bluuebunny/crossref_metadata_2025 huggingface dataset:
Motion compensated multi-contrast MRI using deep factor model
Authors: Chen Yan , Holmes James , Corum Curtis , Magnotta Vincent , Jacob Mathews
Published: August 2024

Recent quantitative parameter mapping methods including MR fingerprinting collect a time series of images that capture the evolution of magnetization. The focus of this work is to introduce a novel approach termed as deep factor model, which offers an efficient representation of the multi-contrast image time series. The higher efficiency of the representation enables the acquisition of the images in a highly undersampled fashion, which translates to reduced scan time in 3D high-resolution multi-contrast applications. The approach integrates motion estimation and compensation, making the approach robust to subject motion during the scan.
Combining FID navigators with field probe monitoring for improved head motion tracking and prospective correction at 7T
Authors: Serger Matthias , Stirnberg Ruediger , Ehses Philipp , Stoecker Tony
Published: August 2024

FID navigators and field probes can measure local motion-induced magnetic field changes at different positions. Both methods are suited for marker-less prospective motion correction but with limited accuracy. A small 7T study with five subjects was performed to compare their performance for small involuntary and large voluntary motion. It is demonstrated that errors of regression models, calibrated between magnetic field measurements and motion parameters, are consistently reduced by combining both techniques. Furthermore, a proof-of-concept prospective motion correction experiment based on FID navigators is presented, which will be extended to include field probe measurements in the near future.
Automatic Extraction of Liver Parenchyma and R2* Estimation using Deep Learning for UTE Imaging for Assessment of Hepatic Iron Overload
Authors: Shrestha Utsav , Morin Cara , Loeffler Ralf , Abramson Zachary R. , Hankins Jane , Hillenbrand Claudia , Tipirneni-Sajja Aaryani
Published: August 2024

Ultra-short echo time (UTE) imaging increases the accuracy of R2*-based hepatic iron content (HIC) quantification in cases of high iron overload when conventional GRE sequences can fail due to rapid signal decay. Segmenting whole liver to estimate liver R2* requires human expert and is time consuming. In this study, we trained a convolutional neural network (CNN) to automatically segment the liver parenchyma on radial UTE acquisitions using magnitude images and R2* maps. Our results show an excellent agreement between manual and CNN-based liver segmentation and mean R2* values, hence demonstrating the potential of our proposed method for automated HIC assessment.
Ammonium quantification in human plasma by 1H-NMR for staging of liver fibrosis in alcohol and non-alcoholic-related liver disease
Authors: Azagra Marc , Pose Elisa , De Chiara Francesco , Pérez Martina , Avitabile Emma , Servitja Joan-Marc , Brugnara Laura , Ramón-Azcón Javier , Marco-Rius Irene
Published: August 2024

Invasive and painful liver biopsy is the gold standard for liver disease diagnosis. Non-invasive methods to assess liver fibrosis in patients with alcohol-related liver disease (ArLD) and non-alcoholic fatty liver disease (NAFLD) are an unmet clinical need. We have developed a robust and reliable 1H NMR protocol to quantify the endogenous ammonium concentration in biological fluids. The measurement of ammonium in blood plasma samples of ArLD and NAFLD patients discerned between some stages of the disease retrospectively and showed that ammonium readout is a robust diagnostic marker of fibrosis stage, more so than current clinically assessed blood hepatic biomarkers.
Age and gender prediction from minimally processed 3D structural brain MRI through multi-task contrastive learning
Authors: Lau Vick , Man Christopher , Su Shi , Ding Ye , Hu Jiahao , Zhang Junhao , Zhao Yujiao , Leong Alex T. L. , Wu Ed
Published: August 2024

Predicting brain age from structural MRI (sMRI) is potentially valuable as the deviation of predicted age from chronological age can be a biomarker for characterising brain health conditions. Currently, extensive pre-processing of sMRI data is required for most deep learning methods. This study presents a multi-task contrastive learning framework for simultaneous brain age prediction and gender classification from minimally processed, noisy 3D T1-weighted images. By including gender classification task and supervised contrastive learning, we demonstrate that leveraging gender information in training and better representation learning can boost age prediction accuracy for both in-domain and out-of-domain datasets.
Biparametric MRI classification model for prostate cancer detection using a combination of prediction maps
Authors: Sunoqrot Mohammed R. S. , Segre Rebecca , Nketiah Gabriel , Patsanis Alexandros , Bathen Tone , Elschot Mattijs
Published: August 2024

Biparametric MRI (bpMRI) is a valuable tool for the diagnosis of prostate cancer (PCa). Computer-aided detection and diagnosis (CAD) systems have the potential to improve the robustness and efficiency of PCa detection) compared with conventional radiological reading. This work explores the combination of the results of two PCa CAD systems as input to a new classification model. We show that this is promising approach that can potentially improve the final detection of PCa.
Development and validation of a deep learning model trained on MRI for the prediction of hepatocellular carcinoma survival
Authors: Ma Lidi , Li Congrui , Li Haixia , Deng Kan , Zhang Cheng , Zhang Weijing , Xie Chuanmiao
Published: August 2024

In this study, we developed a deep learning model based on GD-DTPA-enhanced MRI data to predict the overall survival (OS) of patients with HCC. Our results showed that 3D-CNN model based on GD-DTPA-enhanced MRI can non-invasively predict the OS of patients with HCC. The combined model integrating the deep learning score and clinical factors showed a higher predictive value than the clinical and 3D-CNN models and may be more useful in guiding clinical treatment decisions to improve the prognosis of patients with HCC.
Repeatability of Quantitative Measures in Long COVID using Hyperpolarized 129Xe MRI
Authors: Staab Keegan , Percy Jonathan , Hahn Andrew , Kruger Stanley , Comellas Alejandro , Sieren Jessica , Hoffman Eric , Fain Sean
Published: August 2024

Repeatability visits with hyperpolarized 129Xe MRI of ventilation and gas exchange measures were acquired at baseline and 3-6 weeks after baseline in patients with persistent dyspnea, fatigue, and neurocognitive symptoms (“Long” COVID). Findings did not support the same repeatability of measures found in a previous study of IPF, suggesting instability of pulmonary pathophysiology is a characteristic of Long COVID.
Evident Cerebral Perfusion Recovery in COVID-19 Patients: Results Based on Arterial Spin Labeling MRI
Authors: Shen Yu , Zhang Xianchang , Wu Yaping , Bai Yan , Wei Wei , Chen Lijuan , Wang Meiyun
Published: August 2024

COVID-19 may affect the brain of patients, ranging in severity from confusion to life-threatening strokes. This study investigated the potential cerebral perfusion change in COVID-19- infected patients using pseudo-continuous arterial spin labeling (pCASL) sequence by follow up after patients recovered for 4, 12 and 18 months. It’s found that both cerebral blood flow (CBF) and bolus arrival time (BAT) values derived from pCASL demonstrated an increasing tendency over time in several brain areas in COVID-19 survivors after whole brain analysis. Our findings indicated that COVID-19 survivors may experience compensatory brain function recovery and this recovery process would be slow.
Quantitative pulmonary perfusion in patients with COVID-19 using dynamic contrast enhanced MRI at 0.55T
Authors: Campbell-Washburn Adrienne , Kanth Shreya , Huapaya Julio , Thurston Matthew , Mancini Christine , O'Brien Kendall , Potersnak Amanda , Wang Haiyan , Regenold David , Baute Scott , Chen Marcus , Javed Ahsan , Suffredini Anthony
Published: August 2024

COVID-19 infection has been reported to cause pulmonary perfusion defects associated with pulmonary embolism and infiltrates. We used quantitative dynamic contrast enhanced 0.55T MRI, with pharmacokinetic modelling, to monitor lung perfusion longitudinally in 139 patients with COVID-19. We observed significant associations between disease severity and perfusion during the convalescent phase (91-365d post symptom onset); and between abnormal perfusion during the acute phase (0-40d) and low pulmonary function later during recovery. Quantitative pulmonary perfusion measured by MRI may be a useful metric to study patients with COVID-19 infection, and early results suggest long-term perfusion abnormalities in patients with severe disease.
Investigating the effects of Long COVID on cerebrovascular reactivity using VASO at 3T
Authors: Alasiri Sharyfah , Zamboni Elisa , Watson Isaac , Owston Heather , Baseler Heidi , McGonagle Dennis , Kennerley Aneurin
Published: August 2024

Strategies to help sufferers from Long COVID (LC) mostly focus on symptoms management. There is an urgent need for understanding whether and how the cerebrovascular system is implicated in emergent symptoms. Here we use advanced cerebral blood volume (CBV)-based imaging techniques to appropriately quantify changes in vascular reactivity in patients affected by LC compared to healthy volunteers. A slower vasodilation mechanisms, leading to inappropriate oxygen supply during neuronal function, could be used as biomarker and help clinical diagnosis.
Combined Microstructural Assessment of Progressive Apraxia of Speech by Diffusion Tensor Imaging-Based Tractography and Multi-Shell NODDI
Authors: Gatto Rodolfo , Duffy Joseph , Utianski Rene , Clark Heather , Botha Hugo , Machulda Mary , Lowe Val , Josephs Keith , Whitwell Jennifer
Published: August 2024

Progressive apraxia of speech (PAOS) is a tauopathy characterized by difficulties with motor speech programming and planning. Grey and white matter (GM & WM) brain regions were interrogated by diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Twenty-three patients with PAOS and 22 matched controls underwent diffusion MRI. Global WM differences in PAOS were better attained by intracellular volume fraction (ICVF), whereas GM global differences were better attained by mean diffusivity (MD) and isotropic volume fraction (isoVF). DTI and NODDI represent unique aspects of brain tissue microstructure and can be used as PAOS biomarkers.
Varied hemodynamic and metabolic responses of disease modifying and curative therapies in adults with sickle cell disease
Authors: Aumann Megan , Eisma Jarrod , Song Alexander , Waddle Spencer , Jones Sky , Juttukonda Meher , Patel Niral , Davis Samantha , Davis Taylor , Jordan Lori , Donahue Manus
Published: August 2024

Two common treatment paradigms for sickle cell disease (SCD) include oral medication hydroxyurea and blood transfusions. Rarely, a curative hematopoietic stem cell transplant (HSCT) is performed. We utilized non-invasive MRI to evaluate how potential biomarkers of infarct risk, cerebral blood flow (CBF) and oxygen extraction fraction (OEF), change in these treatment paradigms (cumulative n=39). Hydroxyurea treatment did not have significant changes to hemoglobin, CBF, or OEF between two scans. Hemoglobin increases by approximately 8.73 and 64.11% for adults with SCD on transfusion and transplant treatments, respectively. These changes most prominently parallel a reduction in CBF of 20.46 and 31.67%, respectively.
Can combined High-resolution and 3D-Arterial spin labeling MR differentiate moyamoya disease from arteriosclerotic moyamoya syndrome?
Authors: Guo Yu , Dou Weiqiang , Wang Xinyu , Wang Xinyi , Mao Huimin , Chen Kunjian
Published: August 2024

This study aimed to investigate whether the combined T1w-CUBE imaging and multiple post-labeling delay 3D pseudo-continuous arterial spin labeling imaging(MP 3D-PcASL)can distinguish moyamoya disease(MMD)from arteriosclerotic moyamoya syndrome(AS-MMS). 26 MMD patients and 25 AS-MMS patients were measured with T1w-CUBE imaging and MP 3D-PcASL. Significantly altered vessel wall in morphology and cerebral perfusion patterns were found on the lesions between AS-MMS and MMD. We thus concluded that the combined T1w-CUBE imaging and MP 3D-PcASL might help distinguish MMD from AS-MMS in clinic.
Quantitative Assessment of Hyperperfusion using ASL to Predict Hemorrhagic Transformation in Acute Ischemic Stroke Patients
Authors: huang jianbin , hao peng , chen zelong , deng kan , liu baoer , xu yikai
Published: August 2024

Hemorrhagic transformation (HT) is a potentially life-threatening complication in acute ischemic stroke (AIS) patients. We developed a quantitative of hyperperfusion on ASL and to evaluate its value in the prediction of HT in AIS patients. Our results indicated that CBFmax in hyperperfusion detected on pretreatment ASL was associated with subsequent HT and higher CBFmax was more likely to experience parenchymal hematoma (PH) in AIS patients. The assessment of CBFmax in hyperperfusion on pretreatment ASL may be available in routine clinical practice to further predict subsequent HT and enable timely intervention to prevent PH.
Does sex matter? A 1H MRS metabolic study in a mouse model of transient ischemic stroke
Authors: Buscemi Lara , Lepore Mario , Lê Thanh Phong , Hirt Lorenz , Mishkovsky Mor
Published: August 2024

A considerable sex bias exists in preclinical research, with studies on male animals outnumbering those in females, yet several preclinical rodent studies of transient middle cerebral artery occlusion (tMCAO) reported that infarct volume is smaller in females than in males. As the neurochemical profile greatly evolves after stroke, the present study aimed to evaluate whether the neurochemical profile is modified differently between male and female mice post tMCAO. We found that baseline values apart from taurine show no differences as previously reported. However, a difference in the metabolic profile between male and female mice becomes visible after tMCAO.
Radiomics Based on Diffusion and Perfusion MRI Image: New Prognostic Biomarkers in PCNSL patients
Authors: LI Liu , Zhang Jun , Ma Lin
Published: August 2024

Prognostic prediction based on clinical data and laboratory tests are facing reliability challenges for immunocompetent primary central nervous system lymphoma (PCNSL). In this study, we attempted to explore new prognostic biomarkers based on MRI-radiomics features to predict the outcomes in PCNSL. Our results showed that radio-score based on the ADC map and ASL was independent risk factors in OS and PFS predictions. Meanwhile adding radiomics features improved the model performance compared with traditional ones among which model based on ASL had better performance than ADC. So radiomics features can effectively classify different prognosis and improve the model performance in PCNSL.
Radiogenomic-based model identifies prognostic-related biological pathways in diffuse midline gliomas
Authors: Su Xiaorui , Yang Xibiao , Li Shuang , Shao Hanbing , Liu Yukun , Yue Qiang
Published: August 2024

To explore biological interpretation of prognosis-related radiomic signatures in diffuse midline gliomas, forty-one cases with paired MRI and RNA sequencing were screened in the public database TCGA-TCIA. We extracted radiomics features from preoperative MRI and divided these patients into high- and low-risk groups. Differential and enrichment analysis showed that high-expression genes of the high-risk group were mainly activated and involved in biological processes such as axon extension, neurotransmitter signaling, and cell connection. Moreover, typical driver molecular changes known in DMG were observed. It suggested that biological interpretation of prognosis-related radiomic signatures could be achieved by integrating MRI and RNA data
Accelerated 4D flow MRI in pediatric patients with congenital heart disease
Authors: Jooybari Fatemeh Rastegar , Huynh Christopher , Portnoy Sharon , Voutsas Jonathan , Balmer-Minnes Diana , Saprungruang Ankavipar , Yoo Shi-Joon , Lam Christopher , Macgowan Christopher
Published: August 2024

The application of conventional 4D flow to evaluate the hemodynamics of the heart and vessels is limited by long scan time. Recent advances aim to reduce scan time while providing sufficient accuracy. Here we investigate a 4D flow pipeline based on an undersampled 3D golden angle radial trajectory that offers reconstruction flexibility. We evaluated this technique in a cross-section of 11 pediatric patients with congenital heart disease and compared flows against conventional 2D phase contrast in target vessels.
Comparison of SAR Distributions around Epicardial and Endocardial Electrodes in Growing Pediatric Patients with Cardiac Pacemakers
Authors: Oguchi Reina , Fujimoto Kyoko , Shiraga Kazuhiro , Kuroda Kagayaki
Published: August 2024

RF-induced SAR distributions around epicardial lead were compared with endocardial lead in the 29-month-old and 6-year-old pediatric anatomical models with cardiac pacemakers. Numerical simulations were performed with a 1.5-T birdcage coil and the pacemaker models segmented from the age-matching patient CT data. In both pediatric models, the simulation with the endocardial lead overall showed lower SAR values compared to that with the endocardial lead. The screw-like electrode attached to the endocardial lead may have resulted in much higher SAR values, compared to the tined-type electrode of the epicardial lead.
View-Sharing and KWIC Filtering Achieves High Spatio-Temporal Resolution in 32-Fold Accelerated Real-Time Cardiac Cine with Radial Sampling
Authors: Fan Lexiaozi , Hong Kyungpyo , Robinson Joshua , Rigsby Cynthia , Kim Daniel
Published: August 2024

Highly-accelerated real-time cine MRI is a rapid technique that is particularly useful for patients with arrhythmia, dyspnea, and/or pediatric patients who may not be able to follow breath-hold instructions. Incorporating view-sharing (VS) and k-space weighted image contrast (KWIC) filtering into a compressed sensing (CS) reconstruction framework improves spatio-temporal resolution in our 32-fold accelerated real-time free-breathing cine MRI using radial k-space sampling. Resulting biventricular volumetric parameters are relatively accurate, which may eliminate the need for sedation/anesthesia in pediatric patients.
The development of Inter-/intra-volume motion correction algorithm for fMRI using a custom MRI acquisition with prospectively injected motion.
Authors: Shin Wanyong , Lowe Mark
Published: August 2024

In this study, we propose the new inter-/intra-volume motion correction algorithm. To test the proposed method, we modify simulated Prospective Acquisition CorrEcted (SIMPACE) EPI sequence and inject both inter- and intra-volume motion during actual EPI acquisition. Using ex-vivo brain phantom, we synthesize inter-/intra volume motion corrupted MR data. We evaluate the proposed method, compared to volume motion correction method. We find that the proposed inter-/intra-volume method outperforms volume motion correction method.
Detection and remediation of ghost artifacts in low b-value diffusion MRI with ghost re-synthetization and 4-way phase-encoded data
Authors: Thai Anh , Pierpaoli Carlo , Chang Lin-Ching , Irfanoglu M. Okan
Published: August 2024

We propose a novel post-processing method for ghost artifact correction in low-b diffusion weighted images (DWIs) using ghost synthetization and four different phase-encoding direction (PED) images. The results from both simulations and real data show that our method can robustly detect and correct ghost artifacts on b=0 s/mm2 images for artifact-free image. The proposed method can be used further to generate ground truth training images for a machine-leaning method to remedy ghost artifacts in single PED acquisition.
SPAMM Tagged EPI Acquisition for Assessment of Geometric Distortion Caused by an Endorectal Coil
Authors: Hwang Ken-Pin , Stafford R. , Bathala Tharakeswara
Published: August 2024

Diffusion weighted imaging is an essential sequence for diagnosis of prostate cancer but is often impacted by distortion. Current existing phantoms designed for assessing geometric accuracy do not sufficiently simulate the environmental factors that affect distortion in diffusion weighted EPI. In this work we apply a rectilinear tagging technique to visualize and understand patterns of distortion caused by an endorectal coil immersed in water when imaged with a PI-RADS compliant protocol. Maximum spatial distortion including regions of spatial collapse was observed near the coil element. Observed distortion pattern supports proper centering of the coil to avoid distortion.
Distortion-free diffusion imaging using single-shot diffusion-prepared TSE sequence with spiral-ring readouts and magnitude stabilizers
Authors: Wang Zhixing , Cao Xiaozhi , Qing Kun , Feng Xue , Mugler John , Meyer Craig
Published: August 2024

This study provides an alternative approach to conventional diffusion-weighted (DW) EPI-based sequences. A 2D single-shot (SS) diffusion-prepared (DP) turbo-spin-echo (TSE) sequence, combined with spiral-ring trajectories and magnitude stabilizers, dubbed “SS-DP-SPRING TSE”, was developed for distortion- and motion artifact-free diffusion imaging. Compared to a SS-DW-EPI sequence, this method is less sensitive to B0-inhomogeneity and thus provides DW-images with improved geometric fidelity.
Visualization of Perivascular Spaces using an Optimized 3D-TSE Sequence with Reduced Flip Angle at 7T
Authors: Saib Gael , Demir Zeynep , Taylor Paul , Talagala S. Lalith , Koretsky Alan P.
Published: August 2024

Perivascular spaces (PVS) dilatation has been recently linked to aging and neurodegenerative diseases. T2-weighted ultra-high field MRI allows to image the PVS burden at high contrast and spatial resolution non-invasively. However, most of sub-voxel sized PVS cannot be resolved due to partial volume effects and remaining signal from blood and tissue. High-resolution 3D-TSE with reduced flip angle allowed the visualization of PVS with a very high CSF-to-tissue ratio of ~37:1 at 7T.
XTE: The All-in-One Short-TE Imaging Sequence
Authors: Ilbey Serhat , Bock Michael , Özen Ali Caglar
Published: August 2024

XTE is a general implementation of various sequences, namely UTE, ZTE, SPI, PETRA, and gmPETRA. Each sequence type and their combinations can be realized within XTE by adjusting only a few parameters. We provide phantom and in vivo images acquired with XTE for different sequence settings.
Nonsusceptibility frequency contributions and brain size affect quantitative susceptibility mapping in a region-dependent manner
Authors: Jochmann Thomas , Salman Fahad , Adegbemigun Ademola , Haueisen Jens , Schweser Ferdinand
Published: August 2024

We studied the dependency of quantitative susceptibility mapping to scaling the resolution and amplitude in a brain phantom with and without tissue microstructure. We found that nonsusceptibility frequency contributions cause a resolution- and region-dependent bias to quantitative susceptibility mapping.
Automated Cardiac Quantification and Cardiomegaly Stratification: Feasibility of an AI-based Approach on Large-scale Non-Cardiac-Gated MRI
Authors: Nguyen Thanh-Duc , Garg Saurabh , Akbari Nasrin , Basar Saqib , London Sean , Chodakiewitz Yosef , Attariwala Rajpaul , Hashemi Sam
Published: August 2024

Despite its ubiquity, cardiac assessment at non-cardiac-gated MRI has yet to be standardized, leading to misdiagnosis. This paper examines the feasibility of AI for automatic 3D volumetric cardiac quantification used to detect and stratify cardiomegaly on non-cardiac-gated torso MRI. Using AI, we automatically measured the cardiothoracic ratio and 3D cardiac volumetric features as indicators for detections of cardiomegaly conditions. Large-scale results on 3485 normal-heart individuals revealed the effect of aging on cardiac features in both men and women. AI findings on non-cardiac-gated imaging offer opportunistic useful information, increasing the diagnostic precision, and allowing potentially useful imaging monitoring for cardiomegaly-associated conditions.
Automatic Couinaud segmentation in Intravenous-Phase Enhanced MRI images by key point detection with deep neural network
Authors: Miao Dong , Ren Xue , Zhao Ying , Liu AiLian , Yao Yu , Xu Qihao , Song Qingwei
Published: August 2024

This study presents an effective framework for automatic Couinaud liver segmentation in Intravenous-Phase Enhanced MRI images, without the time-consuming delineation of each segment or identifying different branches of the vessel system. We define seven key points located at the bifurcations of the vascular system to divide liver into Couinaud segments II-VIII. We train a key point detection model to locate the coordinate of key point. The overall dice score is 81.17% and average surface distance is 2.35mm in test set.
Noninvasive direct assessment of the left gastric vein using 4D flow MRI for risk stratification of esophageal variceal bleeding
Authors: Higaki Atsushi , Fukukura Yoshihiko , Kanki Akihiko , Yamamoto Akira , Moriya kazunori , Tamada Tsutomu
Published: August 2024

This study focused on the feasibility of 4D flow MRI with low-velocity encoding sensitivity as a non-invasive tool for direct estimation of the left gastric vein and stratification of bleeding risk of esophageal varices. Our study showed that the development of esophageal varices was associated with decreased and increased net flow volumes in the left gastric and azygos veins, respectively. These results suggest the promise of 4D flow MRI with low-velocity encoding sensitivity as a non-invasive and accurate method for stratifying the bleeding risk of esophageal varices.
Differentiating Chronic Prostatitis and Prostate Cancer Using a Continuous-Time Random-Walk Diffusion Model at High b-Values
Authors: Sheng Yurui , Xue Ke , Dai Yongming , Zeng Qingshi
Published: August 2024

In clinical practice, distinguishing between Prostate cancer (PCa) and chronic prostatitis (CP) is difficult but necessary. PCa and CP are heterogeneous at the tissue and cell level, and the continuous time random-walk (CTRW) model can provide information on tissue heterogeneity at the microscopic level. We used the CTRW model to characterize tissue heterogeneity and complexity in CP and PCa. Significant differences were found for the CTRW parameters (α, Dm) between CP and PCa. Moreover, CTRW parameters (α, β, Dm) combined with ADC showed optimal diagnostic efficacy for diagnosis, and this combination would be benefit for the clinical diagnostic work.
Correlation of Endolymphatic Hydrops and Perilymphatic Enhancement with Clinical Features of Ménière’s Disease
Authors: Li Jinye , Liu Mengxiao , Wang Linsheng , Li Chuanting , Sun Lixin , Liu Yafei
Published: August 2024

To investigate the correlation of the EH grade and PE with clinical features in MD, we evaluated their correlations by using the cubic spline models and multivariate analysis. We found that a nonlinear or linear correlation of EH grade and SIR with duration of disease-related symptoms and hearing thresholds. Additionally, the higher duration of vertigo and LFHT were associated with a higher EH grade, as well as duration of tinnitus and vestibular EH for SIR. Consequently, the grades of EH and the extent of PE in patients with MD can be evaluated by use of some clinical features and PTA.
Estrogen Deprivation has a Negligible Impact on Thalamic Metabolism under Central Sensitization
Authors: Richter Dayna , Holder Samuel , Craythorne Harrison , Grant Samuel
Published: August 2024

Previous examinations of the nitroglycerin (NTG)-based central sensitization, a chemical model of migraine, in the Sprague-Dawley model revealed increases in thalamic lactate signal. This held across sexes, albeit at different strengths. To investigate the potential source of any sex differences, estradiol deprivation is examined using 1H relaxation-enhanced spectroscopy localized to the thalamus. While the same energetic deprivation is seen, estradiol deprivation had negligible impact on the thalamic metabolic profile under NTG. Further examinations under alternate modalities are needed.
Ultra High Spatial Resolution MRI of Intact Ex Vivo Multiple Sclerosis Brain
Authors: Sakaie Ken , Sidhu Jagjit , Mahajan Kedar , Nakamura Kunio , Ontaneda Daniel , Trapp Bruce , Lowe Mark , Jones Stephen , Obusez Emmanuel
Published: August 2024

Treatment options for progressive multiple sclerosis (MS) are limited and the lack of sensitive and specific MRI biomarkers is a major hurdle in therapeutic development. A number of pathophysiological processes are repeatedly found on histology but are difficult to identify accurately on MRI. Ultra-high spatial resolution MRI of intact ex vivo brain promises to help bridge the gap between MRI and pathology. We demonstrate progress towards visualizing potential biomarkers for progressive MS.
Progressive Lactic Acidosis is Associated with Infarct Growth Volume in Acute Ischemic Stroke: A Longitudinal 3D MRSI Study
Authors: Bo Bin , Wang Tianyao , Meng Ziyu , Zhao Yibo , Li Yudu , Guo Rong , Jin Wen , Yu Xin , Liang Zhi-Pei , Li Yao
Published: August 2024

Imaging lactic acidosis is of significance for injury assessment in acute stroke. In this study, we investigated the progression of lactate, along with the concomitant changes in N-acetylaspartate and creatine concentrations, and its relationship to infarct growth using high-resolution MRSI data acquired from a longitudinal cohort of 42 ischemic stroke patients. The results showed that the progression in lactate level was predictive of infarct growth volume from acute to subacute stroke. Our study might provide a useful biomarker for lactic acidosis and tissue injury assessment in ischemic stroke.
The Relationship between MR Imaging Characteristics of Bilateral Carotid High-risk Plaques and Recurrence of Stroke
Authors: Xin Ruijing , Wang Maoxue , Zhang Bing
Published: August 2024

Carotid HRP is one of the major sources of ischemic stroke. Recent studies have focused on identifying characteristics of HRP which is defined as lesion with IPH, FCR, or LRNC. We compared the plaque characteristics of patients with bilateral carotid HRPs between patients with recurrent stroke and those without recurrent stroke using MR vessel wall imaging. We determined the association between HRP plaque features and recurrent stroke in patients with bilateral carotid HRPs. We found that those with larger plaque burden, more juxta luminal IPH and/or thrombus, and juxta luminal calcification in HRPs were more likely to have recurrent stroke.
A Preliminary study on evaluation of collateral compensatory by high-resolution CS TOF MRA and 4D flow：Case Series
Authors: Ma Yue , Jiang Yueluan , Tong Dan , Yu Zechen , Liu Xinpeng
Published: August 2024

Evaluation of hemodynamic and geometric changes of intracranial atherosclerosis and follow-up is of great clinical significance. A comprehensive quantification of the whole collateral recruitment in the circle of Willis (CW) is needed. In this work, we combined High-resolution CS TOF-MRA and 4D Flow MRI to investigate the situation of collateral recruitment. We were able to demonstrate a new way to visual and quantify the cerebrovascular impact of a significant intracranial stenosis and the compensatory mechanism of the collaterals.
The application of MTP synthetic sequence in the diagnosis of acute ischemic stroke
Authors: Chang Peipei , liang xinyue , Miao Yanwei , dai yongming
Published: August 2024

Multiple parametric (MTP) is a novel quantitative MRI technique that allows the generation of quantitative maps as well as synthetic weightings from a single acquisition. Preliminary results show that MTP synthetic sequence can effectively distinguish infarcted brain from normal tissue with a good diagnostic performance. MTP imaging offers the potential to create a standardized brain imaging protocol providing multiple types of quantitative tissue property information and qualitative information in just a few minutes. The aim of this study is to evaluate the potential of MTP in the mapping-based identification of acute ischemic stroke.
Texture analysis of mean apparent propagator-magnetic resonance imaging in distinguishing glioblastoma and solitary brain metastasis
Authors: Zhao Guohua , Su Yizhou , Lin Yusong , Dong Jie , Gao Eryuan , Ma Xiaoyue , Bai Jie , Zhang Huiting , Yan Xu , Yang Guang , Cheng Jingliang
Published: August 2024

Preoperative differentiation between glioblastomas (GBM) and solitary brain metastases (SBM) would aid in appropriate treatment planning and follow-up. Mean apparent propagator (MAP) MRI is effective in evaluating the inhomogeneity of brain microstructure. Texture analysis can be used to extract and quantify these inhomogeneities. In this study, we extracted the texture features from MAP-MRI, and validated the candidate features in discriminating between GBM and SBM. The RTAP model achieved the best discriminative power for the single metric model, and performed similarly to the MAP-MRI combined model. Texture analysis based on MAP-MRI has great potential to distinguish between the two entities.
Grading brain astrocytoma using convolutional neural network: contrast-enhanced T1 and susceptibility-weighted imaging
Authors: Chen Zong-Ze , Lai Yong-Han , Liao Ching-An , Huang Teng-Yi , Lai Ping-Hong , Chuang Tzu-Chao
Published: August 2024

Susceptibility-weighted imaging (SWI) has shown its potential to discriminate between high-grade and low-grade astrocytoma. In this study, we developed a fully automatic diagnosis system for astrocytoma grading by using convolutional neural network with contrast-enhanced T1-weighted images and SWI, separately or jointly, as input data. The results show that the model with both imaging modalities as input data provides high accuracy in astrocytoma grading and is potentially helpful for clinical diagnosis.
The application value of Radiomics combined with clinical features and genomics in predicting glioma survival
Authors: He Jinlong , Gao Yang , Wang Shaoyu , Zhang Huapeng
Published: August 2024

This study aimed to explore the value of MR multi-sequence radiomics combined with clinical features and genomics in predicting the survival of patients with glioma. Results showed that the clinical and imaging characteristics, radiomics features, and genotype status were important risk factors for glioma survival. The combination of multiple factors can better predict and evaluate the prognosis of glioma. Multi sequence based radiomics combined with clinical and imaging features and genotype status can better reflect the heterogeneity and prognosis of glioma.
Prediction of glioma genotypes by APTw-derived radiomic features combined with deep learning networks
Authors: Ren Xinying , Xiong Diaohan , Li Yujing , Ai Kai , Zhang Jing
Published: August 2024

The study aimed to predict glioma genotypes combined with radiomic features and deep learning networks by using amide proton transfer (APT) imaging. The genetic subtypes of gliomas can be predicted by radiomics and deep learning networks using conventional MRI, however there are still problems with low accuracy and insufficient generalization. This study puts the screened APT radiomics features into a neural network and compares it with traditional radiomic. The results demonstrated that the proposed model had better performance. Therefore, APTw-derived radiomic features have good ability to predict 3-class molecular typing, providing novel classification tool for non-invasive evaluation for glioma genotypes.
Identification of NF2 loss in meningiomas using T2-weighted MRI and Deep Learning
Authors: Bas Abdullah , Danyeli Ayca , Can Ozge , Ozduman Koray , Dincer Alp , Ozturk-Isik Esin
Published: August 2024

NF2-L in meningiomas is a relevant indicator of prognosis. NF2-L is one of the most common genetic mutations in meningiomas. As a result of that situation, developing a non-invasive approach may assist the current clinical procedures. To our knowledge, some studies try to predict NF2-L using MRI modalities but either they use registration or performed using the modalities of MRI that are not in default MRI scanning procedures. Hence, the solutions that they provide are not clinically feasible. In this study, we aim to develop new approaches that are capable to implement directly into clinical procedures.[1]
Self-Navigated Rapid Radial Free-Breathing Liver MR Elastography: Assessment of Technical Performance in Children at 3T
Authors: Kafali Sevgi , Bolster Bradley , Shih Shu-Fu , Delgado Timoteo , Zhong Xiaodong , Deshpande Vibhas , Adamos Timothy , Ghahremani Shahnaz , Calkins Kara , Wu Holden
Published: August 2024

Hepatic stiffness measured by MR elastography (MRE) is a biomarker for fibrosis. Standard liver MRE requires breath-holding (BH) to avoid motion artifacts, but BH is challenging for children. Radial free-breathing (FB) MRE can overcome this challenge but requires longer scan times. Radial FB-MRE using rapid wave encoding decreases the scan time and self-navigation supports motion compensation. With the help of fractional encoding to reduce echo times, image quality can be further improved. This work demonstrated that self-navigated rapid and rapid fractional FB-MRE methods measure hepatic stiffness with close agreement and similar repeatability compared to corresponding BH-MRE in children at 3T.
Magnetic resonance and diffusion tensor imaging of the adolescent rabbit growth plate of the knee
Authors: Kvist Ola , Damberg Peter , Dou Zelong , Berglund Johan Sanmartin , Flodmark Carl-erik , Nilsson Ola , Ruiz Sandra Diaz
Published: August 2024

The hindlimbs of female rabbits aged 16, 20, and 24 weeks were studied in a 9.4T MRI scanner to assess the ability of MRI-DTI to evaluate growth plate morphology and activity compared with that of histomorphometry and micro-computed tomography (μCT) in rabbits. The MRI sequences included a multi-gradient echo 3D sequence and DTI in 14 directions (b-value= 984 s/mm2). The growth plate height and volume were similar for all modalities at each time point and age. Tract number and volume declined with age; however, tract length did not show any changes. MRI-DTI may be useful for evaluating the growth plates.
Validating UTE-based Assessment of Bronchopulmonary Dysplasia at 3T
Authors: Iyer Narayan , Borzage Matthew , Doyle Eamon
Published: August 2024

Bronchopulmonary dysplasia (BPD) is the most common serious complication of prematurity affecting approximately 30,000 infants annually in the USA alone. Decisions regarding treatment course as well as prognostication require an understanding of regional lung changes. However, chest radiographs poorly distinguish the severity of BPD. Advances in ultra-short echo time imaging have made lung imaging feasible at clinically relevant field strengths. We have implemented a UTE-based imaging protocol at our institution and started validation in pre-term infants. Initial results demonstrate that clinically interpretable images can be acquired in an infant with BPD.
Investigating the Accuracy of PD Measurements at 3T
Authors: Pang Zach , Schmidt Maria , Kousi Evanthia , Hughes Julie
Published: August 2024

We investigated the accuracy of clinical proton density (PD) mapping employing the variable flip-angle (VFA) method at 3T, considering the effects of B1+ and B1- fields. Following B1+ correction, the PD measurements were within 5% of the expected value for flip-angle variations up to 18%. Considerable discrepancies were observed for T1<300ms and flip-angle variations >25%. Using image intensity filters, considerable PD variations were found at the edges of the test object. Clinically, the B1+ and B1- corrected PD values of the brain were similar to values reported in the literature, rendering the VFA method a viable tool for PD mapping.
Finding Precise, Direct, and Personalized Landmarks of Deep Brain Stimulus Tremor Targeting on Advanced MR imaging
Authors: Chung Sohae , Song Ha Neul , Lui Yvonne , Kopell Brian , Choi Ki Sueng
Published: August 2024

Deep brain stimulation (DBS) is an efficacious treatment for tremors. The clinical outcome is critically dependent on precisely personalized targeting, yet localization of DBS target remains challenging owing to difficulties in resolving individual thalamic nuclei or dentato-rubro-thalamic (DRT) pathways. Here we investigated retrospectively to identify neurosurgical landmarks of DBS targeting by examining the volume overlap and centroid distance between DBS contacts and DRT delineated from quantitative susceptibility imaging. Our findings show a significantly higher volume overlap of DBS contacts with DRT in the good-response tremor group, showing potential of our approach as a direct and personalized neurosurgical guidance tool.
Efficient fetal brain and placental T1 mapping at 0.55T
Authors: Verdera Jordina Aviles , Tomi-Tricot Raphael , Story Lisa , Hajnal Joseph , Rutherford Mary , Malik Shaihan , Hutter Jana
Published: August 2024

Fetal MRI provides crucial anatomical and functional information. At low field it could benefit from reduced distortion, increased bore size and increased B1 homogeneity. T1 contrast and mapping in the fetal brain provides complementary information for example for haemorrhages, infarcts and in placental disease. Here, a low-field (0.55T) fetal T1 inversion-recovery EPI-based sequence benefiting from the lower T1 and hence higher efficiency is demonstrated for placenta and brain in a cohort of pregnant participants including two clinical cases. Significant correlation with gestational age is demonstrated (p<0.05) and high quality maps allowing sub-regions analysis in the brain are shown.
Soma and neurite density imaging in multiple sclerosis reveals cortical cell body signal fraction loss associated with thalamic atrophy
Authors: Krijnen Eva , Russo Andrew , Karam Elsa Salim , Lee Hansol , Schoonheim Menno , Huang Susie , Klawiter Eric
Published: August 2024

Multiple sclerosis (MS) features complex microstructural changes in gray matter (GM) ranging from demyelinating lesions to neuronal loss. We hypothesize that GM microstructural metrics obtained from diffusion MRI can predict cortical and deep GM atrophy in MS. In this cross-sectional study of 41 people with MS, the soma and neurite density imaging (SANDI) compartment-based model was fitted to high-gradient diffusion MRI data acquired on the Connectome scanner. SANDI metrics were used to characterize MS-related microstructural pathology in cortical and deep GM. Cortical fsoma decreased with declining thalamic volume, suggesting a microstructural correlate of thalamic atrophy in MS.
Glymphatic system abnormality in systemic lupus erythematosus identified by diffusion tensor image analysis along the perivascular space
Authors: Mo Jiaying , Deng Kan , Tan Xiangliang , Xu Yikai
Published: August 2024

DTI-ALPS is an non-invasive method to measure glymphatic clearance function in brain. Here, we aimed to utilize DTI-ALPS to evaluate the activity of glymphatic system and explore its relationship with grey matter volumes in patients with SLE. Our results demonstrated that the ALPS-index are lower in SLE patients than that in healthy control group. And there were significant correlations between lower ALPS-index and smaller gray matter volumes in some brain regions in SLE group.
Abdominal MR Fingerprinting with In-bore Breathing Guidance
Authors: Lee Yoo Jin , Koken Peter , Sonnabend Kristina , Bratke Grischa , Heuvelink-Marck Annerieke , Doneva Mariya
Published: August 2024

MR fingerprinting (MRF) in the abdomen is challenging due to respiratory motion. In this study, as an alternative to a series of extended breath-holds which could be challenging especially for patients, visual and auditive in-bore breathing guidance was used during the MRF scans for better patient comfort. MRF sequences were designed based on predefined breathing patterns such that data are acquired only during exhale holds. The corresponding MRF dictionaries were calculated beforehand to enable real-time matching of quantitative maps. We demonstrate that MRF scans with guided breathing provide comparable abdominal T1 and T2 maps as those with breath-holds.
Deep learning optimization of CEST MR Fingerprinting (CEST-MRF) for Quantitative Human Brain Mapping
Authors: Cohen Ouri , Otazo Ricardo
Published: August 2024

CEST MR fingerprinting (CEST-MRF) enables fast quantitative relaxation and exchange mapping. The CEST-MRF signal depends on multiple acquisition and tissue parameters which makes optimization of the acquisition schedule challenging. The goal of this work is to develop a deep learning approach that uses a quantification network and a surrogate network to optimize the acquisition schedule for in vivo scans. Numerical simulations are used to characterize the optimized schedule and the benefits of optimization are demonstrated in vivo in a healthy subject. The optimized schedule can reduce scan time by 12% and provide better image quality than a randomly generated schedule.
Decoding of 3T and 7T bSSFP profile asymmetries for T1, T2, and fraction quantification in two-compartment systems
Authors: Plähn Nils , Mackowiak Adèle , Açikgöz Berk , Bastiaansen Jessica
Published: August 2024

A novel Off-Resonant encoded Analytical parameter quantification using Complex Linearized Equations (ORACLE) method using phase-cycled bSSFP profiles was developed. The approach decodes complex asymmetry profiles in multi-compartment systems for simultaneous proton fraction, T1/T2 ratio, T1 and T2 quantification. The approach was validated in simulations and in an acetone-water phantom at 3T and 7T. Simulations and experiments validated the proposed method for multi-parameter quantification using phase-cycled bSSFP for two compartment singlet systems with high accuracy and precision. This provides the first step towards proton fraction quantification of more complex multiplet-systems, such as fat or myelin, exploiting complex asymmetry profiles.
Split spin-echo acquisition for ultrashort T2* mapping: a simulation study
Authors: Zubkov Mikhail , Melchakova Irina
Published: August 2024

MRI serves as a non-invasive way of assessing the degree of iron overload. This is done via T2*-mapping commonly performed with muti-echo gradient echo sequences. This approach fails in cases with extreme iron overload where the relaxation times drop down to submillisecond range. A method allowing ultra-short T2* mapping is simulated, employing a temporal acquisition offset in a spin-echo pulse sequence. Two acquisitions are suggested: one – before the spin-echo centre, and another – after, resulting in two different T2*-weighted images, acquired with half-line radial encoding. This method allows obtaining T2*-weighted images with weightings starting effectively at zero echo time.
An improved postprocessing method for more accurate R2* measurements in the presence of macroscopic B0 field variations
Authors: Lee Chu-Yu , Lullmann Olivia , Steinbach Emily , Thedens Daniel , Harshman Lyndsay , Magnotta Vincent
Published: August 2024

Macroscopic field variations result in an overestimate of R2*. One common approach to correct the bias is to utilize a three-parameter fit; however, the fitting is subject to overfitting. This study presents a new two-stage fitting of the three-parameter model by assuming that the macroscopic field variation is slowly varying in space. Using a numerical simulation and in vivo mice data, we demonstrate that the proposed method allows for a more accurate R2* measurement, and is less sensitive to noise.
Reduction of ADC bias with deep learning-based acceleration in diffusion-weighted MRI: A phantom validation study
Authors: Nolte Teresa , Yoneyama Masami , Morsch Chiara , Barabasch Alexandra , Schulze-Hagen Maximilian , Peeters Johannes , Kuhl Christiane , Zhang Shuo
Published: August 2024

Further acceleration of diffusion MRI in clinical examinations is desired but challenging mainly due to low signal and associated potential bias in the quantitative apparent diffusion coefficient (ADC) values. Artificial intelligence-based denoising and image reconstruction may provide a solution to address this challenge. We investigate and compare different image reconstruction methods, including conventional parallel imaging, compressed sensing, and a deep learning-based technique, in ADC accuracy and precision using a diffusion phantom with illustration of the principle in numeric simulation.