bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Diffusion MRI to Characterize Connectome Changes Associated with EED Ablation
Authors: Alkhalily Majd , Currey Laura , Piper Michael , Kurniawan Nyoman
Published: August 2024

Mutation in embryonic ectoderm development (EED) gene in mice have been shown to exhibit microcephaly at birth, however, the adult phenotype is unknown. This study investigates brain connectivity changes arising from EED ablation in adult mice using high angular resolution diffusion imaging. Three groups of adult mice (homozygotes, heterozygotes, controls) were scanned using 16.4 T to acquire diffusion data. Data was then used to compute iFOD2 maps, probabilistic whole brain tractograms, and the connectomes. Connectomic were compared both connectivity- and network-wise. Homozygotes had abnormal connectivity and network metrics suggesting brain under-development, highlighting the importance of EED’s role in brain development.
Towards Applying Deep Learning to Predict Rigid Motion-Induced Changes in Q-matrices from UHF-MRI pTx Simulations
Authors: Blanter Katherine , Plumley Alix , Malik Shaihan , Kopanoglu Emre
Published: August 2024

Patient motion affects the specific absorption rate (SAR), a safety parameter in MRI. SAR is often calculated using so-called Q-matrices. We used conditional generative adversarial networks (cGANs) to estimate the effect of motion on magnitude from Q-matrices, which were extracted from body models simulated in a parallel-transmit (pTx) coil tuned to operate at 7T. Networks trained on Q-matrices from two positions were extrapolated to nine others. Network-predicted Q-matrices corresponded well with simulated ground truth motion-affected Q-matrices.
On the Importance of Solving for Temperature Versus Local SAR When Evaluating RF-Induced Heating in the Magnetic Resonance Environment
Authors: Anttila Eric , Baker Grant , Leewood Alan , Gross David
Published: August 2024

Previous work has determined that solving for a weighted average local SAR is a relatively easy to way to estimate worst-case RF-induced heating in MRI. The purpose of this study was to determine the importance of solving for temperature using a sequentially coupled electromagnetics and heat transfer model versus local SAR alone when evaluating worst-case RF-induced heating. The results demonstrate that to fully capture RF-induced heating in MRI, temperature rise must be solved for using a sequentially coupled electromagnetic and heat transfer model due to the complex interplay of electric and thermal material properties for implants and the surrounding tissue.
Using interpretable deep learning on task fMRI data to understand brain regions related to working memory - a repeatability study
Authors: Zhao Tianyun , Tubiolo Philip , Hagan Thomas , Williams John , Van Snellenberg Jared , Huang Chuan
Published: August 2024

Deep learning, especially convolutional neural networks (CNN), has been shown to be able to identify the non-linear relation between functional magnetic resonance imaging (fMRI) and task performance. CNN can generate an interpretable result called saliency map highlighting regions that are important for task performance. It can uncover other neural processes that linear modeling cannot due to the high dimensionality nature of the fMRI. The CNN result can be presented as a saliency Previously, we developed a pipeline to produce the saliency map for working memory tasks. In this work, we further evaluated the repeatability of our pipeline.
fMRI signal characteristics underlying human white-matter functional connectivity
Authors: Menon Nayana , Polimeni Jonathan , Chen J. Jean
Published: August 2024

In this study, we illustrate the BOLD fMRI signal characteristics underlying functional correlations in the white matter of healthy adults. We use a group-level white-matter only Pearson’s correlation matrix to identify several high-connectivity regions of interest. Our results show that the BOLD signal spectra of connected white-matter regions contain a low-frequency peak unseen in unconnected regions.
A comparative study of Kaiser score and BI-RADS in the diagnosis of non-mass enhancement lesions on breast MRI
Authors: Zhou Jiejie , Miao Haiwei , Liu Huiru , Chen Zhongwei , Zhao Youfan , Wang Meihao , Su Min-Ying
Published: August 2024

A total of 102 malignant and 60 benign non-mass enhancement lesions were analyzed. Two radiologists with 6 (Reader1) and 14 (Reader2) years of experience assigned the BI-RADS category and Kaiser score (KS). KS decreased biopsy or surgery by 20% for Reader 1 and 16.7% for Reader 2 compared with BI-RADS 4-5. The sensitivity, specificity and accuracy were 87.2%, 78.3% and 84.0% for Reader 1, and 85.2%, 83.3% and 84.6% for Reader 2. Using cutoff threshold of KS>4, the specificity of modified KS increased by 6.7% for both readers, increasing the accuracy slightly by 1.7%-2.5% and keeping the same sensitivity.
Optimizing Breast Isotropic DCE-MRI Imaging Based on Compressed SENSE Technique
Authors: Ning Ning , ZHANG Lina , WANG Zhuo , WU Qi , LIANG Hongbing , SONG Qingwei , LIU Ailian , Wang Yiming
Published: August 2024

Dynamic contrast-enhanced (DCE) MRI is a multi-phase sequence that is limited by long scan times, which makes acquisition acceleration necessary to accomplish clinical feasibility. The aim of this study was to investigate the effect of different Acceleration Factors (AFs) on the image quality of isotropic DCE-MRI acquired with the Compressed SENSE (CS) technique, and to find the optimal AF for the isotropic DCE-MRI. CS factors of 4 to 7 were compared against the conventional SENSE technique in 43 patients. Preliminary results show a CS factor of 5 is the optimal AF with optimized image and velocity data quality.
Ultrashort Echo Time (UTE) MRI in the Detection and Classification of Microcalcification in Breast Cancer
Authors: Ayoub Yazan , Cheung Sai Man , Maglan Boddor , Husain Ehab , Masannat Yazan , He Jiabao
Published: August 2024

Micro-calcification is a central feature of breast cancer, and clinically revealed on mammography. Mammography, a two dimensional imaging approach, is inadequate to provide refined classification. Conventional MRI cannot capture the rapid signal decay from micro-calcification, with Ultra Short Echo Time (UTE) developed to image short T2* species. UTE demands precise control of the hardware to minimise the time delay between radiofrequency transmission and image acquisition, while substantial effort is required to optimise image quality and contrast. We set out to examine the degree of calcification in breast tumour specimens freshly excised from patients using UTE, with comparison against histopathological findings.
Longitudinal change of white matter-specific brain age is associated with Alzheimer's disease-related regional atrophy
Authors: Chen Chang-Le , Li Jinghang , Wang Linghai , Schweitzer Noah , Tudorascu Dana , Aizenstein Howard , Wu Minjie
Published: August 2024

The white matter (WM) network integrity is assumed to associate with Alzheimer's disease (AD)-related gray matter (GM) atrophy. To investigate this hypothesis, we estimated WM-specific brain age to quantify WM integrity and calculated twelve AD-related GM signatures in a longitudinal cognitively normal cohort. We identified that the change rate of WM brain age was significantly correlated with the left hippocampal and amygdala volumetric changes; that is, the accelerated aging in WM was associated with the more atrophic GM volumes. This result suggested that changes of structural network characterized by brain age metrics can reflect the alteration of AD-related GM signatures.
Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies
Authors: Aja-Fernandez Santiago , Martin-Martin Carmen , Pieciak Tomasz , Planchuelo-Gomez Alvaro , Faiyaz Abrar , Uddin Nasir , Tiwari Abhishek , Shigwan Saurabh , Zheng Tianshu , Cao Zuozhen , Blumberg Stefano , Sen Snigdha , Avci Mehmet , Li Zihan , Wang Xinyi , Tang Zihao , Rauland Amelie , Merhof Dorit , Maria Renata , Campos Vinicius , HashemizadehKolowri SeyyedKazem , DiBella Edward , Peng Chenxu , Chen Zan , Ullah Irfan , Mani Merry , Eckstrom Samuel , Baete Steven , Scifitto Scifitto , Singh Rajeev , Wu Dan , Goodwin-Allcock Tobias , Slator Paddy , Bilgic Berkin , Tian Qiyuan , Cabezas Mariano , Santini Tales , Vieira Marcelo da Costa , Shen Zhimin , Abdolmotalleby Hesam , Filipiak Patryk , Tristan-Vega Antonio , de Luis-Garcia Rodrigo
Published: August 2024

This work gathers the results of the QuadD22 challenge, held in MICCAI 2022. We evaluate whether Deep Learning (DL) Techniques are able to improve the quality of diffusion MRI data in clinical studies. To that end, we focused on a real study on migraine, where the differences between groups are drastically reduced when using 21 gradient directions instead of 61. Thus, we asked the participants to augment dMRI data acquired with only 21 directions to 61 via DL. The results were evaluated using a real clinical study with TBSS in which we statistically compared episodic migraine to chronic migraine.
Quantitative T2 measurements of diffusely-abnormal white matter in relapsing-remitting MS patients at baseline
Authors: Musall Benjamin , Yang Yanyu , Kamali Arash , Lincoln John , Ly Vi , Luo Xi , Narayana Ponnada , Gabr Refaat , Hasan Khader
Published: August 2024

Quantitative T2 of diffusely-abnormal white matter (DAWM), assessed at baseline in a population of 800 patients with relapsing-remitting MS with U-Net segmentation and T2 mapping, is distinct and intermediate to T2-hyperintense focal lesions and normal-appearing white matter (NAWM).
Hidden lesions may confound 1H-MRS metabolite quantification by internal water referencing in individuals with multiple sclerosis
Authors: Medeiros Catherine , Igwe Kay , Prinsen Hetty , Kurada Abhinav , Swanberg Kelley , Juchem Christoph
Published: August 2024

A current standard practice in proton magnetic resonance spectroscopy (1H-MRS) uses water as an internal reference for absolute metabolite quantification. We investigate how apparent metabolite concentrations might be affected by tissue-level changes, specifically multiple sclerosis lesions, via water versus creatine referencing in voxels considered normal-appearing at time of scan. Our results suggest that multiple possible routes of confound by hidden lesions on metabolite quantification in even normal-appearing tissue should be considered when applying internal water referencing to 1H-MRS studies in cohorts with multiple sclerosis.
New Multiple Sclerosis Lesion Segmentation in Longitudinal FLAIR MR Images using Subtraction Image
Authors: Kang Junghwa , Yim Jeongmin , Jang Jinhee , Nam Yoonho
Published: August 2024

Measurement of new lesions in longitudinal images is crucial in the evaluation of MS but is laborious and time-consuming. In this study, wWe investigate the effect of subtraction images between two time point FLAIR images on new MS lesion segmentation in longitudinal FLAIR images. The results showed that our method with combination of longitudinal FLAIR images and their subtraction images together helps to improve the accuracy of segmentation of new MS lesion.
The abnormal functional connectivity of the locus coeruleus can classify migraine without aura patients
Authors: Liu Xiaozheng , Chen Jinming , Chen Keyang , Liu Kun , Zhang Xi , Dong Lipeng , lu han , Li Yan , Wang Zhihong , Cao Yungang
Published: August 2024

Blood flow to the brainstem region is increased as a hypothesis for migraine. Locus coeruleus (LC) is the main noradrenergic nucleus in the brainstem. However, the functional characteristics of LC in migraine without aura (MwoA) patients are not currently known. Our results demonstrated that patients with MwoA exhibited significant LC FC differences in the brain areas associated with visual and cognitive function. Understanding the changes in the LC brain network in MwoA patients can provide us with new ideas to understand the pathological mechanisms of MwoA.
Aberrant functional connectivity density in different cognitive states of T2DM patients
Authors: Zhang Dongsheng , Liu Shasha , Huang Yang , Liu Weirui , Liu Wanting , Ai Kai , Lei Xiaoyan , Zhang Xiaoling
Published: August 2024

To investigate the underlying neural mechanism of T2DM-related brain damage, the functional connectivity density (FCD) mapping method was used to examine the density distribution of whole-brain resting functional connectivity from 77 patients with T2DM under different cognitive states (with normal cognitive function, DMCN and mild cognitive impairment, DMCI) and 40 healthy controls (HCs). The decreased long-range FCD in the left superior temporal gyrus (STG) in DMCI patients and its correlation with Rey Auditory Verbal Learning Test (RAVLT) score in all T2DM patients, which suggested left STG may be involved in the neuropathology of auditory memory in T2DM patients.
Brain redundancy metric in cerebral small vessel disease:A community-based study.
Authors: Cui Lei , Zang Minming
Published: August 2024

We applied a dynamic whole-brain network metric, redundancy, to a community-based middle-aged and elderly population, revealed the potential mechanisms of SVD on cognitive impairment ; we also explored the relationship between cognitive reserve and brain redundancy metric. We found that aging, hypertension and lacunes could impair redundancy in brain networks, whereas better brain redundancy corresponds to better executive function, which partly explains the potential mechanism of cognitive impairment by SVD. Secondly, we found no significant correlation between redundancy and cognitive reserve.
Comparison of the electric field and its line integral along the lead of a device across five different RF transmit coils
Authors: Speltz Lydia Bardwell , Lee Seung-Kyun , Shu Yunhong , Tarasek Matt , Trzasko Joshua , Foo Thomas , Bernstein Matt
Published: August 2024

We introduce a method to calculate lead-tip voltage for implanted devices by considering 1) the individualized lead path extracted from X-ray-based images, 2) the incident electric field per unit B1+rms derived for the RF transmitter and a digital human body model, 3) the complex RF wavenumber in an insulated conductor derived from antenna theory. T/R coil transmitters in whole-body at 1.5T and 3.0T were considered, as well as a head coil on a compact 3T. Based on leads in 10 subjects, the results show the compact 3T produces less lead tip voltage than whole-body T/R coils.
A Modular Parallel Radiofrequency Transmission System Platform for MRI Safety Investigations at 3 T
Authors: Yang Benson , Tam Fred , Arianpouya Maryam , Leone Cathleen , Li Vicki , Rock Jason , Graham Simon
Published: August 2024

Parallel radiofrequency transmission (pTx) continues to show great promise in resolving MRI challenges at higher magnetic field strengths. Commercial pTx MRI systems can be very costly with limited system channel count options. This work presents the current state of an 8-channel pTx MRI system with expansion flexibility up to 32-channels that is based on software-defined radio technology.
A novel PNS measurement setup for body gradient coils at an ultrasonic driving frequency of 20kHz
Authors: McGrory Michael , Versteeg Edwin , Siero Jeroen , Klomp Dennis
Published: August 2024

Large dB/dt swings in gradient coils can induce peripheral nerve stimulation (PNS) in the human body. This limits the slew rates used in whole-body MRI reducing scan speeds and spatial resolution. Ultrasonic head gradients can enable fast and silent imaging, however extension to whole-body gradients is challenging due to the required larger dB/dt swings. In this work, we present a body gradient coil which can be used to investigate PNS induction at an ultrasonic driving frequency of 20kHz.
Behavioural and functional assessment of mice inner ear after chronic exposure to an ultra-high static magnetic field of 11.7T or 17.2T.
Authors: Le Ster Caroline , Selingue Erwan , Poirier Roseline , Edeline Jean-Marc , Mériaux Sébastien , Boulant Nicolas
Published: August 2024

High static magnetic (B0) fields are known to induce a transient disturbance of the inner ear. Recently a study demonstrated long-term behavioural effects in mice chronically exposed to a B0 field of 16.4T. In the current study, mice underwent chronic B0 exposure at 11.7T or 17.2T and longitudinally performed behavioural tests over the study. An auditory brainstem response (ABR) test was performed at the end of the full exposure period to assess inner ear properties. Despite the transient disturbance of mice inner ear observed immediately after B0 exposure, no short-term or long-term alteration was detected with behavioural or ABR tests.
Working Harder at MRI Safety, But Getting Poorer MRI Safety Results.
Authors: Gilk Tobias
Published: August 2024

US data suggests that MRI adverse events are growing at a rate of nearly 3x the rate of MRI examinations. While MRI accidents and injuries remain infrequent, the long-term trend of significant growth in MRI adverse events highlights needs for vigilance in MRI safety.
The value of regional radiomics score based on postoperative conventional MRI in evaluation of glioma recurrence
Authors: Ren Jinfa , Zhai Xiaoyang , Han Dongming , Yin Huijia , Yan Ruifang , Wang Kaiyu
Published: August 2024

Early diagnosis of postoperative glioma recurrence is difficult. But emerging measurements of radiomics could provide a powerful tool for this dilemma. We used the least absolute shrinkage and selection operator to select features and generate radiomics scores based on multiple modalities of conventional MRI to discriminate recurrence from treatment-related effects. We found that tumor recurrence could be independently identified by features from both the postoperative enhanced region and edematous region with a best performance of the combined one.
Increasing temporal SNR, sharpness, specificity, and sensitivity of ASLfMRI using the partial separability model
Authors: Marchini Charles , Sutton Brad
Published: August 2024

ASLfMRI temporal SNR (tSNR) and sharpness in the inferior-superior direction was improved by using partial separability, a low rank model. The method requires an additional novelty to the partial separable model which allows time points with no corresponding imaging data, only temporal navigator data, to be reconstructed. A finger tapping task was used to demonstrate the detection of cerebral blood flow to the motor cortex. Mean squared error, structural similarity index, and the area under the curve of a receiver operating characteristic curve was also improved as shown by using a simulation of ASLfMRI data.
Comparison of velocity-selective-inversion arterial spin labeling schemes
Authors: Zhang Ke , Triphan Simon , Sedlaczek Oliver , Ziener Christian , Kauczor Hans-Ulrich , Schlemmer Heinz-Peter , Kurz Felix
Published: August 2024

Velocity-selective pulses include VS saturation pulses (VSS) and VS Inversion (VSI) pulses. Previous study (1) concluded that both dual-sBIR8-VSS and sinc-VSI achieved the highest SNR efficiency among the VS labeling schemes. Overall, the dual-sBIR8-VSS pulse was the most robust against field imperfections, whereas sinc-modulated VSI pulse showed greater tSNR and was the best among the VSI methods. In this study, VSI sequence with rectangular small flip-angle RF pulses (rect-VSI), sinc-VSI with and without VS gradients during the control condition are compared. Bloch simulation and in vivo experiments for their robustness against B1, B0 variation and eddy current (EC) are investigated.
High Resolution MR Reconstruction with Functionally Separate Neural Networks
Authors: Kutsuna Hideaki , Uematsu Shun , Shinoda Kensuke
Published: August 2024

The authors propose a new reconstruction method to obtain higher resolution images from an MR acquisition. The method incorporates MR physics and two neural networks, which are functionally separate, for denoising and upsampling. The proposed method was evaluated by applying it to both retrospectively and prospectively undersampled data. The result showed that the proposed technique is capable of reconstructing higher resolution images over a conventional method, by multiplying the matrix size while keeping more detail structure in the originally sampled data.
When System Model meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging
Authors: Jalata Ibsa , Nakarmi Ukash
Published: August 2024

Unsupervised deep learning framework that integrates system priors using unrolled optimization and general image priors can reconstruct high quality Magnetic Resonance images comparable to supervised methods from highly undersampled k-space data. We develop an unsupervised deep learning framework that integrates system priors in MR acquisition and image priors to reconstruct high quality MR images from highly undersampled k-space data without using ground truth images.
Association of neuroanatomical changes with neuropsychological changes in Treated Adult HIV-Positive Patients
Authors: Joy Ajin , Nagarajan Rajakumar , Daar Eric , Paul Jhelum , Yadav Santosh , Guerrera Mario , Macey Paul M. , Thomas M. Albert
Published: August 2024

This study was designed to use the structural MRI data to characterize volumetric changes in gray matter and white matter, and to determine variations in cortical thickness, in a group of HIV-infected individuals to understand how their brain structural changes are associated with their neuropsychological state compared to a group of healthy individuals with similar social, behavioral backgrounds. Despite the demographic similarities and cART, we observed reduced gray and white matter volumes, as well as altered cortical thickness in HIV-infected participants compared with healthy controls. In addition, the neuroanatomic changes in HIV-infected patients showed statistically significant correlations with memory scores.
Generative diffusion model for DSC MRI artifact correction
Authors: Asaduddin Muhammad , Kim Eung Yeop , Park Sung-Hong
Published: August 2024

Dynamic susceptibility contrast (DSC) MRI may suffer from artifacts due to long acquisition time. Past methods are limited in their performance and may change the contrast passage timing. In this work, we present a generative diffusion model that can restore signal loss and movement artifacts. We showed the generated DSC MRI images to have proper post-contrast vessel and grey matter structure with accurate contrast agent arrival/washout timing. The brain shape was also accurately generated as shown by the DICE score. This approach could provide a solution to restore a corrupted DSC MRI data while maintaining accurate contrast passage timing.
Predicting the Risk of Non-Saccular Aneurysms Based on the Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Authors: Li Yan , Xu Ziming , Dong Linggen , Wang Yajie , Liu Peng , Lv Ming , Chen Huijun
Published: August 2024

Assessment of intracranial aneurysm rupture risk is clinically critical. Recent studies have shown that the aneurysm wall permeability (Ktrans) and wall enhancement index are independent risk factors for predicting saccular aneurysm rupture. However, this conclusion has not been confirmed in non-saccular aneurysms. Our study suggested that Ktrans was significantly associated with the aneurysm size and PHASES score in non-saccular aneurysms. But Ktrans did not associate with the wall enhancement index in non-saccular aneurysms. Therefore, Ktrans can provide an independent quantitative indicator for assessing the risk of rupture of in non-saccular intracranialaneurysms.
To evaluate the utility of magnetization transfer (MT) imaging in the study of normal uterus and common uterine lesions.
Authors: Bi Qiu , Wu Kunhua , Wu Yunzhu
Published: August 2024

In this study, we explored the value of MT imaging to characterize normal uterine structures and common uterine lesions by measuring MTR values. The results showed the MTR values were significantly different among normal uterine structures, among uterine lesions of different origin, or between some uterine lesions and corresponding normal structures. MTR values were found to be effective in the diagnosis and differential diagnosis of certain uterine diseases. It might provide a preoperative basis for neoplastic histologic origin in the uterus.
Test-retest repeatability of motility MRI in healthy volunteers and patients with Crohn’s disease
Authors: Bane Octavia , Bennett David , Altinmakas Emre , Abboud Ghadi , Geahchan Amine , Cuevas Jordan , Menys Alex , Ungaro Ryan , Colombel Jean-Frederic , Taouli Bachir
Published: August 2024

Our study aims to determine test-retest repeatability in motility (bowel wall motion) index derived from CINE-MRI measured in involved and uninvolved small bowel in patients with Crohn’s disease and in healthy volunteers, to determine a clinically significant threshold of motility change in response to treatment. Motility was lower in the involved areas compared to uninvolved small bowel, and in the uninvolved small bowel ofpatients compared to that of healthy volunteers. We found moderate test-retest repeatability in the motility index of involved bowel (provide average CV) and in the ratio ofmotility indices in involved small bowel and in uninvolved small bowel.
Characterization of glycogen storage disease type III using glycoNOE MRI
Authors: Zeng Qing , Bie Chongxue , van Zijl Peter , Li Yuguo , D'souza Valentina , Machado Michael , Poon Kirsten , Grimm Andrew , Yadav Nirbhay
Published: August 2024

Glycogen storage disease type III (GSD III) is characterized by abnormally high glycogen accumulation in liver, muscle, and heart. Treatments such as diet modification and drugs are currently being developed, but there is a lack of suitable methods for assessing disease load and possible treatment efficacy. Recently, it was shown that glycoNOE MRI can image glycogen levels in vivo and here we apply this technique to distinguish GSD III from controls in a mouse model. The results show that glycoNOE can clearly distinguish GSD III and that glycoNOE contrast exhibits a linear correlation with ex vivo quantification of glycogen levels.
Evaluation of Biological Metabolic Activity within an Atherosclerotic Plaque using Chemical Exchange Saturation Transfer Imaging
Authors: Kanazawa Yuki , Miyati Tosiaki , Harada Masafumi , Miyoshi Mitsuharu , Matsumoto Yuki , Hayashi Hiroaki , Kanematsu Yasuhisa , Takagi Yasushi
Published: August 2024

We demonstrated biological metabolic activity within an atherosclerotic plaque of the carotid artery using CEST imaging. 35 patients with carotid stenosis, of which all were pathologically diagnosed with carotid endarterectomy, were evaluated. The following estimation parameters in CEST image were evaluated; bulk water, magnetization transfer, amide proton transfer (APT), and nuclear Overhauser effect (NOE). As a result, there were weak positive correlations between T1w-signal-ratio and the above-mentioned parameters: bulk water (R = 0.37), APT (R = 0.39), and NOE (R = 0.37). Multi-parametric analysis of CEST imaging can obtain detailed information concerning the activity in an atherosclerotic plaque.
Highly Accelerated Chemical Exchange Saturation Transfer Imaging with Partially Separable Network
Authors: Liu Chuyu , Chen Zhensen , Song Xiaolei
Published: August 2024

Herein, we developed a partially separable network (PSN) for CEST acceleration. Our contributions are: 1) We found that the reconstruction error of CEST mainly exists in the spatial subspace. 2) A deep learning network based on partially separable model was developed to optimize CEST images in spatial subspace. Retrospective results suggested that our method enabled a highly accelerated CEST imaging (14X for healthy adults and 11X for brain tumor patients) with contrast maps and Z-spectrum consistent with gold standard, which could have great clinical utility.
Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network
Authors: Chen Huan , Lin Liangjie , Chen Lin , Chen Zhong
Published: August 2024

Chemical exchange saturation transfer (CEST) MRI is a versatile technique that exploits the saturation transfer between exchangeable protons and water for non-invasive detection of diluted metabolites. Although theoretically promising, the practical application of CEST MRI is still challenged by low CEST contrast and low signal-to-noise ratio (SNR) of acquired images. Here, we proposed a deep learning-based method, dubbed denoising CEST network (DCEST-Net), to fully exploit the spatiotemporal correlation prior embedded in the CEST images and restore noise-free images from their noisy observations. Results suggested that DCEST-Net can achieve better performance compared to the state-of-the-art denoising methods.
Diffusion MRI tractometry findings in Dystonia: a UK Biobank Study
Authors: MacIver Claire , Tax Chantal , Jones Derek , Schalkamp Ann-Kathrin , Sandor Cynthia , Bailey Grace , Wadon Megan , Peall Kathryn
Published: August 2024

Dystonia is a hyperkinetic disorder involving uncontrolled muscle contractions. Brain motor networks have been implicated, with heterogenous methodology and findings in the existing diffusion MRI literature. We compared diffusion findings in white matter motor pathways in dystonia (n=76) and healthy controls (n=311) derived from the UK biobank, assessing differing preprocessing and analysis approaches. An in-house pipeline identified localised tractometry MD and kurtosis differences in cerebellar peduncles, thalamic radiations and thalamo-premotor tracts in dystonia, findings not replicated using differing analysis and preprocessing approaches. Overall, localised white matter differences are implicated in dystonia, with the impact of methodology on group-level findings highlighted.
Sex-specific differences of the number of fiber orientations (NuFO) in the human brain
Authors: David Szabolcs , Leemans Alexander , de Luca Alberto
Published: August 2024

Diffusion MRI-based biomarkers are commonly used to assess brain microstructural properties. Mathematical models have been developed to calculate various metrics; each are sensitive to different tissue features. Here, we investigate whether there are differences in the number of fiber orientations (NuFO) between male and female brains and how these results compare to corresponding DTI-derived fractional anisotropy (FA) findings. Results show NuFO-based differences with high effect size (>1 Cohen’s D) in hippocampi, which are undetected in FA-tests. Therefore, NuFO could provide complementary aspects to DTI metrics to capture differences in microstructural organization.
Functional connectivity to entorhinal cortex in hypertensive Alzheimer’s disease rat models
Authors: Chen Yi , Fernandez Zachary , Scheel Norman , Gifani Mahsa , Qian Chunqi , Dorrance Anne , Counts Scott , Zhu David
Published: August 2024

Extensive studies have revealed that the entorhinal cortex (EC) plays a critical role in Alzheimer’s disease (AD) development. However, EC functional connectivity and its associated network abnormalities are understudied, especially in rodent models. To the best of our knowledge, this is the first study to report disrupted EC functional connectivity in hypertensive AD rodents using resting-state fMRI. Our results may provide new insights into the impaired EC connectivity patterns and enable the search for novel preclinical EC-based fMRI biomarkers for AD studies. In addition, our novel animal model provides new information to understand the link between hypertension and AD.
Predicting brain-behavior relationships using Voxel-based Predictive Modeling in ASL data of older subjects
Authors: Peltier Scott , Karker Michelle , Hernandez Luis , Paulson Henry , Giordani Bruno , Hampstead Benjamin , Noll Doug
Published: August 2024

A recent technique, Connectome-based Predictive Modeling (CPM), has shown promise in relating imaging-derived measures to clinical/behavioral observations. In this work, we adapt this method to relate volumetric CBF data to continuous composite measures of memory, learning, and language in subjects with MCI and DAT, along with healthy subjects. Models using the learning and memory composite scores had the largest effect sizes and statistical significance using permutation testing. Regions in the feature masks indicate involvement of brain regions that may be impacted in DAT. This demonstrates the utility of ASL-based perfusion measurement as a predictor of cognitive status in older subjects.
Association between 3D Geometry of Vertebrobasilar Arteries and Basilar Artery Atherosclerosis: An MRI Study
Authors: Liu Jiachen , Shen Rui , Yang Dandan , Yu Miaoxin , Zhao Xihai
Published: August 2024

Geometry of VBA has been proved to be associated with the presence of BA plaques, yet relative studies are lack of 3D information due to methodological difficulties. We proposed a semi-automated algorithm for quantitative measurement, which can evaluate local diameter, local curvature and angles between vessels directly in 3D space. We used the proposed algorithm to measure the 3D geometric metrics and found significant association between VBA geometry and the presence of BA plaques. Normalized diameter variation of BA and BA & PCA-R angle projected to lateral view were also associated with the presence of BA plaques independently.
Automated Localization of the Extracranial Carotid Artery in Black Blood Contrast MR Images Using a Deep Learning Approach
Authors: HashemizadehKolowri SeyyedKazem , Zanaty Nadin , Canton Gador , Balu Niranjan , Hatsukami Thomas , Yuan Chun
Published: August 2024

In this work, a deep learning approach for automated localization of carotid arteries in black blood contrast MR data is proposed. This is the first step in automated analysis of vessel wall imaging data. Carotid arteries supply oxygenated blood to the brain and are susceptible to atherosclerosis, so their vessel wall imaging is of significant importance in clinical evaluations. However, currently only qualitative assessment of VW imaging data relying on visual inspection is implemented in clinics that are not scaleable. Therefore, developing automated image processing tools to quantitatively analyze vessel wall imaging data can have a major clinical impact.
The application of Quantitative Perfusion Analysis of GRASP for assessing pathologic prognostic factors in rectal cancer
Authors: Zhou Mi , Chen Meining , Wang Yuting
Published: August 2024

Colorectal cancer’s pathological prognostic factors directly affect the patient's prognosis. Golden-angle RAdial Sparse Parallel (GRASP) imaging was invented to calculate the accurate perfusion parameters including influx forward volume transfer constant (Ktrans), rate constant (Kep), and plasma volume fraction (Ve). We found GRASP parameters showed significant differences in many prognostic factors, including histology type, extramural venous invasion (EMVI), lymphovascular invasion (LVI), tumor deposit (TD) and lymph node metastasis (LNM), and were independent factors for histology type, LNM, LVI and EMVI. GRASP parameters were strongly associated with preoperative prognostic factors in rectal cancer, providing useful information for treatment and follow-up protocol.
Evaluation of multi-echo-based Hybrid-EPI (HEPI) technique for measuring brain oxygenation
Authors: Venugopal Krishnapriya , Warnert Esther , van Dorth Daniëlle , Smits Marion , van Osch Matthias , Poot Dirk , Hernandez-Tamames Juan
Published: August 2024

The reversible component of transverse relaxation time, R2’, enables the measurement of blood oxygenation, an important biomarker in several diseases. We propose a multi-echo HEPI technique to estimate R2’. HEPI combines GRE and SE and hence provides R2* and R2, when acquired at different echo-times. The accuracy of ME-HEPI in measuring R2’ is evaluated in a phantom in this work. The sensitivity of HEPI to different oxygenation levels, attained using respiratory challenge MRI, is studied in a healthy subject. This is also investigated using a simulation tool that simulates microvasculature and MR signal for varying oxygenation in the vessels.
Towards motion-resolved interleaved radial 23Na/1H magnetic resonance imaging of the human heart at 7 Tesla
Authors: Huber Jörn , Ruck Laurent , Günther Matthias , Nagel Armin , Konstandin Simon
Published: August 2024

Motion correction in interleaved 23Na/1H MRI of the human heart is important to improve the diagnostic reliability of reconstructed images and derived quantitative parameters. Therefore, this work demonstrates and compares the application of different reconstruction techniques to undersampled and motion-gated 23Na/1H MRI data at 7 T.
High temporal resolution DCE-MRI improves the performance of model fitting parameters
Authors: Li Xin , Rice-Stitt Travis , Gao Lina , Aguiñaga Marina , Turner Kevin , Foster Bryan , Coakley Fergus , Garzotto Mark , Kopp Ryan
Published: August 2024

Recent advance in data acquisition makes fast DCE-MRI data acquisition feasible. This work investigated the impact of DCE-MRI temporal resolution on the data’s pharmacokinetic modeling and the water exchange effect imparted into the model parameters. Using both the Tofts model and the water-exchange sensitized Shutter-Speed model, our results showed that DCE data with higher temporal resolution (shorter intersample interval) is beneficial in model parameter precision and in quantifying transcytolemmal water exchange effect. The later may offer additional lesion-detection specificity in clinical prostate MRI.
B0 Inhomogeneity Distortion Corrected Image Reconstruction with Deep Learning on An Open Bore MRI-Linac
Authors: Shan Shanshan , Gao Yang , Ma Meng , Gan Hongping , Waddington David , Whelan Brendan , Liu Paul , Liu Chunyi , Gao Mingyuan , Liu Feng
Published: August 2024

MRI-Linac systems require real-time anatomical images with high geometric fidelity to localize and track tumours during radiotherapy treatments. Image distortions caused by B0 field inhomogeneity and slow MR acquisition hinder the application of real-time MRI-guided radiotherapy. Here, we develop and investigate a deep learning-based reconstruction pipeline to reconstruct B0 inhomogeneity distortion-corrected images (B0ReconNet) directly from k-space. MR acceleration techniques such as compressed sensing (CS) were integrated into B0ReconNet to further reduce acquisition time. Simulated and experimental data with fully sampled and retrospectively subsampled acquisitions on a 1T open bore MRI-Linac were used to validate the proposed method.
Unsupervised model for removing Nyquist/motion artifacts in SPatiotemporal Encoding MRI
Authors: Bao Qingjia , Xia Liyang , Liu Kewen , Liu Xinjie , Sun Peng , Frydman Lucio , Liu Chaoyang
Published: August 2024

Although a major advantage of SPEN vs EPI is a higher immunity to artifacts, it suffers from Nyquist or motion artifacts. We proposed a new unsupervised CNN model that takes advantage of both physical model and Deep learning. The model consists of three parts: phase feature extraction module, which can extract the phase features of even/odd phase differences or motion-caused phase differences in multi-shot echo data. Then, the phase maps are generated with these phase difference features. Lastly, the phase correction modules to remove artifacts. The results show that the proposed model can effectively correct Nyquist/motion artifacts in single-shot/multi-shot SPEN.
Task-based evaluation of deep learning-based reconstruction for highly-accelerated 3D T1-weighted brain MRI scans
Authors: Ahn Sangtae , Bhushan Chitresh , Huston John , DeMarco J. , Shih Robert , Trzasko Joshua , Brada Rafi , Mckinnon Graeme , Jansen Isabelle Heukensfeldt , Rettmann Dan , Burns Brian , Cashen Ty , Mazor Nir , Zhu Xucheng , Foo Thomas
Published: August 2024

3D MRI enables thin slices at the cost of long scan times, causing practical challenges. Recently, deep-learning (DL) techniques have successfully accelerated MR scans. However, it is challenging to characterize the image quality (IQ) performance of DL methods by conventional metrics because IQ depends on applications, i.e., how images are used. We evaluate the IQ performance of DL-Speed, our DL-based acceleration method, for 3D T1-weighted MPRAGE brain scans, in 1) post-reconstruction subcortical structure segmentation, and 2) a reader study. The results imply DL-Speed can accelerate scans with reduction factor R=10 while maintaining IQ comparable to standard parallel imaging with R=2.1.
Self-Supervised Image Reconstruction of 7T MP2RAGE for Multiple Sclerosis: 0.5mm Isotropic Resolution in 10 Minutes
Authors: Yu Thomas , La Rosa Francesco , Piredda Gian Franco , Silva Jonadab , Bourie Faye , Dieckhaus Henry , Nair Govind , Liebig Patrick , Thiran Jean-Philippe , Kober Tobias , Beck Erin , Hilbert Tom
Published: August 2024

High-resolution 3D MR imaging is necessary for the detailed assessment of focal pathologies, such as cortical lesions. However, high-resolution demands tradeoffs with acceleration and SNR, which is difficult to address with standard machine learning reconstructions due to the infeasibility of collecting large datasets of fully sampled data. Using a dataset of high-resolution (0.5mm isotropic), 3D, 7T MP2RAGE scans of multiple sclerosis patients, we show that a self-supervised reconstruction from one scan, requiring no fully sampled data, has higher apparent SNR than a median of three scans, currently used for assessment, with comparable tissue contrast and lesion conspicuity.
Improving interpretation accuracy for curved planar reformation of intracranial vessel wall MRI by reducing intra-plane rotation
Authors: Wang Xin , Guo Yin , Zhang Kaiyu , Canton Gador , Balu Niranjan , Hatsukami Thomas , Mossa-Basha Mahmud , Yuan Chun
Published: August 2024

This work aims to develop an algorithm for straightened curved planar reformation (CPR), i.e., extracting the 2D cross-sectional images along a vessel centerline in a vessel wall MRI scan. Previous methods determine the orientation of CPR images in a fixed way, leading to undesired rotation along the centerline. Our method instead calculates the local coordinate system with respect to previous slices, thus keeping the continuity of cross-sections. Our CPR results show a better readability of the straightened vessel image, especially when one wants to utilize the spatial information among adjacent CPR slices for a more comprehensive and accurate medical analysis.
Diaphragm Excursion Measured by Free-breathing 1H MRI in Patients with Asthma: Repeatability and Bronchodilator Response
Authors: Friedlander Yonni , Capaldi Dante , Konyer Norm , Kjarsgaard Melanie , Venegas Carmen , Nair Parameswaran , Svenningsen Sarah
Published: August 2024

Using free-breathing 1H MRI, diaphragm excursion was measured in 9 patients with severe asthma at two visits 4-months apart. At each visit, patients with asthma were imaged before and after administration of a bronchodilator. Diaphragm excursion measured at the two visits were not significantly different from one another (mean bias=0.34cm, p=0.07) and were well correlated (r=0.53, p=0.004), demonstrating repeatability of the measurement. In addition, diaphragm excursion was significantly increased following bronchodilator administration (p=0.01).
Using 13C MRS to Assess Fasted and Postprandial Glycogen Stores in Healthy Children: A Randomized Controlled Study
Authors: Bawden Stephen , Horstman Astrid , Spicer Abi , Darwish Noura , Breuille Denis , Gowland Penny , Macdonald Ian , Simpson Liz
Published: August 2024

The aim of this study was to use 13C MRS to compare hepatic glycogen levels before and after an overnight fast and following a small breakfast of varying carbohydrate quantities (0, 15.5 and 31g CHO) in children. Liver glycogen concentration decreased overnight from 378 ± 141 to 277 ± 107 mmol l-1 with a between visit coefficient of variation of 21 ± 15 %. There was also a significant difference in the postprandial AUC (P < 0.005) with a linear CHO ‘dose’ response (R=0.51, P < 0.001). This study expands knowledge of normative glycogen storage in children.
Characterising the effect of free breathing on abdominal MR Spectroscopy and impact on X-nuclei spectra.
Authors: Spicer Abi , Bawden Stephen , Peggs Zachary , Daniel Alexander , Peters Andrew , Francis Susan , Gowland Penny
Published: August 2024

Multinuclear spectroscopy requires the use of free breathing acquisitions to achieve acceptable SNR. Here proton spectroscopy is used as an analogue for multinuclear MRS along with dynamic phase imaging to characterise the effect of respiration. Consistent agreement was seen between the respiratory bellows trace and the timeseries of the water peak frequency and imaging field offset, with overlapping primary frequencies on respective Fourier transforms. On free breathing a maximum frequency shift of 31Hz was measured, this equates to a 0.24ppm shift which could cause significant line broadening in the spectra of multinuclear 31P and 13C liver experiments.
Functional and Microstructural Comparative Study on Monogenic vs Idiopathic Parkinson's Disease
Authors: Dasgin Hacer , Turan Basak , Salanci Bilge , Gun Eser , Cakmakli Gul , Elibol Bulent , Oguz Kader
Published: August 2024

Clinical presentation of monogenic PD differs from idiopathic PD, which might relate to different structural and functional alterations. Previously, we examined a small group of genetic PD patients with connectivity changes in the basal ganglia, compared with healthy control (HC)s. In this study we further examined monogenic PD patients and compared idiopathic PD group and HCs that functional and microstructural changes would be different in these groups of patients. There was no significant basal ganglia network (BGN) alteration between PD groups, but ACC activation is remarkable in both groups. Significantly decreased fractional anisotropy in mPD patients compared to iPD patients.
Dynamic characteristics of functional network activity in brains with left-frontal glioma
Authors: Cai Siqi , Liang Yuchao , Wang Yinyan , Liu Yufei , Chen Fanfan , Jiang Chunxiang , Wang Lei , Zhang Lijuan
Published: August 2024

This study investigated the temporal features of the brain network activity with dynamic fractional amplitude of low-frequency fluctuation (dfALFF) and sliding window approach. The time-varying brain activity was clustered into two distinct states. Patients’ brains featured high occurrence of the weak state, low occurrence of the strong state, and network dALFF that decreased but spatially extended with the tumor malignancy. The dfALFF variance of networks was attenuated in HGGs but not LGGs. These malignancy-specific alterations indicate a diverse neuropathological profile of gliomas, and highlight the importance of temporal features of brain activity in the disease characterization of glioma.
Evaluation of postcontrast images of glioma using 7T and 3T magnetic resonance imaging: an intraindividual comparison study
Authors: Li Chenxi , Cheng Kun , Qu Jianxun , Ma Xiaoxiao , Lou Xin
Published: August 2024

With the advent of the 7T device meeting the need for ultra-high resolution, we planned to explore the advantages of 7T over 3T in terms of the internal detail display of gliomas. Seventeen patients with glioma were individually rated for internal tumor structure and feeding artery by 6 radiologists at 7T and 3T MR, and the DCS score was calculated. 7T revealed better details of internal tumor structure and higher diagnostic confidence than 3T.
Guided field Map Estimation and Image Correction for MRI with LargeMagnetic Field Inhomogeneity
Authors: Reyhanian Navid , Mullen Michael , Froelich Taylor , Garwood Michael , Haupt Jarvis
Published: August 2024

Many methods deployed for Magnetic Resonance Imaging (MRI) suffer from degraded image quality when the static magnetic field ($$$B_0$$$) is nonuniform, as $$$B_0$$$ inhomogeneity causes different types of image artifacts and distortions. ﻿Image correction methods require a prior estimate of the field map. In this work, we study the problem of static $$$B_0$$$ inhomogeneity estimation from distorted and undistorted image pairs, despite undistorted images being noisy. The estimated field map is later utilized to correct distorted images. The efficacy of the proposed approach is demonstrated for different encoding methods in the presence of large magnetic field inhomogeneity via extensive simulations.