bluuebunny/crossref_metadata_2025 huggingface dataset:
Feasibility of Accelerated T2 Mapping for the Quantitative and Qualitative Assessment of Endometrial Carcinoma
Authors: Zhang Zanxia , Li Shujian
Published: August 2024

The objectives of this study were to investigate the feasibility of accelerated T2 mapping in the clinical diagnosis of the pathologic subtypes and histologic grades of endometrial carcinoma (EMC), and to compare synthetic T2-weighted and diffusion-weighted (sT2W/DW) images to conventional T2W and diffusion-weighted (cT2W/DW) images for the myometrial invasion depth. 56 EMC patients underwent T2mapping and DW. Distinct T2 values were obtained for the various pathologic and histologic grades of EMC. Furthermore, pathologic EA grading was more accurate with the T2 values than ADC values. Additionally, in terms of detecting deep myometrial invasion, sT2W/DW showed similar accuracy to cT2W/DW.
Diagnostic Value of Ultrafast Dynamic Contrast-Enhanced MRI in Assessing the Status of Axillary Lymph Node Metastasis in Breast cancer
Authors: He Lincheng , Yan Ping , Liu Wenhong , Song Weijia , Zhang Huiting , Grimm Robert , Zhou Hong , Luo Guanghua
Published: August 2024

This study investigated the feasibility of ultra-fast DCE-MRI in accurately assessing axillary lymph node (ALN) metastasis in breast cancer. Our results showed that maximum slope (MS) accurately estimated the axillary lymph node status using the early-stage data of ultra-fast DCE-MRI. Furthermore, larger size (≥10mm diameter) of ALN and absence of hilum in the ultrafast DCE-MRI was associated with ALN metastasis in breast cancer patients. Our study demonstrated that MS from ultrafast breast MRI is a potential imaging biomarker of ALN metastasis in breast cancer.
MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: Correlation with subtypes and pathological response
Authors: Wang Mengfan , Du Siyao , Xie Lizhi , Zhao Min , Zhang Lina
Published: August 2024

We analyzed the correlation between MRI-based tumor shrinkage patterns after the early stage (first and second cycles) of NAC and pathological response in different subtypes. Fragmentation and diffuse decrease are collectively referred to as non-CS. We found that non-CS could be observed in some patients after the early stage of NAC, and non-CS and pCR were significantly correlated in HR+/HER2 subtypes after the first cycle of NAC.
Early parenchymal changes on MRI and fluoroestradiol db-PET during neoadjuvant endocrine therapy in patients with ER +/HER2- breast cancer
Authors: Carmona Julia , Onishi Natsuko , Liang Jiachao , Gibbs Jessica , Jones Ella , Bareng Teffany , Li Wen , Newitt David , Ray Kim , Lawhn Courtney , Joe Bonnie , Mukhtar Rita ,   I-SPY 2 Investigator Network,   I-SPY 2 Imaging Working Group, Esserman Laura , Chien Jo , Hylton Nola
Published: August 2024

The aim of our study was to assess early parenchymal changes during neoadjuvant endocrine therapy (NET) using both DCE-MRI and dedicated breast PET with [18F]-fluoroestradiol (FES-dbPET). We investigated background parenchymal enhancement (BPE) on MRI and background parenchymal uptake on FES-dbPET for seventeen patients with ER+/HER2- breast cancers. Statistically significant decrease in BPE was shown after 3 weeks of NET. Estimated SUVs (mean, max and peak) were lower after 3 weeks of NET, although the difference did not reach statistical significance. Our results illustrate the potential of DCE-MRI and FES-dbPET to detect early change in breast parenchyma during NET.
Improved Assessment of Brain Tissue Viability in Acute Stroke Using Fast High-Resolution 3D-MRSI and Quantitative T2 Imaging
Authors: Meng Ziyu , Wang Tianyao , Bo Bin , Zhao Yibo , Li Yudu , Guo Rong , Jin Wen , Yu Xin , Liang Zhi-Pei , Li Yao
Published: August 2024

Accurate assessment of tissue viability is of great importance for the design of therapeutic interventions in acute stroke. 1H-MRSI and quantitative T2 imaging can provide neurochemical biomarkers sensitive to the pathological changes in stroke but their applications have been limited by long scan times. This study introduces a novel approach that combines fast high-resolution 3D-MRSI with quantitative T2 imaging to assess the viability of ischemic tissues in acute stroke. This approach achieved improved discrimination between ischemic brain tissues that ultimately infarcted and those recovered using joint neurometabolite concentrations and quantitative T2 values, in comparison with classical DWI and PWI methods.
4D CSF flowmetry to map brain-wide slow CSF flow dynamics and patterns in subarachnoid space
Authors: Dong Zijing , Wang Fuyixue , Strom Amelia , Eckstein Korbinian , Bachrata Beata , Robinson Simon , Rosen Bruce , Wald Lawrence , Lewis Laura , Polimeni Jonathan
Published: August 2024

Cerebrospinal fluid (CSF) flow is a key component of the brain’s waste clearance system. However, little is known about the brain-wide CSF flow in subarachnoid space (SAS), due to the low sensitivity of MRI-based flow imaging methods for measuring slow flow. Here, we proposed a phase-contrast 4D CSF flowmetry method using a pulsed-gradient-spin-echo EPI sequence, providing high sensitivity and efficiency to measure brain-wide slow CSF flow dynamics in SAS. Whole-brain CSF flow dynamics including velocity and direction changes were measured and our preliminary data suggest that both cardiac pulsation and respiration can drive CSF flow in both ventricles and SAS.
Altered neurovascular coupling in patients with MELAS evaluated by combining cerebral blood flow and regional homogeneity
Authors: Wang Rong , Li Yuxin , Lin Jie , Zhang Yong , Dai Jiankun
Published: August 2024

This is the first study that used a combined arterial spin labeling (ASL) and resting-state fMRI approach to assess the neurovascular coupling in patients with mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes (MELAS), which may provide a new mechanistic perspective into understanding numerous brain diseases.
Evaluation of whole-brain oxygen metabolism in Alzheimer's disease using QSM and quantitative BOLD
Authors: Yang Aocai , Zhuang Hangwei , Ma Guolin , Wang Yi
Published: August 2024

We assessed the whole-brain oxygen metabolism perturbations in AD using QSM and quantitative BOLD. mGRE data and QQ model was employed to calculate OEF and ASL data was used to reconstruct CBF map. The CMRO2 can be estimated from CBF and OEF based on Fick’s principle. Our results demonstrated a characteristic whole-brain hypoperfusion and hypometabolism pattern in AD, predominantly located within default-mode network. Additionally, decreased CBF and CMRO2 in substructures of bilateral hippocampus strongly correlated with global cognition. QQ model-based noninvasively quantitative measurements have a great potential to be complementary biomarkers for evaluating cognitive impairment in AD.
Seasonal variations of functional connectivity of human brains
Authors: Xu Lyuan , Choi Soyoung , Zhao Yu , Li Muwei , Rogers Baxter , gore John , Gao Yurui , Ding Zhaohua
Published: August 2024

Seasonal variations have been observed in various aspects of human behavior. While studies have explored the seasonality effects in cognition and mood, possible underlying seasonal variations of human brain activity have not gained wide attention. Functional magnetic resonance imaging (fMRI) based on blood-oxygenation-level-dependent (BOLD) effects can detect and map functional activity and thus provides opportunities to characterize seasonal variations in brain functions. This work used fMRI data from the Human Connectome Project (HCP) to quantify seasonal patterns of brain connectivity. Knowledge of seasonality effects in brain activity offers the potential of advancing our understanding of seasonal variations in human behavior.
Functional Connectivity in Smokeless Tobacco Dependent Users in a Craving ‘Primed’ State
Authors: Polisetty Vasishta , Kumaran S Senthil , Bhat Priyanka , . Pankaj , Dhawan Anju , Jhanjhee Sonali
Published: August 2024

Tobacco is a leading cause of preventable cancer and death and is consumed in various forms. There is a paucity of literature regarding cue-induced craving in smokeless tobacco, commonly found in the South East Asian Region. This study aimed to investigate the functional connectivity in a ‘primed’ state after cue-induced craving. We found facilitatory connectivity within salience network (SN) and inhibitory connectivity between default mode network (DMN) and anterior cingulate cortex (ACC) in smokeless tobacco users.
Relating left hippocampal microstructure and delayed memory in cognitively intact adults at genetic-risk for developing Alzheimer's disease
Authors: VanGilder Jennapher Lingo , Baxter Leslie , Hooyman Andrew , Hu Leland , Zhou Yuxiang , Caselli Richard , Schilling Kurt , Beeman Scott
Published: August 2024

We have recently shown that the functional connectivity of the left hippocampus is significantly related to memory trajectory in cognitively intact ApoE4 carriers, independent of hippocampal volume. The purpose of this preliminary study was to determine if dendritic orientation dispersion of the left hippocampus explains variance in delayed verbal memory in this cohort. Results indicated that dendritic complexity of the left hippocampus was related to delayed memory in ApoE4 carriers. These findings suggest that ApoE4 carriers may experience subtle microstructural declines in the left hippocampus at the cognitively-intact stage.
APOE ε4 and Hypertension: Cardiovascular Risk Accelerate the Brain Structure Atrophy and Small Vessel Disease Pathologies in MCI and Dementia
Authors: Aman Aniket , Yadav Neha , Majumdar Arkaprava , Tiwari Vivek
Published: August 2024

Transformation of brain heath with aging comprehend a series of brain structure, vascular and functional changes over time. The key to understanding the brain health in normal and pathological aging is to identify the series of early, intermediate and late events that encodes for brain health. Here, we have investigated the temporal and spatial orders of brain volumetry, small vessel pathology (white matter hyperintensity) and its kinetics with normal aging and aging with cardiovascular risks and gene defects such as APOE ε4, across subjects classified as cognitively Normal (CN), Mild Cognitive Impairment (MCI) and Dementia (DM).
The association of amyloid PET, metabolic brain MRI, and age in Alzheimer's disease and normal controls: An OASIS-3 dataset analysis
Authors: Matsushita Shu , Tatekawa Hiroyuki , Miki Yukio
Published: August 2024

Revealing the association of amyloid PET and metabolic MRI measurements would be useful for future studies or clinical situations that evaluate Alzheimer's disease (AD). We investigated the relationship between imaging measurements and clinical information in 29 AD patients and age- and sex-matched normal controls (NCs) using OASIS-3 dataset. A significant positive correlation was found between brain temperature and index of diffusivity along the perivascular space (ALPS index) among all subjects and NCs, while a significant negative correlation was found between age and ALPS index among all subjects, AD patients, and NCs.
Within-network changes in strength of the default mode network are related to Alzheimer’s Disease biomarkers in APOE e4 carriers
Authors: Koenig Katherine , Durgerian Sally , Lowe Mark , DiFilippo Frank , Bekris Lynn , Leverenz James , Rao Stephen
Published: August 2024

The apolipoprotein E (APOE) ε4 genotype is a genetic risk factor for late onset Alzheimer’s Disease (AD). Consistent differences in network connectivity have been described in ε4 carriers (e4+). Here, we compare resting state connectivity in the default mode network between elderly, cognitively intact e4+ and non-carriers (e4-) and assess the relationship of connectivity to AD-related biomarkers. Regional changes in the e4+ group primarily consisted of weakened connectivity. Connectivity strength in the middle temporal gyrus was negatively related to amyloid PET centiloid score and p-tau in the e4+ group.
A Fully-Automatic Method to Segment Choroid Plexus in Multiple Sclerosis Using Conventional MRI Sequences
Authors: Storelli Loredana , Pagani Elisabetta , Rubin Martina , Margoni Monica , Rocca Maria Assunta , Filippi Massimo
Published: August 2024

Choroid plexus (CP) is a structure of the brain ventricular system that demonstrated an involvement in the inflammatory process of patients with multiple sclerosis (MS). However, its role in the pathophysiology of the disease needs to be further explored but its manual delineation on MRI is time-consuming. In this study, we developed a fully-automatic method to segment CP using 3DT1-weighted and FLAIR MRI sequences. The algorithm proved to be accurate, easy to implement and do not require an initial training phase on huge amount of data, being generalizable and a fast tool to potentially be included in a clinical setting.
Dexmedetomidine Administration in a Rat Model of Kaolin-induced Hydrocephalus
Authors: Karatas Meltem , Yahya Diaa , Ayan Merve , Muftuoglu Sevda , Oguz Kader Karli , Oge Halil
Published: August 2024

Hydrocephalus is defined as an abnormal enlargement of cerebral ventricles due to disturbed cerebrospinal fluid (CSF) dynamics. It is characterized by neuroinflammatory processes in the brain parenchyma and CSF, with pathological findings including reactive gliosis, axonal and neuronal damage, and loss of myelin sheaths. The use of anti-inflammatory medications in hydrocephalus may be an effective treatment strategy for neuroprotection. In this study, we used a rat model of hydrocephalus induced by kaolin. We aimed to demonstrate the potential anti-inflammatory and neuroprotective effects of dexmedetomidine on hydrocephalic brains using MRI and morphometric analysis.
Novel MRI techniques for the Assessment of Activated Innate Immunity in Progressive Multiple Sclerosis
Authors: Kim Seong-Eun , Francis Trieste , Wong Ka-Ho , Rose John , MacNally J Scott , Soldan M Mateo Paz
Published: August 2024

While the specific pathologic mechanisms that underpin ongoing axonal loss in progressive forms of MS are not fully characterized, ongoing innate immune activation in chronic MS lesions, particularly activated microglia and macrophages, has been proposed to be a prevailing mechanism of axonal loss in the progressive phase of disease. Ultrasmall superparamagnetic iron oxide particles have been introduced as a potential MRI biomarker for macrophage activity in focal MS lesions. This work presents a Feromoxytol enhanced MRI to measure perilesional activated microglia and macrophages in progressive MS. which is anticipated to reflect risk for ongoing loss of CNS axons and neurons.
Whole Brain MRI Reveals that Children with Acute Disseminated Encephalomyelitis have Enlarged Brain Ventricles at Disease Onset
Authors: Millward Jason , Pilgrim Elias , Baumann Matthias , Wendel Eva , El-Naggar Ines , Bertolini Annikki , Bartels Frederik , Finke Carsten , Niendorf Thoralf , Rostásy Kevin , Waiczies Sonia
Published: August 2024

Pediatric patients with acute disseminated encephalomyelitis (ADEM) are at risk of long-term neurocognitive consequences. We investigated a multi-center cohort of ADEM patients with serial whole brain MRI, to distinguish transient reversible expansion of brain ventricle volume (BVV) from persistent changes. Using the automated brain segmentation tool SynthSeg, we observed that ADEM patients had significantly enlarged BVV relative to sex- and age-matched pediatric control subjects, already at the first clinical presentation, before any steroid treatment. Most ADEM patients developed even greater BVV expansion over the observation period. The majority of patients recovered, though some showed persistent BVV enlargement, suggesting brain atrophy.
Visualization of Deep Brain Stimulation Targets at 0.5T
Authors: Harris Chad , Curtis Andrew , Wiens Curtis , Germann Jurgen , Boutet Alexandre , Lozano Andres , Stainsby Jeff
Published: August 2024

The utility of visualizing deep brain stimulation targets at 0.5T was explored. 3D SWI images show direct visualization of the subthalamic nuclei and surrounding iron-rich structures. With the excellent gray-white matter contrast possible at mid-field, 3D T1-weighted imaging can directly visualize the globus pallidus interna. The elevated T1 contrast produces excellent 3D T1-weighted imaging at multiple inversion times which are suitable for, and aid in, atlas-based segmentation approaches for DBS targeting.
A Multimodal Atlas of the Human Cerebellum at 760 μm Resolution
Authors: Lyu Wenjiao , Wu Ye , Huynh Khoi , Ahmad Sahar , Yap Pew-Thian
Published: August 2024

The human cerebellum is engaged in a broad array of tasks related to motor coordination, cognition, and emotional regulation. Here, we construct a cerebellar atlas using high-resolution multimodal MRI, capturing multiple characteristics of the cerebellum, including cortical morphology, tissue microstructure, and cerebellar/cerebello-cerebral connectivity. Our atlas facilitates the understanding of the neurodevelopment and neurodegeneration of the cerebellum.
Maternal neural and behavioral sensitivity to baby emotional sounds
Authors: Lin Jiayu , Su Wei , Du Xiaoyu , Sun Zhenhua , Zhang Xiang , Zhang Kaihua , Du Xiaoxia
Published: August 2024

After giving birth, women will experience a series of physiological and psychological changes. Exploring the changes in postpartum women's neurological function contributes to comprehending their cognitive and emotional processing mechanisms. Therefore, we recruited 43 new mothers and 26 nulliparous women to participate in the current fMRI study based on the baby sounds’ task. Results suggested that the brain function of new mothers showed dynamic plasticity in the temporal lobe. This study reflected the adaptive changes in new mothers' brain function toward nurturing the babies.
Realistic Abdominal QSM phantom
Authors: Silva Javier , Lambert Mathias , Milovic Carlos , Uribe Sergio , Tejos Cristian
Published: August 2024

Abdominal Quantitative Susceptibility Mapping (QSM) involves a series of additional challenges compared with brain QSM, mainly because of the presence of undesired contributions related to fat and gasses. Previously, we proposed a QSM phantom with fat contributions, which emulated different susceptibility scenarios in the abdominal region. In this work, we present an improved version which now considers additional features including a variable multi-peak fat model, variable R2* and background field features. Simulation experiments show how these new components produce of different effects, like increased signal decay in specific tissues, 1st and 2nd kind chemical shift artifacts and water/fat swaps in graph cuts reconstructions.
A new cascaded fully convolutional neural network for the simultaneous segmentation of parasagittal dural space and arachnoid granulations
Authors: Hett Kilian , McKnight Colin , Lindsey Jennifer , Leguizamon Melanie , Eisma Jarrod , Song Alexander , Elenberger Jason , Considine Ciaran , Claassen Daniel , Donahue Manus
Published: August 2024

The overarching goal of this work is to develop and validate novel deep learning algorithms for segmenting the peri-sinus space, including parasagittal dural (PSD) space, which has been hypothesized to harbor cerebral lymphatic channels, and intra-veinous arachnoid granulations, which has been long-hypothesized as a site a CSF egress, from standard non-contrast anatomical imaging. The new segmentation method is based on cascaded neural networks using non-contrasted 3D T2-weighted MRI; the method is method in a mixed cohort of adults with and without neurodegeneration.
Self-Calibrating Aliasing-Controlled Simultaneous Multi-Slice Reconstruction for Diffusion MRI
Authors: Lim Eun Ji , Maeng Hyunkyung , Park Jaeseok
Published: August 2024

To jointly resolve inter-slice leakages and in-plane aliasing for combined in-plane- and slice-accelerated diffusion MRI data, we proposed a novel, one-step solution for SMS-reconstruction optimally exploiting self-calibrating data from generalized 3D Fourier encoding perspective. To this end, we propose a generalized SMS forward signal model with an extended controlled aliasing and an extended self-calibration. Aliasing artifacts are jointly resolved in ky-and kz-directions by balancing null space consistency with a low rank prior while enforcing data fidelity in 3D k-space. We demonstrated the proposed method outperforms competing methods for diffusion MRI at SMS=3, R=2.
Orthogonal diffusion encoding gradient sequence (ODEG) improves time-dependency measurements in the human brain
Authors: Zhu Qinfeng , Li Haotian , Hsu Yi-Cheng , Sun Yi , Wu Dan
Published: August 2024

Oscillatory gradient dMRI is used to access restricted diffusion at short diffusion times (td). But its clinical application is limited due to the limited gradient strength, leading low b-value and low resolution, and thus is subject to contamination from microcirculation and CSF partial volume. Here we proposed an orthogonal diffusion encoding gradient (ODEG) sequence to improve td–dependency measurements in human brain, by applying a pulse gradient orthogonal to the oscillating gradient to suppress the fast diffusion from microcirculation and free water. The results showed that td-dependency was significantly improved by the ODEG sequence in the hippocampus and cortical gray matter.
Accelerating High Resolution Diffusion Tensor Imaging Using Intra- and Inter-image Correlation
Authors: Xu Zhongbiao , Zhang Rongli , Huang Wei , Cheng Junying , Mei Yingjie , Guo Yihao , Sun Hengwen , Wang Yaohui , Chen Zhifeng
Published: August 2024

DTI is challenged by the prolonged scan time in frontier studies and clinical applications. Parallel imaging can reduce the scan time, but with the SNR loss and the limitation of acceleration factor. In this work, we combined SENSE with self-supervised BM4D reconstruction model to improve image quality. The in vivo experiments demonstrated that the proposed method can obtain greatly improved image quality even with high acceleration factor of 5, compared to conventional methods.
Evaluation of the impact of protocol settings on the variability of model estimations in multicenter diffusion MRI studies
Authors: Tong Qiqi , Li Jinsong , Zhong Jianhui , He Hongjian
Published: August 2024

A multicenter diffusion magnetic resonance imaging (dMRI) study was designed with different b-table schemes, non-diffusion b0 number, and varied echo time (TE) in two 3T scanners of different vendors. Global sensitivity analysis of 6 traveling subjects was conducted to evaluate the impact of imaging protocol setting on the observed cross-scan variability of diffusion metrics.
High-resolution Diffusion Tensor Imaging with Deep Learning Reconstruction: Preliminary Results in Sub-cortical Fiber Tracking
Authors: Hu Zhangxuan , Wei Xiaocheng , Lu Jie , Wu Bing
Published: August 2024

Diffusion tensor imaging (DTI) is a well-established tool for providing insights into brain structural connectivity and detecting brain microstructure. High spatial resolution diffusion MRI can provide improved resolvability of fibers with high-curvature (u-fibers). Segmented k-space methods such as Multiplexed sensitivity-encoding (MUSE) are often used to achieve high resolution diffusion images, however the shortcomings, such as prolonged scan time and low signal-noise-ratio (SNR), still exist. In this study, we aim to further improve the image quality of high-resolution diffusion images acquired with MUSE by combing with a deep learning based reconstruction method and thus to improve the sub-cortical fiber tracking accuracy.
Super-resolution diffusion tensor imaging at 64 mT
Authors: Plumley Alix , Cercignani Mara , Planchuelo-Gómez Álvaro , Gholam James , Jones Derek
Published: August 2024

A super-resolution approach was used to create 2mm isotropic diffusion tensor images (DTI) from diffusion-weighted imaging data acquired on a low field, portable system. Mean diffusivity, fractional anisotropy and principal eigenvector orientation maps are shown. This work extends the very recently implemented capability of performing DTI on a 64mT system, and shows substantial improvement due to the increased through-plane resolution achieved with super-resolution.
Value of mDIXON-Quant mDixon-Quant sequence Imaging in Evaluation of Renal Function Damage in Patients with Liver Cirrhosis
Authors: Wang Yue , Ju Ye , Wang Nan , Liu Ailian
Published: August 2024

Patients with liver cirrhosis are easy to be complicated with renal function injury, and symptoms of early renal injury are hidden and often difficult to be detected in time, which may ultimately lead to poor prognosis. mDixon-Quant imaging, a novel fat quantitative MRI technique was used to evaluate the degree of renal function injury in patients with cirrhosis. Results showed that mDixon-Quant imaging can be an effective method for noninvasive diagnosis and early assessment of renal function injury in liver cirrhosis.
Morphological and Functional Evaluation of Diabetic Kidney Disease Cohorts by using T2-Weighted and Diffusion Weighted MRI
Authors: Zhao Kaixuan , Li Sheng , Wu Zhigang , Niendorf Thoralf , Wang Wenjian , Liu Zaiyi
Published: August 2024

Diabetic Kidney Disease (DKD) is the leading cause of end-stage renal disease worldwide. Morphological evaluation of renal compartment volume changes and functional evaluation of renal ADC changes provide comprehensive insight into DKD disease progression. This study compares renal compartment volume changes including: 1) parenchyma volume ,2) pelvis volume, 3) whole kidney volume and 4) parenchyma volume percentage and the functional parameter ADC for DKD groups with different CKD staging. Our results demonstrate that cortical/medullary ADC, parenchyma volume and whole kidney volume are correlated with eGFR and suggest that the cortical ADC is a stronger predictor of eGFR in DKD.
Diagnostic Performance and Interobserver Agreement of Clear Cell Likelihood Score Using T2-Weighted Imaging with Fat Suppression Technique
Authors: Hao Yu-Wei , Ye Hui-Yi , Wang Hai-Yi
Published: August 2024

Whether T2-weighted imaging with or without fat suppression technique affects the performance of Clear Cell Likelihood Score v2.0 (ccLS v2.0) for diagnosing ccRCC in SRMs is not known. The final results showed that the tumor signal intensity between T2-weighted imaging with and without fat suppression was statistically significant (P < 0.001), but diagnostic performance and interobserver agreement of ccLS v2.0 in the diagnosis of ccRCC based on the two imaging techniques was comparable (P>0.05). Fat-suppressed T2-weighted imaging is also applicable to ccLS v2.0. This finding is helpful to expand the clinical application scope of ccLS and increase its clinical universality.
Denoising Vastly Undersampled Radial Portal Venous 4D Flow Data via Deep Learning
Authors: Naren Tarun , Wieben Oliver , Oechtering Thekla , Reeder Scott , Johnson Kevin
Published: August 2024

Radially undersampled 4D flow MRI is a promising method for non-invasive mapping of blood flow in the portal venous system. However, collecting sufficient projections to produce clinically viable images can lead to long scan times (10+ minutes) as fewer projections cause undersampling artifacts that appear as structured noise. In this study, we propose a data-driven, deep learning method to denoise vastly undersampled (<10% of full Nyquist sampling) radial 4D flow MRI data in the portal vein. We train a network on a heterogeneous, time-averaged dataset with two levels of undersampling and perform a quantitative hemodynamic analysis to compare results.
Improving the segmentation over time of 4D flow MRI images, using a medical image registration neural network VoxelMorph
Authors: Ponce Aaron , Uribe Sergio , Sotelo Julio
Published: August 2024

The segmentation of large vessels in 4D Flow MRI remains a challenge, due to different problems such as random acquisition noise, low spatial and temporal resolution, velocity aliasing, respiratory motion, phase offsets. For that reason the use of a single segmentation has been standardized to represent the geometry throughout all the cardiac phases. However, recent studies have proposed the use of image registration to be able to solve this problem. In this work, an algorithm based on a medical image registration neural network is proposed to improve the segmentation over time for the cardiac phases of the systole period.
Utility of Noncontrast-enhanced Turbo-field Echo-planar Imaging-based 4D Flow MRI for Portal Venous System
Authors: Kinota Naoya , Abo Daisuke , Kato Daisuke , Tsuneta Satonori , Nishioka Noriko , Ishizaka Kinya , Fujima Noriyuki , Minowa Kazuyuki , Kudo Kohsuke
Published: August 2024

Echo-planer imaging-based three-dimensional cine phase contrast (4D flow) MRI has been reported to achieve good image quality with a short acquisition time in cardiovascular imaging, but its application to the portal venous (PV) system has not been reported. In this study, the turbo-field echo-planar imaging (TFEPI) 4D flow MRI with a turbo-field echo (TFE)-based one in the PV system was compared. The TFEPI sequence showed a better image quality and flow consistency at the splenic and superior mesenteric vein confluence with a shorter acquisition time compared to the conventional TFE-based one.
Characterizing across-trial variation in the hemodynamic responses using ultra-fast fMRI data at 7T
Authors: Bianchi Samuel , Heinzle Jakob , Engel Maria , Frässle Stefan , Stephan Klaas , Pruessmann Klaas
Published: August 2024

Characterizing hemodynamic responses with great temporal precision is crucial for the interpretation of fMRI data with respect to the underlying neuronal activity. Recent literature highlights that analyses based on a canonical hemodynamic response function (HRF) may fail to capture relevant aspects of neuronal activity in certain conditions1. Ultra-fast fMRI enables precise temporally precise characterizations of hemodynamic responses and their trial-by-trial variation. Here, we analyzed fMRI timeseries sampled at which allowed us to model hemodynamic responses for individual trials during a visuo-motor task. Trial-by-trial variability of hemodynamic responses are analyzed by principal components analysis (PCA) and related to trial-specific conditions.
Combining the benefits of 3D acquisitions and spiral readouts for VASO fMRI at UHF
Authors: Monreal-Madrigal Alejandro , Kurban Denizhan , Laraib Zoia , Huber Renzo , Ivanov Dimo , Boulant Nicolas , Poser Benedikt
Published: August 2024

VASO fMRI can provide beneficial localization specificity and quantifiability compared to the commonly used BOLD contrast. Previous work has also shown the benefits of using spiral readouts compared to Cartesian EPI. In this work, we employ 3D stack-of-spirals readouts and compare it with the current state of the art 3D EPI readouts for VASO fMRI. The sequence implementation is done using Pulseq, images were reconstructed with MRIReco.jl; functional analysis with an openly available pipeline. We find that a VASO tSNR improvement of a factor of 2 over EPI is achieved using the proposed spiral implementation.
Proprioceptive engagement in the human cerebellum using 7T-fMRI
Authors: Brouwer Emma , Hashimoto Julie , Priovoulos Nikos , van der Zwaag Wietske
Published: August 2024

The human cerebellum forms an important part of the sensory and motor networks. Specifically, cerebellar damage has been shown to result in difficulty to perform proprioceptive tasks. Hence, studying the functional cerebellar organisation can be of great neuroscientific and clinical interest. This requires high-resolution images due to the thin, highly-foliated cortex of the cerebellum. We investigated the difference between a simultaneous-unilateral-finger-flex (SUFF) and midline-contralateral-finger-touch (MCFT) using B1-shimmed fMRI at 7T. Movements with higher proprioceptive engagement (MCFT) resulted in stronger, more medially located activations on the cerebellar surface compared to movements which are less reliant on proprioception (SUFF).
High-Resolution J-Edited MRSI Using Multi-Slab Acquisition and Learned Subspaces
Authors: Guo Rong , Zhao Yibo , Li Yudu , Ma Chao , Jin Wen , Li Yao , Fakhri Georges , Sutton Brad , Liang Zhi-Pei
Published: August 2024

High-resolution mapping of GABA in the brain has long been desired by the neuroscience community. But it is still challenging due to several long-standing technical obstacles including low SNR, long scan time, and spectral overlapping. This work proposes an MRSI method integrating multi-slab EPSI acquisition, MEGA spectral editing, and subspace modeling to overcome these difficulties, successfully achieving 3D GABA and metabolite mapping (at 3.0×3.0×4.0 mm3 nominal resolution) in a 12-minute scan time.
Whole-Brain Multi-Parametric Molecular Imaging Using Accelerated J-Resolved Subspace 1H-MRSI
Authors: Wang Zepeng , Li Yahang , Lam Fan
Published: August 2024

J-resolved MRSI is a powerful molecular imaging tool for measuring brain metabolites, neurotransmitters and other important biophysical parameters. The inherent SNR challenge of MRSI and prolonged scan time for multi-TE data limit the imaging resolution. This work presents a brand-new capability of whole-brain multiparametric, quantitative MRSI, by integrating a fast-scanning J-resolved MRSI sequence with SNR-efficient multi-band excitation, task-specific experiment designs, subspace imaging and optimized parameter estimation. Experimental studies and initial validation were performed to demonstrate this capability for high-resolution metabolite, neurotransmitter and metabolite T2 mapping from a single scan.
Selective Extraction of J-coupled Signals Using MEGA-PRESS with Conditional Saturation Pulses
Authors: Takeshima Hidenori , Maruyama Shuki , Yui Masao
Published: August 2024

In this abstract, a spectral editing method using MEGA-PRESS with conditional frequency-selective saturation pulses is proposed. The proposed method used additional frequency-selective saturation blocks before the excitation block. The saturation pulses were activated only when the MEGA pulses were inactive. When saturation pulses were activated, the sequence acted as the conventional MEGA-PRESS whose editing pulses were inactive except that the passband of the saturation pulse was not excited. Spectrum reconstruction for the proposed method was same as that for the conventional MEGA-PRESS. Experimental results showed that the proposed method selectively extracted J-coupled signals with all frequencies.
Localized 31P Magnetic Resonance Spectroscopy of Normal Human Kidneys at 3T
Authors: Zhou Limin , Hulsey Keith , Udayakumar Durga , Wiethoff Andrea , Madhuranthakam Ananth
Published: August 2024

Phosphorous (31P) MR spectroscopy (MRS) can measure high energy phosphate metabolism non-invasively in vivo, which can provide metabolic insights into kidney pathophysiology. However, obtaining spectra from healthy volunteers for reference is challenging. In this study, we investigate the feasibility of localized 31P MRS in kidneys of healthy volunteers with a 3T clinical MR scanner. 31P spectra were successfully obtained in 10 healthy volunteers with metabolite ratio calculated to provide information about the energy metabolism.
Comparison of data-driven and physics-informed learning approaches for optimising multi-contrast MRI acquisition protocols
Authors: Planchuelo-Gómez Álvaro , Descoteaux Maxime , Aja-Fernández Santiago , Hutter Jana , Jones Derek , Tax Chantal
Published: August 2024

Multi-contrast MRI is used to assess the biological properties of tissues, but excessively long times are required to acquire high-quality datasets. To reduce acquisition time, physics-informed Machine Learning approaches were developed to select the optimal subset of measurements, decreasing the number of volumes by approximately 63%, and predict the MRI signal and quantitative maps. These selection methods were compared to a full data-driven and two manual strategies. Synthetic and real 5D-Diffusion-T1-T2* data from five healthy participants were used. Feature selection via a combination of Machine Learning and physics modelling provides accurate estimation of quantitative parameters and prediction of MRI signal.
Predicting Abdominal MRI Protocols using Electronic Health Records
Authors: Shokrollahi Peyman , Chaves Juan Zambrano , Sharma Avishkar , Lam Jonathan , Pal Debashish , Bahrami Naeim , Chaudhari Akshay , Loening Andreas
Published: August 2024

Inaccurate selection of MRI protocols can impede diagnostics and therapeutic workflows, delay appropriate treatment, increase misdiagnosis likelihoods, and increase healthcare costs. Here we depict a machine-learning (ML) based system to accurately predict abdominal MR protocols, trained on the electronic medical records from 11,251 MR exam orders on 6,882 patients. The best model achieved a cumulative F1-score of 95.6% for top-three most-often-ordered protocols and a top-one F1 score of 78.5%. The proposed system can guide radiologists to appropriate protocol selections quickly, optimize workflows, and improve diagnostic accuracy, thereby by serving to support optimal patient outcomes.
A Faithful Deep Sensitivity Estimation Makes High-quality MRI Reconstruction
Authors: Wang Zi , Fang Haoming , Qian Chen , Shi Boxuan , Bao Lijun , Zhu Liuhong , Zhou Jianjun , Wei Wenping , Lin Jianzhong , Guo Di , Qu Xiaobo
Published: August 2024

Recent deep learning is superior in providing high-quality images and ultra-fast reconstructions in accelerated magnetic resonance imaging (MRI). Faithful coil sensitivity estimation is vital for MRI reconstruction. In this work, we propose a Joint Deep Sensitivity estimation and Image reconstruction network (JDSI). During the image artifacts removal, it gradually provides more faithful sensitivity maps, leading to greatly improved image reconstructions. Results on in vivo datasets and radiologist reader study demonstrate that, the proposed JDSI achieves the state-of-the-art performance visually and quantitatively, especially when the accelerated factor is high. Besides, JDSI also owns nice robustness to abnormal subjects.
Super resolution imaging from low-field strength scanners using generative adversarial networks
Authors: Arnold Thomas , Okar Serhat , Tu Danni , Nair Govind , Pitts John , Poorman Megan , Kawatra Karan , Desiderio Lisa , Schindler Matthew , Litt Brian , Shinohara Russell , Reich Daniel , Stein Joel
Published: August 2024

High-field MRI provides superior imaging for diverse clinical applications, but cost and other factors limit availability in various healthcare and lower resource settings. Lower-field strength units promise to expand access but involve tradeoffs including reduced signal, longer scan times, and lower resolution. Here we develop super-resolution methods that can generate high-field quality images from low-field scanner inputs, thus increasing signal and resolution. We use generative adversarial networks to demonstrate image enhancement in T1, T2 and FLAIR sequences.
The role of training on the robustness of domain-transform manifold learning
Authors: Bhutto Danyal , Zhu Bo , Liu Jeremiah , Cauley Stephen , Koonjoo Neha , Rosen Bruce , Rosen Matthew
Published: August 2024

Domain-transform manifold learning is a trained reconstruction approach where care needs to be taken to appropriately represent the forward encoding model during training, including for example the numerical properties of the source sensor data, phase relationship of complex sensor data, and field-of-view to prevent artifacts arising in the reconstruction. Here, we study the role that the training corpus and the numeral properties of the training have on the performance of the reconstruction of MRI data and demonstrate reconstruction artifacts that result from inference on out-of-training-distribution data if the training data is not augmented sufficiently.
In-bore Preamplifier Nonlinearity Calibration
Authors: Vassos Chris , Pauly John , Robb Fraser , Vasanawala Shreyas , Scott Greig
Published: August 2024

Present MRI preamplifiers are very linear but use 10s of mA bias current and over 150mW power. For wireless arrays, low power alternatives based upon SiGe transistors are needed. These achieve the needed gain and noise figure, with order of magnitude power reduction, but at the cost of increased nonlinearity. Using pilot tone technology, we present a calibration system for preamplifier nonlinearity correction targeted to low power SiGe preamplifiers. This system integrated a phase-locked SDR into a form of prescan to demonstrate that in-bore preamplifier linearity calibration and correction are possible.
Development of 1H/23Na dual-tuned RF probe using inductive coupling for 9.4T vertical wide-bore superconducting MRI for rat’s kidney
Authors: Momiyama Naoto , Haishi Tomoyuki , Terada Yasuhiko
Published: August 2024

A superconducting magnet for vertical NMR, commonly used as a high-field magnet, is effective for the MRI of X nuclides with low detection sensitivity. Even in a narrow magnetic field space, an inductively coupled RF coil with a simple structure can be used to image small animals one size larger. In this study, to visualize 23Na distribution in the kidney region of anesthetized rats, we developed 1H/23Na dual-tuned RF coils using inductive coupling with a 9.4T wide bore magnet (room temperature bore diameter 89 mm) and performed in vivo imaging.
Stretchable Coil for Small Animal MRI
Authors: Ramesh Thejas Vishnu , Narongrit Folk , Rispoli Joseph
Published: August 2024

This work demonstrates a simple, easy to use, stretchable coil system for small animal MRI at 7T. Phantom images obtained using the stretchable coil were analysed for coil SNR. The SNR of the stretchable coil was compared with SNR of a standard commercial coil. Ex-vivo imaging of a mouse and rat brain was also performed. Current work involves minimizing SNR reduction due to coil stretch. Future work involves developing a 4-channel stretchable coil array for in-vivo imaging of a rat brain.
B1 improvement of a birdcage coil using a flexible metamaterials at 7 T
Authors: Solis-Najera Sergio , Lazovic Jelena , Ruiz Rodrigo , Vazquez Fabian , Rodriguez Alfredo
Published: August 2024

This work presents a flexible metasurface to improve the B1 and the image SNR of a transceiver quadrature birdcage coil for preclinical MRI applications at 7 T. The metasurface was not tuned so no passive components were used. The imaging phantom was entirely covered with the metasurface and produced an improvement of both B1 and the SNR. This easy-to-implement approach offers an alternative to improve the B1 field for preclinical applications at high field.
manganese-based nanosystem for dual-modality imaging guided STING pathway with immunotherapy against triple-negative breast cancer
Authors: Guan Xiuhong , Zhao Yue , Huang Xin , Wang Zhiyong , Yang Ruimeng
Published: August 2024

Due to the high incidence and mortality rate, breast cancer has become the major cause of cancer death among females. This study reports a kind of functional nanocomposite, which was designed to comprises Pluronic F127 to self-assembly manganese carbonyl (MnCO) and IR780 dyes into one system, exhibiting NIR-II and MR dual-modal imaging guided STING pathway and anti-tumor immunity against triple-negative breast cancer.
Dynamic MR Imaging-guided Photothermal Therapy of Solid Tumor and Monitoring of Vascular Invasion
Authors: Zhang Rong , Hua Zhang
Published: August 2024

Timely evaluating the abundance of vessels and infiltration by noninvasive ways together with synchronous photothermal therapy (PTT) still faces great challenges. A multifunctional and biocompatible nanoprobes (NaBiF4: Gd@PDA@PEG) with high longitudinal relaxation rate and photothermal conversion efficiency was designed as promising photosensitizer for tumor PTT and contrast agent for MR imaging. The anatomic decrease and thinning of tumor blood vessels could be observed in real-time using noninvasive MR angiography ( TRICKS and DSC-PWI) during PTT. We demonstrated that the vascular invasion status of tumor during PTT can be monitored by utilizing our multifunctional nanoprobes, which provide possibility for clinical transformation.
Extraction of the Utero-Placental and Fetal Vasculature using 2D Time-of-Flight Imaging
Authors: Subramanian Karthikeyan , Jella Pavan , Qu Feifei , Chaiworapongsa Tinnakorn , Haacke Mark
Published: August 2024

Mapping the vasculature, flow and tissue properties of the placenta and umbilical cord can serve as a means to study placental and fetal health. The goal of this work is to use a rapid, multi-echo, interleaved GRE sequence to minimize motion artifacts and cover the entire abdomen of the mother in a few minutes. To better map out the vasculature, we propose to both separate the arteries and veins in the umbilical cord using an R2* mapping thresholding technique and use vessel tracking to create 3D renderings. We have successfully done this in a series of 10 fetuses.
Enhancing Vessel Continuity in Deep Learning based Segmentation using Maximum Intensity Projection as Loss
Authors: Chatterjee Soumick , Chintalapati Karthikesh , Radhakrishna Chethan , Kumar Sri Chandana Ram , Sutrave Raviteja , Mattern Hendrik , Speck Oliver , Nürnberger Andreas
Published: August 2024

Vessel Segmentation with deep learning is a challenging task that involves not only learning high-level feature representations but also the spatial continuity of the features across dimensions. Semi-supervised patch-based approaches have been effective in identifying small vessels of 1-2 voxels in diameter but failed to maintain vessel continuity. This study focuses on improving the segmentation quality by considering the spatial correlation of the features using the maximum intensity projection (MIP) as an additional loss criterion. It was observed that the proposed method quantitatively improves the segmentation while also improving vessel continuity, as evident in the visual examinations of ROIs.
tDKI-Net: a joint q-t space learning network for diffusion-time-dependent kurtosis imaging and Karger’s model fitting
Authors: Zheng Tianshu , Ba Ruicheng , Wang Xiaoli , Wang Xizhen , Ye Chuyang , Wu Dan
Published: August 2024

Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for non-invasive characterization of tissue microstructure. The TDDMRI models require both densely sampled q-space (b-value and diffusion direction) and t-space (diffusion time) data for microstructural fitting, leading to very time-consuming acquisition protocols. In this work, we presented a tDKI-Net to estimate diffusion kurtosis at multiple diffusion times, which was fed into the Karger model to obtain K0 and transmembrane exchange time, using downsampled q-space and t-space data. We tested the proposed network in the normal rat brains, as well as those in a rat model of Middle Cerebral Artery Occlusion.
Hybrid-space reconstruction for simultaneous multi-slab DWI with blipped-CAIPI
Authors: Zhang Jieying , Liu Simin , Guo Hua
Published: August 2024

3D simultaneous multi-slab imaging (SMSlab) can achieve high-resolution DWI with high SNR efficiency. Multi-band acceleration can also achieve less SNR reduction. Recently, we integrated SMSlab DWI with blipped-CAIPI gradients to reduce the g-factor penalty and proposed a 4D k-space framework (kx-ky-kz-km) to model the signal encoding, with km representing the multi-band encoding. Because the blipped-CAIPI gradients are applied along the slice direction, they introduce kz deviations from the nominal k-space location. This study proposed a hybrid-space reconstruction algorithm, REACH, to solve the phase interferences introduced by the blipped-CAIPI gradients.