bluuebunny/crossref_metadata_2025 huggingface dataset:
MR microscopy of human embryo at high isotropic spatial resolution
Authors: Makihara Kazuyuki , Kunieda Kazuki , Yamada Shigehito , Kose Katsumi , Terada Yasuhiko
Published: August 2023

High-resolution MR microscopy is advantageous for the human embryo study, but had not been realized because of many challenges. In this study, we demonstrated high-resolution MR microscopy of a human embryo specimen with 18 µm isotropic resolution. To achieve the higher spatial resolution than the previous system, we improved the hardware and optimized the pulse sequence. The MR images of the embryo showed detailed anatomical structures and were similar in appearance to the stained images obtained from an embryo specimen at the same developmental stage.
Deuterium metabolism imaging of rat brain at 9.4T using a double-nuclear transceiver
Authors: Du Feng , Yuan Jiawen , Li Nan , Zhou Chao , Wan Qian , Qin Qikai , Thompson Garth J. , Ye Qiong , Zhang Xiaoliang , Liu Xin , Zheng Hairong , Li Ye
Published: August 2023

Deuterium metabolic imaging (DMI) is an emerging technique, which can measure the metabolism in the brain non-invasively after intake of deuterated glucose. In this work, we construct a versatile and dedicated 1H/2H dual-nuclear transceiver for a 9.4T pre-clinical research system. The performance of the transceiver was evaluated by measuring the in vivo 2H spectra data. The metabolites of water, glucose, Glx and lactate after glucose infusion were quantified in healthy and glioma rats using the constructed double-nuclear transceiver.
Renal MRI at 5T: A feasibility and quantitative study
Authors: Zheng Liyun , Yang Chun , Sheng Ruofan , Dai Yongming , Zeng Mengsu
Published: August 2023

Compared to clinical field strengths, MRI at ultra-high magnetic fields allows higher SNR. However, imaging at 7T remains challenging, especially in renal MRI. This study investigated the feasibility of renal MRI at 5T, with a brand new 5T MR scanner. Compared to 3T examination, 5T renal MRI demonstrated higher SNR and improved corticomedullar discrimination with diagnostic image quality. Functional imaging, including DWI and T2* mapping, was also feasible at 5T. Therefore, in vivo 5T renal MRI may better elucidate the renal diseases with both anatomical and functional imaging, compared to conventional clinical MRI scanners.
Transient Computations of Eddy-Currents Induced by an Amplitude-Modulated Sinusoidal Gradient Pulse
Authors: Alsharafi Sadeq , Kassahun Haile , Badawi Ahmed , El-Sharkawy AbdEl-Monem
Published: August 2023

Eddy-currents are generated in MRI scanners’ metallic structures due to the rapid switching of gradient coils. They may result in image distortions and induce acoustic-noise particularly for fast/spiral sequences. Transient eddy-currents computations can be used to understand the extent of such effects. In this work, a numerical framework was devised to compute transient eddy-currents induced by an amplitude-modulated sinusoidal pulse for a longitudinal gradient coil configuration. Stream functions representation of eddy-currents, Multilayer Integral Method, and an excitation current with amplitude-modulated sinusoidal function are used to solve the circuit equation and efficiently compute transient eddy-currents generated in the cryostat.
Association of Blood Biomarkers and Brain Tissue Volume Loss in Patients of Mild Cognitive Impairment and Alzheimer’s Disease
Authors: Jahng Geon-Ho , Lee Kyung Mi , Kim Sang Tae , Park Soonchan , Jung Sue Min , Rhee Hak Young , Ryu Chang-Woo , Kim Eui Jong
Published: August 2023

To report the values of a battery of blood inflammatory biomarkers from cognitive normal (CN) to Alzheimer’s disease (AD) in our reasonably sized patient cohort and to evaluate the association between gray matter volume (GMV) loss in AD and plasma levels of blood biomarkers, we included 38 elderly CN elderly, 40 mild cognitive impairment (MCI), and 33 AD subjects and obtained blood biomarkers and GMV. We found that GMV was negatively associated with the levels of IL1b, P-tau, and T-tau. There were no significant associations between brain tissue volumes and the levels of mAβ, NLRP3, miR155, oAβ, and Nogo-A.
Brain structure, amyloid and behavioural features for predicting clinical progression in subjective cognitive decline
Authors: Liu Siwei , Luo Xiao , Jiaerken Yeerfan , Chong Joanna , Shim Hee Youn , Zhang Minming , Zhou Juan
Published: August 2023

Subjective cognitive decline (SCD) is a risk factor for dementia. However, multiple pathologies, including amyloid deposition, cerebrovascular pathology, and depression, contribute to the heterogeneity in SCD. We included 170 non-demented elderly with 2-years follow-up to examine brain structural abnormalities in SCD. We found progressive and stable SCD individuals differed in deep white matter hyperintensities and temporoparietal grey matter atrophy. We used multi-model brain and behavioural factors to predict cognitive impairment and dementia progression. Periventricular white matter hyperintensities mediated the effect of amyloid accumulation on cognitive decline and disease severity, while depressive symptoms directly predicted disease severity.
Improved Multiple Sclerosis Lesion Visualization using Tailored FLAWS-MP2RAGE at 7T
Authors: Zhang Zhe , Gao Chenyang , Zhu Wanlin , Zhang Yingkui , Kong Qingle , Tian Decai , Jing Jing , Wang Yongjun
Published: August 2023

Accurate visualization and evaluation of the MS lesions is an essential step for clinical practice. FLAWS-MP2RAGE has been proposed and applied at ultra-high field to better visualize both white matter and gray matter lesions. This work proposed the optimized method, tailored FLAWS(tFLAWS)-MP2RAGE, using a new image combination method for better lesion contrast. Results of MS patients showed higher lesion CNR of tFLAWS-MP2RAGE compared with conventional FLAWS-MP2RAGE and MPRAGE methods. This method might be a potential tool for lesion detection and evaluation at UHF for MS and other brain diseases.
The Contribution of Increased Choroid Plexus Volume in the Alzheimer’s Disease
Authors: Li Jiaxin , Hu Yueqin , Feng Xue , Dai Weiying , Meyer Craig , Alsop David , Zhao Li
Published: August 2023

Alzheimer’s disease (AD) may be caused by the dysfunction of glymphatic system, in which anatomic changes of the choroid plexus may be associated with reduced CSF production. Our previous work showed significantly increased choroid plexus volume in AD patients compared to healthy controls. However, contributions of the lateral ventricle volume were not investigated. Here, the lateral ventricle and choroid plexus were segmented using two cascaded deep learning models and the volumes were measured on 733 subjects. Increased lateral ventricle volume was found in AD patients, similar to previous studies. More importantly, choroid plexus volume showed a unique contribution to AD.
Quantitative cerebrovascular reactivity MRI in mice using acetazolamide challenge
Authors: Wei Zhiliang , Li Yuguo , Hou Xirui , Han Zheng , Xu Jiadi , McMahon Michael , Duan Wenzhen , Liu Guanshu , Lu Hanzhang
Published: August 2023

Cerebrovascular reactivity (CVR), which denotes brain’s vasodilatory capacity, is broadly utilized in cerebrovascular and neurodegenerative diseases. However, the most popular hypercapnia method in human studies is unsuitable for small animals due to the difficulty in measuring end-tidal CO2. Here, we took a different approach using a pharmacological vasodilatory stimulus, acetazolamide. Plasma level of acetazolamide and vascular responses were quantified by high-performance liquid chromatography and perfusion MRI, respectively. Evidences of feasibility, safety, temporal characteristics, and dose-dependence have been demonstrated. This new CVR technique may open several avenues for preclinical research on cerebrovascular diseases and therapeutic testing in different animal models.
Automatic parameter selection for quantitative susceptibility mapping (QSM) with regard to Shearlet/TGV-regularization
Authors: Stiegeler Janis , Straub Sina
Published: August 2023

In this work noise is assumed to be a random vector and the method of unbiased predictive risk estimator (UPRE) is used to select suitable data/regularization parameters to solve the local phase to susceptibility deconvolution problem of quantitative susceptibility mapping (QSM). The proposed algorithm is tested on the simulated multi-echo data provided at the 2019 QSM Reconstruction Challenge. This work is a further development of the algorithm presented at the ISMRM Meeting 2021 and its purpose is to show that the method of UPRE can be applied advantageously to a shearlet /TGV based susceptibility reconstruction.
SENSE-like reconstruction of multi-average body DWI to remove motion-induced signal loss: application in liver DWI
Authors: Van Anh , McTavish Sean , Raspe Johannes , Harder Felix , Peeters Johannes , Weiss Kilian , Makowski Marcus , Braren Rickmer , Karampinos Dimitrios
Published: August 2023

Motion-induced signal loss and phase maps were generated and used in a SENSE-like reconstruction routine to solve for a single DWI from a multi-average liver diffusion-weighted imaging experiment. The proposed reconstruction yields homogeneous liver signal and possibly improves diagnostic values.
Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Fiber Clustering
Authors: Chen Yuqian , Zhang Chaoyi , Song Yang , Xue Tengfei , Makris Nikos , Rathi Yogesh , Cai Weidong , Zhang Fan , O'Donnell Lauren
Published: August 2023

We propose a novel unsupervised deep learning framework for white matter fiber clustering. Self-supervised learning is adopted to enable joint deep embedding and cluster assignment. Anatomical information is incorporated into the neural network to improve anatomical coherence. In addition, outlier removal is performed to further improve cluster quality. Our method is evaluated on three datasets and showed superior performance in terms of cluster compactness, anatomical coherence and generalization across subjects compared to several state-of-the-art algorithms.
Consistent White Matter Parcellation in Adolescent Brain Cognitive Development (ABCD): A ~10k Harmonized Diffusion MRI Study
Authors: Zhang Fan , Cetin-Karayumak Suheyla , Pieper Steve , Rathi Yogesh , O'Donnell Lauren
Published: August 2023

We present a large-scale harmonized dMRI study where we have performed successful white matter(WM) tractography parcellation across ~10k subjects from the ABCD study. We first assess the effects of data harmonization on WM parcellation, followed by an evaluation of WM parcellation using the entire harmonized dataset. We show that after harmonization, more anatomical tracts are identified and their FA values are closer to the harmonization reference data. We also demonstrate highly successful WM parcellation, where overall 99.9% of tracts(73 per subject) are identified. The parcellated WM tracts, as well as their diffusion measures, will be made available to the public.
A Dedicated Transceiver 8Tx/16Rx pTx Coil Array for Ex-vivo MRI Histology of Post-infarction Myocardium on a Whole-body 7T Scanner
Authors: Elabyad Ibrahim , Terekhov Maxim , Schreiber Laura
Published: August 2023

The purpose of this work was to develop and investigate a dedicated transceiver 16-element antisymmetric loop array for high-resolution imaging of the ex-vivo porcine heart at 7T. The array was interfaced to a 7T scanner in parallel transmit (pTx) mode (8Tx/16Rx). Electromagnetic-field (EMF) simulations were performed with the antisymmetric array loaded with a spherical phantom and a human heart (Billie). The optimization of the B1+-shimming for both sTx and pTx applications was performed using simulated and experimental B1-maps. The array was successfully tested to acquire ultra-high resolution (0.1x0.1x0.8mm voxel) images of the post-infarction scar tissue in the excised pig heart.
Direct Signal Control combined with dynamic, Fast Online Customized (FOCUS) parallel transmit excitation pulses for TSE at 7 Tesla
Authors: Herrler Jürgen , Endres Jonathan , Tomi-Tricot Raphael , Liebig Patrick , Gumbrecht Rene , Meixner Christian , Maier Andreas , Dörfler Arnd , Malik Shaihan , Nagel Armin
Published: August 2023

Direct Signal Control with Variable Excitation and Refocusing (DiSCoVER) was combined with a dynamic, Fast Online-Customized (FOCUS) parallel transmit excitation pulse for a 3D TSE sequence using an 8Tx/32Rx head RF coil at 7 Tesla. DSC could improve the signal, mainly in the cerebellum region compared to CP mode. FOCUS excitation pulses achieve better FA and phase homogeneity than static pTx pulses (standardly used in DiSCoVER). Combining a FOCUS excitation pulse with DiSCoVER-optimized refocusing pulses, led to signal gain across the echoes, which was evaluated in simulations for 132 subjects. Universal and individual DiSCoVER-refocusing pulses showed comparable performance.
Optimization of wide-field optical imaging method towards fMRI integration in mice
Authors: Pan Wen-Ju , Wang Yunmiao , Watters Harrison , Meyer-Baese Lisa , Smith Alaina , Jaeger Dieter , Keilholz Shella
Published: August 2023

We present an optimized wide-field optical imaging method with GEVI in mice to probe the relationship between slow changes in neuronal membrane potential and the BOLD signal in hindpaw stimulation, demonstrate neuronal sub-threshold activity of slow fluctuations could be possibly isolated from hemodynamic signals.
RF shielding designs for birdcage coils for high-resolution animal fMRI at 9.4T
Authors: Yang Zhangyan , Lu Ming , Drake Gary , Wang Feng , Yang Pai-Feng , Chen Li Min , Gore John , Yan Xinqiang
Published: August 2023

RF shields are key components of volume coils, but they may cause imaging distortions and the significant heating. The effects of different shielding strategies were evaluated for a birdcage coil used to image animals at 9.4T. Three shields with various thicknesses and two shields with different slot patterns were comparatively investigated ed in terms of performance and temperature rise during fMRI acquisitions.
BOLD response in squirrel monkey brains evoked by green light without exogenous opsin
Authors: yang zhangyan , Yang Pai-Feng , Luo Huiwen , Wang Feng , Reed Jamie , Grissom William , Chen Li Min , Gore John
Published: August 2023

Optogenetic stimulation combined with MRI detection of blood oxygenation level dependent (BOLD) effects has been developed as a powerful tool to delineate brain circuits. Opsin targeting specific cell types induce neural activity when irradiated with light at a specific wavelength. We detected robust BOLD effects in secondary somatosensory cortex (S2) and downstream interconnected caudate putamen (CPu) of monkey brains from irradiation with low-intensity green light without exogenous green light specific opsin, suggesting hemodynamic changes can be stimulated without any associated neural activity.
A global spatially-adaptive method for task fMRI activation analysis with the advantage of alleviated spatial blurring
Authors: Yang Zhengshi , Zhuang Xiaowei , Lowe Mark , Cordes Dietmar
Published: August 2023

Accurately localizing brain activation is of great importance for promoting basic science and clinical application of task fMRI data. In this study, we proposed a global and time-efficient way to conduct brain activation analysis, with the property of spatially-adaptive smoothing and determining individual voxel’s activation status with wholebrain fMRI data considered simultaneously. We have demonstrated its advantage over traditional methods in alleviating spatial blurring artifacts.
Pain and the NeuroMatrix in the Brain: Feasibility and Safety Study of 3T DWI in a Chronic Low Back Pain Patient Treated with Spinal Cord Stimulation
Authors: Ailes Isaiah , Kang KiChang , Sathe Anish , Miao Jingya , Frizon Leonard , Krisa Laura , Fleming Kristen , Natale Peter , Talekar Kiran , Middleton Devon , Mohamed Feroze , Sharan Ashwini , Alizadeh Mahdi
Published: August 2023

Spinal cord stimulation (SCS) in patients with failed back surgery syndrome aims to reduce neuropathic pain. However, minimal studies show a safe procedure using 3T diffusion weighted imaging (DWI) MRI for patients with SCS. Additionally, more studies looking at the neurological SCS treatment responses can lead to better optimization of SCS. It was our objective to safely develop a systematic procedure for 3T DWI MRI while also generating a map of the neural network connectivity in structures associated with pain. Long term application of this protocol aims to provide an objective assessment to SCS treatment.
Aberrant Structural Brain Network Hierarchy in Trigeminal neuralgia
Authors: Jacob Yael , Verma Gaurav , Alper Judy , Delman Bradley , Seifert Alan , Shrivastava Raj , Balchandani Priti
Published: August 2023

Trigeminal neuralgia (TN) is a physically and mentally incapacitating disorder characterized by extreme, sporadic, sudden facial pain. TN is associated with the trigeminal sensory pathway, however, the etiology of TN remains unclear. Implementing a graph-theory analysis using diffusion MRI we tested whether whole brain network structural connectivity hierarchies differentiate between TN patients and healthy controls. We found aberrant centrality measures of various brain regions in TN. Specifically, this whole-brain data-driven network analysis was able to depict two major regions of the trigeminal sensory circuit, the brainstem and thalamus, and highlight their dysfunction role in the whole brain network.
Longitudinal assessment of nonalcoholic steatohepatitis with MRI and MRE – changes of imaging biomarkers and their relationships
Authors: Zhu Zheng , Li Jiahui , Yaqoob Usman , Allen Alina , Therneau Terry , Glaser Kevin , Hoodeshenas Safa , Venkatesh Sudhakar , Manduca Armando , Shah Vijay , Ehman Richard , Yin Meng
Published: August 2023

We measured the longitudinal change of MRE-assessed liver stiffness (LS), loss modulus (LM) and MRI-assessed proton density fat fraction (PDFF) in a preclinical NASH model of 25 rats and 52 patients with NAFLD to assess disease severity, as well as the direction of progression/regression. Our pilot studies suggest that ΔLM and ΔPDFF are promising for monitoring treatment effects in a short-term period, while ΔLS is recommended for stratifying significant fibrosis that needs treatment in long-term follow-ups.
Diffusion and perfusion MRI for prediction of HCC response to neoadjuvant immunotherapy
Authors: Bhuiyan Enamul , Kennedy Paul , Bane Octavia , Shareef Muhammed , Hectors Stefanie , Cheung Hung Kam , Miller Elizabeth , Fiel M. Isabel , Schwartz Myron , Ward Stephen , Marron Thomas , Merad Miriam , Taouli Bachir
Published: August 2023

Neoadjuvant immunotherapy has the potential to decrease the risk of hepatocellular carcinoma (HCC) recurrence post resection. The objectives of this study were to assess the value of pre-treatment MRI parameters for prediction of HCC immunophenotype and response in a cohort of patients undergoing neoadjuvant immunotherapy prior to liver resection. We hypothesize that diffusion and perfusion MRI can predict HCC response to neoadjuvant immunotherapy. It was observed that abundant of TILs decreases ADC in tumors. Moreover, uptake rate is higher in highly necrotic tumors.
Regional Lung Ventilation Mapping at 0.55T based on Feature Tracking
Authors: Yang Yijing , Zhao Ziwei , Tian Ye , Kato Roberta , Cui Sophia , Kuo C.-C. Jay , Nayak Krishna
Published: August 2023

Assessment of regional lung ventilation has significant clinical value for the diagnosis and follow-up of pulmonary diseases. High-performance 0.55T systems have provided new opportunities for pulmonary imaging due to prolonged T2* and reduced susceptibility. Here, we describe an image-based regional lung ventilation assessment method based on real-time bSSFP imaging with 0.3s temporal and 1.64x1.64 mm2 spatial resolution, and feature tracking. In healthy adult volunteers, we demonstrate the ability to detect posture-related left-right differences in ventilation, and test-retest repeatability. We detected -5% to 64% regional volume changes throughout the respiratory cycle from end of exhalation to total lung capacity.
A cross-modality deep learning model for esophageal cancer segmentation and quantitation on 18F-FDG PET/CT and diffusion weighted MRI
Authors: Zhou Zijian , Panthi Bikash , Rauch David , Son Jong Bum , Wu Carol , Lin Steven , Pagel Mark , Ma Jingfei
Published: August 2023

We applied a deep learning (DL) model developed for 18F-FDG PET/CT of mantle cell lymphoma to esophageal cancers on 18F-FDG PET/CT and diffusion-weighted MRI. We compared the performance of the DL-based segmentation with the manual segmentation on PET and evaluated the quantitation on both PET and apparent diffusion coefficient (ADC). The model achieved promising results of detecting and segmenting esophageal cancers, and the DL-based imaging metrics were consistent with the reference standards.
A clustering method to classify stages of NAFLD based on the metabolites results obtained in two mouse models with MRS
Authors: Xavier Aline , Gainza Constanza , Zacconi Flavia , Cabrera Daniel , Arese Marco , Sing-Long Carlos , Andia Marcelo
Published: August 2023

In this study, we analyzed the liver fatty acids results obtained by magnetic resonance spectroscopy and gas chromatography in non-alcoholic fatty liver disease (NAFLD) mice with principal component analysis (PCA) and a clustering method. The study was made with two different mouse models (CDAA and Western diet), and a control group. Our results, as evidenced by PCA, showed that the liver fatty acid composition changed as NAFLD progressed and it was possible to identify the 3 most relevant NAFLD groups with MRS (healthy, steatosis, and steatohepatitis) with excellent agreement with the gold-standard histopathological scores.
Deep Learning Approaches Using Convolutional Neural Networks to Generate Synthetic CT from Spinal MRI for Radiotherapy Planning
Authors: Zhang Yang , Nouizi Farouk , Lang Ning , Xing Xiaoying , Chen Yongye , Wang Qizheng , Zhang Enlong , Yuan Huishu , Nie Ke , Su Min-Ying
Published: August 2023

A total of 27 patients receiving both spinal CT and MR for evaluation of back pain were identified for analysis. MR images and CT image were co-registered first, and the CT was used as ground truth for training a deep learning algorithm using MR images to generate synthetic CT. In this study, we implemented cycleGAN to generate these synthetic CT images from their corresponding MR slices. Five-fold cross validation was used to evaluate the performance of the trained model. Compared to the original images, the Mean Average Error was 27.63±11.51, and the Peak Signal-to Noise Ratio was 19.44±5.72.
Pre-Therapy Ferumoxytol-Enhanced Magnetic Resonance Imaging (MRI) Predicts Response of Metastatic Breast Cancer to Liposomal Irinotecan
Authors: Ravi Harshan , Lorza Andres Arias , Costello James , Han Hyo Sook , Jeong Daniel , Klinz Stephan , Sachdev Jasgit , Korn Ronald , Raghunand Natarajan
Published: August 2023

R*2 and the apparent concentration of FMX in the tumor (FMXC) are considered biomarkers of liposomal irinotecan (nal-IRI) drug uptake into that tumor lesion, which in turn would determine response of that tumor to nal-IRI. Historically, quantification of R*2 and FMXC had been implemented by using a calibration phantom and acquiring patient scans both pre-FMX and post-FMX. Here we have demonstrated a pre-treatment FMX-enhanced MRI companion biomarker of response to nal-IRI in mBC patients that can be computed from a single16-24 h post-FMX MRI scan without the need for calibration phantoms or pre-FMX scans.
In Vivo Oxygen Imaging of Implanted Islet Encapsulation Devices
Authors: Kotecha Mrignayani , Viswakarma Navin , Siddiqui Eliyas , Patel Sonny , Epel Boris
Published: August 2023

The lack of oxygen supply to the highly metabolic pancreatic islet cells is one of the major factors contributing to the failure of islet transplantation devices designed to cure type I diabetes (T1D). Several approaches to improve oxygenation in these devices have been developed. However, the lack of available technologies to provide reliable pO2 assessment in and around devices hinders the progress severely. We performed in vivo oxygen imaging of cell loaded encapsulation devices using pulse electron paramagnetic resonance oxygen imaging (EPROI) technique. For the first time, whole-body EPROI is used to monitor pO2 of implanted devices in this work.
Deuterium (2H) MR Spectroscopy Distinguishes Tumor (Glioblastoma) from Radiation Necrosis in Mouse Brain
Authors: Song Kyu-Ho , Engelbach John A. , Quirk James D. , Rich Keith M. , Ackerman Joseph J.H. , Garbow Joel R.
Published: August 2023

Employing mouse models of radiation necrosis (one that displays the histologic hallmarks of the clinical condition) and glioblastoma (GL261), deuterium (2H) MR spectroscopy, in concert with infusion of 2H-labelled glucose, was employed to ascertain whether the 2H MRS signatures could differentiate the two lesions, an unmet clinical need. The 2H MR metabolic profiles of the two lesions were markedly different. In the tumor, the Warburg effect (aerobic glycolysis, fermentation) converted glucose nearly exclusively to lactate. In radiation necrosis, oxidative phosphorylation (respiration) dominated, with glucose converting to TCA cycle intermediates glutamate and glutamine. Thus, 2H MR distinguishes glioblastoma vs. radiation necrosis.
Multimodal molecular imaging assessment of tumor microenvironment. Hyaluronan depletion induces tumor reoxygenation and radiosensitization
Authors: Kishimoto Shun , Seki Tomohiro , Saida Yu , Otowa Yasunori , Yamashita Kota , Yamamoto Kazutoshi , Devasahayam Nallathamby , Brender Jeffrey , Krishna Murali
Published: August 2023

PEGPH20 is a PEGylated form of recombinant human hyaluronidase PH20. The purpose of this study is to investigate physiologic changes in pancreatic adenocarcinoma xenograft after PEGPH20 treatment using multi-modal imaging and further determine the utility of PEGPH20 as radiosensitizer. PEGPH20 treatment significantly increased intratumor pO2, blood perfusion and volume, and decreased glycolytic flux assessed by EPR, MRI with USPIO or Gd, and 13C DNP MRI, respectively. PEGPH20 enhanced treatment effect of radiotherapy. The results validated the utility of the imaging methods to monitor the changes in the tumor microenvironment after hyaluronan depletion and to predict the radio-sensitizing effect of PEGPH20.
Bayesian sensitivity encoding enables parameter-free, highly accelerated joint multi-contrast reconstruction
Authors: Lin Alexander , Ba Demba , Bilgic Berkin
Published: August 2023

To address limitations with classical SENSE algorithms, we propose Bayesian Sensitivity Encoding (Bayes-SENSE), which obviates the need to tune regularization penalties, provides variance maps that can quantify algorithmic uncertainty, and is easily extendable to multi-contrast reconstruction. Bayes-SENSE is a synergistic combination of SENSE and Bayesian CS (BCS). We adapt recent work accelerating BCS to develop an efficient and highly parallelizable inference algorithm for Bayes-SENSE based on the conjugate gradient (CG) method. We evaluate Bayes-SENSE in several undersampling settings with parallel imaging, and demonstrate that it outperforms L2-/L1-SENSE in terms of reconstruction error while also providing the aforementioned benefits.
High-Quality 0.5mm Isotropic Functional MRI Using a Synergistic Combination of NORDIC Denoising and Deep Learning Reconstruction
Authors: Demirel Omer , Moeller Steen , Vizioli Luca , Yaman Burhaneddin , Dowdle Logan , Yacoub Essa , Ugurbil Kamil , Akçakaya Mehmet
Published: August 2023

Submillimeter fMRI allows studying brain function at the mesoscale level, but scans at such resolutions require trade-offs in SNR and coverage, necessitating better image reconstruction. In this work, we combine NOise Reduction with Distribution Corrected (NORDIC) denoising prior to image reconstruction with self-supervised physics-guided deep learning (PG-DL) for high-quality 0.5mm isotropic fMRI. The former removes components of image series that cannot be distinguished from thermal noise, while the latter enables higher acceleration rates. Results show that the proposed combination of NORDIC and PG-DL improves on NORDIC or PG-DL alone, both visually, and in terms of tSNR and GLM-derived t-maps.
Using deep learning to generate missing anatomical imaging contrasts required for lesion segmentation in patients with glioma.
Authors: Genc Ozan , Chunduru Pranathi , Molinaro Annette , Pedoia Valentina , Chang Susan , Villanueva-Meyer Javier , Palladino Janine Lupo
Published: August 2023

Missing value imputation is an important concept in statistical analyses. We utilized conditional GAN based deep learning models to learn missing contrasts in MR images. We trained two deep learning models (FSE to FLAIR and T1 post GAD to T1 pre-GAD) for MR image conversion for missing value imputation. The model performances are evaluated by visual examination and comparing SSIM values. We observed that these models can learn the output contrast.
Mammography Lesion ROI Drawing Guided by Breast MRI MIP to Extract Features from Corresponding Lesions to Build Radiomics Diagnostic Models
Authors: Liu Yan-Lin , Chen Zhongwei , Zhao Youfan , Zhang Yang , Zhou Jiejie , Chen Jeon-Hor , Nie Ke , Wang Meihao , Su Min-Ying
Published: August 2023

268 patients with DCE-MRI and mammography were analyzed to evaluate the diagnostic performance of radiomics models. The dataset was split to 202 (146 malignant 56 benign) for training, and 66 (48 malignant 18 benign) for testing. The MIP of MR contrast enhancement maps was generated to simulate the CC and MLO view as guidance for manual ROI drawing on mammography. The models were built using features extracted by PyRadiomics. Combined MRI and mammography features can reach 89.6% accuracy in training and 83.3% in testing datasets, and the addition of mammography can improve specificity while maintaining high sensitivity of MRI.
SMILR - Subspace MachIne Learning Reconstruction
Authors: Iyer Siddharth , Sandino Christopher , Yurt Mahmut , Cao Xiaozhi , Liao Congyu , Schauman Sophie , Setsompop Kawin
Published: August 2023

Recent developments in spatiotemporal MRI techniques enable whole-brain multi-parametric mapping in incredibly short acquisition times through highly-efficient k-space encoding, subspace reconstruction and carefully-designed regularization. However, this comes at the cost of long reconstruction times making such methods difficult to integrate into clinical practice.

This abstract proposes a framework denoted SMILR (pronounced smile-r) to reduce the reconstruction times of subspace methods from multiple hours to a few minutes through machine learning. To evaluate performance, the framework is applied to multi-axis spiral projection MRF (denoted SPI-MRF) where it achieves improved reconstruction over conventional subspace reconstruction with locally low-rank at ~16-20x faster speed.
A domain-agnostic MR reconstruction framework using a randomly weighted neural network
Authors: Pal Arghya , Rathi Yogesh
Published: August 2023

Can a random weighted deep network structure encode informative cues to solve the MR reconstruction problem from highly under-sampled k-space measurements? Trained networks update the weights at training time, while untrained networks optimize the weights at inference time. In contrast, our proposed methodology selects an optimal subnetwork from a randomly weighted dense network to perform MR reconstruction without updating the weights - neither at training time nor at inference time. The methodology does not require ground truth data and shows excellent performance across domains in T1-weighted (head, knee) images from highly under-sampled multi-coil k-space measurements.
Image Reconstruction with a Self-calibrated Denoiser
Authors: Liu Sizhuo , Schniter Philip , Ahmad Rizwan
Published: August 2023

Plug-and-play (PnP) methods can reconstruct images by employing iterative algorithms that leverage the knowledge of the forward model and a sophisticated denoiser. The performance of PnP can be improved by utilizing an application-specific denoiser. However, training such denoisers may not be feasible for many MRI applications. Here, we describe a PnP-inspired method that does not require data beyond the single, incomplete set of measurements. The proposed method, called recovery with a self-calibrated denoiser (ReSiDe), trains the denoiser from the patches of the image being recovered. For validation, ReSiDe is applied to T1-weighted brain and myocardial first-pass perfusion data.
Towards Whole Brain Diffusion Tensor Spectroscopic Imaging
Authors: de la Rocque Guimaraes Bruno Sa , Talaat Khaled , Mullen Michael , Yacoub Essa , Posse Stefan
Published: August 2023

Here we describe the development of a high-spatial resolution multi-slice single-shot Diffusion-Tensor proton-echo-planar-spectroscopic-imaging (PEPSI) technique using a binomial spatial-spectral refocusing RF pulse for mapping the diffusion tensor of water, Cho, Cr and NAA. Analysis of NAA and water diffusion in white matter obtained in a 4-slice acquisition with 1cc voxel size in 6 minutes (bmax = 2430.7 mm2/s) showed a mean ADC value of 0.15*10-3 and 0.66*10-3 mm2/s, which is consistent with values reported in the literature. Single-shot high spatial resolution diffusion sensitive MR spectroscopic imaging has the potential to probe metabolite diffusion across extended brain regions.
High-quality Lung imaging with FLORET UTE and Fibonacci interleaved trajectory ordering
Authors: Krishnamoorthy Guruprasad , Willmering Matthew , Woods Jason , Pipe James
Published: August 2023

FLORET (Fermat looped, orthogonally encoded trajectories) is an efficient center-out 3D spiral trajectory, and it supports ultra-short echo times. In this work, a new trajectory ordering scheme and FLORET balanced steady-state free precession (FLORET-bSSFP) were developed at 1.5T with inline reconstruction. Simulations, phantom, and human lung imaging were performed to compare the performance of the proposed trajectory ordering with standard ordering. The proposed trajectory ordering scheme minimized artifacts caused by the changing gradient moments while improving temporal stability and motion robustness. High-quality free-breathing lung images were obtained using FLORET-bSFFP and spoiled gradient echo-based UTE FLORET.
Compressed sensing for motion-robust real-time fetal cardiac imaging
Authors: Rubert Nicholas , Lu Quin , Jategaonkar Gaurav , Goncalves Luis
Published: August 2023

We examined undersampled real-time bSSFP reconstructions for fetal cardiac imaging. Two compressed sensing reconstructions, ICTGV and L plus S, were compared to k-t SENSE with respect to spatial and temporal blurring with and without fetal motion. Results with a digital fetal cardiac MRI phantom demonstrated ICTGV was able to capture expansion and contraction of the fetal heart even during periods of fetal motion while k-t SENSE and L plus S were not. Digital phantom results were confirmed on a 1.5T MRI scanner with implementation of ICTGV and acquisitions demonstrating pulsation of the fetal heart during periods of fetal motion.
Inductively Coupled Floating Coil for Hyperpolarized 13C Imaging of Mouse Brain
Authors: Takahashi Atsushi , Guarin David , Hardy Erin , Miller Julie , Wakimoto Hiroaki , Cahill Daniel , Yen Yi-Fen
Published: August 2023

We report an inductively coupled floating coil designed for hyperpolarized 13C MR spectroscopic imaging of mouse brain, with emphases on the simplicity of the circuit design, the ease of use, whole-brain coverage, and high SNR obtained. The floating coil is designed to “crown” the mouse head for a snug fit to achieve full coverage of the brain with good sensitivity. Here, we demonstrated the coil’s performance in normal mouse and glioblastoma multiforme mouse model at 4.7 T using a next-generation hyperpolarizer. High signal to noise ratio exceeding 70:1 was obtained in the brain with good spatial resolution (1.53mm x 1.53mm).
Spatially resolved FID spectroscopy using a 3D spiral UTE imaging sequence
Authors: Fischer Anja , Martirosian Petros , Schick Fritz
Published: August 2023

This method allows for the calculation of pixel-wise FID spectra based on a 3D spiral UTE imaging sequence. Images were acquired for 36/72 TE and extrapolated. The method is advantageous for rapidly decaying 1H signals such as those of collagen in tendons or fibrotic tissue. A phantom (6 collagen solutions) served for evaluation. Resulting spectra are comparable to a standard non-localized FID spectrum and show positive correlation between collagen concentration and signal. First in-vivo results recorded in the subcutaneous adipose tissue exhibit the typical fat resonances. The presented UTE-FID spectroscopy seems feasible for spatially resolved applications of rapidly decaying signals.
Quantitative Metabolite Mapping of 12 Metabolites in the Human Brain
Authors: Wright Andrew , Henning Anke
Published: August 2023

Very short TR (TR < 300) MRSI is a popular method that enables fast acquisition of spectroscopic imaging data; however, raw metabolite signals following short TR acquisitions are influenced by strong T1-weighting. In order to gather more accurate images and to be able to relate MRSI results to SVS studies, it is valuable to correct for T1-weighting and to quantify MRSI images. This study presents results that utilize a voxel-specific, T1-correction method which is an advancement from more traditional methods that utilized average T1-corrections for metabolites. Fully sampled, single-slice 1H MRSI metabolite maps are presented for 12 metabolites.
Intuitive Angle-Aware Bilateral Filtering Revealing Asymmetric Fiber ODF for Improved Fiber Tractography
Authors: Poirier Charles , Descoteaux Maxime
Published: August 2023

Although the voxel-wise signal acquired by diffusion MRI is symmetric, it is not always the case of the underlying fiber configurations. We present angle-aware bilateral filtering, an intuitive method for denoising fiber ODF fields revealing asymmetric fiber ODFs. To evaluate the effect of the filtering, tractography is performed on the resulting asymmetric fiber ODF field. Compared to the tractogram obtained from the original fiber ODF field, we show that using asymmetric filtered fiber ODF field as input to a fiber tracking algorithm reduces the ratio of incomplete streamlines and false connections and increases the proportion of true connections.
Quantitative Susceptibility Mapping Artifact Reduction in Ex Vivo Tissue Specimens Using Adaptive Multi-Contrast Informed Regularization
Authors: Balasubramanian Priya , Guo Lingfei , Huang Weiyuan , Kovanlikaya Ilhami , Ramineni Alisa , Garcia Nector , Liechty Benjamin , Nguyen Thanh , Spincemaille Pascal , Pisapia David , Wang Yi
Published: August 2023

Quantitative susceptibility mapping (QSM) solves an ill-posed dipole field inversion problem and is prone to streaking and shadowing artifacts. This report presents a novel QSM reconstruction algorithm that effectively suppresses these artifacts using prior information from traditional MRI contrasts. The proposed algorithm was evaluated using ex vivo high resolution QSM of cerebellum and brainstem specimens using COSMOS as the reference method, showing improved QSM accuracy and artifact reduction and better agreement with myelin sensitive Luxol Fast Blue staining compared to conventional MEDI and MEDI-SMV methods.
Quantitative Evaluation of Pyruvate Uptake and Metabolism in Cells using Mass Spectrometry and Hyperpolarized 13C NMR
Authors: Harlan Collin , Niedzielski Joshua , Michel Keith , Chen Yunyun , Martinez Gary , Lorenzi Philip , Tan Lin , Merritt Matthew , Ragavan Mukundan , Sandulache Vlad , Lai Stephen , Bankson James
Published: August 2023

Metabolic imaging of hyperpolarized pyruvate can provide new insight into cancer progression and therapeutic response. Pharmacokinetic modeling can be used to determine kPL, the apparent rate constant for conversion of hyperpolarized pyruvate into lactate. Quantitative evaluation of signal evolution in vivo can be challenging due to nonstationary signal and multiple barriers between the intravascular precursor and its intracellular conversion into lactate. In this work, we evaluated intracellular kPL using suspensions of anaplastic thyroid cancer and prostate cancer cells. A pharmacokinetic model with two physical compartments and two chemical pools was utilized for quantitative analysis.
Mapping Pyruvate-to-Lactate Rate Constants in Hyperpolarized Data with bSSFP Acquisitions
Authors: Sahin Sule , Dwork Nicholas , Tang Shuyu , Liu Xiaoxi , Wang Zhen , Larson Peder
Published: August 2023

Using a metabolite-specific bSSFP sequence for hyperpolarized [1-13C]pyruvate MRI has been shown to increase SNR significantly, yet specialized kPL methods have not been developed for this sequence. A kPL fitting method for bSSFP lactate acquisition was developed and voxel-wise kPL fitting was performed on four renal cell carcinoma subjects. The kPL values and maps were compared to and showed agreement with lactate over pyruvate AUC ratio maps and spoiled gradient echo kPL values and maps.
Study of B1 and SAR Field Distribution for loop coil with different bending angles at 3T
Authors: Sharma Tripta , Zhang Xiaoliang
Published: August 2023

The aim is to investigate the RF field behavior of flexing loop coils as resonant elements in flexible RF arrays. Numerical modeling and simulation of a mechanically flexible single channel RF coil at different bending angles for 3T MRI are implemented to determine the best bending angle that will generate highest B1 magnetic field inside imaging area with least flux cancellation at center. Results include B1 magnetic and SAR field distribution of the coronal, sagittal and transverse planes of phantom at 9 bent angles. It also includes the comparative quantitative analysis of magnetic field at different biological samples.
Brain structural development on oriental and occidental neonates: a comparison between ITPNBDI and dHCP datasets
Authors: Zhang Yan , Wang Miaomiao , Liu Congcong , Wang Xiaoyu , Ge Yao , He Yichu , Shi Feng , Li Xianjun , Yang Jian
Published: August 2023

Despite studies that have demonstrated population differences due to differences in genetics, culture, and environmental exposures, a comparison of brain structural development between oriental and occidental neonates remains to be fully examined. We compared 108 neonates from ITPNBDI and 170 neonates from dHCP to examine differences in neonatal brain structure. Results demonstrated ITPNBDI neonates held shorter brain length, wider brain width and higher brain height than dHCP neonates. They also had greater total brain volume, greater grey matter and less white matter than dHCP neonates. Specifically, volumes of some brain regions involved in speech perception were different between two datasets.
The value of first-order features based on ADC map in evaluating the neuroprotective effect of LIPUS for acute traumatic brain injury with rat model
Authors: Du Dan , Liu Lanxiang , Shi Qinglei
Published: August 2023

In this study we studied the value of LR model established with first-order features based on ADC map in evaluating the neuroprotective effect of Low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI). The results demonstrated that the model based on the first-order features may have potential value in predicting the therapy effect of LITUS in clinical practice in future.
Dysfunctional interaction between the dorsal attention network and the default mode network in Patients with Type 2 Diabetes Mellitus
Authors: Lei Yumeng , Zhang Dongsheng , Qi Fei , Gao Jie , Tang Min , Ai Kai , Yan Xuejiao , Lei Xiaoyan , Shao Zhirong , Su Yu , Zhang Xiaoling
Published: August 2023

To investigate the specific neural substrate of type 2 diabetes mellitus (T2DM) -related cognitive impairment, independent component analysis (ICA) and functional network connection analysis (FNC) methods were applied to resting-state fMRI images from 44 patients with T2DM and 47 healthy controls (HCs). This study found the inherent neural mechanism between the dorsal attention network (DAN) and default mode network (DMN) was eliminated, and these abnormal changes were correlated with the scores of multiple neuropsychological assessments (P < 0.05), indicated that the abnormal changes of the DAN-DMN may be the neural basis of T2DM-related cognitive deficits.
Disrupted small-world networks in children with attention-deficit/hyperactivity disorder: a DTI-based network analysis
Authors: Wu Liuhui , Chen Yingqian , Su Shu , Yang Zhiyun , Dai Yan , Qian Long
Published: August 2023

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in school-age children, the pathogenesis is still unclear. In current study, 49 pediatric with ADHD and 51 age- and gender-matched typically developing (TD) children were included. Diffusion tensor imaging (DTI) and graph theory approaches was used. At the global level, patients with ADHD showed increased characteristic Lp, γ, σ and decreased Eglob; regionally, altered nodal profiles were mainly in the default mode, central executive network and basal ganglia. In particular, nodal betweenness of left caudate was negatively associated with the clinical symptom severity.
Radiomics based characterization of peritumoral edema segmented from DCE MRI to differentiate glioblastoma from solitary brain metastasis
Authors: P Suhail Parvaze , Gupta Rakesh , Bhattacharjee Rupsa , Singh Anup , Singh Rakesh Kumar , Khanna Gaurav , Chaudhary Amal Roy , Patir Rana , Vaishya Sandeep , Neelavalli Jaladhar , Shah Tejas
Published: August 2023

Edema in GB is characterized by the presence of tumor cells infiltration as compared to brain metastasis with only pure edema. Radiomics features extracted using FLAIR images in GB and BM are found to be exhibiting variation in some of the entropy and non-uniformity-based features, which could be used as signature to differentiate GB from brain metastasis.
Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status
Authors: He Jinlong , Wu Jianlin , Gao Yang , Wu Qiong , Shen Jing , Wang Shaoyu , Zhang Huapeng , Ren Jialiang , Wang Peng
Published: August 2023

Objective:To compare the performance of clinical model, radiomics model, and combined model in predicting biomarker status (IDH, MGMT, TERT, 1p/19q) of glioma.Methods: 81 glioma patients confirmed by histology were enrolled in this study. The predictive performance of each model was validated by receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA).Results: The mixed model showed the highest performance in each genic phenotype (IDH AUC = 0.93, MGMT AUC=0.88, TERT AUC=0.76, 1p/19q AUC=0.71).Conclusion: The mixed model is an effective tool to distinguish genic phenotype of brain glioma which have highest diagnostic efficiency than other models.
Decreased brain GABA levels in patients with migraine without aura: an exploratory 1H-MRS study
Authors: Wu Xiaojuan , Han Shuting , Yang Yang , Dai Hui , Wu Peng , Zhao Hongru , Li Yonggang
Published: August 2023

Increasing neurophysiological studies had revealed that regional excitation-inhibition imbalance in brain played a key role in the pathogenesis of migraine. This study explored the alterations in GABA and Glx levels in the anterior cingulate gyrus (ACC) and medial prefrontal lobe (mPFC) of patients with migraine without aura (MWoA) using MEGA-PRESS at 3 Tesla. Compared with healthy controls, the GABA+ levels in the ACC and mPFC of patients were lower and correlated with attack frequency, and Glx levels had no difference, suggesting a relationship of the abnormalities of GABAergic system in the ACC and mPFC with the pathophysiological mechanism of MWoA.