Safety of 4-channel parallel RF transmission MRI at 3 T: Effects of system uncertainty and system failure pertinent to deep brain stimulation
Authors: Yang Benson , Chen Chih-Hung , Graham Simon
Published: August 2023

Parallel radiofrequency transmission (pTx) technology continues to demonstrate its potential at addressing MRI safety concerns relating to patients with implanted deep brain stimulation devices. One promising technique involves electromagnetic simulation that determine optimized pTx inputs to generate a safe mode of imaging surrounding the implanted device. However, in practice, instrumentation uncertainty can impact the ability of the pTx system to accurately produce the desired signals. The present work studied the safety implications of system uncertainty and system failure in a 4-channel pTx platform. The preliminary results showed that in a worst-case scenario, temperature elevations that exceed MRI guidelines are possible.
Assessing Skeletal Muscle Metabolism with PCr, NAD+NADH, and pH measurement with Dynamic 31P MRS at 7T
Authors: Merugumala Sai , Liao Huijun , Zhao Wufan , Lin Alexander
Published: August 2023

A supine leg extension ergometer targeting the quadriceps femoris was built to be MR compatible and dynamic 31P-MR spectroscopy was acquired during an exercise challenge in a 7 Tesla MRI system. With the higher field strength, PCr and PCr recovery could be measured with a high confidence of fit without the need for additional smoothing and filtering steps. The increased spectral dispersion at 7T shows sufficient separation between the NAD+NADH resonance in addition to increased SNR. pH estimation in the active skeletal muscle was also performed.
Restoration of Missing or Erroneous Muscle Fiber Tracking Data Using Smoothed Polynomial Coefficients
Authors: Damon Bruce , Hooijmans Melissa , Lockard Carly , Zhou Xingyu
Published: August 2023

Diffusion-tensor tractography is used to quantify functionally relevant muscle architectural variables, including fiber tract length, orientation, and curvature. However, image noise and artifacts cause positional errors in the fiber tracking points and may cause tracts to terminate prematurely. The effect of the points’ positional errors on estimates of muscle fiber curvature can be mitigated through the use of polynomial fitting. Here we test several approaches for smoothing the spatial field of polynomial fitting coefficients and reconstructing missing or shortened-length fiber tracts. We show that median filtering of the polynomial coefficients retains additional fiber tracts without altering the median architectural properties.
Optimization of Compressed Sense accelerated 3D pelvis view for diagnosis of rectal cancer
Authors: Gong Xiaoling , Wen Daguang , Shen Yu , Wei Mingtian , Zhang Xiaoxiao , Zhang Xiaoyong , Huang Haoyu , Wang Ziqiang , Wu Bing
Published: August 2023

Although 3D T2W imaging can make up for deficiencies, such as thick layer thickness, low spatial resolution and no retrospective post-processing, of 2D acquisitions, the long imaging time and uncertain diagnostic benefits have limited its clinical application. We compared the quality of 2D, 3D and CS sense accelerated 3D T2W imaging in patients with rectal cancer and found that 3D T2W imaging resembled CS sense accelerated 3D T2W imaging, both superior to 2D acquisitions, while the latter scanning faster than the former. It’s conclude that CS sense accelerated 3D T2W imaging can substitute the 2D acquisitions.
In vivo characterization of preclinical hereditary RCC models by Electron Paramagnetic Resonance and Magnetic Resonance Imaging
Authors: Shibata Yuki , Crooks Daniel , Kishimoto Shun , Krishna Murali , Linehan W.
Published: August 2023

Human renal cell carcinomas (RCC) have a variety of pathologies and are known to have alterations in cellular metabolism, although many aspects remain unknown. Fumarate hydratase (FH)-deficient tumors exhibit a shift to aerobic glycolytic system due to several factors including loss and mutation of mitochondrial DNA. We investigated the partial pressure of oxygen, vascular permeability, and blood perfusion in FH-deficient UOK262 xenografts and a type 1 papillary RCC xenograft using EPRI and DCE-MRI. Despite low oxygen consumption rates in vitro, UOK262 xenografts showed a modest median pO2 and increased hypoxic fraction as compared to a type 1 papillary RCC xenografts.
Low-grade glioma resting-state fMRI pre-operative maps: a comparison with functional atlas from direct electrode stimulation.
Authors: Luciani Beatrice , Cabalo Donna , Saviola Francesca , Zigiotto Luca , Tambalo Stefano , Zacà Domenico , Novello Lisa , Sarubbo Silvio , Jovicich Jorge
Published: August 2023

A cortical-subcortical functional atlas has been recently proposed from direct-electrode stimulation on low grade glioma patients. The agreement between that atlas and non-invasive pre-operative resting-state functional MRI (rs-fMRI) data has not yet been investigated. In this study, we use pre-operative rs-fMRI data and the RestNeuMap tool to investigate the agreement between language and sensory networks in a group of low grade glioma patients. We find that rs-fMRI networks of language and speech arrest show greater overlap with DES-derived functional atlas than the sensorimotor network.
Quantitative characterization of fibrous tissues in the knee joint using magnetization prepared 3D spiral UTE sequence at 3 T
Authors: Martirosian Petros , Zhang Cecilia , Schwartz Martin , Benkert Thomas , Schick Fritz
Published: August 2023

Magnetization prepared 3D spiral UTE sequences were developed for T1, T2, T1rho and MTR measurements of fibrous structures. The robustness of the parameter mapping for tendons, ligaments, menisci, cartilage and muscle of the human knee joint was evaluated in a test-retest repeatabilty study. Multiparametric UTE imaging was successfully performed for both test and retest examination. The results of the study demonstrate good repeatability of the applied multiparametric protocol. Parameter maps such as T2 and T1rho show less robustness than T1 and MTR measurements. Especially with small structures as tendons and ligaments, there is the least agreement between scan and rescan.
Orientation Dependence of Myelin Water Fraction as Measured by MET2
Authors: Alderson Hannah , Does Mark
Published: August 2023

This study investigated the orientation dependence of myelin water fraction (MWF) as evaluated with a 3D multiple-spin echo sequence (MSE). MSE and diffusion tensor scans were acquired at 7-T from two excised rat brains at three different orientations with respect to the main magnetic field. Region of interest analysis of the corpus callosum and the internal capsule revealed that there is no clear orientation dependency for MWF in these white matter tracts. This result is also evidenced by the minimal orientational modulation of the T2 spectra for both ROIs across both brains.
Myelin Water Imaging and Diffusion Tensor Imaging in Pediatric Acute Lymphoblastic Leukemia Patients
Authors: Song Ruitian , Glass John , Reddick Wilburn
Published: August 2023

Myelin water imaging (MWI) and diffusion tensor imaging (DTI) was performed at two longitudinal time points, approximately two years apart, during chemotherapy in patients treated for acute lymphoblastic leukemia (ALL). DTI metrics correlated with MWF and LWF at time point 1, but the correlations were weaker at time point 2 (TP2). This may be caused by a possible decoupling of the relationship at TP2 as the brain is recovering from the impact of chemotherapy.
Towards a robust and reproducible GluCEST analysis pipeline
Authors: Jee Joelle , Nanga Ravi Prakash Reddy , Cember Abigail , Jacobs Paul , Robinson Heather , Elliott Mark , Reddy Ravinder , Roalf David
Published: August 2023

Robust, reproducible methods are paramount in neuroimaging. This is a challenge for leading-edge and novel techniques at 7T MRI, such as glutamate-weighted chemical exchange saturation transfer (GluCEST). As such, our primary objective is to move towards a robust and reproducible analytical pipeline for GluCEST imaging data. Here we show, using python-based neuroimaging tools, the development of GluCEST-prep. GluCEST-prep incorporates common neuroimaging analysis steps—brain extraction, tissue segmentation, co-registration and normalization—that are optimized for 7T MRI and uses python-based analysis—in place of in-house MATLAB scripts—to generate post-processed 2D or 3D GluCEST images in both native and template space.
A Novel Volume-Surface Integral Equation Formulation of Global Maxwell Tomography: Simulations and Experiments.
Authors: Giannakopoulos Ilias , Seralles Jose , Paska Jan , Guryev Georgy , Ianniello Carlotta , Daniel Luca , White Jacob , Brown Ryan , Sodickson Daniel , Lattanzi Riccardo
Published: August 2023

Global Maxwell Tomography (GMT) is an inverse scattering technique that estimates electrical properties (EP) from magnetic resonance measurements. The original GMT relies on an approximation of the incident fields, which is not accurate for experiments, especially in-vivo. We propose a new GMT formulation, based on the volume-surface integral equation (VSIE) method, where we implicitly re-estimate the incident fields accounting for the updated EP in every GMT iteration. We show average EP reconstruction error below 8% for a uniform phantom experiment and below 10% for a simulation experiment with a heterogeneous head model and realistic SNR.
Toward static-inhomogeneity-insensitive detection of neuro-electro-magnetic fields via compensated rotary saturation
Authors: Gram Maximilian , Albertova Petra , Schirmer Verena , Blaimer Martin , Gamer Matthias , Herrmann Martin J. , Jakob Peter Michael , Nordbeck Peter
Published: August 2023

Resonant absorption during spin-lock preparation can be used to measure tiny oscillating magnetic fields acting as direct evidence of electrical neuronal activity. Different spin-locking techniques were compared with respect to their sensitivity in magnetic field detection. As a specialty, the oscillating magnetic fields were generated by the built-in gradient system in an offcenter slice. The spin-lock time was identified as the crucial parameter for the performance of NEMO (neuro-electro-magnetic-oscillations) detection, since minima and maxima in the signal amplitude emerged in phantom and in vivo experiments. Affirmative, the experimental results show an excellent agreement with simulation results.
Gradient based emulation of neuro-electro-magnetic oscillations: A validation technique for MRI-based detection of Biomagnetism
Authors: Albertova Petra , Gram Maximilian , Schirmer Verena , Blaimer Martin , Herrmann Martin J. , Gamer Matthias , Nordbeck Peter , Jakob Peter Michael
Published: August 2023

Spin-lock based absorption of magnetic oscillations offers potential for direct detection of electrical neuronal activity. We propose a novel versatile validation and calibration technique which paves the way for emulation and quantification of biomagnetic fields. Using ultra-weak gradient waveforms, the method mimics brain activity and thus projects artificial fields onto the tissue under investigation. The method applicable for sequence validation or signal calibration was tested in phantom and in vivo experiments with the built-in gradient system providing sinusoidal field modulations down to 1 nT. It proved to be reliable and reproducible and hence can potentially enable quantification of biomagnetic fields.
Frequency-selective pTx pulses for 3D echo planar imaging at ultra-high field
Authors: Joseph Arun , Liebig Patrick , Bonanno Gabriele , Jin Jin , Majewski Kurt , Kober Tobias , Hilbert Tom
Published: August 2023

Echo planar imaging is an important MR technique used for different applications in both structural and functional imaging. It is typically used with fat suppression to avoid phase inconsistencies induced by the chemical shift of the fat signal. pTx pulses are used to mitigate the B1+ bias field occurring at higher fields strengths; typical pTx pulses do however not suppress the fat signal. In this work, we designed a frequency-selective water excitation pTx pulse to be used in 3D EPI acquisitions, enabling homogenous, high-resolution whole-brain fat-free imaging at 7T.
Velocity selective arterial spin labelling using parallel transmission
Authors: Wu Chia-Yin , Jin Jin , Dixon Carl , Maillet Donald , Barth Markus , Cloos Martijn
Published: August 2023

In this work, we demonstrate a parallel transmit implementation of velocity selective arterial spin labelling (VSASL) at 7 Tesla on a custom flow phantom developed in house. The use of tailored pTx pulses can greatly mitigate the transmit field inhomogeneities present at higher field strengths. By manipulating the time symmetry of the pTx pulses in the VSASL module we were able to show significant improvement in velocity selective inversion fidelity.
Region-specific neurovascular decoupling associated with cognitive decline in Parkinson’s disease
Authors: Shang Song'an , Dou Weiqiang , Wu Jingtao
Published: August 2023

Cognitive deficits are prominent non-motor symptoms in Parkinson’s disease (PD) and have been involved with neurovascular unit. However, sufficient neuroimaging studies are lacked investigating the associated modulating mechanisms. This study aimed to identify the contribution of neurovascular decoupling to the pathogenesis of cognitive decline in PD by integrating informative data obtained from the blood oxygen level-dependent and arterial-spin-labeling approaches. The involvement of neurovascular decoupling in cognitive impairment in PD is regionally specific and most prominent in the visual-spatial cortices, which could potentially provide a complementary understanding for the pathophysiological mechanisms underlying cognitive deficits in PD.
Early disturbance of dynamic synchronization and neurovascular coupling in cognitively normal Parkinson’s disease: an integrated MRI study
Authors: Shang Song'an , Dou Weiqiang , Wu Jingtao
Published: August 2023

For Parkinson’s disease (PD), the time-varying properties of functional coherence and their coupling to regional perfusion are rarely elucidated. We aimed to investigate early disruption of dynamic regional homogeneity (dReho) pattern and neurovascular coupling (NC) in PD patients before onset of cognitive impairment and their classification performance. PD patients at early stage exhibited an impaired dynamic pattern of neuronal synchronization and disrupted NC. The features of CBF/dReho provided robust performance in differentiating PD from healthy controls. With this findings, the insights into early pathophysiological mechanism underlying PD from regional dynamic pattern and NC were reinforced.
Fixel-Based Analysis of White Matter Degeneration in Patients with Progressive Supranuclear Palsy and Corticobasal Syndrome
Authors: Uchida Wataru , Kamagata Koji , Andica Christina , Saito Yuya , Takabayashi Kaito , Hagiwara Akifumi , Fujita Shohei , Akashi Toshiaki , Wada Akihiko , Hori Masaaki , Aoki Shigeki
Published: August 2023

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are neurodegenerative disorders associated with corticobasal degeneration pathology. A previous study evaluated white matter (WM) alteration using diffusion tensor imaging; however, the details are unclear due to the crossing fiber. This study evaluated cross-sectional and longitudinal WM changes in PSP and CBS using fixel-based analysis. This study also demonstrated consistent cross-sectional and longitudinal WM degeneration with previous histopathological studies and higher sensitivity than classical magnetic resonance imaging findings in differentiating PSP and CBS. Our results suggest that FBA can be a biomarker to classify PSP and CBS and estimate disease progression.
The Diagnostic Value of Quantitative Analysis of Synthetic MRI, ASL and DWI in Grading Gliomas as Compared to Conventional MRI: A Preliminary Study
Authors: Ge Xin , Huang Xueying , Wang Aijun , Zhu Kai , Wei Xiaocheng , Li Min , Shen Ying , Liu Wenxiao , Yong Peng , Lv Ruirui , Yang Xuhong , Wang Xiaodong
Published: August 2023

This work sought to investigate the performance of synthetic MRI, ASL and DWI in differentiating LGGs from HGGs as compared to conventional MRI. It was concluded that the T1 and PD from synthetic MRI can be used as novel quantitative imaging biomarkers for grading gliomas. Combining T1, PD, CBF and ADC may explore as an effective strategy to improve the ability for discriminating gliomas grade, and outperformed conventional approaches.
Understanding auditory cognition and its underlying acoustic characteristics
Authors: Singh Himanshu , Kumaran S Senthil , A Ankeeta
Published: August 2023

Auditory working memory is associated with sound pressure level for perception of information. However, its acoustic characteristics that represent information is not well understood. We used 1-back and 2-back auditory working memory tasks and acoustic characteristics (including pure tone assessment, audiometric threshold) to understand cognitive connectome with respect to frequency. This study explores the association of frequency characteristics underlying semantics necessary to understand auditory cognition.
Use lesion network localization to locate related brain lesions in incidental white matter lesions children with verbal comprehension delay
Authors: Wang Xiaoyu , Li Mengxuan , Wang Miaomiao , Liu Congcong , Li Xianjun , Yang Jian
Published: August 2023

Incidental white matter lesions (IWMLs) is a common disease in children with an incidence rate between 1.9% - 20%. Locating the brain lesions that might be related to the decline in verbal comprehension by overlapping lesion-associated networks can help define the possible response lesion. Our finding would help pediatricians to recognize the significant IWMLs that could potentially cause language delay in children. Thus, an early intervention can be applied to prevent the occurrence and progression of verbal comprehension decline in children.
Lesion assessment in multiple sclerosis using a two-compartment spherical mean technique
Authors: Eggenreich Stefan , Pirpamer Lukas , Khalil Michael , Enzinger Christian , Ropele Stefan
Published: August 2023

Various diffusion-based approaches were suggested for the characterization of lesional tissue in MS-patients. The multi-compartment spherical mean technique (SMT) has been proposed as a way to investigate microscopic diffusion properties in multiple water compartments. However, the potential of SMT for lesion characterization remains unclear. We investigated diffusion-based SMT properties in active and chronic lesions in 58 MS patients and related them to conventional diffusion tensor imaging (DTI). We found that SMT allows a more specific characterization of MS-lesions than DTI and provide evidence that SMT can be considered as a sensitive and robust measure for myelin content in MS patients.
Correlation between hippocampal subfields volume and white matter hyperintensity in patients with type 2 diabetes mellitus
Authors: Liu Yangyingqiu , Wang Weiwei , Jiang Yuhan , Liu Ailian , Miao Yanwei
Published: August 2023

Volume of hippocampal subfields in patients with type 2 diabetes mellitus(T2DM) was quantitatively assessed, and its’correlation to white matter hyperintensity (WMH) grade was also analyzed. The results show that the severity of WMH in T2DM patients may affect the atrophy of hippocampal subfields.
Clinical Value of Synthetic MRI and DWI in the diagnosis of Hippocampal Sclerosis in medial temporal lobe Epilepsy
Authors: Bai Yucai , LI Jian , Wei Xiaocheng , Ma Yaoxing , Chen Bing
Published: August 2023

The purpose of this study is to explore the value of different quantitative parameters derived from Synthetic MRI and combined with DWI in the diagnosis of hippocampal sclerosis. It was concluded that the values of T1, T2 and ADC in the hippocampal sclerosis were significantly higher than those in the normal control group .In addition, the AUC of the combined model of T2 and ADC was 0.96, which was higher than that of ADC (AUC 0.884) or T2 alone (AUC 0.952). Its sensitivity, specificity, positive predictive value and negative predictive value were 0.95,0.91,0.81,0.98 respectively.
Disruption on specific segments of uncinate fasciculus in first-episode drug-naïve adolescent depression
Authors: Liang Kaili , Feng Ruohan , Bu Xuan , Zhang Suming , Gao Yingxue , Bao Weijie , Cao Lingxiao , Liu Jing , Li Hailong , Zhang Lianqing , Huang Xiaoqi
Published: August 2023

We aimed to measure diffusion parameters along the uncinate fasciculus and examine the specific and focal alterations of the uncinate fasciculus in first-episode and drug-naïve patients with major depressive disorder in adolescents by using a tract-based quantitative technique. Notably, we found the opposite alterations of the diffusion metrics in the insular and frontal segments of left uncinate fasciculus in adolescents with depression. It will help us to better understand the neurobiological mechanisms of adolescent depression and optimize adolescent-specific treatments for depression.
Performance of single-shot echo-planar imaging DTI in rat sciatic nerve compared with readout-segmented echo-planar imaging
Authors: Chen Yueyao , Pan Zhongxian , Meng Fanqi , Li Zhujing , Gao Jinyun , Hu Yuanming , Guo Yihao , Xu Qian , Huang Leyu , Lv* Hanqing
Published: August 2023

This study compared single-shot echo-planar imaging (SS-EPI) with readout-segmented echo-planar imaging (RS-EPI) diffusion tensor imaging (DTI) in vivo anesthetized rat sciatic nerve at 3T. The result showed that the image quality scores of SS-EPI were higher than those of RS-EPI in terms of the nerve morphology and homogeneity of the neuromuscular region. The coefficients of FA and RD obtained with SS-EPI were higher than those obtained with RS-EPI SS-EPI. This suggests that in rat sciatic nerve DTI, SS-EPI showed higher image quality and offered more sensitive and stable parameters to detect the histopathological change in the rat sciatic nerve.
Conversion map from quantitative parameter mapping to myelin water fraction
Authors: Kitano Shun , Kanazawa Yuki , Harada Masafumi , Taniguchi Yo , Matsumoto Yuki , Hayashi Hiroaki , Ito Kosuke , Bito Yoshitaka , Haga Akihiro
Published: August 2023

We determined MWF derived from QPM-relaxation parameters using quadratic polynomial approximation. Two types of myelin imaging were generated; MWF derived from multi-echo gradient-echo and R1·R2* map derived from QPM, which were standardized from twelve healthy volunteers to MNI. As a result, the relationship between MWF and R1·R2* values on the white matter region strongly correlated with a quadratic polynomial approximation (R2 = 0.991). Using acquired quadratic polynomial approximation, the R1·R2* map was converted to MWF. Our MWF map derived from QPM can dramatically improve image quality when compared to the general MWF.
Iron Spatial Distributions in Deep Gray Nuclei are Related to Motor Outcomes of Subthalamic Nuclei Deep Brain Stimulation for Parkinson's Disease
Authors: Zhao Weiwei , Wu Xi , Yang Chunhui , Chen Luguang , Qiu Yiqing , Ma Chao , Li Gaiying , Song Yang , Wang Yi , Li Jianqi
Published: August 2023

The objective of this study was to investigate the relationship between motor outcomes of subthalamic nuclei deep brain stimulation (STN-DBS) and spatial distribution of iron in the deep gray nuclei for patients with Parkinson's disease (PD). The first and second texture parameters were obtained from the preoperative QSM of 40 PD patients. Significant correlations were found between motor improvement after DBS and QSM texture parameters in substantia nigra (SN) and dentate nucleus (DN). Linear regression showed that second-order texture parameter angular second moment in SN (r = -0.449, p = 0.004) had the highest correlation with the STN-DBS motor outcomes.
Radiomics Molecular Mechanism and Candidate Prognostic Biomarker Investigation for Glioblastoma Multiforme Utilizing WGCNA
Authors: Luan Jixin , Chen Jun , Fan Hua , Zhang Di , Wu Peng , Zhang Chuanchen
Published: August 2023

In this study, we aimed to explore the deeper molecular mechanism of radiomics features, and uncover new GBM prognostic biomarker. We extracted radiomics features out of 57 patients with MRI data obtained from TCIA database and corresponding clinical and transcription information from TCGA database. WGCNA revealed that the radiomics features are correlated with numerous cancer-associated biological processes, including regulation of vasculature development and so on. HMGA2 as the hub gene was screened by Cytoscape software. There was significant difference in survival analysis between the high and low expression groups, indicating that HMGA2 may be a new prognostic biomarker for GBM.
Fixel-Based Analysis Identifies White Matter Tract Degeneration in Parkinson’s Disease with Mild Cognitive Impairment
Authors: Tsai Chih-Chien , Liao Ting-Wei , Wu Yih-Ru , Wu Yi-Ming , Wang Jiun-Jie
Published: August 2023

Cognitive decline is a common non-motor symptom in Parkinson's disease (PD) patients, described as mild cognitive impairment (PD-MCI). PD-MCI is identified as a risk for PD with Dementia. Previous studies indicated that PD-MCI patients showed gray matter volume decrease and white matter tract degeneration. We investigate the utility of fixel based analysis as a biomarker for disease progression. The results show a significant degeneration of white matter in PD-MCI patients. Our findings indicated the white matter tract degeneration in PD-MCI patients and shed light on the value of the fiber-specific method to the clinical diagnosis of PD-MCI.
Relaxometry of the Substantia Nigra Pars Compacta and Subsegment Analysis: A Healthy Volunteer Study
Authors: Fujiwara Yasuhiro , Ishida Shota , Matta Yuki , Kanamoto Masayuki , Kimura Hirohiko
Published: August 2023

An anatomical atlas of the three regions (medial, dorsal, and ventrolateral) of the substantia nigra pars compacta (SNpc) were created based on neuromelanin (NM)-sensitive images, and Proton density, T1, and T2 values for each region were characterized in healthy volunteers. The T1 value of the ventrolateral group was higher than the other SNpc regions, which may be correlated with the NM concentration. The measured relaxation times can be used as baseline values for the SNpc.
Changes in neurochemicals of patients with depression observed using two MRS sequences at 7T
Authors: Okada Tomohisa , Yoshihara Yujiro , Kubota Manabu , Suwa Taro , Miyata Jun , Takado Yuhei , Near Jamie , Dehghani Masoumeh , Akasaka Thai , Thuy Dinh , Seethamraju Ravi , Ahn Sinyeob , Isa Tadashi , Murai Toshiya
Published: August 2023

Major depressive disorder (MDD) afflicts up to 20% of the total population. MRS findings are different among studies. One of the reasons is differences in MRS sequences used. This study compared two sequences: sSPECIAL and STEAM, which consistently found significant and marginally significant reduction of taurine in the anterior cingulate cortex in MDD compared with healthy controls, although concentration of neurochemicals in sSPECIAL and STEAM was different. The difference was lost when concentration was normalized by total creatine due to its significant positive correlation to Taurine. Differences between the two sequences did not result in different neurochemical findings for MDD.
CSE-MRI Detects the Changes in Bone Marrow Fat after Weight Loss Induced by Healthy Low-carbohydrate Diet
Authors: Gengyun Lin , Junying Wu , Zhibo Wen , Chen Zhao
Published: August 2023

Obesity is a global health condition that leads to many kinds of diseases. Bone marrow fat (BMF) is considered as the third largest fat depot in human body. It has been proved that BMF is closely related with energy storage, bone metabolism, endocrine function and hematologic diseases. To understand the relation between BMF and weight loss is crucial within obesity related diseases scenario. Few studies have been published focusing on BMF variation so far. In this study, chemical shift encoding-based water-fat MRI (CSE-MRI) was employed to demonstrate the positive correlation between BMF and parts of the weight loss indicators.
QMRI for assessment of anterior cruciate ligament mucoid degeneration and injury
Authors: Fan Guangtao , Li Yudan , Xue Fenglin , Huang Yilong , Li Yanlin , Wang Guoliang , Qi Tianfu , Nie Lisha , He Bo
Published: August 2023

The study aims to explore the difference in relaxation time between mucoid degeneration (MD) and injured anterior cruciate ligament (ACL), and evaluate the performance of QMRI (Quantitative magnetic resonance imaging) to identify the grade of MD and injured ACL. It was concluded that T2 * value of the ACL-MD group was higher than that of the injured group, T1, T2 and T2* could be used to quantitatively identify different grades of ACL-MD (T2* may deliberately has the highest diagnostic efficacy), and the same goes for T1 to evaluate ACL injury.
Preliminary study of various models of DWI and diffusion kurtosis imaging on differential diagnosis of spinal metastase and chordoma
Authors: Zhang Jiahui , Wang Qizheng , Lang Ning
Published: August 2023

Metastases and chordoma are both malignant tumors. When the manifestations are not typical, the two are prone to misdiagnosis. DWI using a biexponential model measured ADC, D, D*, and f. DWI using a stretched-exponential model obtained DDC, and α. DKI derived MD and MK. The monoexponential, biexponential, and stretched-exponential models of DWI and DKI have differential diagnostic value for spinal metastases and chordoma. Among the single parameter values, the D value has the highest AUC. Combining the values of three parameters (D, f, and α) can significantly improve the diagnostic efficiency of identifying spinal metastases and chordoma.
Changes of brain function in patients with type 2 diabetes by different analysis methods: A new coordinate based meta-analysis of neuroimaging
Authors: Li Zeyang , Ma Teng , Yan Lin-Feng , Cui Guangbin
Published: August 2023

Neuroimaging meta-analysis have identified abnormal neural activity alterations involved in type 2 diabetes mellitus (T2DM) patients, but there is no consistency and heterogeneity analysis between different brain imaging processing strategies. For the indicators obtained from varied post-processing methods reflect different neurophysiological and pathological characteristics, we further conducted a coordinated-based meta-analysis (CBMA) for two categories of neuroimaging literature grouped by similar data processing indicators. Compared to healthy controls, T2DM patients showed a significantly decreased brain activity in the right rolandic operculum, right supramarginal gyrus and right postcentral gyrus, providing a new non-invasive biomarker for T2DM neuropathy.
The T1mapping, T2mapping findings in patients with minimal hepatic encephalopathy and their impact on cognition value
Authors: Liu Wenxiao , Wang Minglei , Wei Xiaocheng , Li Min , Zhao Jianguo , Ge Xin , Yang Xuhong , Yong Peng , Wang Xiaodong
Published: August 2023

In this study, we aim to investigate whether T1mapping and T2mapping can be used as diagnostic tools for screening MHE, and strive earlier time for diagnosis and treatment for these patients. It was concluded that T1 values of bilateral putamen, right globus pallidus and bilateral frontal lobe in MHE group were statistically significant compared with HC group and NMHE group and the T2 values of right putamen and right frontal lobe were statistically significant. In addition, the T2 values of the HC group in this study were highly correlated with Hallgren and Sourander’s autopsy results.
Cerebellar iron accumulation in idiopathic cervical dystonia evaluating by quantitative susceptibility mapping
Authors: Li Hongxia , Zhang Ming , Wei Hongjiang , Wu Yiwen
Published: August 2023

We found increased susceptibility in patients compared with HCs that primarily involved cerebellar structures . The result of 2D-flatmap visualization showed that the involved subregions of iron accumulation were in the right Crus Ⅱ and right lobule Ⅶb. Interestingly, no significant differences in QSM value of basal ganglia, thalamus, or motor cortex were observed between ICD patients and HCs. Moreover, there was no significant difference between groups regarding the GMV in the cerebellum. Of consistent findings with standard structural MRI technique highlights the potential of probing tissue iron across the cerebellum with QSM as a disease biomarker
Molecular subgrouping of pediatric medulloblastoma by APT radiomics
Authors: Wen Junjie , Zhang Hongxi , Shen Zhipeng , Ma Xiaohui , Chen Xinchun , Chen Weibo , Wu Dan , Zhang Yi
Published: August 2023

APT imaging and its derived metric maps were applied to identify molecular subgroups of medulloblastoma for the first time. Thirty-eight newly-diagnosed pediatric patients with medulloblastoma were enrolled in this study and scanned on a 3T scanner. We implemented a radiomic analysis of the APT-related metric maps, with initial regions of interest delineated by an experienced radiologist and then shrunk automatically. After feature extraction and selection, five different classifiers were tested with both single-metric and multi-metric maps. We successfully established predictive models to differentiate the subgroups of medulloblastoma with good accuracy of 0.754.
Differentiation of T1 stage nasopharyngeal carcinoma and lymphoid hyperplasia by mono-exponential and bi-exponential metrics of TSE DWI
Authors: Liu Yifan , Bao Shasha , Xu Nan , Guo Xiaobin , Liao Chengde , Zhang Zhongping , Ke Tengfei
Published: August 2023

We aimed to differentiate between T1 stage nasopharyngeal carcinoma (NPC) and nasopharyngeal lymphoid hyperplasia using multiple b-values Turbo-spin-echo DWI acquisition. Turbo-spin-echo DWI were adopted to minimize susceptibility artifacts in nasopharynx. Mono-exponential and bi-exponential models were both used to generate ADC, D, D* and f maps. We found that T1 stage NPC had significant lower ADC and D, higher D* than nasopharyngeal lymphoid hyperplasia. Furthermore, D has best diagnostic efficacy with highest area under curve in ROC analysis, indicating that it's a potential imaging biomarker for accurate early diagnosis of T1 stage NPC.
Structural connectivity abnormality in trigeminal neuralgia with pain relief using graph theory analysis
Authors: Shen shanshan , Zhang shuqian , Chen yingmin , Xie Lizhi
Published: August 2023

Trigeminal neuralgia (TN) characterized by recurring paroxysmal pain, severely affects the quality of life (QoL) of patients. In this study, we compared brain network frame remodeling in TN patients before and after percutaneous micro-balloon compression (PMC) operation with healthy controls (HCs) using graph theory analysis. Both TN pre-treatment patients (Pre) and HCs exhibited small-world network organization. Pre TN patients had abnormal global network construction, Pos recovered, but in local network index increased. Graph theory analysis could be a useful method to detect instant change after operation.
Accelerated T1 weighted PROPELLER imaging of the brain with deep-learning based parallel imaging reconstruction
Authors: Kawamura Motohide , Tamada Daiki , Sato Kazuyuki , Hamasaki Masahiro , Funayama Satoshi , Wakayama Tetsuya , Motosugi Utaroh , Morisaka Hiroyuki , Onishi Hiroshi
Published: August 2023

PROPELLER sequence is useful because of its robustness to patient motion. Longer acquisition than FSE is a major drawback limiting its wider application in clinical practice. Here, we propose an accelerated T1 weighted PROPELLER of the brain using deep learning based parallel imaging (PI) reconstruction. Our method can unfold highly undersampled aliased images (PI factor = 7), enabling 2.3 times faster acquisition than full-sampling. A preliminary reader study with prospectively undersampled data showed that the proposed method significantly outperformed a conventional SENSE reconstruction in terms of streak artifact.
Using the Artificial Intelligence Based Compressed SENSE Technology in Acute Cerebral Infarction
Authors: Ning Cong , Ma Yue , Yu Di , Tong Dan , Zhu Yi , Jiang Ke
Published: August 2023

MRI has advantages in detecting acute ischemia and describing the core volume of the infarct without radiation, but the long scanning time affects clinical use. Compressed sense combined with artificial intelligence (CS-AI) technology accelerates the acquisition of imaging. This study aims to use the CS-AI technique to accelerate common sequences of Acute cerebral infarction and investigate the effect of different acceleration factors on image quality and diagnosis. The results show that CS-AI reconstruction scans reduce scanning time while maintaining image quality compared to conventional SENSE.
MRS Denoising Model: ReLSTM-Net Trained by few In vivo Measured Data
Authors: Chen Dicheng , Hu Wanqi , Liu Huiting , Qiu Tianyu , huang Yihui , Lin Liangjie , Guo Di , Lin Jianzhong , Qu Xiaobo
Published: August 2023

1H Magnetic Resonance Spectroscopy (MRS) suffers low Signal-Noise Ratio (SNR) due to low concentrations of metabolites. To improve the SNR, the current mainstream is to do Signal Averaging with repeated samplings but it is time-consuming. Therefore, we designed a novel denoising ReLSTM-Net to learn the mapping from the low SNR MRS to the high SNR one in the time-domain by a few in vivo measured data. Denoised spectra by the proposed method has higher accuracy and reliability in quantifying metabolites Glx, tCho and mI, compared with the state-of-art Low-Rank method.
Deep Learning Based Automated Diagnosis of Epilepsy in Patients with WHO II-IV Grade Cerebral Gliomas from Multiparametric MRI
Authors: Yang Hongxi , Gao Ankang , Wang Yida , Yan Xu , Cheng Jingliang , Bai Jie , Yang Guang
Published: August 2023

We had retrospectively enrolled 371 glioma patients in this study to develop an automated scheme to predict epilepsy in patients with WHO II-IV grade cerebral gliomas from multi-parametric MRI (mp-MRI). Gliomas tumor was segmented by a segmentation model trained with nnU-Net. Then a classification model based on ResNet-18 using segmented tumor region as anatomical attention was used to predict epilepsy from mp-MRI images. In the independent test cohort, the segmentation model achieved a mean dice of 0.899, while the classification model achieved an AUC of 0.890, better than the baseline ResNet-18 model with a test AUC of 0.783.
Toward Universal Tumor Segmentation on Diffusion-Weighted MRI: Transfer Learning from Cervical Cancer to All Uterine Malignancies
Authors: Lin Yu-Chun , Lin Yenpo , Huang Yen-Ling , Ho Chih-Yi , Lin Gigin
Published: August 2023

This study retrospectively analyzed diffusion-weighted MRI in 320 patients with malignant uterine tumors (UT). A pretrained model was established for cervical cancer dataset. Transfer learning (TL) experiments were performed by adjusting fine-tuning layers and proportions of training data sizes. When using up to 50% of the training data, the TL models outperformed all the models. When the full dataset was used, the aggregated model exhibited the best performance, while the UT-only model exhibited the best in the UT dataset. TL of tumor segmentation on diffusion-weighted MRI for all uterine malignancy is feasible with limited case number.
Deep learning based liver segmentation using T1 weighted abdominal MRI
Authors: Hossain Md Sakib Abrar , Chowdhury Muhammad E. H. , Bhuyian Enamul H. , Rahman Tawsifur , Mahbub Zaid B. , Khandakar Amith , Tahir Anas , Hossain Md Shafayet , Khan M. Salman
Published: August 2023

MR scans are preferred by clinicians for liver pathology diagnosis over volumetric abdominal CT scans, due to their superior resolution for soft tissues. Nevertheless, deep learning based automated liver segmentation from abdominal MRI is challenging as the liver exhibits variable characteristics. This study investigates multiple state-of-the-art segmentation architectures (UNet, UNet++, and FPN) with varying encoder and decoder backbones. Here, T1 weighted MR images are investigated as it demonstrates brighter fat content. Among the investigated networks UNet++ with DenseNet backbone demonstrates top performance for the liver segmentation with a DSC and IoU of 94.3% and 91.0%, respectively.
Combination of Echo Planar Imaging Correction and Compressed SENSE Framework for enhanced Diffusion weighted imaging
Authors: Wu Zhigang , Sun Peng , Zhang Yajing , Hu Xiuquan , Zhang Jing , Jiang Guangyu , Zhao Yan , Wang Jiazheng
Published: August 2023

Diffusion-weighted imaging (DWI) using single-shot EPI (ssEPI) has suffered from distortion, blurring, and signal loss caused by B0 inhomogeneity. SENSE can be used to reduce distortion. However, it also suffers from noise breakthrough issues when the accelerator factor is high. It’s still a challenge to get DWI images with reduced distortion and high SNR without significantly increasing the scan time. We propose a framework that combines FSL top-up technique, Compressed Sensing and SENSE framework simultaneously to overcome these challenges. This framework allows a new solution for ssEPI based diffusion imaging with high resolution, low distortion, and without noise breakthrough issue.
A Semantic Segmentation Method with Emphasizing Edge information for Automatic Vessel Wall Analysis
Authors: Xu Wenjing , Zhu Qing , Cheng Guanxun , Wan Liwen , Zhang Lei , He Qiang , Dai Yongming , Liang Dong , Li Ye , Zheng Hairong , Liu Xin , Zhang Na
Published: August 2023

Edge information is essential for medical image analysis, especially for image segmentation. This paper aims to develop a precise semantic segmentation method with emphasizing the edges for automated segmentation of arterial vessel wall and plaque based on the convolutional neural network (CNN) for facilitating the quantitative assessment of plaque in patients with ischemic stroke. An end-to-end architecture network that can emphasize the edge information is proposed. The results suggest that the proposed segmentation method improves segmentation accuracy effectively and will facilitate the quantitative assessment on atherosclerosis.
T1 mapping for liver with EOB enhanced MRI: comparison of look-locker inversion recovery and B1 inhomogeneity-corrected method
Authors: Li Chenhui , Long Liling , Zhang Huiting , Nickel Dominik
Published: August 2023

Two different T1 mapping sequences, based on the inversion recovery SNAPSHOT-FLASH sequence (LLIR-T1) and on B1 inhomogeneity-corrected variable flip angle (VFA-T1) acquisitions, were compared in a clinical setting. Results showed that the LLIR-T1 method had better image quality, and higher contrast between tumor and healthy liver tissue.c had a strong correlation with VFA-T1 method whether at different time point or regions. But LLIR-T1 had lower T1 in healthy liver lobe and higher T1 in tumor compared with VFA-T1.
Development of self-calibrating B1 correction for three-dimensional variable flip angle T1 mapping
Authors: Fukuda Nagomi , Kanazawa Yuki , Hayashi Hiroaki , Matsumoto Yuki , Harada Masafumi , Sasaki Motoharu , Haga Akihiro
Published: August 2023

We determine the accuracy of our B1 correction method using a cylindrical digital phantom and a digital brain phantom. Comparing the B1 correction accuracy of each sample, the relative uncertainties of each T1 value were less than 5%, and when long TR, the accuracy of B1 correction was almost equal to short TR. In addition, our method enabled us to correct the slice direction accurately. The proposed method can correct B1 inhomogeneity with high accuracy to in-plane and slice direction without additional scanning
Prostate imaging with Integrated Multi-modal Antenna with coupled Radiating dipoles (I-MARS) at 7T
Authors: Li Mingyan , Jin Jin , Weber Ewald , Engstrom Craig , Destruel Aurelien , Crozier Stuart , Liu Feng
Published: August 2023

Prostate imaging is challenging at 7T due to its small size seated deeply inside the pelvic region. As such, both transmit receive performance of the RF coils are heavily challenged. We have recently developed a new paddle-shape Integrated Multi-modal Antenna with coupled Radiating structures (I-MARS) allowing an ensemble of eight elements to be placed tightly together among each other and closely to the imaging region. In the current work, we demonstrate optimized work-flow and in vivo imaging results using such an 8-element paddle I-MARS coil with an upgraded MAGNETOM 7T Plus system.
Triple-nuclear RF coil system for Simultaneous acquisition of 1H / 19F / 23Na MR imaging at 3T
Authors: Li Nan , Du Feng , Zhang Xiaoliang , Liu Xin , Zheng Hairong , Li Ye
Published: August 2023

The lower natural abundance and gyromagnetic ratios of non-hydrogen nuclei require the use of a highly efficient RF coil to optimize the quality of the image. In this study, a novel triple-nuclear RF coil system capable of 1H / 19F / 23Na imaging was designed. The coil consists of a triple-tuned four-ring birdcage transmit coil and the tight fit local X-nuclei single-loop receive coils. A range of bench tests were performed by using the developed triple-nuclear coil. The performance evaluations showed that the coil system was appropriately tuned, matched and decoupled at 1H/19F/23NA frequencies when working simultaneously.