bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of streak-removal on deep learning reconstruction of radial datasets
Authors: Toner Brian , Fu Zhiyang , Philip Rohit , Martin Diego , Altbach Maria , Bilgin Ali
Published: August 2023

Recently, deep learning models have been developed for reconstructing data acquired using radial turbo spin echo sequences, yielding images at multiple echo times as well as co-registered T2 maps. In radial imaging, streaking artifacts from anatomical regions where the magnetic field gradients are nonlinear can obscure pathology and impact accuracy of parameter mapping. In this work, we demonstrate that removal of streaking artifacts from data prior to training can provide substantial improvement in the reconstruction performance of deep learning methods.
Cross-correlation between metabolites due to spectral overlap
Authors: Hong Sungtak , An Li , Shen Jun
Published: August 2023

It is shown that spectral overlap can cause an apparent correlation between metabolites regardless of underlying biological correlations or the lack thereof. Because MRS signals are often used to correlate with other MRS signals or clinical measures a theoretical framework is developed to estimate correlations originating from spectral overlap at long echo time. Monte Carlos simulations were also performed to quantify the correlations. Our results showed that significant correlations may occur even at long TE, when the contribution from macromolecule background becomes negligible. The proposed theoretical framework was proven to be useful for predicting cross-correlation coefficients originating from spectral overlap.
Deep generative model for learning tractography streamline embeddings based on a Convolutional Variational Autoencoder
Authors: Feng Yixue , Chandio Bramsh , Chattopadhyay Tamoghna , Thomopoulos Sophia , Owens-Walton Conor , Jahanshad Neda , Garyfallidis Eleftherios , Thompson Paul
Published: August 2023

We present a deep generative model to autoencode tractography streamlines into a smooth low dimensional latent distribution, which captures their spatial and sequential information with 1D convolutional layers. Using linear interpolation, we show that the learned latent space translates smoothly into the streamline space and can decode meaningful outputs from sampled points. This allows for inference on new data and direct use of Euclidean distance on the embeddings for downstream tasks, such as bundle labeling, quantitative inter-subject comparisons, and group statistics.
Unsupervised Domain Adaptation for Neural Network Enhanced Turbo Spin Echo Imaging
Authors: Zhou Zechen , Börnert Peter , Yuan Chun
Published: August 2023

Supervised learning is widely used for deep learning based image quality enhancement for improved clinical diagnosis. However, the difficulties to acquire a large number of high-quality reference image for different MR applications can limit its generalization performance. An unsupervised domain adaptation (DA) approach is proposed and incorporated into the deep learning based image enhancement framework, which improves the performance of trained network on new datasets. Preliminary evaluation on point spread function enhanced turbo spin echo imaging has showed that the unsupervised DA approach can provide more stabilized image sharpness improvement without severe amplified noise.
Deep CNNs with Physical Constraints for simultaneous Multi-tissue Segmentation and Multi-parameter Quantification (MSMQ-Net) of Knee
Authors: Lu Xing , Ma Yajun , Xu Kody , Jerban Saeed , Jang Hyungseok , Hsu Chun-Nan , Gentili Amilcare , Chang Eric , Du Jiang
Published: August 2023

In this study, we proposed end-to-end deep learning convolutional neural networks to perform simultaneous multi-tissue segmentation and multi-parameter quantification (MSMQ-Net) on the knee without and with physical constraints. The performance robustness of MSMQ-Net was also evaluated using reduced input magnetic resonance images. Results demonstrated the potential of MSMQ-Net for fast and accurate UTE-MRI analysis of the knee, a “whole-organ” approach which is impossible with conventional clinical MRI.
Radiomics to Predict Pathological Complete Response in Patients with Triple Negative Breast Cancer
Authors: Hirano Michael , Kazerouni Anum , Zecevic Mladen , Kennedy Laura , Vinayak Shaveta , Rahbar Habib , Nyflot Matthew , Dintzis Suzanne , Partridge Savannah
Published: August 2023

Radiomics is an advancing field of medical image analysis based on extracting large sets of quantitative features that can be used for outcome modeling for clinical decision support. Our study investigated the value of radiomics features extracted from pre-treatment dynamic contrast-enhanced MRI for the prediction of neoadjuvant chemotherapy response in patients with triple-negative breast cancer. In a retrospective cohort of 103 TNBC patients, radiomics-based models using post-contrast images and kinetics maps were moderately predictive of pathologic response, and lesion size and shape features were the most consistent predictors across all image types.
Dual-domain Self-supervised Learning for Accelerated MRI Reconstruction
Authors: Zhou Bo , Schlemper Jo , Salehi Seyed Sadegh Mohseni , Dey Neel , Sheth Kevin , Liu Chi , Duncan James , Sofka Michal
Published: August 2023

We present a self-supervised approach for accelerated non-uniform MRI reconstruction, which leverages self-supervision in k-space and image domains. We evaluated the performance on both simulation and real data, where fully sampled data is unavailable. The experimental results on a non-uniform MRI dataset demonstrate that the proposed method can generate reconstruction that approaches the accuracy of the fully supervised reconstruction. Furthermore, we show that the approach can be applied to highly challenging real-world clinical MRI reconstruction acquired on a low-field (64 mT) MRI scanner with no data available for supervised training while demonstrating improved perceptual quality as compared to traditional reconstruction.
K-space refinement method for DL-based MR reconstruction by regularizing k-space null space constraint with auto-calibrated kernel
Authors: Ryu Kanghyun , Alkan Cagan , Vasanawala Shreyas
Published: August 2023

In this study, we propose a novel refinement method using auto-calibrated k-space null-space kernel to reduce the k-space errors and enable reconstruction of improved high-frequency image details and textures. The refinement algorithm can be easily plugged in after DL-based reconstructions. We show that our method enables the reconstruction of sharper images with significantly improved high-frequency components measured by HFEN and GMSD while maintaining overall error in the image measured by PSNR and SSIM.
SuperRes-EPTI: in-vivo mesoscale distortion-free dMRI at 500μm-isotropic resolution using short-TE EPTI with rotating-view super resolution
Authors: Dong Zijing , Polimeni Jonathan , Wald Lawrence , Wang Fuyixue
Published: August 2023

To achieve high spatial resolution in-vivo dMRI (mesoscale at isotropic 500μm), we propose a novel SuperRes-EPTI technique that combines our recently developed EPTI technique with a rotating-view super-resolution acquisition and reconstruction. The SuperRes-EPTI can achieve an overall 3.5× SNR gain (SuperRes×EPTI = 2.7×1.3), while providing images completely-free from distortions that allow for improved super-resolution reconstruction and high effective resolution. The SuperRes acquisition scheme was designed to avoid spin-history artifacts, and incorporates rigid motion correction between thick-slice volumes for high motion-robustness. In-vivo distortion-free dMRI data were acquired at 500μm-isotropic resolution at 3T that reveals detailed fibers in gray matter.
Accelerated 5D Echo Planar J-Resolved Spectroscopic Imaging and Dictionary Learning Reconstruction: Pilot Findings in Obstructive Sleep Apnea
Authors: Joy Ajin , Macey Paul , Sarma Manoj , Saucedo Andres , Thomas M
Published: August 2023

Obstructive sleep apnea (OSA) affects 10% of the population, and is associated with brain injury. Neurochemical changes in the brain of OSA patients can be recorded using 5D echo-planar J-resolved spectroscopic imaging. Accelerated acquisition is achieved with non-uniform undersampling, which requires data reconstruction that can be done with compressed sensing (CS). We implemented CS with a hybrid DLTV reconstruction method combining dictionary learning (DL) and total variation (TV), and compared its performance with Perona-Malik (PM) reconstruction. The metabolite ratios were consistent with both DLTV and PM while DLTV recovered the metabolite peaks near residual water better in many voxels.
Generative Image Prior Constrained Subspace Reconstruction for High-Resolution MRSI
Authors: Zhao Ruiyang , Wang Zepeng , Lam Fan
Published: August 2023

We propose a novel method that integrates generative image priors with subspace constrained MRSI reconstruction. A sufficient and flexible image representation was first generated by adapting a pretrained StyleGAN to subject-specific anatomical images. We validate that StyleGAN can be flexibly adapted to accurately represent different contrast of the same subject. The adapted GAN prior is then used to model the spatial coefficients in the subspace-based reconstruction. Improved performance over the original subspace reconstruction in the SPICE framework is demonstrated using simulation and in vivo data.
Deblurring for Spiral Imaging with Intra-Voxel Dephasing Modeling
Authors: Wang Dinghui , Pipe James
Published: August 2023

Advantages of spiral imaging include fast imaging speed, high scan efficiency and low sensitivity to motion. However, spiral imaging remains challenging in regions where the field map Δf0 changes rapidly in space, especially with long spiral readouts. The goal of this work is to address this issue by modeling the signal decay in deblurring procedure. Volunteer data demonstrated that image quality can be improved by the proposed method.
Once upon a chiasm: Reconstruction of mouse optic pathways with ODF-Fingerprinting
Authors: Filipiak Patryk , Sajitha Thajunnisa , Shepherd Timothy , Lin Ying-Chia , Placantonakis Dimitris , Chan Kevin , Boada Fernando , Baete Steven
Published: August 2023

We reconstruct mouse optic pathways with ODF-Fingerprinting in a challenging crossing area of the optic chiasm. Our method replaces the commonly used peak finding approach with pattern matching when reconstructing white matter fiber directions from orientation distribution functions. As reference, we perform analogous reconstructions using Radial Diffusion Spectrum Imaging and Generalized Q-space Imaging. To obtain ground truth information, we inject intravitreally a 0.1M solution of manganese chloride into four C57BL/6N mice. The optic pathways reconstructed with deterministic tractography based on directional information calculated with our approach reach higher agreement with the ground truth than the other two methods.
Automated Quantification of Ventilation Defects and Heterogeneity in 3D Isotropic 129Xe MRI
Authors: Ranota Tuneesh , Guo Fumin , Wu Tingting , Fox Matthew , Ouriadov Alexei
Published: August 2023

Hyperpolarized 129Xe MRI provides a way to investigate and assess pulmonary diseases. To improve the performance of 129Xe MRI in lung imaging, a method for acquiring two VDP calculations using high-resolution 3D static ventilation imaging from FGRE combined with a key-hole method was proposed and demonstrated in participants with ventilation abnormalities. SNR was calculated as well as semi-automated VDP and fully automated VDP, which showed a strong positive linear correlation with a zero intercept and close to unity slop. This study confirms the feasibility of using isotropic-voxel 129Xe MRI acquired in a single breath-hold to study ventilation heterogeneity.
A k-space transformer network for undersampled radial MRI
Authors: Gao Chang , Shih Shu-Fu , Ghodrati Vahid , Finn Paul , Hu Peng , Zhong Xiaodong
Published: August 2023

Deep learning-based undersampled MRI reconstruction generally requires the k-space data consistency term to constrain the output. However, this requires gridding onto a Cartesian basis for radial data, which slows down the training process profoundly and may even make it impractical. To avoid the repeated gridding process in training, we developed a transformer network to directly predict unacquired radial k-space spokes. The developed network was evaluated in vivo, accurately predicted the unacquired k-space spokes and generated better image intensity and less streaking artifacts compared to the undersampled images.
Noise2DWI: Accelerating Diffusion Tensor Imaging with Self-Supervision and Fine Tuning
Authors: Martin Phillip , Altbach Maria , Bilgin Ali
Published: August 2023

In this work we propose a novel algorithm of denoising accelerated diffusion weighted MRI (dMRI) acquisitions using deep learning and self-supervision. This method effectively enables the prediction of diffusion-weighted images (DWIs), without the need for large amounts of training data with high directional encodings. We demonstrate that accurate diffusion tensor metrics can be obtained with as few as 6 DWIs using only a few training datasets with high directional encodings.
A Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using sMRI in Very Preterm Infants
Authors: Li Zhiyuan , Li Hailong , Parikh Nehal , He Lili , Braimah Adebayo , Dillman Jonathan
Published: August 2023

Between 35-40% of very preterm infants (≤32 weeks’ gestational age) develop cognitive deficits, thereby increasing their risk for poor educational, health, and social outcomes. Timely and accurate identification of infants at risk soon after birth is desirable for early intervention allocation. We proposed a novel Ontology-guided Attribute Partitioning Ensemble Learning (OAP-EL) model using quantitative structural MRI data obtained soon after birth to predict cognitive deficits at 2 years corrected age in very preterm infants.
A Dissolved-Phase 129Xe Phantom for Quantitative Gas-Exchange MRI
Authors: Albert Brice , Plummer Joseph , Willmering Matthew , Lindquist Diana , Walkup Laura , Cleveland Zackary
Published: August 2023

Many single-site studies, and increasingly multi-site clinical trials, employ hyperpolarized 129Xe MRI to assess lung structure and function. The lack of reliable imaging 129Xe standards hampers image quantification and rigorous comparisons across research sites. This is particularly true for 129Xe imaging of pulmonary gas-exchange, which must detect the large gaseous resonance and the two, 50-fold-smaller 129Xe dissolved resonances, corresponding to 129Xe dissolved in red bloods cells and adjacent plasma/parenchymal barrier tissues. This work demonstrates the feasibility of constructing practical, thermally-polarized, dissolved-phase 129Xe phantoms that mimic in-vivo resonances and will enable multi-site studies of gas-exchange imaging to be harmonized.
Development of Hyperpolarized 15N-labeled Metronidazole as an MR Contrast Agent by d-DNP Technique: A Potential Antibiotic and Hypoxia Probe
Authors: Bedoya David Guarin , Hardy Erin , Samoilenko Anna , Joshi Sameer , Stockmann Jason , Ardenkjaer-Larsen Jan Henrik , Rosen Matthew S. , Goodson Boyd M. , Theis Thomas , Chekmenev Eduard Y , Yen Yi-Fen
Published: August 2023

In this work, we developed a DNP hyperpolarized 15N-labeled metronidazole contrast agent. The formulation of the sample and the DNP process were optimized to reduce the build-up time constant down to 22 min while reaching liquid state signal enhancements of 104. The T1 relaxation times were measured in liquid-state, and found to be minutes long. Due to the high enhancement and long T1, MNZ hyperpolarized 15N signal could be monitored for several minutes. The contrast agent was tested with MRS in-vivo, in a rat brain. The hyperpolarized MNZ signal remained above the noise level for more than a minute.
User-Friendly Application for Consistent Multi-Vendor Hyperpolarized 129Xe MRI Analysis
Authors: Bdaiwi Abdullah , Plummer Joseph , Willmering Matthew , Roach David , Woods Jason , Walkup Laura , Cleveland Zackary
Published: August 2023

Advances hyperpolarized 129Xe production, data acquisition and image analysis have allowed 129Xe MRI to emerge as a leading pulmonary imaging modality. As the number of sites capable of 129Xe MRI and quantitative image-derived metrics grow, the need for an intuitive, organized analysis tool increases. Here, we provide a user-friendly application, designed as MATLAB language-based interface, to analyze HP 129Xe data. This open-source, research tool enables standardized analysis of hyperpolarized 129Xe calibration, ventilation, diffusion, and gas-exchange data. Furthermore, the modular design allows developers to easily implement additional functions and analysis procedures, providing a framework for growth and sharing of analysis techniques.
Feasibility of Simultaneous Measurements of GABA, Glx and GSH in the Thalamus Using HERMES
Authors: Liang Xiao , Saleh Muhammad , Roys Steve , Gullapalli Rao , Zhuo Jiachen
Published: August 2023

It is desirable to measure GABA, glutamate, and GSH in the thalamus for understanding pathological and pharmacokinetic changes. In this study, we study the feasibility of simultaneous measurements of these metabolites in the thalamus using HERMES. HERMES data were acquired on 20 healthy adult volunteers with and without saturation bands. HERMES data were processed in Gannet with and without spectral alignment. The results demonstrated the feasibility of using HERMES for simultaneous measurements of GABA, Glx and GSH in the thalamus. HERMES combined with saturation bands and retrospective spectral alignment yields high SNR spectra and reproducible measurements in the thalamus.
Using Strong Coupling Effect to Increase Signal Strength of Glutamate, Glutamine, and Glutathione at 7 T
Authors: An Li , Evans Jennifer , Burton Courtney , Tomar Jyoti , Araneta Maria Ferraris , Zarate Carlos , Shen Jun
Published: August 2023

Unlike weakly coupled spin systems, the signal strength of Glu H4, Gln H4, and GSH glutamyl H4 is affected by the timing of refocusing pulses for a fixed total TE. Using full density matrix simulations, it was found that glutamate H4, glutamine H4, and glutathione glutamyl H4 peak amplitudes can be significantly increased by shortening the echo time of the first spin echo (TE1) in PRESS from a previously reported 69 ms to 16 ms. The improved sequence was tested in vivo and validated using Monte Carlo simulations.
Glutamate Metabolism Mapping after Oral Administration of 1-13C-Glc using 1H MRSI in the human brain at 9.4 T
Authors: Ziegs Theresia , Ruhm Loreen , Wright Andrew , Henning Anke
Published: August 2023

Glutamate is the major excitatory neurotransmitter in the brain and malfunction of glutamatergic metabolism is associated with various neurological disorders. Respective metabolic rates can be determined via direct 13C or indirect 1H-[13C] MRS after intake of 13C labelled tracers. In this work, labeling effects after oral intake of [13C-1]glucose are observed in human brain using a 1H-FID-MRSI sequence at 9.4T. Spectral time series of GM and WM voxels as well as metabolite maps show regionally distinct and tissue type specific labelling induced changes of Glu and Gln spectral pattern that allow for the determination of 13C label uptake rates.
Accurate thermometry using hyperpolarized 129Xe free induction decay and spin-echo chemical shift imaging in rats
Authors: Kern Agilo , Gutberlet Marcel , Rumpel Regina , Brüsch Inga , Hohlfeld Jens , Wacker Frank , Hensen Bennet
Published: August 2023

Thermometry using the proton resonance frequency (PRF) is challenging in inhomogeneous, fatty tissues and moving organs. Purpose of this study was to develop and test a combined free induction decay (FID)/spin-echo chemical shift imaging sequence for accurate hyperpolarized 129Xe MR thermometry in rats exposed to hypothermia. Significant changes of 129Xe lipid chemical shift and good agreement with core body temperature are observed. Bland–Altman analysis shows narrower limits of agreement and reduced mean difference for spin-echo acquisitions, suggesting improved precision and accuracy in fatty tissues. The method may be valuable as reference standard for development of more accurate 1H MR thermometry.
Changes in lung microstructure during the cardiac cycle assessed by rapid hyperpolarized 129Xe chemical shift saturation recovery
Authors: Kern Agilo , Gutberlet Marcel , Hohlfeld Jens , Wacker Frank , Vogel-Claussen Jens
Published: August 2023

A rapid chemical shift saturation recovery (CSSR) pulse sequence is developed for reconstructing CSSR uptake curves in different cardiac phases by employing retrospective gating. The sequence is tested in a study with 6 healthy volunteers and compared to conventional CSSR. A significant difference in septal wall thickness between trough and crest of the pulse wave in lung tissue is found. Results from rapid and conventional CSSR are strongly correlated and show good absolute agreement. The proposed rapid CSSR pulse sequence may provide valuable new insights into normal lung function, improve precision of CSSR results and may have clinical applications.
Simultaneous Mapping of Water Diffusion Coefficients and Metabolite Distributions of the Brain Using MRSI without Water Suppression
Authors: Guo Rong , Li Yudu , Zhao Yibo , Wang Tianyao , Li Yao , Sutton Brad , Liang Zhi-Pei
Published: August 2023

The feasibility of high-resolution metabolic imaging using water-unsuppressed MRSI has been recently demonstrated in clinical settings using SPICE. This work utilizes the unsuppressed water spectroscopic signals for distortion-free mapping of water diffusion coefficients, thus adding a new feature to SPICE for multi-modal brain mapping. Experimental results demonstrated that simultaneous distortion-free diffusion imaging at 1.0×1.0×2.0 mm3 resolution and metabolic imaging at 2.0×3.0×3.0 mm3 nominal resolution were successfully obtained in a total 8-min scan.
Two-pool model with exchange is more sensitive to exchange increases during apoptosis than the partially absorbing wall model
Authors: Djayakarsana Daniel , Stanisz Greg , Bailey Colleen
Published: August 2023

Modeling diffusion that incorporates the microscopic partially absorbing wall is a more realistic description compared to the standard Bloch equation based two-site model with exchange. The resulting signal equations are more complex and involve working in the Laplace domain. Here, we demonstrate that the increased spatial relevance of the partially absorbing wall model does not improve fitting in our AML model treated with cisplatin for cell death. In fact, the partially absorbing wall model fits and parameters are poorer. Therefore, extracting diffusion parameters from the Bloch equation based two-site exchange model is sufficient for our diffusion MRI datasets.
High-SNR J-Resolved MRSI by Jointly Learning Nonlinear Representation and Projection
Authors: Li Yahang , Wang Zepeng , Lam Fan
Published: August 2023

J-resolved 1H-MRSI offers several unique advantages but suffers from long acquisition time and lmited SNR, especially for longer TEs. Leveraging the recent progress on constrained MRSI reconstruction using learned nonlinear low-dimensional representations, we propose here a new method for SNR-enhancing reconstruction from rapidly generated, noisy J-resolved data, that can computationally efficiently enforce an accurate nonlinear low-dimensional representation of high-dimensional J-resolved spectroscopic signals through a learned network-based project as well as complementary spatial constraints. The proposed method has been shown to improve the SNR significantly for in vivo J-resolved 1H-MRSI of the brain.
Imaging Gas Exchange Using Hyperpolarized 129Xe as a Better Predictor of Endobronchial Valve Outcome
Authors: Hamedani Hooman , Amzajerdian Faraz , Kadlecek Stephen , Baron Ryan , Ruppert Kai , Duncan Ian , Ismail Mostafa , Xin Yi , Achekzai Tahmina , Loza Luis , Rizi Rahim
Published: August 2023

Bronchoscopic lung volume reduction (LVR) using endobronchial valves has proven effective at improving lung function and quality of life in certain severely emphysematous patients. Successful lung volume reduction of the target lobe shifts ventilation and perfusion to the healthier ipsilateral lobe and improves breathing mechanics. Functional imaging with spatially-resolved metrics using inhaled hyperpolarized 129Xe (HXe) may provide a deeper understanding of the physiology underlying clinical benefit.
RF coil modeling with mechanical components: initial investigation
Authors: Chen Xin , Steckner Michael
Published: August 2023

Electromagnetic modeling has been widely used to study MRI RF coils, but the coil model usually only consists of conductors and lumped elements. The impact of mechanical components (such as coil housing, patient table) has not yet been thoroughly investigated. This work showed that including mechanical parts in the model lead to noticeable changes of total B1 and E fields (up to 15% and 32% increase respectively in the central axial slice), peak SAR (22%), and coil input power (67%) calculations.
Magnetic Susceptibility of Common Metals and Alloys Used in Medical Devices
Authors: Baker Grant , Anttila Eric , Smith Erick , Robison Andrew , Gross David
Published: August 2023

The goal of this study was to characterize the magnetic susceptibility and accompanying magnetically induced force, torque, and image artifact of metals and alloys that are commonly used in medical devices. These values were reported for 46 metals and alloys, with an overall trend that magnetically induced force, torque, and image artifact increased with increasing susceptibility of a material. The results of this study can inform medical device design for the development of safer and better performing devices, especially in the growing area of MR guided procedures.
A Parallel-Transmit Halbach Magnet TRASE MRI System
Authors: Sharp Jonathan , Purchase Aaron , Sedlock Christopher , Tomanek Boguslaw
Published: August 2023

We have designed and constructed a low-field TRASE RF imaging system. In TRASE k-space encoding is achieved by refocusing with RF phase gradients. The system includes a motorized rotatable magnet, twin RF power amplifiers, two geometric decoupled truncated twisted solenoid RF transmit coils (1D radial TRASE encoding), and a multi-channel transmit SDR console. The magnet is a 2.835 MHz 8-ring Halbach design. All components are custom made. An inherent axial gradient of the inhomogeneous magnet function as slice selection. The unique feature of this imaging configuration is the simplicity. Two RF channels and magnet rotation provide multi-slice projection reconstruction imaging.
A high-resolution whole-brain CBF atlas based on more than 100 adult normal mice
Authors: Chen Xiang , Xu Wenjing , Han Xiaoyang , Zhai Yuting , Xu Jiadi , Zhang Xiao-Yong
Published: August 2023

Arterial spin labeling (ASL) is a powerful MRI technique used to noninvasively measure cerebral blood flow (CBF). In preclinical studies, rodent brain CBF serves as an important indicator in many brain disease models. In this work, we established a whole-brain CBF atlas based on 102 adult normal mice and profiled CBF distributions in 27 brain regions. We found that there is a high correlation of CBF between the left and right hemispheres. Additionally, the high-resolution mouse CBF atlas can be used to distinguish mice with autism disorder, indicating the potential applications of the atlas in preclinical studies.
Longitudinal Development of Regional Cerebellar Volumes from Birth to 27 Months of Age
Authors: Wang Ya , Chen Liangjun , Sun Yue , Li Tengfei , Wu Zhengwang , Huang Wenhua , Lin Weili , Wang Li , Li Gang
Published: August 2023

Early cerebellar development in infant brains is very dynamic and highly related to normal cognitive functions and neurodevelopmental disorders, but remains largely unexplored, due to the lack of densely-sampled longitudinal data of early ages. Herein, we unprecedently explored the dynamic developmental trajectories of the volumes in 27 cerebellar lobules based on 511 high-resolution longitudinal structural MRI scans from 235 healthy infants from the Baby Connectome Project (BCP) densely covering the age ranging from birth to 27 months. The trajectories of the cerebellar structures reveal lobule-specific nonlinear developmental patterns and are sexually dimorphic starting from different ages.
The Brain Functional Connectivity can Predict Response to Treatment with Transcutaneous Auricular Vagus Nerve Stimulation in Primary Insomnia
Authors: Luo Wenting , Zhang Yue , Hou Xiaoyan , Feng Menghan , Fu Chengwei , Chen Weicui , Liu Xian , Yan Zhaoxian , Deng Kan , Xu Biyun , Liu Bo
Published: August 2023

The individual response to treatment with the transcutaneous auricular vagus nerve stimulation ( taVNS ) in primary insomnia varies greatly, while there is lack of objective markers for patient’s treatment outcome. In this work, we demonstrated that the baseline functional connectivity combined with machine learning algorithms can predict response to treatment with taVNS in primary insomnia. The functional connectivity values within and between brain networks such as the default mode network, affective network, visual network, and cerebellar network maybe potential objective markers of patient’s treatment outcome.
Abnormal functional connectivity of default mode network subsystems in first-episode drug-naïve major depressive disorder
Authors: Qiu Hui , Li Hailong , Gao Yingxue , Cao Lingxiao , Liu Jing , Bao Weijie , Wang Yingying , Zhou Zilin , Zhang Suming , Tang Mengyue , Zhang Lianqing , Lu Lu , Huang Xiaoqi , Gong Qiyong
Published: August 2023

Most previous studies took DMN as a whole and measured its FC abnormalities on a network level while recently, researchers revealed DMN has three subsystems (core, dMPFC and MTL subsystem). Few studies had explored FC on subsystem levels in first-episode drug-naïve (FEDN) MDD patients. We used seed-based whole-brain functional connectivity analysis in a relatively large sample of FEDN MDD patients, we found hyper-connectivity between DMN three subsystems and frontoparietal network as well as cerebellum network, and hypo-connectivity between dMPFC subsystem and dorsal attention network. These findings might provide a more comprehensive understanding for DMN FC changes in MDD.
Diffusion-Relaxation Correlation Spectrum Imaging for the Assessment of Pituitary Macroadenomas Consistency: A Preliminary Study
Authors: Su Chun-Qiu , Hu Wentao , Hong Xun-Ning , Lu Shan-Shan , Dai Yongming
Published: August 2023

Preoperative evaluation of the consistency of pituitary macroadenomas plays a significant role in the determination of the surgical strategy. However, previous studies concerning the assessment of tumor consistency of macroadenomas were controversial1-4. Diffusion-relaxation correlation spectrum imaging (DR-CSI), which provides a correlation spectrum of both water molecular diffusion and T2 relaxation, could be used to resolve the information of tissue compositions, compartments, and heterogeneity at a sub-voxel level. The purpose of our study is to evaluate the utility of DR-CSI in assessing the consistency of pituitary macroadenomas.
Towards fast and precise tissue conductivity imaging in brain
Authors: Cao Jun , Ball Iain , Rae Caroline
Published: August 2023

Here we tested the boundaries of the speed and precision of phase MREPT in brain using balanced FFE. Baseline maps with conductivity variance of < 5% could be safely accelerated with compressed SENSE 6 without sacrifice of precision, and scans acquired as quickly as 1.89 s. Precision could be further improved by whole head B1 mapping. MREPT mapping should be conducted task free for best results.
Regional Hippocampal Changes in Patients with Hyperthyroidism
Authors: Singh Sadhana , Rana Poonam , Kumar Pawan , Kaur Prabhjot , Shankar L Ravi , Khushu Subash
Published: August 2023

Hyperthyroid patients showed structural and functional abnormalities in the hippocampus region of the brain as suggested by neuroimaging studies. However, the extent of structural, functional, and metabolic changes in hyperthyroid patients is still unclear. We examined the regional hippocampal volume and neuro-metabolite changes in hyperthyroid patients using high resolution T1-weighed imaging and 1H MRS techniques. Hyperthyroid patients showed reduced bilateral hippocampal volume and altered metabolic changes, i.e., Glu/tCr, mI/tCr, and NAA/tCr ratios in the hippocampus, compared to healthy controls. These findings provide evidence that hyperthyroidism results in structural and metabolic alterations in the hippocampus region of the brain.
Global and Regional Iron Content Changes of Gray Nucleus Using Quantitative Susceptibility Mapping in Type 2 Diabetes Mellitus Patients
Authors: Hu Rui , Liu Yangyingqiu , Gao Bingbing , Li Wanyao , Wang Weiwei , Song Qingwei , Liu Ailian , Miao Yanwei
Published: August 2023

Assessing whole-structural and regional high iron content in deep gray matter nuclei using STAGE-based QSM in T2DM Patients. Excessive deposition and uneven distribution of iron protein occur in all nuclei in T2DM patients. The MSVwh of significant differences (P < 0.05) between groups were present in right HCN, right PUT, bilateral GP, right STN and left GF, with the largest AUC of 0.723 in the right GP. The MSVhi in right HCN, right PUT, bilateral GP and left GF were significant differences (P < 0.05) With a largest AUC of 0.714 in right GP.
Correlation between Iron Burden and Cognitive Status in Type 2 Diabetes Mellitus Patients Using Quantitative Susceptibility Mapping
Authors: Hu Rui , Liu Yangyingqiu , Gao Bingbing , Du Wei , Wang Weiwei , Song Qingwei , Liu Ailian , Miao Yanwei
Published: August 2023

The relationship between iron accumulation and cognitive decline in T2DM has not been fully revealed and publicized. This research focuses on assessing the global iron content and high iron content levels of the gray nucleus using QSM, and to analyze the correlation between MSV with significant differences and clinical laboratory indicators and cognitive scores in T2DM Patients. Excessive deposition and uneven distribution of iron protein occur in all nuclei in T2DM patients. Iron is important in the pathophysiology of T2DM, especially the MSVhi in the right PUT was significantly negatively correlated with MoCA (r = -0.485, P = 0.004).
Comparison of BOLD detectability of ‘multi shot EPI’ and ‘single shot EPI with GRAPPA’ at 7T
Authors: Liu Guoxiang , Shah Adnan , Ueguchi Takashi , Ogawa Seiji
Published: August 2023

We compare the detectability of multi shot EPI (msEPI) and single shot EPI with GRAPPA (ssEPI-GRAPPA) using D-value maps to show the benefit of BISEPI (Block-Interleaved Segmented EPI) [1] for the same total acquisition time. D-values were derived based on the relationship between target effect, the significance level of detection, the number of time points (volumes), and tSNR [2]. The proposed D-value maps can be a useful quality assurance measure for determining the tSNR gain and activity detection performance of msEPI in comparison to ssEPI-GRAPPA in high-resolution fMRI at 7T.
Quantitative CAIPIRINHA-Dixon-TWIST-VIBE parameters correlate with molecular subtypes of invasive ductal carcinoma
Authors: Xie Tianwen , Jiang Tingting , Fu Caixia , Nickel Marcel Dominik , Peng Weijun , Gu Yajia
Published: August 2023

In this study, we analyzed the relationship between CAIPIRINHA-Dixon-TWIST-VIBE (CDTV)-derived DCE parameters and clinicopathological factors, including molecular subtypes of invasive ductal carcinoma (IDC). Our results showed that the values of semi-quantitative parameters were similar for various prognostic factors and molecular subtypes of IDC. However, the values of quantitative inline pharmacokinetic kinetic parameters, kep_minimum and kep_difference, were significantly different for the luminal A and HER2-positive subtypes. AUC value for accurately distinguishing luminal A and HER2-positive subtypes based on combined kep_minimum and kep_difference values was 0.820. Therefore, our study demonstrates that CDTV-derived quantitative parameters are associated with molecular subtypes of IDC.
O2-inhalation T2* BOLD and dual-VENC 4D flow MRI: hypoxic evaluation of pediatric transplanted kidneys
Authors: Nagao Michinobu , Ando Taro , Goto Yasuhiro , Shiina Isao , Kodaira Kazuo , Yoneyama Masami , Miura Kenichiro , Hattori Motoshi , Sakai Shuji
Published: August 2023

For pediatric patients with end-stage renal failure, kidney transplantation is the only treatment that can provide growth and long-term survival. Although rejection is the common cause of renal dysfunction, there are other causes of chronic transplant nephropathy, in which the transplanted kidney develops fibrosis. Hypoxia is considered as possible causes of this order. We used O2-inhalation T2*-BOLD and dual-VENC 4D flow MRI to assess hypoxia in pediatric transplanted kidneys. In patients with chronic transplant nephropathy, hypoxia was found in the renal medulla and small vessel’s flow was reduced. This analysis is an effective means of monitoring hypoxia in transplanted kidneys.
Differentiating Benign from Malignant Renal Cystic Masses Using Continuous-time Random-walk diffusion model
Authors: Yang Xiaojun , Duan Xiaohui , Wang Mengzhu , Yan Xu , Yang Lingjie , Zeng Weike , Jiang Wei , Hu Yaojun , Yang Guang , Shen Jun
Published: August 2023

This study evaluated whether continuous-time random-walk (CTRW) diffusion model could be used to distinguish benign from malignant renal tumors, as well as compared the diagnostic effectiveness between the diffusion parameters of CTRW and apparent dispersion coefficient (ADC). The results demonstrated that CTRW diffusion model as a new noninvasive MR technique, was able to differentiate benign from malignant renal masses in vivo, and further improve the diagnostic efficiency of renal malignant masses compared with conventional diffusion imaging.
Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features.
Authors: Moribata Yusaku , Kurata Yasuhisa , Nishio Mizuho , Kido Aki , Otani Satoshi , Himoto Yuki , Nishio Naoko , Furuta Akihiro , Masui Kimihiko , Kobayashi Takashi , Nakamoto Yuji
Published: August 2023

This multi-center retrospective study performed automatic segmentation of bladder cancer (BC) on MRI with a convolutional neural network and evaluated the reproducibility of radiomics features. Of the total 170 patients, 140 were used to train our U-net model and 30 were used to evaluate the segmentation performance of the model. Our U-net model achieved a median Dice similarity coefficient of 0.811 in the test dataset and most of the automatically extracted radiomics features showed high reproducibility (median intraclass correlation coefficient: 0.83-0.86). Our model would lead to efficient medical image analysis of BC using the radiomics approach.
Optimize and Evaluate the Efficacy of Pairwise AE Model in Predicting the Prognosis of Concurrent Chemo-radiotherapy for Cervical Cancer
Authors: Liu Miao , Wang Qi , Shi Gaofeng , Yang Li , Shi Qinglei
Published: August 2023

To overcome the small data set problems in clinical situations, this paper proposed a pairwise auto encoder (AE) model, which can learn more relationship information among samples to enhance the generalization ability, in predicting the prognosis of concurrent chemo-radiotherapy for LACC and demonstrated potential in this field.
Susceptibility-weighted MR sequence for the evaluation of intra-tumoral hemorrhage: Differentiation of benign and malignant ovarian tumors
Authors: Takeuchi Mayumi , Matsuzaki Kenji , Harada Masafumi
Published: August 2023

Intra-tumoral hemorrhage is one of the suggestive pathological findings of malignancy. Surgically proven 16 benign and 64 malignant solid or complex ovarian tumors were retrospectively evaluated. High intensity hemorrhagic foci on T1WI were detected in 16 of 64 malignant lesions (25%), whereas signal voids due to hemorrhage on susceptibility-weighted sequence (SWS) were detected in 41 of 64 lesions (64%). Neither high intensity foci on T1WI nor signal voids on SWS was detected in all 16 benign tumors. We conclude that the demonstration of intra-tumoral hemorrhage in patients with ovarian tumors by SWS may provide valuable diagnostic findings.
Quantitative Susceptibility Mapping as an Alternative to CT for Localizing Gold Intraprostatic Fiducial Markers
Authors: Stewart Ashley , Goodwin Jonathan , Robinson Simon , O’Brien Kieran , Jin Jin , Barth Markus , Bollmann Steffen
Published: August 2023

Gold fiducial markers (FMs) for prostate radiotherapy are commonly localized using Computed Tomography (CT), though interest in MR-only workflows is growing. One current limitation with magnitude-based MR-only workflows is the ability to distinguish FMs from blood products and calcifications because all appear as signal voids. Quantitative Susceptibility Mapping (QSM) separates sources based on their susceptibility, and may be a potential solution. We apply the QSMxT pipeline to gradient-echo images of a prostate cancer patient with FMs and a calcification. We found that QSM provided a contrast that could differentiate the FMs from calcifications to a degree comparable to CT.
Added value of deep learning-accelerated T2-weighted imaging of the bladder on image quality and lesion evaluation
Authors: Zhang Gumuyang , Chen Li , Zhou Hailong , Wang Yunna , Zhu Jinxia , Nickel Marcel , Weiland Elisabeth , Sun Hao , Jin Zhengyu
Published: August 2023

This study evaluated deep learning accelerated T2w imaging (T2DL) of the bladder in terms of acquisition time (TA), overall image quality, presence of artifacts, diagnostic confidence, sharpness of lesions, and VI-RADS T2 score compared to a standard T2w (T2S) sequence in twenty-five patients. Two radiologists evaluated the images independently. TA of T2DL was reduced by nearly 50% compared to T2S. Overall image quality and sharpness of lesions were superior in T2DL, while artifacts, diagnostic confidence and T2 score were similar between T2S and T2DL. T2DL has the potential to replace T2S in bladder MR.
Effects of oscillating frequency and SNR on quantifying microstructural properties in breast tumor using oscillating gradient diffusion MRI
Authors: Ba Ruicheng , Wang Xiaoxia , Zhang Zelin , Yi-Cheng Hsu , Sun Yi , Zhang Jiuquan , Wu Dan
Published: August 2023

The oscillating frequency and SNR are important for accurate microstructural mapping in diffusion-time-dependent diffusion MRI, which however, are limited on clinical scanners. This study demonstrated that the dMRI acquisition protocol with frequency up to 50 Hz achieved significant higher accuracy than that with 33Hz, based on 1) Monte-carlo simulation, 2) clinical data on 37 breast tumor patients, and 3) correlation with histological data. Also, for the first time, we demonstrated the feasibility of oscillating gradient dMRI-based microstructural mapping in distinguishing breast tumor status clinically.
Differentiation between benign and malignant breast masses using 3D amide proton transfer weighted imaging and dynamic contrast-enhanced MRI
Authors: Wang Ruhua , Zhang Yan , Lin Liangjie , Cheng Jingliang
Published: August 2023

This study evaluated the diagnostic value of dynamic contrast-enhanced MRI (DCE-MRI) combined with 3D amide proton transfer weighted imaging (APTWI) for differentiation between benign and malignant breast masses. Results indicated the quantitative MTRasym(3.5 ppm) value calculated by APTWI was significantly different between benign and malignant lesions, and the combination of APTWI and DCE-MRI improves the diagnostic performance for discriminating benign and malignant breast masses, especially category 4 masses.
The value of diffusion-weighted imaging and dynamic contrast-enhanced imaging in the differential diagnosis of male breast diseases
Authors: Wang Ruhua , Zhang Yan , Cheng Jingliang
Published: August 2023

The male breast is often ignored because of its rudimentary and nonfunctional nature. However, the male breast can develop many benign and neoplastic diseases, including breast cancer.Much less is known regarding the appearance of benign and malignant male breast conditions. Therefore, in this retrospective study, we explored the value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE-MRI) in the differential diagnosis of male breast diseases and confirmed the importance of DWI and DCE-MRI in the end.
Texture analysis of multiparametric MRI in the diagnosis of the ovarian sex cord-stromal tumors (SCSTs)
Authors: zhang hui , zhang hui
Published: August 2023

The accurate diagnosis of malignant SCSTs is still a challenge. We retrospectively analyzed the MRI texture features of 69 cases, and used t-test, one-way ANOVA, the Mann-Whitney U-test and ROC curve to evaluate these parameters. The results showed that the derived texture parameters may be valuable tool in predicting malignant SCSTs.
Comparison between Biparametric and Multiparametric MRI for Detection of Prostate Cancer in the Peripheral Zone using PI-RADS Version 2.1
Authors: Zhang Jiahui , Xu Lili , Zhang Gumuyang , Sun Hao , Jin Zhengyu
Published: August 2023

This study aimed to compare and analyse the diagnostic value of PI-RADS v2.1 when used with bpMRI versus mpMRI, DWI versus T2WI to detect peripheral-zone prostate cancer (pzPCa) and clinically significant prostate cancer (csPCa). The diagnostic efficiencies of mpMRI and bpMRI as well as DWI and T2WI in pzPCa and csPCa were compared using a PI-RADS score of ≥4 as the positive threshold and pathologic results as the gold standards. MpMRI and bpMRI as well as DWI and T2WI using PI-RADS v2.1 exhibited similar diagnostic efficiency in pzPCa and csPCa, whereas bpMRI demonstrated increased diagnostic specificity compared with mpMRI.
Feasibility of synthetic short TR and short TE DWI in prostate cancer
Authors: Ueda Yu , Tamada Tsutomu , Sanai Hiroyasu , Moriya Kazunori , Kido Ayumu , Obara Makoto , Ogino Tetsuo , Van Cauteren Marc
Published: August 2023

Diffusion-weighted imaging (DWI) with shorter echo time (TE) could be exploited to improve diffusion contrast by minimizing T2 shine-through due to longer T2 in normal prostate. However, clinical magnetic resonance imaging (MRI) scanner has limitation in shortening TE in conventional DWI. It would be beneficial to generate additional DWI with short TE from DWIs with two different TE, in addition to short repetition time (TR) which improvement of diffusion contrast has been reported. The synthetic DWI with shorter TR (1000 ms) and TE (1 ms) tended to show better diffusion contrast than real-acquired DWI with conventional TR and TE.
Research on the Application of Diagnosis and Invasion Assessment of Transition Zone Prostate Cancer by Relaxation Maps From Synthetic MRI
Authors: Song Na , Chen Zhiqiang , Chen Xiaohua , Wang Zhuo , Zhang Shaoru , Wei Xiaocheng , Zhang Dan , Zhu Kai
Published: August 2023

In this retrospective study, we aim to investigate the application value of quantitative relaxation time obtained from synthetic MRI in the diagnosis and assessment of aggressiveness of transition zone prostate cancer. It was concluded that quantitative relaxation T1 and T2 values of synthetic MRI are useful parameters for discriminate TZ PCa from BPH, and T1 value demonstrated the similar diagnostic performance as ADC value. Gleason staging could be preliminarily assessed by T2 value of SyMRI in patients who cannot be punctured.
Combining diffusion kurtosis imaging and clinical data for predicting the extramural venous invasion of rectal adenocarcinoma
Authors: Wei QiuRong , Chen WeiCui , Mao LiTing , Deng Kan , Huang WeiKang , Liu Bo , Liu Xian , Yan ZhaoXian
Published: August 2023

The extramural venous invasion (EMVI) is considered as the potential prognostic factor for patients with rectal carcinoma. We tried to investigate the diagnostic ability of diffusion kurtosis imaging (DKI) - derived parameters as risk factors for EMVI’s involvement status.Our results showed that the Kmean values, lymph node involvement, and an advanced tumor stage (T3) were independent risk factors for the prediction of EMVI status, which may suggest that the DKI as a potential biomarker for evaluating the EMVI status of rectal cancer is feasible.