bluuebunny/crossref_metadata_2025 huggingface dataset:
Water/Fat separation with spatio-temporal EPI-based acquisition and reconstruction in body imaging
Authors: Zhou Xuetong , Lee Philip , Hargreaves Brian
Published: August 2024

Water/fat separation is a reliable fat suppression technique. However, it is challenging in EPI-based imaging due to the large displacement along phase-encoding direction. We demonstrate the artifacts resulting from the poor-conditioning reconstruction of water/fat separation with EPI-based acquisition in body imaging. As a solution, unlike conventional multi-echo acquisition methods, our approach encodes the spectral components (water/fat) by acquiring and reconstructing the spatial and echo-time dimensions jointly. EPTI sampling trajectories and water/fat masking were used to improve the conditioning of the reconstruction. Phantom and in vivo (brain and breast) experiments were performed to show both results and limitations of this approach.
High resolution 4D-cine MRI of pulsatile aneurysmal motion with radial acquisition at 7T
Authors: Akasaka Thai , Fujimoto Koji , Cloos Martijn , Okada Tomohisa , Urayama Shinichi , Tadashi Isa
Published: August 2024

The pulsation of intracranial aneurysms (IAs) is a novel risk factor of rupture. We aim to visualize the pulsation of IAs with 7T MRI using GRASP, a relatively novel MRI technique that provides high spatial and temporal resolution. Using thsis method, we were able to depict the pulsation of an aneurysm phantom as a 4D-cine movie. This technique may be useful in predicting the probability of IA rupture more accurately.
Non-contrast high-resolution 4D-peripheral MR angiography using retrospective echo planar imaging with Compressed SENSE
Authors: Goto Yasuhiro , Nagao Michinobu , Yoneyama Masami , Peeters Johannes M , Katsumata Yasutomo , Shiina Isao , Kodaira Kazuo , Hamatani Yutaka , Ogawa Takumi , Kato Mana , Sakai Shuji
Published: August 2024

In this study demonstrated that the higher reduction factor (R=10.0) with a one-minute scan still provided sufficient image quality with significantly faster scan time compared with conventional REPI-SENSE. REPIX would be useful for further assessment of PAD pathology even with multiple VENC acquisitions still in a clinically feasible scan time. REPIX 4D-MRA well depicted peripheral arteries clearly in a significantly short time thanks to Compressed SENSE, compared with conventional SENSE.
Dual Domain Deep Learning Framework for Cardiac MR Image Reconstruction
Authors: Najeeb Faisal , Arshad Madiha , Shafique Muhammad , Omer Hammad
Published: August 2024

Most deep learning methods apply U-Net either in image or k-space domain. Nevertheless, these methods have limitations: (1) Directly applying U-Net in k-space domain is not optimal for extracting features; (2) conventional image-domain oriented U-Net does not fully utilize the information of encoder part of the network for extracting features in the decoder part. In this paper, a dual-domain deep learning-based approach is presented, incorporating multi-coil data consistency layers for the reconstruction of cardiac MR images from 1-D Variable Density (VD) under-sampled data. Experiments show superior reconstruction results of the proposed method than conventional Compressed Sensing (CS) method.
FIRE and MATLAB for Free-Breathing Segmented LGE – A Novel Sequence and Reconstruction Approach for Selecting and Correcting Data by Respiration
Authors: Rehwald Wolfgang , Chow Kelvin , Rojas Rafael , Mena Nestor , Alexandrov Diana , Gamoneda George , Wendell David , Seward Ryan , Dement Jeana , Kimbrell Vera , Kim Han , Borgohain Indraneel , Klem Igor , Kim Raymond
Published: August 2024

We introduce a free breathing segmented LGE technique combining a new acquisition, reordering and reconstruction scheme. The on-scanner reconstruction uses MATLAB and FIRE. The method produces image quality (IQ) and SNR otherwise only obtainable with breath held segmented interleaved LGE. In 27 patients, we show that IQ is superior to free breathing segmented interleaved LGE with multiple averages. SNR is higher compared to averaged motion corrected single shots when matching spatial and temporal resolution, the number of used measurements per image, and the readout type. Being a segmented technique, temporal and spatial resolution limitations of single shots do not apply.
4D Cardiac MR Image Reconstruction by Deep Learning with Wavelet Transform
Authors: Zhang Junhao , Zhao Yujiao , Hu Jiahao , Ding Ye , Men Christopher , Lau Vick , T.L.Leong Alex , Wu Ed X.
Published: August 2024

We present a CNN-based deep learning model to reconstruct the cardiac cine images from undersampled single-channel 4D MR data. The wavelet transform and spatial-temporal attention mechanisms are introduced in the model. The proposed model could reconstruct the cardiac images and recover the cardiac wall motion more robustly than the low-rank plus sparsity (i.e., L+S) reconstruction method. This approach presents one promising solution for accelerated cardiac dynamic imaging with one single channel through deep learning from the sparsity in spatial and temporal domains.
Improved diagnostic efficacy on structural abnormalities of knee using high-resolution deep learning-based 2D FSE images
Authors: Wu Xiaxia , Liu Weiyin , Zha Yunfei
Published: August 2024

Diagnostic performance was limited to image resolution and contrast between target tissues and surrounding tissues. A rapid knee imaging has been perused but no loss of image quality is critical. This study proposed a rapid knee imaging based on two-dimensional fast spin echo sequence and examined the reliability and diagnostic performance of deep learning-based reconstruction T1-, T2- and PD- weighted images on knee joint pathology via comparison of images with and without deep-learning reconstruction algorithm (DLR). Diagnostic efficacy on knee structural abnormalities of 2D DLR FSE sequence elevated using knee arthroscopy results as the gold standard.
Accelerating 7T susceptibility-weighted imaging with complex-valued convolutional neural network
Authors: Duan Caohui , Bian Xiangbing , Cheng Kun , Wang Xiaoyu , Lyu Jinhao , Wang Xueyang , Qu Jianxun , Zhou Xin , Lou Xin
Published: August 2024

Ultra-high field 7T susceptibility-weighted imaging (SWI) has shown great potential in visualizing and evaluating a broad range of pathology, but suffers from long acquisition times. In this study, a complex-valued convolutional neural network (ComplexNet) model was proposed to reconstruct highly accelerated 7T SWI data. The average reconstruction time of ComplexNet was 0.56 seconds per slice (45.16 seconds per participant). Meanwhile, ComplexNet can provide high-quality 7T SWI for visualizing subtle pathology, including cerebral microbleeds, asymmetric deep medullary veins, and swallow tail sign.
Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LT$$$^2$$$LR-Net)
Authors: Zhang Yinghao , Li Xiaodi , Li Peng , Hu Yue
Published: August 2024

Tensor low-rank models have recently emerged as powerful alternative representations for three-dimensional dynamic MR datasets. In this paper, we introduce a novel learned transform-based tensor low-rank network for dynamic MRI based on the tensor singular value decomposition (t-SVD). Instead of manually designing the t-SVD-based transform, we propose to utilize CNN to adaptively learn the relatively optimal transformation from the dynamic MR dataset for more robust and accurate tensor low-rank representations. Experimental results on cardiac cine MRI reconstruction demonstrate the superior performance of the proposed framework compared with the state-of-the-art methods.
Digital Reference Objects with BART
Authors: Scholand Nick , Schilling Martin , Heide Martin , Uecker Martin
Published: August 2024

Digital Reference Objects (DRO) are important for developing imaging and reconstruction techniques especially in medical imaging applications. They allow a stepwise increase in complexity during testing of methods by simulating reproducible datasets. In this work we present a variety of tools the BART toolbox provides for the creation and simulation of DROs. We present a workflow for designing DROs with Bézier curves using vector graphics applications which are then imported into BART. Furthermore, we show simulation of analytical k-space data with 2D and 3D coil sensitivities and combining them with simulated signal curves to obtain k-space data for complex scenarios.
Pharmacokinetic Modelling of Gd-EOB-DPTA Uptake: Early Progression of NASH in A Clinically Relevant Cohort, at 1.5 and 3 T
Authors: Simonsson Christian , Dahlström Nils , Karlsson Markus , Cai Shan , Ignatova Simone , Nasr Patrik , Ekstedt Mattias , Kechagias Stergios , Lundberg Peter
Published: August 2024

Due to the increased global prevalence of non-alcoholic fatty liver disease (NAFLD), there is a significant need for precise and non-invasive clinical methods to detect early stages of non-alcoholic steatohepatitis (NASH), which can progress to cirrhosis. We investigate the possibility of using the hepatocyte specific contrast agent Gd-EOB-DPTA based DCE-MRI in combination with mathematical modelling to assess hepatobiliary influx, as a possible biomarker for early NASH detection. We show a tentative correlation between increased portal inflammation and decreased hepatic Gd-EOB-DPTA uptake in a cohort of prospectively included patients with suspected chronic liver disease.
Diffusion Metrics for Staging Liver Fibrosis: An Experimental Study in Rats with Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI
Authors: Lu yimei , Wang qianfeng , Wang dengbin
Published: August 2024

As a common pathological feature of chronic liver diseases, liver fibrosis is a significant cause of global morbidity and mortality. An accurate assessment of the fibrosis stage and early detection of hepatic fibrosis are essential for preventing further adverse consequences. Our study suggests diffusion metrics are useful tools for noninvasively staging liver fibrosis. Among them, MK is a more valuable imaging biomarker for evaluating the degree of liver fibrosis, and f is less consistent in our two fibrosis models.
Optimization of Saturation Power for pH-enhanced MRI in Stroke Rodents
Authors: Chung Julius , Jin Tao
Published: August 2024

The sensitivity of CEST to pH makes it a potential modality for the assessment of intracellular pH alterations under pathologic conditions. We previously introduced a method for pH-enhanced MRI using amide and guanidyl protons. In this study, we determine saturation powers for imaging both exchangeable protons to optimize either contrast or contrast-to-variation ratio (CVR) between healthy and infarcted tissue in stroke rats. The contrast across parameters remained steady at ~2-3%, while CVR was dominated by variation across ROIs due to residual non-specific contrast. Optimizing CVR minimizes contrast within the lesion and contralesional tissue while preserving contrast between the two tissues.
A Steady State Free Precession CEST Sequence with Short Saturation at 3T Human Scanner
Authors: Liu Chuyu , Li Yifan , Li Zhongsen , Song Xiaolei
Published: August 2024

In this study, we proposed a steady state free precession CEST sequence with short saturation at 3T scanner. Our contributions are: 1) We investigated the SSFP process containing chemical saturation pulses and gave an approximate analytic solution. 2) Simulation and phantom results revealed that the proposed SSFP-CEST sequence had higher SNR and higher saturation efficiency than previous steady-state CEST, while the acquisition time was relatively short.
Baseline cerebral structural morphology predicts future freezing of gait in early drug-naïve Parkinson’s disease
Authors: Li Yuting , Ruan Xiuhang , Xu Yongzhou , Wei Xinhua
Published: August 2024

We developed a model that could predict the occurrence of Freezing of gait (FOG) at the individual level using machine learning with the clinical, laboratory, and cerebral structural imaging information of early drug-naïve Parkinson’s disease (PD) patients. Data from 158 early drug-naïve PD patients at baseline were obtained from the Parkinson’s Progression Markers Initiative cohort. The predictive performance of future FOG in early PD was evaluated using elastic net-support vector machine models. T1WI morphometric markers have the potential to help predict future FOG in patients with early PD at an individual level, with improved performance when integrated with clinical variables.
Reproducibility of Iron and Neuromelanin Changes of Deep Grey Matter in 2 Large Movement Disorder Cohorts
Authors: He Naying , Haacke Ewart , Wang Ying , Zhang Youmin , Wang Xinhui , Jin Zhijia , Li Yan , Wu Peng , Yan Fuhua
Published: August 2024

Diagnosing movement disorders (MDS) is a major challenge clinically. Neuromelanin and iron serve as biomarkers for MDS but few studies have evaluated a large number of cases for multiple disorders. We studied 614 patients consisting of two cohorts with different resolutions. The QSM and NM-MRI data were automatically processed using a unique template program. The results from both cohorts showed reproducible changes of iron and neuromelanin in the deep gray matter. Specifically, a loss of neuromelanin volume, an increase in iron content of the SN for both PD and MSA; increased RN iron and decreased putamen volume in MSA.
Retrospective Comparison of Brain Imaging in Patients at 0.55T and 1.5/3T
Authors: Lavrova Anna , Kim John , Lobo Remy , Masotti Maria , Richardson Jacob , Itriago-Leon Pedro , Gulani Vikas , Wright Katherine , Srinivasan Ashok , Seiberlich Nicole
Published: August 2024

This study aims to compare the image quality of clinical brain imaging on an FDA-approved commercial low-field 0.55T MRI scanner and conventional higher field 1.5/3T MRI systems. The image quality of 205 compatible image series in 30 patients acquired at 0.55T and 1.5T/3T MRI systems was rated by two neuroradiologists. Despite significant differences in image quality ratings between low- and higher-field scanners, all brain sequences performed at 0.55T received ratings indicating that they were acceptable for diagnostic use. This work indicates that the commercial 0.55T system can be used for routine brain imaging in clinical practice.
Effects of radiotherapy on tissue in patients with brain metastases in terms of OEF and CMRO2
Authors: Leeuw Jordi , Cho Junghun , van Grinsven Eva , Siero Jeroen , Philippens Marielle , Bhogal Alex
Published: August 2024

Radiotherapy might have an influence on the ratio of deoxygenated versus oxygenated blood in the venous blood vessels (OEF) in the brain. The relationship between delivered dose and the OEF may be a more direct measure of tissue damage or recovery. Preliminary results suggest that there is a marginal significant increase in OEF values after radiotherapy. This indicates that OEF can be of valuable use in determining the effects of radiotherapy. Additionally, CMRO2 maps show an identical increase or decrease in cerebral metabolic activity. Keywords: Oxygen extraction fraction Cerebral metabolic rate of oxygen extraction Radiotherapy Brain tumor
Evaluation of lymphovascular space invasion in endometrial carcinoma by APTw and mDIXON-Quant
Authors: Zongyuan Xie , Shifeng Tian , Ailian Liu
Published: August 2024

Lymphovascular space invasion(LVSI)is one of the important factors for poor prognosis of endometrial carcinoma(EC). Quantitative parameters of amide proton transfer weighted(APTw)and Modified Dixon quantification of fat(mDIXON-Quant) is a novel MRI tool to evaluating LVSI in EC. The APT and R2* values of LVSI(+)EC were higher than those of LVSI(-)EC. APT value was moderately positively correlated with R2* value, and APT value was weakly positively correlated with FF value. Both APTw and Mdixon-Quant techniques can effectively evaluate EC LVSI, and their combined application can improve the evaluation efficiency.
The value of multimodal functional magnetic resonance imaging in differentiating p53abn from p53wt endometrial carcinoma
Authors: Zongyuan Xie , Shifeng Tian , Ailian Liu
Published: August 2024

p53 genotyping is important for EC lymph node metastasis and prognosis determination. Multimodal MRI techniques APTw, T2 mapping, mDIXON-Quant and DWI are new tools to determine p53 genotyping. Results of this study indicate the APT value and R2* value in the p53abn group were higher than those in the p53wt group, while the ADC value was lower than those in the p53wt group. Therefore, APTw, mDIXON-Quant and DWI techniques can quantitatively identify p53abn and p53wt EC, it provides a new way for preoperative quantitative evaluation of EC molecular typing.
The value of APT combined with squamous cell carcinoma antigen in predicting parametrial invasion of stage IA to IIB cervical cancer
Authors: Zhang Mengdi , Han Qinghe , Yuan Qinghai , Ma Rui , Lian Jianxiu
Published: August 2024

Cervical cancer is one of the most common gynecological malignancies. The accurate diagnosis of cervical cancer is of great significance for the selection of treatment plan. This study is to explore the diagnostic value of the new magnetic resonance technology of amide proton transfer-weighted(APTw) imaging combined with squamous cell carcinoma antigen (SCCA) for parametrial invasion(PMI). The results showed amide proton transfer-weighted(APTw) imaging could provide more valuable for diagnosis efficiency, which maybe an invasive alternative method for evaluating parametrial invasion.
Simultaneous Neuromelanin Sensitive Imaging and Quantitative Susceptibility Mapping by 3D Multi-echo GRE sequence with Optimized MTC Pulse
Authors: Chen Mengying , Wu Yupeng , Pang Qifan , Zhong Haodong , Li Gaiying , Song Yang , Wang Yi , Li Jianqi
Published: August 2024

Although 3D magnetization transfer contrast (MTC) GRE sequence can image neuromelanin and magnetic susceptibility simultaneously, MTC saturation pulse takes too long time, and whether MTC affects accuracy of the susceptibility is unclear. Six subjects were scanned using 3D multi-echo GRE sequences with different durations of MTC pulse. 3D GRE sequence with 5ms of MTC pulse provided same saturation effects in highlighting neuromelanin as 10ms of MTC pulse, and yielded susceptibility values in the deep gray matter nuclei similar to sequence without MTC pulse. Short MTC pulse provides a practical means to simultaneously image the neuromelanin and magnetic susceptibility.
Demonstration of B1 mapping based RF shimming for CEST imaging at 7T
Authors: Demetriou Eleni , Dimitrov Ivan , van Zijl Peter , Hoogduin Hans , Vinogradov Elena , Zhang Bei , Henning Anke
Published: August 2024

In this work, we sought to evaluate CEST in combination with RF shimming that is based on the modulation of the amplitudes and phases of the RF pulses transmitted by an eight channel 7T MR system.
Bloch-McConnell Simulation for Arterial Blood Contrast at 3T and 7T: Adiabatic Null Passage vs Binomial Magnetization Transfer Preparation
Authors: Abbasi-Rad Shahrokh , Norris David
Published: August 2024

Arterial blood contrast (ABC) uses on-resonance binomial pulse for magnetization transfer preparation to saturate the tissue signal and highlights the contribution of arterioles. Previously, using Bloch-McConnel simulations, we showed that Binomial MT contaminates ABC with T2 contrast. We suggested the use of adiabatic null passage to decrease the T2 effect. We performed Bloch-McConnel simulations at 3T and 7T comparing the performance of binomial and ANP pulses. ANP increased the arterial contribution from 32% to 42% at 3T and from 18% to 30% at 7T. This study concludes that ANP reduces the T2-contamination imposed by binomial MT block and improves ABC.
Ultrafast submillimeter model-based NN quantification of whole-brain T1 and T2 using phase-cycled bSSFP
Authors: Birk Florian , Scheffler Klaus , Heule Rahel
Published: August 2024

The bSSFP sequence is intrinsically sensitive to T1 and T2, motion robust, and allows highly efficient data acquisition. Slow convergence in qMRI parameter fitting can potentially be mitigated by machine learning, which benefits greatly from the availability of accurate ground truth data. This work presents an unsupervised model-based NN that incorporates the analytical bSSFP signal equation into the training loop, thus avoiding the need for ground truth relaxometry measurements and enabling instantaneous multi-parametric submillimeter whole-brain mapping of T1 and T2. NN performance was compared to MIRACLE quantitatively for in silico noise corrupted data and qualitatively for in vivo data.
Laminar effective connectivity of the default mode network assessed using 7T fMRI
Authors: Huynh Nguyen , Deshpande Gopikrishna
Published: August 2024

High-resolution fMRI presents opportunities in the study of fine-scale functional architecture, such as directional interactions between cortical layers. The Default Mode Network (DMN) is a major network in the brain associated with many social behaviors, however, little is known about the feed-forward and feedback information flow between different layers in regions of the DMN. We used high-resolution fMRI combined with effective connectivity to investigate the layer-to-layer interactions of regions in the DMN including medial prefrontal cortex, posterior cingulate cortex, and inferior parietal cortex. The results suggest that the middle layers of PCC are dominant in information flow within the DMN.
Clinical deployment of novel quantitative neuro-image analysis techniques using containerisation technology
Authors: Moggridge James , Vos Sjoerd , Prados Ferran , Grech-Sollars Matthew , Matthews Daniel , Schmidt Peter , Alexander Daniel , Duncan John , Barkhof Frederik , Yousry Tarek , Thornton John
Published: August 2024

The challenges encountered in development and clinical deployment of quantitative neuroradiological software techniques for in-house use can be overcome to some degree, through the application of a multi-disciplinary approach, and the use of containerisation. However, full life-cycle support including post-market surveillance presents a more significant obstacle.
Mapping sodium relaxation parameters in brain using magnetic resonance fingerprinting at 7T
Authors: O'Donnell Lauren , Rodriguez Gonzalo , Lemberskiy Gregory , Yu Zidan , Dergachyova Olga , Cloos Martijn , Madelin Guillaume
Published: August 2024

We present a new MRF technique for simultaneous mapping of sodium T1, biexponential T2*, ion density, B+1 shift and B0 in the brain at 7T. This is accomplished using a 23 pulse MRF train combined with a UTE FLORET trajectory readout. Our technique is demonstrated in a 3 compartment phantom and in vivo across four healthy volunteers. Matching to a dictionary with over 800,000 signals produced parameter maps with good agreement to literature values. Flow and partial volume effects may interfere with matching T*2,short in CSF.
Modality-adaptive Network Learning for Brain Tumor Segmentation with Incomplete Multi-modal MRI Data
Authors: Li Haoran , Li Cheng , Huang Weijian , Wang Yeqi , Zhang Yu , Liu Xue , Zheng Hairong , Wang Shanshan
Published: August 2024

Automated brain tumor segmentation with multi-modal magnetic resonance imaging (MRI) data is crucial for brain cancer diagnosis. Nevertheless, in clinical applications, it is difficult to guarantee that complete multi-modal MRI data are available due to different imaging protocols and inevitable data corruption. A large test time performance drop could happen. Here, we design a modality-adaptive network learning method to extract common representations from different modalities and make our trained model applicable to different data-missing scenarios. Experiments on an open-source dataset demonstrate that our method can reduce the dependence of deep learning-based segmentation methods on the integrity of input data.
Uncertainty-based Quality Control for Subcortical Structures Segmentation in T1-weighted Brain MRI
Authors: Lambert Benjamin , Forbes Florence , Doyle Senan , Tucholka Alan , Dojat Michel
Published: August 2024

The performance of Deep Learning (DL) models may drastically drop in the presence of characteristics in test images not present in the training set. Then, the automatic detection of these Out-Of-Distribution (OOD) inputs is important to deploy these methods especially for clinical applications. We address this issue in the context of DL-based subcortical structures segmentation on T1w brain MRI. We compare two OOD detection frameworks equipping DL segmentation models, Maximum Softmax Probability and Deterministic Uncertainty Method, and demonstrate the superiority of the latter which allows a robust and versatile identification of artifacts in images.
Network analysis reveals differences in the topology of structural brain networks of young asymptomatic APOE-epsilon4 carriers
Authors: Messaritaki Eirini , Lancaster Thomas , Tansey Katherine , Jones Derek
Published: August 2024

This work explores the link between the topological properties of brain structural networks and APOE-epsilon4 in young asymptomatic adults. We investigated the sensorimotor, visual and default-mode networks. We found evidence that there are differences in the mean clustering coefficient of the sensorimotor network of carriers versus non-carriers, with the left caudal middle frontal, left precentral, right postcentral and right precentral gyri driving the differences. Interestingly, the mean clustering coefficient was higher in carriers compared to non-carriers. In contrast, no differences were found for the visual or the default-mode networks.
Mapping Connectivity of the Nucleus Basalis of Meynert in Alzheimers using fMRI and probabilistic tractography
Authors: Becerra Sergio , Jordan Kaya , Haroon Jon , Mahdavi Kennedy , Jordan Sheldon , Surya Rama , Rindner Elisabeth
Published: August 2024

The nucleus basalis (NBM) is the major source of cholinergic innervation to the cerebral cortex, hippocampus and other subcortical structures. Focusing DTI and fMRI on the NBM can shed light on the potential state of subjects with Alzheimer’s disease. We aim to use DTI to provide insight into the white matter projections from the NBM and use fMRI to depict how it is functionally wired. We found that imaging of the NBM differentiated dementia patients from controls, and captured the level of cognitive decline. While the results are preliminary, this analysis introduces a method of observing the progression of AD.
Accelerating 3T MRI standardized protocol for detection of Amyloid Related Imaging Abnormality (ARIA) using Philips SmartSpeed
Authors: Ganji Sandeep , Johnson Brian , Waddle Spencer , Peeters Johannes , Mechtler Laszlo , Pinter Nandor
Published: August 2024

Amyloid Related Imaging Abnormality (ARIA) was reported in 40% of patients treated with anti-amyloid beta drugs in phase 3 trials. It is expected to be a significant factor in the clinical application of new Alzheimer’s Disease (AD) modifying therapies and requires standardized and practical imaging. By employing Compressed-SENSE (CS-SENSE) and newer deep learning based SmartSpeed to accelerate acquisition we created a robust MRI protocol that can be completed in under ten minutes without loss of any image quality. This accelerated protocol can provide a clinically feasible strategy for scanning large populations.
Intrinsic brain abnormalities in chronic rhinosinusitis and the effect of mood and cognitive function: a resting-state functional MRI study
Authors: LIN SIMIN , NIE MIAOMIAO , WANG BINGSHAN , HAN YI
Published: August 2024

Chronic rhinitis (CRS) is one of the most prevalent chronic diseases that increases the risk of anxiety, depression and cognitive disorders. Here we collected rs-fMRI data to assess global brain activity and functional connectivity (FC) in CRS patients. Compared with controls, CRS patients demonstrated increased ALFF in the left orbital superior frontal cortex and decreased FC in the right precuneus cortex, with the former positively correlated with the severity of inflammation and the scores of anxiety and depression. These rs-fMRI studies provided several important hints into the potential neural mechanism related to mood and cognitive dysfunctions in CRS patients.
Altered intrinsic brain functional network dynamics in drug-naïve, first-episode adolescents with major depressive disorder
Authors: Wu Baolin , Jia Zhiyun , Gong Qiyong
Published: August 2024

This study aimed to explore the dynamic FC in adolescent MDD patients, with a focus on the temporal properties of functional connectivity states as well as the variability of network topological organization. We found that adolescent MDD patients spent more time in the weakly-connected and relatively highly-modularized State 1, spent less time in the strongly-connected and low-modularized State 2, and had higher variability in the network efficiency than healthy controls. These findings suggest impaired local segregation and global integration of functional networks, as well as segregation-integration imbalance in adolescent MDD patients.
Anesthetic modulation of water diffusion: Insights from a diffusion tensor imaging study
Authors: Peng Shin-Lei , Huang Sheng-Min , Chan Chun-Chieh
Published: August 2024

A critical step in animal diffusion tensor imaging (DTI) studies is the use of anesthetics. Understanding the influence of specific anesthesia regimes on DTI-derived parameters is imperative when comparing results between animal studies using different anesthetics. Here, the quantification of fractional anisotropy (FA) and mean diffusivity (MD) under different alpha-chloralose and isoflurane is discussed. The estimated MD under isoflurane anesthesia is higher than that under alpha-chloralose anesthesia. FA quantitation was also influenced by anesthesia regimens to varying extents, depending on the brain regions and b-values. In summary, both scanning parameters and the anesthesia regimens significantly impacted quantifications of DTI indices.
Non-exponential transverse relaxation in the brain’s basal ganglia
Authors: Oliveira Rita , Raynaud Quentin , Kiselev Valerij , Jelescu Ileana , Lutti Antoine
Published: August 2024

Non-exponential transverse relaxation in the brain’s basal ganglia has been investigated in theoretical studies but little evidence from in-vivo MRI data exists in support of this behaviour. Here, we provide experimental observation of non-exponential transverse relaxation in-vivo MRI data in the basal ganglia at 3T. The strongest deviations from exponential behaviour take place in the iron-rich pallidum and substantia nigra. Our results suggest that water diffusion through the inhomogeneous magnetic field induced by paramagnetic iron deposits may be at the source of non-exponential transverse relaxation in the basal ganglia.
Time dependent diffusion and kurtosis of human brain metabolites
Authors: Döring André , Rösler Frank , Şimşek Kadir , Afzali Maryam , Kreis Roland , Jones Derek , Valette Julien , Palombo Marco
Published: August 2024

This work demonstrates that metabolites diffusion and kurtosis time-dependence can be measured in vivo in the human brain using Diffusion-Weighted MR Spectroscopy (DW-MRS) and ultra-strong gradients. At short diffusion-times, DW-MRS is sensitive to cytoplasmic viscosity and short-range structures; at long diffusion-times to long-range structures. We show that modeling the diffusion-time dependence of intracellular and cell-type specific metabolites can be used to infer brain cell morphology and recover fiber radii consistent with healthy human brain histology. Furthermore, we show that water diffusion at long diffusion-times is affected by exchange between intra- and extracellular compartment, which poses challenges for microstructural modeling.
High resolution diffusion tensor imaging shows non-linear trajectories in the human cortex over the healthy lifespan
Authors: Acosta-Franco J. Alejandro , Little Graham , Beaulieu Christian
Published: August 2024

The brain cortex is thin and has a complex morphology making it difficult to analyze with in vivo diffusion MRI. A high-resolution 1.5 mm isotropic diffusion MRI protocol and an automated cortex segmentation methodology on the diffusion images alone was used to assess cortical diffusion changes over the healthy lifespan (n=165, 5-74 years). The diffusion metrics versus age trajectories differed across the cortical surface despite similar cortical thickness reductions with age. The most robust age changes were for axial diffusivity (quadratic U) and radiality (cubic) potentially reflecting changes in columnar microstructural organization of the cortex in typical development and aging.
White matter macrostructure simultaneously predicts perceived rejection and cognitive inflexibility in late life
Authors: Wolfe Tatiana , Salmon Carlos Ernesto Garrido , James G. Andrew , Dunn Laura , Kilts Clint
Published: August 2024

The interplay between brain white matter health and cognitive flexibility in late life is intimate. Understanding the age-related patterns of white matter disintegration along the cingulum network will aid in elucidating factors underlying individual susceptibility to psychiatric illness related cognitive flexibility impairment. We evaluated Bayesian Pearson correlations between a measurement of T1/T2-FLAIR kurtosis and psychiatric risk factors available in a UK Biobank sample. Our findings strongly suggest (BF10>100) that MRI apparent integrity loss in the cingulum, uncinate fascicles and corticothalamic fibers is a significant corollary of an older-age exclusive effect of increased perceived rejection that co-occurs with cognitive flexibility decline.
Multiparametric MRI neuroimaging signatures predict cognitive decline in Multiple Sclerosis: a 5-year longitudinal study
Authors: Al-iedani Oun , Lea Stasson , Alshehri Abdulaziz , Maltby Vicki E. , Lea Rodney , Ramadan Saadallah , Lechner-Scott Jeannette
Published: August 2024

This novel longitudinal study evaluates multiparametric MRI signature for predicting cognitive decline in multiple sclerosis (MS) cohort followed for 5-years using a penalised regression machine learning approach (GLMnet). 43 MS participants were assessed at baseline and 5-years follow-up. Baseline (input) data consisted of 76 multiparametric MRI measures for different brain regions and tissues. The best performing model was for a change in tARCS (15 features; r=0.7±0.07), which was substantially higher than that for SDMT (r=0.496±0.08). These findings highlight the importance of using measures from multiple MR modalities analysed in combination with machine learning techniques when assessing cognitive decline.
Cingulum network myelination structure by SHIFT MRI characterizes higher order cognitive function in multiple sclerosis
Authors: Wolfe Tatiana , Pike Ashley , Colonese Sienna , Salmon Carlos Ernesto Garrido , Dunn Laura , Archer R. Lee , Kilts Clint , James G. Andrew
Published: August 2024

Impairment of higher-order cognition is a difficult aspect of MS pathology that poses a long-standing challenge for patient care advancement. Understanding how myelination integrity in the cingulum network – a brain pathway implicated in cognition – is related to lost or preserved cognitive functions is fundamental to enable comprehensive MS care and personalized remyelination therapeutics. We investigated if myelination integrity data has the potential to aid in characterizing individual differences in information processing in MS patients. Our findings support that myelination structure-function measured by SHIFT MRI is elucidatory variable to describe individual differences in higher-order cognitive function in MS patients.
Identification of Subcortical White Matter Biomarkers in Multiple Sclerosis Patients using Machine Learning
Authors: Montalba Cristian , Caulier-Cisterna Raul , Franco Pamela , Labbé Tomás , Andia Marcelo E , Guevara Miguel , Mangin Jean-François , Cruz Juan Pablo , Ciampi Ethel , Cárcamo Claudia , Guevara Pamela , Salas Rodrigo , Uribe Sergio
Published: August 2024

Radiological biomarkers of cognitive impairment in Multiple Sclerosis (MS) are still scarce. This study aimed to identify subcortical white matter biomarkers of cognitive impairment related to verbal episodic memory in MS patients and healthy controls using a Machine Learning approach.
Machine learning based prediction of clinical progression in multiple sclerosis
Authors: Noteboom Samantha , Seiler Moritz , Chien Claudia , Rane Roshan , Strijbis Eva , Paul Friedemann , Schoonheim Menno , Ritter Kerstin
Published: August 2024

Machine learning may aid in individualized prediction of disease progression in multiple sclerosis (MS). In this study, we used data from 354 patients with MS to evaluate the capability of different machine learning approaches at predicting future disease worsening. Multiple clinical end points of disease worsening were tested and different combinations of clinical and structural MRI measures were used as inputs. Machine learning models were capable of discriminating between patients with low and high disability but did not perform well in predicting future disease course.
Clinical implementation of Multiplied, Added, Subtracted and/or Divided (MASDIR) sequences on white matter lesions in Multiple Sclerosis
Authors: Losa Letizia , Peruzzo Denis , Bydder Graeme , Salmaggi Andrea , Agarwal Nivedita
Published: August 2024

Multiple Sclerosis (MS) is a demyelinating progressive chronic disease. MR imaging is a key diagnostic tool that allows long-term monitoring of disease progression. Since T1 values can identify clinically relevant tissue properties such as increased water content, myelin loss and changes in microstructure, we assessed the whole brain using Multiplied, Added, Subtracted and/or Divided Inversion Recovery (MASDIR) in patients with MS in an attempt to improve contrast and quantify T1 of lesions. We show that MASDIR is a clinically reliable, easy to implement technique that greatly increases T1 contrast and simultaneously provides quantitative T1 maps.
Fixel Based Analysis detection of peri-lesion and NAWM abnormalities in Relapsing Remitting Multiple Sclerosis
Authors: Lesack Nikolai , Levy Sarah , Sumowski James , Brown Stephanie , Horng Sam , Feldman Rebecca
Published: August 2024

Diffusion Tensor Imaging and Fixel Based Analysis (FBA) techniques were used to analyze microstructural properties of multiple sclerosis (MS) lesions and normal appearing white matter (NAWM) in relapsing-remitting multiple sclerosis (RRMS) subjects. FBA metric values were similar in peri-lesion white matter and MS lesions compared with bulk NAWM which may indicate FBA metric sensitivity to the infiltration of RRMS lesion pathology into surrounding NAWM. FBA fibre density in bulk NAWM was significantly different between subjects treated with Copaxone vs. Tysabri, which may indicate FBA metric sensitivity to NAWM differences between disease modifying therapies.
Automated QSM Processing in Multiple Sclerosis
Authors: Stewart Ashley , Liu Po-Jui , Weigel Matthias , Bollmann Steffen , Granziera Cristina
Published: August 2024

In this work, an automated and scalable processing tool for Quantitative Susceptibility Mapping (QSM), QSMxT, is applied to a large dataset of 3D echo-planar imaging (3D-EPI) acquisitions of Multiple Sclerosis (MS) patients and volunteer controls. This is used to reconstruct QSMs for all subjects and generate a group space for the study. MS lesions are depicted and compared across multiple contrasts, including FLAIR, MP2RAGE, 3D-EPI magnitude and QSM. The group space is used to generate average QSM images for the MS and control groups along with a difference image to investigate iron accumulation and demyelination patterns.
Altered amide proton transfer weighted signal and diffusion in multiple sclerosis: correlation with neuroflament light and disease duration
Authors: Huang Jing , Shen Zhiwei , Lu Jie
Published: August 2024

APTw imaging can help us understand the pathological changes in MS more sensitively and accurately.
Current UK perspectives on the challenges for clinical translation of quantitative MR imaging biomarkers.
Authors: Markus Julia , So Po-Wah , Hyare Harpreet , Cristinacce Penny
Published: August 2024

A web-based survey was developed from the “Steps on the Path to Clinical Translation” workshop, at the British & Irish Chapter-ISMRM conference held on 7th September 2022. The survey explored the UK MRI community’s perspective on the clinical translation of quantitative MR imaging biomarkers. Three main themes emerged from the results: the need for 1) consensus; continued development of resources that unite existing work and improve shared lexicon; 2) context dependency; defining the steps to clinical translation, in ways that appreciate the uniqueness of the imaging biomarker and the clinical question; 3) a clearer definition of imaging biomarker expectation or product profile.
Differentiation of Triple-negative and HER2 Positive Breast Cancer Using DISCO CE-MRI
Authors: Haodong Guo , Pylypenko Dmytro , Haige Li , Jianguo Zhu , Xiaofan Yuan , Ziyan Zhang
Published: August 2024

This study aims to investigate the feasibility triple-negative and HER2 positive breast cancer using DISCO CE-MRI. A total of 96 patients were recruited in the study. Quantitative and semi-quantitative parameters were used. kep and TTP had diagnostic value for triple-negative breast cancer. The AUC of kep and TTP were 0.870 and 0.928. kep had diagnostic value for HER2 positive breast cancer. The AUC of kep was 0.832. Our findings suggest that DISCO CE-MRI parameters might be reliable quantitative indicators for the differential diagnosis of triple-negative breast cancer and HER2 positive breast cancer.
Spatial variation of the negative BOLD response in human primary visual cortex
Authors: Vinogradov Artemy , Fesharaki Nooshin J. , Taylor Amanda , Ress David , Kim Jung Hwan
Published: August 2024

The negative hemodynamic response functions (nHRF), temporal dynamics of the negative BOLD response (NBR) evoked by a brief stimulus, have been reported as an inverted version of the corresponding positive HRF (pHRF). With a careful delineation of the nHRF from the stimulus representation (SR), we found that the nHRF adjacent to the SR was not the inverted version of the corresponding pHRF. We also characterized the nHRF with respect to the depth and found inverse proportion of the nHRF amplitudes between contralateral and ipsilateral sides, which can indicate different underlying mechanisms of the nHRF.
Optimised navigator correction of physiological field fluctuations in multi-echo GRE of the lumbar spinal cord at 3T
Authors: Beghini Laura , David Gergely , Liechti Martina D. , Büeler Silvan , Vannesjo S. Johanna
Published: August 2024

Multi-echo GRE sequences acquired in the spinal cord are sensitive to breathing-related field variations, leading to ghosting artifacts. While navigator-based corrections are often used in the brain to account for field variations, standard implementations often fail in the spinal cord due to the close proximity to the lungs. Here, we investigated optimised navigator corrections including a fast Fourier transform combined with region selection encompassing the spinal canal. Besides a visual improvement of image quality, the optimised navigator correction yielded statistically significant improvements in the CNR between WM and CSF and the SNR in the WM.
Isotropic sub-mm bSSFP imaging near metal at 0.55T
Authors: Keskin Kübra , Lee Nam , Acharya Jay , Nayak Krishna
Published: August 2024

At conventional field strengths, the large magnetic susceptibility difference between metallic implants and surrounding tissues causes severe artifacts often requiring multi-spectral imaging. Recent low-field MRI systems offers new opportunities for imaging adjacent to metallic implants, including balanced SSFP. Here, we utilize phase-cycled bSTAR, a short-TR 3D dual-echo radial bSSFP sequence, for isotropic 3D banding artifact free imaging near metallic implants at 0.55T. We demonstrate diagnostic quality images in volunteers with wrist and spinal hardware with high SNR efficiency compared to TSE-based sequences.
Spatiotemporal B0 correction in Oscillating Steady State Imaging (OSSI) fMRI using Free Induction Decay Navigators (FIDnavs)
Authors: Salifu Mariama , Noll Douglas , Haskell Melissa
Published: August 2024

Temporal field variations (e.g., physiological noise) in oscillating steady state imaging (OSSI) not only increases signal fluctuations as seen in GRE, but also alters signal characteristics that lead to inconsistent k-space acquisitions from TR to TR. This effectively reduces the overall functional contrast and temporal signal to noise ratio (tSNR). Here, we utilized free induction decay (FID) signal phase to estimate up to the first-order field inhomogeneity coefficients for prospective spatiotemporal B0 field correction in OSSI.
EPI Nyquist Ghost Correction by Iteratively Enforcing Structural Low Rankness
Authors: Liu Yilong , Lyu Mengye , Zhao Yunlin , Xiao Linfang , Wu Ed
Published: August 2024

This study presents a Nyquist ghost correction method by iteratively enforcing low rankness of the block-wise Hankel matrix and updating the 1D linear model for phase correction. The proposed method was evaluated with multi-shot EPI data at both ultra-high field (7T) and low field (0.3T). Compared with existing SVD-based method, the proposed method requires much fewer iterations to achieve similar performance, provides a computationally efficient and robust solution to EPI Nyquist ghost correction.
Preclinical spiral imaging with a high-performance gradient insert: a comparison of trajectory correction methods
Authors: Scholten Hannah , Wech Tobias , Köhler Sascha , Schneider Jürgen
Published: August 2024

We compared three different trajectory correction methods in spiral phantom images on a preclinical 7T scanner with a high-performance gradient insert. The first was an isotropic delay-correction, the second a gradient correction based on the gradient system transfer function (GSTF), and the third employed measured trajectories. In both an axial and a double-oblique slice, the measured trajectory resulted in the best image quality, while the delay-corrected images suffered from halo effects and signal bleeding. The GSTF-corrected images only had minor remaining artifacts, stemming from trajectory deviations due to non-linearities in the gradient chain.
Cardiac T1 and T2 Mapping: The Importance of Rest Periods in Quantitative Tissue Property Mapping
Authors: Garrett Seth , B.S.  , Hamilton Jesse , Ph.D.  , Seiberlich Nicole , Ph.D.
Published: August 2024

The aim of this study is to assess whether the presence of rest periods in the form of breathhold commands affects T1 and T2 values measured in the myocardium using both clinically standard pulse sequences and cardiac Magnetic Resonance Fingerprinting (MRF). When mapping data are collected immediately following cine acquisitions, T1 maps from both MOLLI and MRF show significant errors, although T2 maps from both T2-prepared bSSFP and MRF are unaffected by the absence of a pause between sequences.
Predicting MR Image Quality from Breathing Patterns
Authors: Vasanawala Soham , Pauly John
Published: August 2024

Motion, particularly from breathing, compromises the quality of magnetic resonance images. In this work, we hypothesize that detected breathing patterns can be utilized to predict whether adequate MR image quality will be obtained. With a K-means clustering algorithm, 9 in 10 forty-second breathing waveforms were correctly predicted as either resulting in a high or low image quality image; this finding can save time from unnecessary scans. Other models achieved similar results as K-means clusterings.