bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of MAP-MRI Diffusion Model in Preoperative Brain Development in Infants with Congenital Heart Disease
Authors: xu shengfang , Wang Shaoyu , Ge Xin , Yue songhong , Li Xinyi , Qian jifang , zhu dalin , zhang jing
Published: November 2024

Motivation: Non-invasive quantitative methods to assess the brain development of children with congenital heart disease (CHD) has been a hot topic . Goal(s): The main focus of this study is to investigate how MAP-MRI can be used to assess preoperative brain development in children with CHD. Approach: In this study, quantitative and correlational analyses of preoperative brain development in CHD children were performed using the multi-parameter indicators of the MAP-MRI diffusion model. Results: The results show that children with CHD exhibit cerebral microstructural abnormalities preoperatively, and MAP-MRI parameter indicators can be used for early prediction of preoperative neurodevelopment in CHD children. Impact: MAP-MRI parameter indicators can serve as imaging reference values for preoperative brain development in children with CHD, aiding clinical professionals in focusing on the neurodevelopment of these patients while treating their CHD.
Differentiating Low- and High-Grade Pediatric Brain Tumor Using Integrated DWI
Authors: Yen Albert , Karaman Muge , Dan Guangyu , Wang He , Li Yuhua , Zhou Xiaohong Joe
Published: November 2024

Motivation: Pediatric brain tumors is the most common cancer among the pediatric population, and DWI-imaging offers a non-invasive method to assess tumor grade to guide appropriate treatments. Goal(s): The study investigates the feasibility of DISMANTLE, an integrated DWI approach for simultaneous assessment of tissue cellularity, vascularity, and heterogeneity, in differentiating high-grade and low-grade pediatric brain tumors. Approach: Seventy pediatric patients with brain tumors, categorized into high-grade and low-grade, were scanned with DWI sequence. Images were analyzed using DISMANTLE and 3 comparison models. Results: Removing the perfusion-related signal in DISMANTLE improved the accuracy and sensitivity of diffusion-related parameters in assessing pediatric brain tumor grades. Impact: The study emphasizes the importance of appropriate signal characterization and fitting strategies for high b-value DWI in robust assessment of brain tumors. Future DWI modeling should consider segmentally fitting the diffusion and perfusion-related signals.
UTE Imaging for Rapid Whole-Body Central Vascular Access Assessment in Children and Young Adults Undergoing Cardiac Surgery
Authors: Young Daniel F. , Zou Qing , Dzelebdzic Sanja , Hussain Tarique
Published: November 2024

Motivation: The motivation for this study is to propose an alternative and more efficient imaging protocol for vascular access assessment for complex congenital heart disease (CHD) casesGoal(s): To determine if UTE imaging can provide a supplemental tool to conventional MR imaging for evaluating vascular access in the context of CHD. Approach: Selection of 15 patients undergoing pre-operative assessment for complex CHD, including ferumoxytol administration, implement a 3D UTE sequence and a quality scoring scale. Results: The study concludes that UTE imaging is a time-efficient method to visualize vascular anomalies, patency, occlusion, and access, and it can complement MRI planning for cardiovascular procedures. Impact: Our study demonstrates that UTE imaging with ferumoxytol can provide high-quality vascular access imaging for patients with complex CHD. This offers an improved diagnostic tool for assessing vascular access as an important addition to the tools available for CHD evaluation.
A Docker-based Ensemble Pipeline for Tractogram with High-throughput, Reproducible and Comprehensive Mapping of White Matter Fibers (DEPTH)
Authors: Lin Runjia , Kim Juri , Ouyang Minhui , Fan Xin , Huang Hao
Published: November 2024

Motivation: The complex whole brain connectome is underlined by white matter (WM) fibers featuring both long and short-range connections. Most existing protocols are tailored to trace long-range fibers, incapable of comprehensively tracing all fibers including both long and short-range fibers. Goal(s): To achieve comprehensive mapping of whole-brain WM fibers in a unified framework including specifically high-fidelity tractogram of short-range fibers. Approach: We developed DEPTH, a Docker-containerized pipeline extending advanced short-range fiber tracing. Results: DEPTH offers high-throughput, reproducible and comprehensive tractogram of both long and short-range WM fibers. The Docker-based containerization ensures cross-platform usability and versatility without complex setup and configuration. Impact: High-throughput, reproducible and comprehensive whole-brain white matter fibers across multisite datasets could now be traced by our software.
DL-based Phase Correction Enables Robust Real Diffusion-Weighted MRI with Increased Diffusion Contrast
Authors: Wang Xinzeng , Lan Patricia , Guidon Arnaud
Published: November 2024

Motivation: Real diffusion-weighted MRI (DWI) has shown improved diffusion contrast and more accurate estimation of diffusion parameters. However, current real DWI is still not optimal and its performance highly depends on the choice of parameters for phase correction, reducing its robustness, especially in body DWI. Goal(s): To enable robust real DWI by improving phase correction and reducing noise floorApproach: We combined deep-learning based phase correction and deep learning reconstruction to enable robust phase correction and to reduce noise floor. Results: The phantom and healthy volunteer results demonstrated improved diffusion contrast in both acquired and synthesized high b-value neural and body DWI images. Impact: DL-based phase correction and image reconstruction enables robust real DWI imaging, improving diffusion contrast and quantitative measurements in both neuro and body. This technique can be used to study cancer staging and treatment response in both low and high field.
Single-shot diffusion trace spectroscopic imaging using tetrahedral encoding with semi-LASER and radial echo-planar trajectories at 7T
Authors: Saucedo Andres , Thomas M. Albert , Wang Danny
Published: November 2024

Motivation: We show the first demonstration of single-shot diffusion trace-weighted radial echo planar spectroscopic imaging with tetrahedral diffusion encoding in both phantom and in vivo at 7T. Goal(s): The advantage of the single-shot DW-REPS is the reduction of the measurement time. This proof-of-concept study applies radial EPSI at 7T for diffusion trace-weighted MRSI. Approach: Trace ADCs from 3 phantom and 2 in vivo datasets were determined from single-shot DW-REPSI acquisitions. Results: Preliminary results show good agreement in the estimated phantom ADC values, while in vivo trace ADCs are generally within the expected range although the values tend to be slightly higher than previously reported. Impact: Our preliminary results indicate a promising approach for determining the orientation-independent trace ADC value with DW-REPSI at 7T. This technique can reduce the total acquisition time for DW-MRSI studies relevant for probing the intracellular properties underlying pathological conditions.
Subvoxel QSM of human knee cartilage: a preliminary study
Authors: Zhang Ming , Lao Guoyan , Wei Hongjiang
Published: November 2024

Motivation: Subvoxel QSM could be beneficial for assessing the knee cartilage but requires two separate sequences for reconstruction by using APART-QSM. Goal(s): To achieve subvoxel QSM reconstruction of knee cartilage in a single scan. Approach: A multi-contrast framework was used to simultaneously estimate $$$T_1$$$, $$$T_2$$$ and $$$T_2^{*}$$$ mapping in one scan. The magnitude and phase images were generated based on the signal equation. The preprocessed phase and $$$R_2^{'}$$$(=$$$1/{T_2^*}$$$-$$$1/{T_2}$$$) were used for subvoxel QSM reconstruction. The results were compared with conventional approach using two sequences (GRE+MSE). Results: The subvoxel QSM results using the multi-contrast framework have good agreement with the conventional condition. Impact: The diamagnetic and paramagnetic susceptibility source separation of the knee cartilage could be achieved in a single scan using a multi-contrast framework. This technique can provide specific information to assess the tissue magnetic properties of the knee cartilage.
A deep image prior based refinement for 3D phase unwrapping in brain MRI
Authors: Zhu Xuanyu , Gao Yang , Xiong Zhuang , Jiang Wei , Liu Feng , Crozier Stuart , Sun Hongfu
Published: November 2024

Motivation: MRI signals have phase information from the GRE sequence, which reflects B0 field homogeneities. Goal(s): Due to acquisition, the phase is converted from complex data, ranging from -π to π and causing visual discontinuities. However, previous learning-based approaches have difficulties processing 3D brain data directly. Approach: In this study, we introduced an unsupervised refinement based on Deep Image Prior to enhance the performance of the pre-trained networks (PHU-DIP), and the inference were performed on one simulated and one in vivo brain. Results: The PHU-DIP method corrected the misclassification regions from the pre-trained networks and exhibited the significant time-efficiency compared to conventional method. Impact: The PHU-DIP provided a refinement scheme that help to improve the performance of a well-trained network. This technique could also be expanded onto other training modes and other pathological conditions.
Investigation and validation for cortical laminar structures of myelin and iron using χ-separation (chi-separation)
Authors: Moon Byeongpil , Shin Hyeong-Geol , Kim Jiye , Ji Sooyeon , Oh Chungseok , Lee Jongho
Published: November 2024

Motivation: Previous studies have demonstrated the correlations between iron and paramagnetic susceptibility and myelin and diamagnetic susceptibility. However, there has yet to be a quantitative layer-wise comparison with histology. Goal(s): Our objective is to validate laminar structures of χ-separation against histology in V1. Approach: In V1, we performed laminar profiling of χ-separation, iron-, and myelin histology. The profile was obtained by sampling points at 5% intervals along the cortical depth, oriented perpendicularly to the cortex. Results: The cortical depth profile reveals that both χpara with iron histology and χdia with myelin staining exhibit similar profiles and peaks at the location of the Gennari line. Impact: By comparing the cortical depth profile in the V1 region including the location of the Gennari line between χ-separation and histology, we have confirmed that χ-separation (χpara, χdia) accurately represents the quantitative amounts of iron and myelin with precision.
Exploring the ocular glymphatic system: The association of MRI-visible perivascular spaces with intraocular pressure and tear total-tau
Authors: van der Thiel Merel , van de Sande Nienke , Meeusen Anouk , Drenthen Gerhard , Postma Alida , Nuijts Rudy , van der Knaap Noa , Ramakers Inez , Webers Carroll , Backes Walter , Gijs Marlies , Jansen Jacobus
Published: November 2024

Motivation: Preclinical research suggests an ocular glymphatic system similar to the cerebral system, driven by intraocular pressure (IOP). However, human studies are scarce. Goal(s): To explore the eye-brain connection by investigating tear total-tau as a potential early marker of cerebral glymphatics and consider the link between IOP (driver of ocular glymphatics) and impaired cerebral waste clearance. Approach: MRI-visible PVS were scored on 7T images and related to IOP and tear total-tau. Results: Higher tear total-tau and lower IOP were associated with more PVS, implying a connection to impaired cerebral waste clearance and aligning with the potential presence of a human ocular glymphatic system. Impact: Our exploratory results suggest that higher tear-tau and a reduced driving force of ocular waste clearance are connected to impaired cerebral waste clearance. Thereby, this study bridges the gap between the potential human ocular glymphatic system and cerebral waste clearance.
Automatic Segmentation and Quantitative Measurement of Deep Medullary Veins Diameter
Authors: Zhou Yichen , Zhao Bingbing , Zong Xiaopeng
Published: November 2024

Motivation: Deep medullary veins (DMVs) stenosis may be one of the causes of small vessel disease, so non-invasive tool for its assessment is desired. Goal(s): Developing automatic DMV segmentation and diameter quantification methods for assessing DMV stenosis. Approach: We trained an automatic segmentation model and proposed a DMV diameter quantification method by analyzing the complex MRI signals at sub-voxel scale. Results: The segmentation model achieved satisfactory performance. The accuracy of the diameter quantification method was verified in phantoms. The fitted DMV diameter distribution was close to earlier ex-vivo report and showed strong correlation with DMV susceptibility from quantitative susceptibility mapping. Impact: Our approach can serve as a useful automatic pipeline to study the role of DMV stenosis in the pathogenesis of small vessel disease.
Microstructure Informed Susceptibility Source Separation (MI-SSS) Improves Correlation with Translocator Protein PET in Multiple Sclerosis
Authors: Şişman Mert , Nguyen Thanh , Kovanlikaya Ilhami , Dimov Alexey , Schwartz Hannah , Karakatsanis Nikolaos , Spincemaille Pascal , Gauthier Susan , Wang Yi
Published: November 2024

Motivation: Noninvasive detection of immune activity of chronic active MS lesions is of great interest. Specific biomarkers of immune activity such as quantitative susceptibility mapping (QSM) was proposed for this purpose. However, QSM suffers from the contamination of diamagnetic myelin. Goal(s): The aim of this study is to show that paramagnetic susceptibility component derived from susceptibility source separation is more specific to immune activity than QSM. Approach: The correlation of QSM and paramagnetic susceptibility against TSPO PET in 34 chronic lesions from 7 MS patients are obtained. Results: Higher correlation of paramagnetic susceptibility shows its higher specificity to immune activity than QSM. Impact: Chronic active MS lesions with immune activity are of great importance as they demonstrate ongoing demyelination. Susceptibility source separation provides an improved noninvasive biomarker for the in vivo quantification of immune activity.
Abnormal brain perfusion detected in elderly Long COVID patients more than one year after initial mild infection
Authors: Cohen Alexander , Ristow Kelly , Umfleet Laura , Franczak Malgorzata , Swanson Sara , Pommy Jessica , Patel Milan , Obarski Shawn , Mason Lilly , Wang Yang
Published: November 2024

Motivation: Long COVID in aging has become a significant public health concern, but the neurological mechanisms of Long COVID symptoms remain elusive. Goal(s): This study aimed to assess abnormal brain perfusion related to cognitive impairments in Long COVID, who had initial non-hospitalized mild COVID-19.Approach: : 3D pCASL with Hadamard-encoded multiple PLDs was applied in 30 elderly Long COVID patients in comparison with 28 controls.Results: Both prolonged arterial transit time (ATT) and reduced ATT-corrected CBF (cerebral blood flow) were detected in Long COVID patients compared with controls, which was linked to cognitive deficits. Impact: This study demonstrates the usefulness of advanced MR perfusion techniques in evaluating Long COVID patients, where CBF and ATT showed distinctive patterns that correlated with cognitive decline, manifesting more than a year following the initial mild infection.
A Matched Case Control Study of Early Cervical Spondylotic Myelopathy Based on Diffusion Magnetic Resonance Imaging
Authors: Ni Ming , Li Shujing , Zhang Xianchang , Lang Ning , Jiang Liang , Yuan Huishu
Published: November 2024

Motivation: Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Goal(s): To explore the value of diffusion MRI (dMRI) in diagnosing early-stage CSM and evaluating uncompressed segments in patients with early CSM. Approach: Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case control study was conducted. Results: The orientation division index (ODI) was positively correlated with early CSM, and the anisotropic water fraction (AWF) was negatively correlated. The ODI and AWF can assist in identifying the scope of early CSM involvement. Impact: The orientation division index (ODI) was positively correlated with early CSM, and the anisotropic water fraction (AWF) was negatively correlated. The ODI and AWF can assist in identifying the scope of early CSM involvement.
Quantitative and Comparative Evaluation of 2D Reduced-FOV Multi-shot Diffusion Tensor Imaging in Spinal Cord
Authors: Yuan Chenglang , Chen Shihui , Liang Liyuan , Xu Xiaorui , Xiong Hailin , Liu Tianbaige , Li Yi , Chang Hing-Chiu
Published: November 2024

Motivation: To our best knowledge, there has yet to be a comprehensive evaluation of the combination of cardiac triggering, reduced-FOV, or multi-shot techniques together for improving spinal cord DTI. Goal(s): This study aims to compare the performances of spinal cord DTI with different parametric combinations. Approach: Extensive and comparative experiments in five aspects were conducted. Results: Results demonstrate that multi-shot DTI with MUSE could achieve better reconstruction in the spinal cord. A combination of reduced-FOV and multi-shot techniques could be adopted simultaneously in pursuit of ultimate distortion correction. In addition, cardiac triggering should be equipped to reduce the influences on cerebrospinal fluid pulsation. Impact: Multi-shot DTI with MUSE and cardiac triggering might be the optimal combination for clinical diagnosis of the spinal cord if available on commercial MRI scanners. Future coil design could focus on customized coil arrangement of the spinal cord for optimization.
Use of the Allen Human Brain spatial transcriptome for the validation of myelin content imaging using BMC-mcDESPOT.
Authors: Bae Jonghyun , Gong Zhaoyuan , Guo Alex , Faulkner Mary , Laporte John , Bouhrara Mustapha
Published: November 2024

Motivation: Myelin water imaging has demonstrated its ability to successfully detect changes of myelin content in different neuropathology. However, the validation of these measures remains challenging. Goal(s): In this study, we aim to validate our MWF measurements with the gene expression that are relevant to myelin. Approach: We utilized the Allen Human Brain Atlas (AHBA) transcriptomics dataset to validate our Myelin Water Fraction (MWF) measurements. We correlated the aggregated gene expression from AHBA with our derived MWF for different brain regions. Results: Our results demonstrate strong correlations of gene expression related to myelin and the transcription of myelin with derived MWF measurements. Impact: We utilized transcriptomics to validate derived Myelin Water Fraction measures, which strongly correlated with the gene expression specific to myelin. The use of transcriptomics further supports on the molecular basis of myelin synthesis and transcriptional changes with aging.
Influence of Maternal Position on Fetal Organ Oxygenation using Low Field MR
Authors: Payette Kelly , Verdera Jordina Aviles , Uus Alena , Hajnal Joseph , Story Lisa , Hall Megan , Rutherford Mary , Hutter Jana
Published: November 2024

Motivation: Maternal supine sleeping position in the third trimester has been linked to decreased uterine blood flow and increases in stillbirth. Goal(s): To investigate the impact of maternal position on fetal and placental T2* values by taking advantage of the increased dynamic T2* range at low field strengthsApproach: We acquired dynamic whole uterus multi-echo gradient echo sequences at 0.55T with the subject in both left lateral and supine positions and compare the T2* placental and fetal body organ values organs in 91 subjects. Results: Significant differences in mean T2* values were observed between both positions in the placenta and 7 fetal body organs. Impact: Maternal position significantly impacts mean placental and fetal body T2* values. In addition, future quantitative fetal T2* studies should consider maternal position in their study design.
Combining orientation changes and fractional anisotropy of white matter fibers to diagnose autism spectrum disorder based on machine learning
Authors: Wang Miaoyan , Zhu Hua , Xu Dandan , Peng Bo , Dai Yakang , Cheng Jian , Jiang Haoxiang
Published: November 2024

Motivation: Autism spectrum disorder (ASD) lacks sensitive and effective imaging biomarkers. Goal(s): Using diffusion tensor imaging to detect white matter tracts damage and changes in local directional fields in children with ASD and combining machine learning to construct a diagnostic model for preschool-aged children with ASD. Approach: Introducing the novel mathematical framework of director field analysis, we investigate the local geometric structure of white matter tracts using tract-based spatial statistics and automated fiber quantification techniques. Results: Children with ASD have reduced fractional anisotropy and increased twist and distortion values. The machine learning model showed an area under the curve of 0.85 for diagnosing ASD. Impact: The director field analysis parameters fill the gap in previous studies and provide a new perspective for exploring the neuropathological mechanisms of ASD. By combining machine learning, the diagnostic efficiency of ASD is improved.
Hyperdynamic CSF flow is related to ventricular volumes and jugular venous flow in adolescents with congenital heart disease (CHD)
Authors: Tuura Ruth O'Gorman , Koch Felicitas , Mojon Francois , Ehrler Melanie , Schmid Alenka , Naef Nadja , Kottke Raimund , Kretschmar Oliver , Latal Beatrice
Published: November 2024

Motivation: Enlarged CSF volumes have been reported in children with congenital heart disease (CHD), and have been linked to neurodevelopmental outcome, but the origin of these enlarged CSF volumes is not yet known. Goal(s): To examine the link between CSF flow, arteriovenous flow and CSF volumes in order to improve our understanding of the observed changes in CSF volume. Approach: Phase contrast MRI of the cerebral aqueduct, carotid arteries and jugular veins was combined with 3D anatomical MRI for segmentation of the CSF spaces. Results: CHD children show hyperdynamic CSF flow, which is linked to enlarged 3rd ventricle volumes and venous flow. Impact: An improved understanding of the link between heart defects and brain development and hydrodynamics may help to foster improved development and outcome for children with CHD in future.
Association with Maternal Diet Quality during Pregnancy and Neonatal Brain White Matter Development
Authors: Na Xiaoxu , Glasier Charles , Andres Aline , Ou Xiawei
Published: November 2024

Motivation: Maternal nutrient intake is important for fetal growth and development. Goal(s): This study examined associations between maternal diet quality during pregnancy and neonatal brain white matter development. Approach: Forty-four healthy pregnant woman/newborn dyads were included in the study. The mothers had nutrition intake assessed by Healthy Eating Index-2015 (HEI-2015) throughout pregnancy. Correlations between neonatal MRI diffusion tensor imaging (DTI)-measured fractional anisotropy (FA) and HEI-2015 scores were evaluated. Results: Significant correlations between maternal sodium intake at 1st trimester of pregnancy and neonatal white matter FA values were found, indicating potential influence of maternal sodium intake during early pregnancy on neonatal brain white matter development. Impact: We found significant correlations between maternal sodium intake at first trimester of pregnancy and neonatal DTI-measured FA values, indicating sodium intake better aligned with the Dietary Guidelines of Americans during early pregnancy is associated with better neonatal white matter development.
Imaging analysis of subcutaneous tumors based on time-dependent diffusion MRI
Authors: Yoshinaga Sosuke , Takeda Atsushi , Shinjo Takuto , Kawachi Yuki , Terashima Yuya , Toda Etsuko , Matsushima Kouji , Tsurugizawa Tomokazu , Terasawa Hiroaki
Published: November 2024

Motivation: Diffusion MRI is a non-invasive imaging method that depicts the water molecule diffusion, but its use for studying peripheral cancers has lagged behind that for deep cancers. Goal(s): To develop a highly accurate MRI method of peripheral cancer diagnosis that is comparable to biopsy-based diagnosis. Approach: To determine the differences in diffusion time-dependency between subcutaneous tumor tissues from normal tissues in tumor-bearing mouse models, we utilized a wide range of diffusion times and obtained information about intra- and inter-tumor cell microstructures. Results: In subcutaneous tumor models, time-dependent diffusion MRI can discriminate tumor tissues and identify cancer cell lines. Impact: The improved MRI method for non-invasive tumor diagnosis based on time-dependent diffusion MRI not only helps physicians determine the grade of malignancy, but also contributes to early detection by its ability to evaluate microstructures.
Time-dependent diffusion-weighted MRI for pathological grade of clear cell renal cell carcinoma
Authors: Li Shichao , Gao Mengmeng , Chen Wei , Li Zhen
Published: November 2024

Motivation: Accurate grading of clear cell renal cell carcinoma (ccRCC) is essential for treatment decisions, particularly in patients with comorbidities. Goal(s): This study aims to investigate time-dependent diffusion MRI to noninvasively characterize the microstructural properties of ccRCC and distinguish between different pathological grades. Approach: A total of 66 patients with histologically confirmed ccRCC underwent MRI scans, and microstructural parameters were estimated using time-dependent diffusion MRI techniques. Results: The study revealed distinct microstructural differences between low-grade and high-grade ccRCC, showing the potential of time-dependent diffusion MRI for preoperative pathological grade characterization. Impact: This study has the potential to reshape the landscape of preoperative ccRCC grading, promote objectivity in treatment planning.
Qualitative and quantitative assessment of accelerated liver DWI using deep learning reconstruction in oncologic patients
Authors: Rata Mihaela , Castagnoli Francesca , Shur Joshua , Evans Emily , Hopkinson Georgina , Benkert Thomas , Weiland Elisabeth , Koh Dow-Mu , Winfield Jessica
Published: November 2024

Motivation: Deep learning (DL) reconstructions can improve image quality and/or reduce acquisition time in diffusion-weighted imaging (DWI). Goal(s): This study aims to assess, quantitatively and qualitatively, DL-accelerated DWI in 50 patients with colorectal cancer undergoing liver examinations. Approach: Three DWI series are compared: a moderately-accelerated DL-DWI, a corresponding standard reconstruction and a highly-accelerated DL-DWI. Results: The moderately-accelerated DL reconstruction method provides better image quality than a standard reconstruction. Its ADC estimates in liver, spleen and liver metastases are slightly higher than ADC estimates from the standard reconstruction. Impact: This study evaluated DL-accelerated DWI in 50 patients undergoing liver examinations by comparing three DWI series. The moderately-accelerated acquisition with DL reconstruction provided better image quality versus the standard reconstruction; its ADC was slightly higher than the standard-based ADC.
An Optimized Analytical Segmented (opAS) Approach to Extract Intravoxel Incoherent Motion (IVIM) Parameters
Authors: Buko Erick , Johnson Casey
Published: November 2024

Motivation: Despite the IVIM model’s ability to noninvasively provide insight into tissue microstructure and perfusion, estimation of IVIM parameters in low-perfused tissues such as bone marrow remains a challenge. Goal(s): In this work, we propose an optimized analytical segmented (opAS) approach for extracting IVIM diffusion (Ds) and perfusion (Df and f). Approach: We compare the performance of this new approach against the analytical segmented (AS) method previously proposed for low-perfused tissues using numerical simulations and a piglet model. Results: Our findings indicate that opAS outperforms AS in the estimation of all IVIM parameters (Ds, Df, and f), particularly in the low perfusion regime. Impact: The proposed opAS method outperforms the prior AS method in estimating IVIM diffusion (Ds) and perfusion (Df and f) parameters, bringing IVIM a step closer to being a clinically useful non-contrast-enhanced technique to assess bone marrow perfusion.
Towards robust myocardial IVIM-DWI: feasibility of single-shot MoCo-DW-EPI with Compressed SENSE AI and elastic registration
Authors: Goto Yasuhiro , Nagao Michinobu , Yoneyama Masami , Wu Adam , Peeters Johannes , Shiina Isao , Kodaira Kazuo , Hamatani Yutaka , Ogawa Takumi , Kato Mana , Morita Yasuyuki , Sakai Shuji
Published: November 2024

Motivation: The purpose of this study was to evaluate the robustness of IVIM mapping using aMoCo-EPICS-AI-DWI-FEIR. Goal(s): Determine how to achieve better image quality, robustness to motion, and quantitative accuracy in myocardial IVIM-DWI. Approach: MoCo-TSE-DWI and aMoCo-EPICS-AI-DWI on a 3.0T MR clinical imager for image comparison. Results: aMoCo-EPICS-AI-DWI-FEIR demonstrated reduced individual and site-specific differences in the parameters obtained from IVIM-DWI imaging, compared with MoCo-TSE-DWI-FEIR. Impact: aMoCo-EPICS-AI-DWI-FEIR might be the best method for myocardial IVIM-DWI with better image quality, motion robustness and improved quantitative accuracy.
Diffusion metrics correlate with the relaxometric constant Dr of the χ-separation model
Authors: Grosso Elena , Ricciardi Antonio , Yannakas Marios , Prados Ferran , Kanber Baris , Grussu Francesco , Battiston Marco , Samson Rebecca , D'Angelo Egidio , Tur Carmen , Palesi Fulvia , Wheeler-Kingshott Claudia Gandini
Published: November 2024

Motivation: χ-separation method relies on assuming a certain relaxometric constant (Dr) calculated as the mean of a group of healthy subjects. Recently, we demonstrated that it is subject-specific. Goal(s): The goal of this study was to evaluate the correlation between Dr and microstructural metrics obtained from diffusion tensor and diffusion kurtosis imaging (DTI and DKI). Approach: We regressed between Dr against DTI and DKI diffusion metrics in a cohort of healthy controls. Results: Results showed a positive correlation with fractional anisotropy and axial diffusivity, and a negative correlation with mean and radial kurtosis. Impact: Understanding how the relaxometric constant of the χ-separation method (Dr) depends on microstructural diffusion metrics will define its personalization. This, in turn, will impact on how we assess the presence of different magnetic susceptibility sources in the brain.
LoopNet: A New Baseline Network for QSM Dipole Inversion
Authors: Chen Chen , Gao Yang , Li Min , Xiong Zhuang , Liu Feng , Sun Hongfu
Published: November 2024

Motivation: Most current deep learning (DL) QSM methods were developed based on U-net, whose performances might not be sufficiently good. Goal(s): To proposed a new network baseline for deep learning QSM methods development. Approach: We developed a LoopNet, by applying the proposed bidirectional loop and a self-tailored GHPA attention module into a Unet backbone, making better use of the latent information in deep networks. Results: Simulated and in vivo experiments showed that the propoed LoopNet led to improved results than U-net. Impact: This work introduces a novel deep neural network backbone, allowing researchers to develop innovative QSM methods easily by upgrading their original U-net to LoopNet, thanks to the plug-and-play design.
Altered Interactive Dynamics of Neurofluids in Cerebral Small Vessel Disease
Authors: Liu Chengxia , Li Yuanhao , Zhu Wenhao , Yang Shiqi , Qin Yuanyuan , Tian Tian , Zhang Jiaxuan , Zhang Shun , Zhu Wenzhen
Published: November 2024

Motivation: While changes of neurofluid dynamic has been observed in CSVD, the potential inter-correlations between them are still unclear. Goal(s): Our goal was to demonstrate the potential interactive dynamics of neurofluids including the parenchyma perfusion, the glymphatic pathway, and the intracranial CSF in CSVD patients. Approach: Parenchyma perfusion was assessed with pASL, glymphatic dynamics was assessed with DTI- ALPS, and CSF volume of ventricles was also quantified. Results: The interactive dynamics of neurofluids of CSVD patients is significantly altered compared with that of normal elderly. Impact: Disruption of neurofluid dynamics may play an important role in the pathophysiology of CSVD.
Diffusion tensor imaging analysis along the perivascular space revealed the dysfunction of glymphatic system in narcolepsy type1 patients
Authors: Hu Pengxin , Zou Yu , Dai Jiankun , Xiong Ruifang , Zhu Hanting , Li Chengyi , Tang Xiao Ping
Published: November 2024

Motivation: The glymphatic system plays an important role in sleep. However, it’s unknown if the glymphatic system was impaired in narcolepsy type1 (NT1) patients. Goal(s): Investigate if the glymphatic system was impaired and the correlation between dysfunction of glymphatic system and clinical symptom. Approach: 31 NT1 and 23 healthy controls (HC) were enrolled. DTI-ALPS was used to assess the function of glymphatic system and compared between NT1 and HC. The correlation between DTI-ALPS index and clinical symptom was analyzed. Results: The DTI-ALPS index was significantly lower in NT1 than in HC and was significantly correlated with the percentage of N3 stage sleep in NT1. Impact: We firstly reported the dysfunction of glymphatic system in narcolepsy type1 patients and its correlation with clinical symptom. Our study suggested the glymphatic system should be taken into consideration for the treatment of narcolepsy type1 patients.
Gibbs Ringing Correction for non-Cartesian Acquisitions
Authors: Wong Jeffery , Coelho Santiago , Lee Hong-Hsi , Chen Jingjia , Feng Li , Fieremans Els , Novikov Dmitry
Published: November 2024

Motivation: Truncation in k-space leads to Gibbs ringing. Removal of Gibbs artifact for non-Cartesian isotropic sampling remains unaddressed. Goal(s): To develop Gibbs ringing correction method for non-Cartesian isotropic k-space readouts. Approach: We generalize the subvoxel-shift Gibbs ringing correction to isotropic sampling schemes. Results: The developed correction removes Gibbs ringing for isotropic sampling schemes. Impact: Gibbs ringing leads to artifacts and biases in parametric maps, especially in diffusion MRI. We generalize the subvoxel-shift Gibbs ringing correction, previously developed for cartesian EPI acquisitions, to non-Cartesian sampling. The method will increase the reproducibility of MRI processing pipelines.
Deep learning based assessment of diagnostic image quality from Free Induction Decay Navigators
Authors: Vasylechko Serge , Wallace Tess , Kober Tobias , Jaimes Camilo , Rispoli Joanne , Warfield Simon , Kurugol Sila , Afacan Onur
Published: November 2024

Motivation: Motion-induced artifacts in pediatric MRI lead to frequent need for rescan, which increases examination time, costs and patient's discomfort. Goal(s): To develop and validate a deep learning-based method for automated assessment of diagnostic image quality, overcoming limitations of existing motion measurement techniques. Approach: FID navigators embedded into MPRAGE sequence can provide valuable motion information without prolonging scan time. We train a deep neural network on these signals to accurately predict the diagnostic quality of the image that is to be reconstructed. Results: Our method surpasses the existing FIDnavΔ approach, achieving AUC of 0.90, with 30% higher specificity and 21% improved precision. Impact: Our model streamlines MRI procedures by accurately predicting the need for rescans due to patient motion. It has potential to reduce healthcare costs and patient discomfort, and opens new avenues for early scan termination and enhanced clinical workflow efficiency.
Real-Time Respiration Feedback System to Correct Respiration Induced Fluctuation of B0 Field
Authors: Jung Kwan-Jin , Larsen Ryan , Shi Yaokun , Sadaghiani Sepideh
Published: November 2024

Motivation: To implement the respiration-feedback system using the respiration monitor signal available at the MRI console and a solenoid shim coil that has been developed for direct neuronal current mapping. Goal(s): To compensate for the respiration induced B0 fluctuation in a real-time mode. Approach: The respiration signal was extracted from the MRI console display using a USB screen capture in real-time. The extracted respiration signal was adjusted and driven to the solenoid shim coil using a custom-built amplifier. Its function was checked by monitoring a resonance frequency at a MRS voxel. Results: The B0 fluctuation was compensated by the captured respiration signal in real-time. Impact: The respiration signal which is available at any MRI console can be used for real-time feedback with a USB capturing device to compensate for the respiration induced B0 fluctuation. This will make the respiration feedback system more easily implementable.
T2* Relaxation Time Measurements of Various Brain Regions at 0.5 T
Authors: Halder Arjama , Harris Chad , Wiens Curtis , Soddu Andrea , Chronik Blaine
Published: November 2024

Motivation: Accurate knowledge of T2* relaxation times is important for optimizing contrast and SNR in multi-echo gradient echo sequences. Goal(s): To measure the nominal T2* relaxation parameter at 0.5 T over subregions in the brain. Approach: A 2 mm isotropic 3D multi-echo GRE sequence was acquired in 5 healthy volunteers. T2* estimates were computed over regions of interest using a mono-exponential fit. Results: T2* estimates of gray (86±8 ms) and white (78±5 ms) matter are in good agreement with previously published measurements in the mid-field. In the deep brain, average T2* values ranged between 70±2 ms to 89±5 ms. Impact: For optimal T2* contrast in the brain at 0.5 T, echoes from multi-echo acquisitions should extend beyond 60 ms. For optimal SNR, echoes should be combined with a target T2* of ~80 ms.
Lactate Spectroscopic Imaging on a portable 46 mT Halbach MRI scanner
Authors: Najac Chloe , Webb Andrew , Ronen Itamar
Published: November 2024

Motivation: Magnetic resonance spectroscopy at ultralow-field (B0 < 0.1T) on portable MRI scanner is challenging due to the low signal-to-noise ratio (SNR) and the impossible spectral separability. Goal(s): To obtain spectroscopic images of lactate at different concentrations in a phantom on our 46mT Halbach point-of-care MRI scanner and maximize SNR with incorporation of composite refocusing pulses. Approach: We modified a non-localized Carr-Purcell-Meiboom-Gill (CPMG) echo train sequence to perform 2D J-spectroscopic imaging in lactate phantom with composite refocusing pulses for improved SNR. Results: We showed the first steps towards lactate spectroscopic imaging at ultralow-field. Impact: The implementation of lactate spectroscopic imaging could add value to the growing list of biomedical applications of low field MR systems, for example in neonatal hypoxic ischemic encephalopathy.
Methods for portable magnetic resonance elastometry
Authors: Selby William , Garland Phil , Mastikhin Igor
Published: November 2024

Motivation: Magnetic resonance elastography can provided quantitative assessment of tissue mechanical properties, but requires large, expensive, in demand clinical MRI scanners, this motivates a more accessible portable MR technique. Goal(s): To develop robust experimental protocols for bulk assessment of tissue mechanical properties using portable magnetic resonance and explore clinical applications. Approach: Effects of phase interference on the MR signal magnitude and phase are investigated to characterize the shear wave velocity for samples with differing mechanical properties under harmonic and transient excitation. Results: Preliminary measurements show that a portable MR instrument can be used to quantify the shear wave velocity in homogeneous samples. Impact: These results show the potential of a portable magnetic resonance instrument for quantification of shear mechanical properties in biological tissues. This merits further investigation of applications to the diagnosis of specific diseases which could potentially improve patient outcomes.
Improved MRI Guided Interventions at 0.55T: Real-time Interactive Imaging with Deep Learning Reconstruction
Authors: Su Pan , Maier Florian , Cui Sophia , Nickel Marcel Dominik , Bhat Himanshu , Pang Jianing
Published: November 2024

Motivation: Contemporary low-field MRI systems hold great promise for guiding interventions. However, due to inherently reduced polarization at lower field, it is more challenging to achieve high-spatiotemporal-resolution with sufficient SNR in interactive real-time imaging. Goal(s): To improve real-time interactive imaging for MRI guided interventions at 0.55T by leveraging deep learning image reconstruction. Approach: We implemented deep learning image reconstruction for interactive real-time imaging, and compared its performance with conventional parallel imaging reconstruction and compressed-sensing on a biopsy phantom and a healthy volunteer. Results: Deep learning image reconstruction allows for accelerated interactive real-time imaging, achieving image quality that compared favorably with conventional reconstructions and compressed-sensing. Impact: The proposed method has the potential to further empower 0.55T MRI as a viable interventional guidance platform by leveraging deep learning image reconstruction in accelerated interactive real-time imaging.
Up to 24-channel receiver coil arrays for concurrent TMS-MRI imaging at 3T
Authors: Lee Hsin-Ju , Lin Fa-Hsuan
Published: November 2024

Motivation: Concurrent TMS-fMRI lacks whole-brain coverage or has low SNR. Goal(s): Develop setups allowing for whole-brain TMS-fMRI with high spatiotemporal resolution and minimizing the interference between MRI and TMS during data collection and neuromodulation. Approach: Combinations of 8- and 16-channel arrays enabled whole-brain TMS-MRI with 16 or 24 channels. Results: Structural and functional images of high spatiotemporal resolution (1.5 mm with 2 s/volume or 5 mm with 0.1 s/volume) were demonstrated with an MRI-compatible TMS coil. Impact: We developed concurrent TMS-MRI setups with whole-brain coverage and high spatiotemporal resolution using combinations of 8- and 16-channel coil arrays. Images of high spatiotemporal resolution were demonstrated.
3D Magnetic Resonance Fingerprinting for Rapid Simultaneous Bilateral T1, T2 and T1ρ Relaxation Mapping of the Hip Joint
Authors: Monga Anmol , Moura Hector , Kijowski Richard , Regatte Ravinder
Published: November 2024

Motivation: MR Fingerprinting (MRF) can accelerate simultaneous acquisition of multiple quantitative parametric maps with respect to conventional qMRI approaches. Goal(s): To demonstrate the feasibility of 3D bilateral hip MRF to map T1 , T2 and T1ρ in the hip Joint. Approach: 3D MRF maps of bilateral hip were acquired for 6 healthy subjects. Parametric maps estimated are compared against parametric maps estimated from VIBE variable flip angle and Turbo-Flash sequences. Results: Parametric maps obtained from 3D MRF are highly correlated (R-square > 0.89) with parametric maps from reference MRI ; 6.3% - 7.4% variance in 3D MRF parametric maps in repeatability test. Impact: 3D MR Fingerprinting (MRF) can accelerate the acquisition of parametric maps in the hip joint without considerably effecting the accuracy of the parametric maps.
Triexponential multi-b-value diffusion-weighted imaging metrics may detect WHO grade and key molecular markers in glioma patients
Authors: Zhu Zhengyang , Zhou Jianan , Lin Zengping , Yuan Jianmin , Yang Huiquan , Tian Chuanshuai , Zhang Xin , Zhang Bing
Published: November 2024

Motivation: WHO grade, Ki67 and IDH mutation are important for management and prognosis evaluation in glioma patients. Goal(s): To investigate the value of Tri-exponential model (TEM) in preidcting WHO grade, Ki67 and IDH mutation of gliomasApproach: 12 b-value DWI were obtained from glioma patients, TEM, SEM and IVIM model were analyzed for each patient. Univariate and Multivariate Logistic Regression were utilized to construct prediction model. Results: TEM model achieved highest AUC on WHO Grade prediction task, while IVIM performed better on Ki67 and IDH mutation prediction task. Impact: This study illustrated the potential of applying TEM model on predicting WHO grade Ki67 and IDH mutation in adult diffuse gliomas.
Diagnostic value of combining radiomics and clinical features in placenta accreta spectrum
Authors: Yang Chongze , Qin Lan-hui , Wei Qiu-ying , Deng Kan , Liao Jin-yuan
Published: November 2024

Motivation: Placenta accrete spectrum disorder (PAS) is a dangerous pregnancy complication that posed a threat to the safety of pregnant women, and its incidence is still on the rise. Goal(s): To develop a machine learning model for effective diagnosis of PAS. Approach: We developed machine learning models based on T2WI radiomics, clinical features, and clinical-radiomics features in the diagnosis of PAS. Results: Radiomics models have a great diagnostic performance for PAS, with sagittal-based model shows better performance. The clinical-radiomics model exhibits the highest diagnostic performance in this study. Impact: Machine learning models that combined with radiomics and clinical features can improve the diagnosis of PAS, and benefit PAS patients. Furthermore, our results provide new insights for future research.
Radiomics based on tumor and multiple body components on MRI to predict outcome in rectal Cancer
Authors: Yu Fu , Jiayi Gao , Mingyang Li , Huimao Zhang
Published: November 2024

Motivation: In rectal cancer, the existing stratification of prognosis is mainly based on the established TNM tumor staging system, which limits clinical decision-making. Goal(s): Construct a model to provides prognostic information preoperatively. Approach: This study established radiomics models to predict the disease-free survival (DFS) in rectal cancer, based on tumor, and multiple body components (including mesenteric fat and pelvic skeletal muscles) in MRI. Results: The radiomics model based on tumor and multiple body components of MRI in rectal cancer, have good predictive value for DFS in rectal cancer patients at 2 years after surgery. Impact: The model that provides prognostic information at the time of cancer diagnosis would be useful for optimizing treatment and monitoring.
Accelerating renal ASL MRI with 3D Cartesian TSE using deep learning-based Compressed SENSE.
Authors: Wang Yiming , Zhang Yajing , Zhang Zhongping , Su Wengu , Ren Zhongchang , Zhao Yan
Published: November 2024

Motivation: Motion and breathing can compromise 3D renal ASL MRI, reducing SNR and causing artifacts. Shorter-time acquisition is crucial for its clinical utilityGoal(s): To Evaluate the potential of CS-AI in accelerating renal ASL MRI with 3D Cartesian TSE. Approach: We accelerated renal ASL MRI 2-, 4-, and 6 times using CS-AI, comparing with SENSE. Results: CS-AI-accelerated images exhibited superior SNR and quality compared to SENSE, without affecting RBF quantification. Impact: This study may enhance the clinical utility of 3D renal ASL, particularly in discerning perfusion alterations in small-sized lesions like small renal masses.