bluuebunny/crossref_metadata_2025 huggingface dataset:
1H-MRS of NAD+ and tryptophan in human brain at 3T in under 5 minutes using a spectrally-selective single-slice pulse sequence
Authors: Wilson Neil , Elliott Mark , Nanga Ravi Prakash , Swago Sophia , Reddy Ravinder , Witschey Walter
Published: November 2024

Motivation: NAD+ and tryptophan are important in energy metabolism, DNA repair, mitochondrial function, and aging. Both have recently been observed in brain at 7T, but observation at 3T is more challenging and has not been shown previously. Goal(s): To detect NAD+ and tryptophan at 3T in brain in a clinically feasible scan time less than 5 minutes. Approach: A single slice spectroscopy sequence with spectrally selective excitation was developed and optimized, allowing high sensitivity acquisition. Results: The H2 (9.3 ppm) and H6 (9.1 ppm) peaks of NAD+ and the indole (10.1 ppm) peak of tryptophan are both unambiguously observed in four healthy subjects. Impact: The ability to identify NAD+ and tryptophan at 3T in less than 5 minutes has the potential to significantly enhance the adoption of this method as part of existing neuroimaging protocols.
Water-cycled STEAM spectroscopy in the liver at 7T
Authors: Montoya Erin McConnell , Mózes Ferenc , Miller Jack , Valkovič Ladislav
Published: November 2024

Motivation: Hepatic choline-containing compounds (CCC) are an important biomarker of metabolic health. Goal(s): The aim of this work is to measure the concentration of fat and choline-containing compounds in the liver using water-suppression cycled (WSC) and water suppressed (WS) spectroscopy at 7T. Approach: Livers of seven healthy volunteers were scanned using water-suppression cycling and the results were compared with standard water-suppressed acquisitions. Results: Similar concentrations of CCC were reported for both techniques, with WSC providing somewhat narrower line widths. Hepatic fat fractions were also very close using each method validating WSC as a method for use at 7T. Impact: Frequency-aligned spectra from water-suppression cycled acquisitions enable the quantification of low-concentration metabolites in vivo at 7T.
Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation
Authors: Zöllner Helge , Davies-Jenkins Christopher , Simicic Dunja , Tal Assaf , Sulam Jeremias , Oeltzschner Georg
Published: November 2024

Motivation: Modeling and application of dynamic MRS is receiving growing interest in the community. Goal(s): Accuracy, precision, and uncertainty of 2D modeling algorithms must be carefully characterized. Approach: Here, we generated synthetic spectra of an idealized (single metabolite with a stable signal across transients) conventional 1D-MRS experiment. We then compared accuracy, precision, and uncertainty estimation between a 2D model of all transients without averaging and a 1D model of the averaged spectrum. Results: Both models performed similarly in terms of accuracy and precision. 2D-LCM afforded small benefits for uncertainty estimation for uncorrelated noise and substantial benefits for correlated noise. Impact: For conventional (non-dynamic, multi-transient) MRS data, 2D-LCM without averaging and 1D-LCM after averaging perform similarly accurate and precise. 2D-LCM affords gains in uncertainty estimation that appear to be related to the degree of noise correlation across transients.
NAD+(H) Dynamics Using 31P Functional MRS in the Brain: Insights into Energy Metabolism Mechanisms during Visual Stimulation.
Authors: Kaiser Antonia , Vind Fatemeh Anvari , Jelescu Ileana , Widmaier Mark , Wenz Daniel , Xin Lijing
Published: November 2024

Motivation: Alterations in brain nicotinamide adenine dinucleotide (NAD+) levels, as observed in aging, neurodegenerative conditions, and psychiatric disorders, necessitate an in-depth exploration of NAD's functional dynamics. Goal(s): Investigating the feasibility of using 31P functional MRS (fMRS) at 7T to measure NAD+ dynamics during a visual stimulation task. Approach: 32 volunteers were measured using 31P fMRS at 7T, during exposure to an established visual stimulation task. Results: The present study provides evidence for the possibility of measuring NAD+ dynamics in the occipital lobe using 31P fMRS during a visual stimulation task. Furthermore, the use of denoising algorithms may boost sensitivity to detect functional changes. Impact: Functional 31P MR Spectroscopy could contribute to complex cognitive and clinical studies, investigating energy metabolism deficits. Eventually, this knowledge could contribute to the development of novel therapeutic strategies targeting brain energy deficits associated with neurodegenerative diseases and cognitive impairments.
Dual use of nitroxyl radicals as a polarizing agent in hyperpolarization 13C-MRS and as a redox probe in EPR spectroscopy to study acute kidney injury
Authors: Elhelaly Abdelazim , Habaka Manal , Hyodo Fuminori , Noda Yoshifumi , Kato Hiroki , Matsuo Masayuki
Published: November 2024

Motivation: Trityl radicals are the main polarizing agents used for hyperpolarization. However parallel monitoring of metabolic and redox conditions is an unmet need. Goal(s): To use nitroxides as a polarizing agent and as a redox probe simultaneously for the same sample. Approach: Four nitroxyl probes were tested. HyperSense DNP polarizer was used for 13C-pyruvate hyperpolarization.13C-MRS and EPR measurements were performed using same samples. Results: CmP showed the highest hyperpolarization signal. A significant reduction in 13C lactate production and EPR decay rates of CmP during disease progression were confirmed. Impact: We described successful application of nitroxyl radicals for simultaneous assessment of energy metabolism and redox status.
5D reconstruction exploiting spatial-motion-echo sparsity for accelerated free-breathing liver R2*/QSM
Authors: Kang Mungsoo , Otazo Ricardo , Behr Gerald , Kee Youngwook
Published: November 2024

Motivation: Conventional compressed sensing-based 4D respiratory motion-resolved image reconstruction techniques are limited in their ability to utilize correlations between echoes for free-breathing 3D multi-echo liver MRI, which is inherently a 5D imaging problem. Goal(s): Develop a 5D reconstruction algorithm to jointly exploit correlations between echoes and motion states. Approach: 5D reconstruction with sparsity constraints along the motion and echo dimensions was developed to reconstruct retrospectively undersampled k-space data and compared with the 4D reconstruction on one volunteer and one patient. Results: Compared to the 4D reconstruction, the proposed reconstruction showed comparable image quality to the reference (undersampling factor=1) and more reliable liver R2*/QSM values. Impact: Using the proposed 5D image reconstruction, the scan time of free-breathing 3D multi-echo liver MRI for R2*/QSM can be reduced while preserving image quality and providing reliable R2*/QSM values.
Measuring Spatiotemporal Resolution in Real-Time MRI
Authors: Chan Chin-Cheng , Haldar Justin
Published: November 2024

Motivation: Real-time MRI can provide powerful insights into dynamic processes, but practical experimental limitations have led to the widespread use of undersampled data. While advanced reconstruction methods can mitigate undersampling artifacts, these methods are unlikely to be perfect, and their rigorous validation has been a longstanding open problem. Goal(s): To introduce a new reference-free approach for evaluating real-time MRI results. Approach: We introduce a framework for measuring spatiotemporal resolution in real-time MRI, based on the propagation of spatiotemporal perturbations through image reconstruction. Results: The proposed approach is sensitive to spatiotemporal resolution features, and provides valuable new information for the interpretation of real-time MRI results. Impact: The proposed framework enables measurement of spatiotemporal resolution, providing new information that is important for the interpretation of real-time MRI results, and can also be useful for the development/tuning of acquisition and reconstruction methods.
Myelin-sensitive inversion recovery (MySIR) for quantification of myelin in the peripheral nerve
Authors: Sada Takayuki , Yokota Hajime , Nitta Keisuke , Kurosawa Ryuna , Sato Hirotaka , Matsumoto Koji , Namiki Takashi , Yoneyama Masami , Gilbert Guillaume , Masuda Yoshitada , Uno Takashi
Published: November 2024

Motivation: Quantification of myelin in peripheral nerves remains challenging. Goal(s): To evaluate new imaging techniques that quantify myelin in the peripheral nerve. Approach: Myelin-sensitive inversion recovery (MySIR) was compared with inhomogeneous magnetization transfer (ihMT) for its ability to reflect myelin value and spatial resolution in the peripheral nerve. Results: Myelin values of MySIR and ihMT were strongly correlated. MySIR had a better ability to visualize nerve fascicles than ihMT. Impact: MySIR could quantify myelin while maintaining high spacial resolution in peripheral nerves.
Patch2self denoising of magnitude- and complex-averaged peripheral nerve DTI data: Challenges and opportunities
Authors: Christopher Kezia Sharon , Ott Lauren , Li Zhiqiang , Dortch Richard
Published: November 2024

Motivation: DTI is effective in characterizing nerve pathology but requires a high-resolution scans, resulting in low SNR data. Goal(s): To analyze the effectiveness of a self-supervised Patch2Self denoising technique on magnitude-averaged and complex-averaged DTI data of human median and ulnar nerve. Approach: The magnitude-averaged and complex-averaged DTI data was denoised with the Patch2Self algorithm; and DTI fitting performed was performed to obtained estimates of FA, AD, and RD in nerves. Results: Patch2Self denoising reduced the variability in the data by 20% at the cost of systematic bias, while complex averaging improved the contrast between muscle/nerve and suppressed fat. Impact: FA estimates obtained from DTI helps monitor nerve regeneration following catastrophic nerve injuries. Improving the quality of the DTI data may improves the reliability of FA estimates so that more subtle treatment effects can be detected.
Optimal Visualization and Morphologic Findings of Thoracic Dorsal Root Ganglia Using MR Neurography
Authors: She Dejun , Yan Yalan , Zhao Xiance , Cao Dairong
Published: November 2024

Motivation: A more consistent visualization of the thoracic ganglia is needed to aid in identifying abnormal anatomical patterns and disease progression for the formulation of therapeutic strategies. Goal(s): To prospectively evaluate the clinical feasibility of MR neurography in detecting thoracic dorsal root ganglia and related morphologic information for clinical decisions. Approach: The T2_FFE, B_FFE, and SHINKEI sequences were applied to identify the best sequence that can precisely provide nerve root visualization and describe the morphological information of thoracic DRG. Results: T2_FFE offers enhanced nerve visualization and improved image quality, and provides valuable morphological information, with shorter sequence acquisition time. Impact: This method has a potential role in the diagnosis and treatment of diseases involving unilateral or even bilateral ganglia. By applying morphological MRN, the detailed nerve visualization may help surgeons develop effective DRG-targeted treatment and detect the therapeutic effect.
Iterative Low-Rank Infilling Approach for Zero Echo-Time (ZTE) Imaging
Authors: Huo Zimu , de Arcos José , Wiesinger Florian , Kaggie Joshua , Graves Martin
Published: November 2024

Motivation: The short, but non-zero, time taken to switch between transmit and receive results in a dead-time gap in Zero Echo-Time (ZTE) imaging, which leads to substantial reconstruction artifacts. Goal(s): Determine the missing data in the dead-time gap without any additional acquisition. Approach: We reformulate the reconstruction problem as a nuclear norm minimization problem to implicitly fill the missing data through iterative reconstruction. Results: The proposed method demonstrates that the missing data can be filled using low-rank without sacrificing image quality. Impact: We present a method for filling the dead-time gap in ZTE imaging using low-rank that does not require the collection of additional data.
Reconstruction of Highly Underdamped 3D Spiral and Golden Angle Radial MRI Data Using Spherical Fourier-Legendre Transform
Authors: Shafiekhani Mojtaba , Ghodrati Vahid , Moghaddam Abbas Nasiraei
Published: November 2024

Motivation: Fast imaging is crucial in MRI for various applications. This study proposes a novel method to reconstruct highly undersampled MRI data for faster and higher-quality imaging. Goal(s): Reconstruct the highly undersampled 3D golden-angle and spiral radial MRI data. Approach: We proposed a novel image reconstruction method for 3D radial MRI data at high acceleration rates, based on the spherical Fourier-Legendre transform. This method reconstructs images directly in the spherical coordinates without using interpolation operator in k-space domain. Results: The feasibility of the proposed method is proven by reconstructing highly undersampled 3D golden-angle and spiral radial data of digital Shepp-Logan and in-vitro ACR phantoms. Impact: A nivel image reconstruction method for fast and high-quality radial MRI imaging. It focuses on highly undersampled 3D golden-angle and spiral radial MRI data, reconstructing images directly in spherical coordinates without any frequency interpolation.
Assessment of Daily Variations of GABA Levels within the Parietal Lobe and Anterior Cingulate Gyrus Regions of Healthy Young Adults Based on MRS.
Authors: Ye Yujie , Zhong Zhaomin , Tian Yangyang , Wu Xiaojuan , Wei Zifan , Han Shuting , WU Peng , Wang Han , Li Yonggang
Published: November 2024

Motivation: The assessment of GABA and Glx levels within the brain with MEscher-Garwood Point RESolved Spectroscopy (MEGA-PRESS) has an important role in the diagnosis and treatment of neuropsychiatric disorders. Goal(s): We evaluate the daily fluctuations of GABA levels within the parietal lobe (PL) and anterior cingulate gyrus (ACC) regions. Approach: The GABA+, GABA+/Cr , Glx/Cr ,Glx were measured at six different time points throughout the day using MEGA-PRESS. Results: Significant variations in GABA+/Cr levels within the PL region, with the lowest point occurring at 9:00 and the highest peak occurring at 21:00 . The melatonin levels were positively correlated with GABA+/Cr within the ACC region. Impact: GABA changes in localized brain regions are strongly associated with many psychiatric disorders. The outcomes of this study could be used to guide the diagnosis and treatment of neuropsychiatric disorders.
Motor hand area GABA could be a physiological switch between motor network and default mode network connectivity
Authors: Edmond Evan , Clarke William , Grigoras Ioana-Florentina , Andrushko Justin , Levenstein Jacob , Nettekoven Caroline , Hinson Emily , Campbell Jon , Steel Adam , Emir Uzay , Turner Martin , Stagg Charlotte
Published: November 2024

Motivation: The functional role of Inhibitory tone in the motor cortex is not completely understood. Previous work has been limited by the coarse spatial resolution in single-voxel spectroscopy. Goal(s): We applied a novel high spatial resolution MR spectroscopic imaging technique to test the relationship between inhibitory tone and motor network (MN) connectivity. Approach: We performed voxel-wise analysis of neurochemical data to correlate measures of inhibitory and excitatory tone with age as a confounder, MN and default mode network (DMN). Results: In the motor hand areas, we demonstrated a reciprocal correlation of inhibitory tone with MN and DMN connectivity. Inhibitory tone could “switch” node connectivity. Impact: The connectivity of key motor network nodes could be influenced by their inhibitory tone and the excitation–inhibition difference. This finding advances the understanding of motor network function and could be a target for modulation in clinical settings.
Multiparameter Quantitative MRI in Diagnosing Dysthyroid Optic Neuropathy in Thyroid Associated Orbitopathy
Authors: Gou Xinyi , Wang Yi , Peng Pai , Wang Ke , Lian Jianxiu , Zhang Yang , Zhang Xiuyi , Cheng Jin , Hong Nan
Published: November 2024

Motivation: Dysthyroid optic neuropathy (DON) is a rare yet highly significant complication of thyroid associated orbitopathy (TAO), which requires urgent treatment. However, diagnosing this condition is a formidable challenge due to the absence of well-defined criteria for its identification. Goal(s): The aim of this study was to use multiparameter MRI for diagnosing DON. Approach: Fifty-five patients were enrolled, who underwent MRI, including conventional imaging, T1 mapping, T2 mapping, and mDIXON Quant sequences for providing quantitative parameters. Results: The quantitative parameters could offer reliable evidence for the differentiation of DON from TAO, especially T1 values of extraocular muscles and water fraction of orbital fat. Impact: The native T1 values of extraocular muscles combined with water fraction of orbital fat provided more accurate diagnostic ability of DON in TAO patients. Moreover, the pathological presentation of fibrosis of extraocular muscles associated with DON may occur.
Vascular Involvement Associated with Hypertension in Trigeminal Neuralgia Patients
Authors: Shen shanshan , Ji Hong , Xie Lizhi , Chen Yingmin
Published: November 2024

Motivation: Trigeminal neuralgia is characterized by vascular compression of the trigeminal nerve, while neurogenic hypertension results from vascular compression in the medulla oblongata. Goal(s): To investigate the pathogenesis of TN in conjunction with hypertension and identify the vessels responsible,Approach: we conducted a retrospective population-based study including 457 TN patients,Results: and found a significant link between neurovascular conflict and hypertension. Specifically, arteries near the root entry zone, such as the anterior inferior cerebellar artery, vertebrobasilar artery, and superior cerebellar artery, were more associated with hypertension, especially when pain localized in the V2,3 area. Conversely, the posterior inferior cerebellar artery displayed an opposing trend. Impact: Patients with TN combined with neurogenic hypertension are recommended to take microvascular decompression (MVD) operation, who have these conditions in our study, will show potential improvements in their hypertension.
Studying Differences in Gray Matter Volume in Patients with Meige syndrome and Facial Paralysis Using a Normative Modeling Approach
Authors: Luan Jixin , Yang Aocai , Xu Manxi , Lv Kuan , Hu Pianpian , Ma Guolin
Published: November 2024

Motivation: This study delves into the variations in gray matter volume among patients with Meige Syndrome (MS), facial paralysis (FP), and healthy controls. Goal(s): It aims to unveil the neurological mechanisms underlying these conditions. With a sample of 53 FP patients, 31 MS patients, and 102 healthy controls, the research assesses disease severity and conducts high-resolution MRI imaging. Approach: Normative modeling and machine learning algorithms are employed to identify differences in specific brain regions. Results: Results reveal significant variations in gray matter volume, particularly in the anterior cingulate region, shedding light on the importance of this area in understanding these conditions. Impact: This study's outcomes could transform clinical practice and research in Ménière's Syndrome and facial paralysis. Enhanced diagnostic and treatment methods may significantly improve patients' quality of life, fostering exploration of innovative therapies and a deeper understanding of these conditions.
Utilizing Synthetic MRI and Amide Proton Transfer-Weighted MRI to Distinguish Malignant from Benign Sinonasal Lesions
Authors: Xiang Ying , Zhang Qiujuan , Chen Xin , Sun HongHong , Li Xiaohui , Wei Xiaocheng , Zhong Jinman , Gao Bo , Huang Wei , Liang Wenbin , Sun Haiqiao , Yang Quanxin
Published: November 2024

Motivation: Distinguishing between benign and malignant sinonasal lesions is crucial for determining the appropriate treatment regimen and predicting patient outcomes. Goal(s): To evaluate the performance of synthetic MRI (SyMRI), combined with amide proton transfer (APT)-weighted MRI (APTw) in differentiating between malignant and benign sinonasal lesions. Approach: Eighty patients with sinonasal lesions were underwent the SyMRI and ATPw scan and the quantitative parameters were analyzed. Results: T1, T2, PD and APT values were significant between the benign and malignant groups. Combined SyMRI and APTw had the best diagnostic efficiency. Impact: Combined the SyMRI with APTw would function as a quantitative and contrast-free approach, significantly enhancing the differentiation of benign and malignant sinonasal lesions. This method also helps overcome the limitations associated with the superficial nature of nasal endoscopic sampling.
Manifold-Aware Swin UNET Transformer for High-Fidelity Diffusion Tensor Imaging from Six Directions
Authors: Kertes Noga , Freiman Moti
Published: November 2024

Motivation: Diffusion Tensor Imaging (DTI) requires numerous diffusion weighted images, resulting in long scan sessions that motivate a need for more efficient DTI estimation techniques. Goal(s): Our goal is to demonstrate that Deep Neural Networks (DNNs) trained with a manifold-respecting loss function can more accurately estimate diffusion tensors from fewer diffusion-weighted images, surpassing networks trained with Euclidean losses while honoring the tensors' manifold structure. Approach: We employed the Swin UNET Transformer architecture and trained two models: one with Log-Euclidean loss and another with Euclidean loss. Results: When evaluating the predicted tensors against conventional techniques, our approach consistently outshined the rest. Impact: The study will enable an accurate estimate of brain microstructure from DTI data acquired with six gradient directions by developing manifold-aware DNN for DTI analysis. This breakthrough may reduce patient discomfort and scanning artifacts, and potentially increase imaging centers throughput.
Generalizable Transformer-based Automatic MRI Quality Control for Infant Brain Imaging
Authors: Deng Haowen , Wu Gaofeng , Zhu Zihao , Gu Zhuoyang , Cai Xinyi , Tao Tianli , Zhu Lixuan , Tao Yitian , Shen Dinggang , Zhang Han
Published: November 2024

Motivation: Manual quality control (QC) for infant brain MRI is time-consuming and labor-intensive. The implementation of automatic QC is necessary for clinical scenarios. Goal(s): To develop a generalizable, highly accurate, automatic tool for infant brain T1w-MRI quality control. Approach: We design a generalizable automatic model with Residual Network (ResNet) and Vision transformer (ViT) modules for infant brain T1w-MRI QC. Our model is trained and validated on two large-scale multi-site infant MRI datasets (including Baby Connectome Project and China Baby Connectome Project). Results: Based on our method, we can automatically classify the data quality with the accuracy of over 95% for BCP and CBCP datasets. Impact: Our automatic MRI quality control tool can consider both local and global image features and shows excellent performance and efficiency, specifically on the infants' 3D brain T1w-MRI. It considerably reduces the requirement of labor in the traditional QC process.
Deep learning-based MRI denoising enhances the reliability of whole-brain volumetric analysis
Authors: Jung Won Beom , Otgonbaatar Chuluunbaatar , Lee Jaebin , Ryu Jae-Kyun , Kim Junhyung , Jeon Seongkyu , Kim Juho , Kim Jin Woo , Shim Hackjoon
Published: November 2024

Motivation: This study investigates the impact of deep learning-based image reconstruction (DLR) in structural brain MRI volumetric analysis. Goal(s): To demonstrate that DLR effectively reduces noise and enhances image quality with short acquisition time, Approach: Ten healthy subjects were scanned with a 3T MRI system with and without DLR reconstruction. Results: Voxel-based morphometry analysis revealed significant improvements in brain volumetric measurements with DLR compared to conventional methods. These advancements are particularly relevant in regions associated with neurodegenerative diseases. Impact: DLR offers the potential to facilitate earlier detection and monitoring of such conditions, providing clinical value with comparable scan duration.
Improved DCE-MRI for Diffuse Gliomas: Clinical Application of Deep Learning-based Super-resolution and Denoising Algorithm
Authors: Lee Junhyeok , Choi Kyu Sung , Jung Woojin , Yang Seungwook , Park Jung Hyun , Hwang Inpyeong , Chung Jin Wook , Choi Seung Hong
Published: November 2024

Motivation: Dynamic contrast-enhanced MRI (DCE-MRI) is invaluable for non-invasive assessment of tissue perfusion and microcirculation dynamics. However, unreliability of DCE-MRI discourages clinical application. Goal(s): To evaluate the image quality and diagnostic performance of enhanced DCE-MRI using a deep learning-based super-resolution and denoising algorithm. Approach: Deep learning-based super-resolution and denoising (DLSD) algorithm was applied to DCE-MRI obtained from 306 patients with adult-type diffuse gliomas to reduce noise and increase resolution. Results: DLSD significantly enhanced image quality without compromising diagnostic accuracy in distinguishing low- and high-grade tumors and IDH mutation, and it also improved the reliability of arterial input functions. Impact: Improving DCE-MRI image quality and reliability through deep learning-based super-resolution and denoising algorithm can help address previous reliability issues and offer clinical applicability not only in the field of diffuse glioma but also in other areas utilizing DCE-MRI.
Deep Learning-Based Super Resolution Reconstruction for Quantitative Susceptibility Mapping
Authors: Patitucci Eleonora , Zappalà Stefano , Driver Ian , Wise Richard , Germuska Michael
Published: November 2024

Motivation: Lengthy acquisitions are needed to produce high-quality quantitative susceptibility mapping (QSM) from which it is possible to segment vasculature and extract physiological parameters. Goal(s): To adapt a deep learning method for super-resolution reconstruction to enhance QSM images. Approach: We applied the 3D densely-connected super resolution network (DCSRN) to QSM data, as it has previously shown promising results in reconstructing T1w high-resolution (HR) images from low-resolution (LR) images. Results: We demonstrated an improvement in the reconstruction of the vascular network, with intravascular susceptibility values distribution close to the true distribution. Impact: Our results show the promise of DCSRN architecture in producing super resolution (SR) images from low resolution (LR) images. Furthermore, the feasibility of segmenting vessels and extracting venous OEF on SR would be beneficial for studies of brain vasculature.
To SSIM, or to not SSIM: Investigating the impact of image artifacts and motion on image quality metrics
Authors: Terpstra Maarten , van den Berg Cornelis
Published: November 2024

Motivation: When quantifying MRI image quality, image similarity metrics must be able to detect image artifacts. Goal(s): To investigate the sensitivity of image similarity metrics to common distortion sources in MRI. Approach: Distorted MRI is simulated using blurring, noise, inter-scan and intra-scan motion. Regression forests are trained to estimate the distortion parameters based on the image similarity metrics. The regression forests' feature importance quantifies the image metric sensitivity. Results: Not all image similarity metrics are equally sensitive to every distortion source, and the best metric depends on the distortion source. The appropriate metric must be used to quantify the image quality. Impact: Typically, standard image similarity metrics such as SSIM are chosen to estimate whether a particular method outperforms another method for all tasks. However, this research can help scientists use the appropriate metric when evaluating MRI reconstruction and processing methods.
Labeling Strategies for Whole-kidney Non-contrast Perfusion-Weighted Imaging using 3D FAIR ASL
Authors: Alvarez Maria Mora , Zhou Limin , Udayakumar Durga , Madhuranthakam Ananth
Published: November 2024

Motivation: Flow-sensitive alternative inversion (FAIR) is one of the recommended arterial spin labeling (ASL) schemes for renal perfusion. Although FAIR can provide robust measurements, it suffers from partial-kidney coverage especially when aorta is close to or even at the same level of kidney in anterior-posterior (A/P) direction. Goal(s): To obtain whole-kidney perfusion measurements using 3D FAIR despite anatomy differences within population. Approach: Two additional labeling strategies of 3D FAIR were proposed and tested in healthy volunteers. Results: Both strategies generated robust and high-quality perfusion maps with whole-kidney coverage within a feasible clinical scan time, which is challenging for existing 3D FAIR and pCASL implementations. Impact: Our labeling strategies in 3D FAIR ASL could be valuable for early detection, diagnosis, differentiation, and management of renal diseases, including chronic kidney disease and acute kidney injury, despite individual anatomy differences between patients.
Evaluation of multi-delay arterial spin labeling MRI-based measures of cerebral blood flow in a PET/MRI study of aging
Authors: Juttukonda Meher , Fu Jessie Fanglu , Garimella Arun , Mercaldo Nathaniel , Wey Hsiao-Ying , Salvatore Andrew , Dickerson Brad , Price Julie
Published: November 2024

Motivation: Arterial spin labeling (ASL) MRI with a single post-labeling delay may not be appropriate for quantifying cerebral blood flow (CBF) in older participants or individuals with Alzheimer’s disease (AD). Goal(s): To evaluate reliability of multi-delay versus single-delay ASL and their associations with [15O]water positron emission tomography (PET) using simultaneous PET/MRI in older adults. Approach: We investigated 4-week test-retest reliability using intra-class correlation (ICC) and assessed Spearman’s correlations between ASL and PET in young and older controls (n=12) and AD patients (n=3). Results: ICC values were similar between ASL approaches but exhibited regional differences. Multi-delay ASL-based CBF was correlated with PET in more regions-of-interest. Impact: Multi-delay arterial spin labeling MRI provides CBF measures with good intermediate-term reliability that are strongly correlated with gold-standard [15O]water PET when studying older adults and AD patients.
Measuring intra-to-extra-vascular cerebral water-transport in patients with small vessel disease using 3D T2-prepared time-encoded pCASL
Authors: Elschot Elles , Verstappen Damon , Voorter Paulien , van Dinther Maud , Staals Julie , van Oostenbrugge Robert , van Osch Matthias , Jansen Jacobus , Backes Walter , Vaclavu Lena
Published: November 2024

Motivation: The blood brain barrier (BBB) is damaged in patients with cerebral small vessel disease (cSVD). Goal(s): To study the role of subtle BBB impairment in cSVD by measuring water-transport over the vessel wall. Approach: T2-prepared time-encoded pCASL was applied in cerebral small vessel disease (cSVD) patients and healthy controls. Results: T2 variations between the groups showed no significance in this preliminary sample yet. However, T2-values tend to decay earlier in VCI patients compared to HC. This suggests earlier water-transport from blood to tissue, possibly referring to stronger BBB impairment. Moreover, broader distributions of T2-values seem to indicate larger heterogeneity in the VCI-group. Impact: This study applied T2-prepared time-encoded pCASL in cerebral small vessel disease (cSVD) patients and healthy controls to study subtle BBB-damage. Although T2-values showed no significant differences yet, the T2-values seem to decay earlier in cSVD, suggesting earlier water-transport into tissue.
Theoretical and experimental optimization of random vessel-encoded ASL to improve vascular territorial mapping and CBF quantification
Authors: He Yining , Tang Jianing , Zhao Tianrui , Gamez Maria , Yan Lirong
Published: November 2024

Motivation: Planning-free random vessel-encoded ASL (rVE-ASL) greatly simplifies the vessel-selective ASL scan settings and shows great potential for vascular territorial imaging in clinical applications. Goal(s): To theoretically and experimentally optimize rVE-ASL to establish an efficient and reliable rVE-ASL protocol Approach: Simulation and in-vivo experiments were conducted to evaluate and optimize rVE-ASL in terms of labeling efficiency, total number of encoding steps, and reliability of vascular territorial and CBF measurements. Results: Reliable territorial mapping and CBF measurements from both ICA and VA can be achieved by optimized rVE-ASL. At least 20 encoding steps are needed to achieve reliable territorial mapping and CBF measurements in rVE-ASL. Impact: We have theoretically and experimentally optimized rVE-ASL, which can provide reliable vascular territorial mapping and CBF quantification. The rVE-ASL technique holds a potential to be a useful imaging tool for assessing vascular territorial alterations and collaterals in various clinical applications.
Multiparametric Metabolic Imaging of Leukoencephalopathy at 7T: A Case Study
Authors: Jacobs Paul , Wilson Neil , Swain Anshuman , Spangler Bailey , Seitz Madeleine , Fu Allen , Orthmann-Murphy Jennifer , Schindler Matthew , Reddy Ravinder
Published: November 2024

Motivation: Standard structural MR imaging techniques are not able to provide information on the metabolic state of white matter lesion. Specialized imaging techniques such as NOE and GluCEST can complement these conventional images by leveraging larger chemical shifts at 7T. Goal(s): To observe potential NOE and GluCEST contrast differences in a leukoencephalopathy patient at 7T. Approach: GluCEST and NOE images were acquired at 7T. NOE experimental z-spectral data was fit with multi-pool Lorentzian fitting to produce five individual pool fits. Results: DS, MT, and rNOE differentiated white matter changes as well as GluCEST changes in the gray matter in a leukoencephalopathy patient. Impact: This method of ultra-high field MR imaging for patients with demyelinating conditions can provide complementary metabolic information to standard structural imaging that, when tracked longitudinally, can yield improved diagnostic outcomes and understanding of disease mechanism for this patient population.
1H-MRSI of white matter in cognitively unimpaired elderly for the detection of early Alzheimer’s disease pathological changes
Authors: Chen Anna , Zheng Helena , Peralta Rosemary , Gajdošík Mia , Azad Dishari , George Ajax , Rusinek Henry , Boutajangout Allal , Ahn Sinyeob , Osorio Ricardo , Kirov Ivan
Published: November 2024

Motivation: APOE4 has been linked to increased amyloid and tau deposition and microstructural WM changes in Alzheimer’s, but despite the major role of APOE in myelination, whether WM metabolism is altered in individuals at risk for Alzheimer’s remains unknown. Goal(s): To examine if choline, a constituent of myelin and a marker of membrane turnover, is associated with APOE4, CSF p-tau181 (a marker of tau burden), and WM volume (a marker of neurodegeneration). Approach: Cognitively unimpaired elderly with and without APOE4 underwent 1H-MRSI. Relationships between WM choline, APOE4, tau, and WM volume were assessed. Results: No associations were found between WM choline and any marker. Impact: WM metabolism is not associated with genotype, tau, or neurodegeneration in healthy elderly, but given that amyloid deposition is the earliest Alzheimer’s pathological hallmark, additional investigations with amyloid biomarkers are needed to better characterize WM metabolism in the preclinical stage.
Characterizing Tissue Relaxation and Magnetization Transfer in Fresh, Thawed, and Fixed White Matter Tissue Samples
Authors: Murguia Amaya , Swanson Scott , Scheven Ulrich , Nielsen Jon-Fredrik , Fessler Jeffrey , Seraji-Bozorgzad Navid
Published: November 2024

Motivation: Studying ex vivo tissue requires preservation by formalin-fixation or freezing. Effects of these methods on tissue parameters compared to fresh tissue is unknown. Goal(s): We investigated how freezing/thawing and fixation affect T1, T2, and MT properties in brain tissue. We created a protocol to apply MR methods (T2-MESE, biexponential T1, qMT, ihMT, NODDI) to pathology specimens in the Michigan Alzheimer’s Disease Research Center (MADRC) repository. Approach: We scanned the same ex vivo sheep brain samples fresh, frozen/thawed, and fixed, and compared their relaxation and MT properties. Results: Effects of fixation are most prominent in white matter and especially influence T1 and T2 relaxation. Impact: Thawed tissue exhibits more similar relaxation and MT properties to fresh tissue than fixed tissue does. In MR studies that use ex vivo tissue samples, such as those correlating MR to histology, thawed tissue may be preferable to formalin-fixed.
Habenula functional connectivity predicts prior night’s sleep in healthy adults: A 5.0 T fMRI study
Authors: Wang Liang , Gao Lei , Xu Haibo
Published: November 2024

Motivation: The habenula is evolutionarily conserved brain region which play a crucial role in sleep regulationGoal(s): To analysis the structural and functional relationship between habenula and individual sleep by 5T ultrahigh-resolution MRIApproach: Using ultrahigh-resolution structural and functional MRI, we parcellated lateral and medial portions of the habenula and calculated structural and functional connectivity on the basis of these parcellationsResults: We parcellated lateral and medial portions of the habenula and identified connectivity with salience, limbic and part of somatomotor networks, which led to the loss in average sleep and cognitive processesImpact: For the first time we identified the correlation between habenula and individual sleep using 5T ultrahigh-resolution MRI. By analyzing 300 samples high -resolution data, we revealed the neurological basis of individual sleep regulation, and provided new opinions for the mechanism of sleep diseases.
Retrieving fiber orientations from any brain histology section and comparison to diffusion MRI
Authors: Georgiadis Marios , Heiden Franca auf der , Liao Congyu , Nirschl Jeffrey , Wakatsuki Moe , Liu Andy , Ho William , Taghavi Hossein Moein , Setsompop Kawin , Amunts Karin , Axer Markus , Zeineh Michael , Menzel Miriam
Published: November 2024

Motivation: Neuronal axons (nerve fibers) facilitate complex connectivity patterns, but retrieving fiber architecture with micrometer resolution remains elusive. Meanwhile, thousands of brain histology sections are produced and archived daily. Goal(s): Here, we show that fiber architecture can be derived with micrometer resolution from new and archived histology sections. Approach: Using Computational Scattered Light Imaging (ComSLI), we generate detailed microscopic maps of nerve fiber orientations in healthy and diseased, animal and human brain sections prepared with various protocols and stains. Results: We compare whole-brain results to diffusion MRI. This opens new avenues to studying microscopic brain fiber architecture in a time- and cost-effective manner. Impact: Using scattered light, we generate micrometer maps of nerve fiber orientations in new and archived histology sections of healthy and diseased, animal and human brains prepared with various protocols and stains. We compare whole-brain fiber orientations to diffusion MRI.
How Do White Matter Tracts Constrain Brain Oscillation Propagation? A Diffusion MRI-MEG Study
Authors: Manolova Svetla , McNabb Carolyn , Messaritaki Eirini , Singh Krish , Jones Derek , Cercignani Mara , Mancini Matteo
Published: November 2024

Motivation: Substantial effort has been invested into understanding how brain structure constrains function. However, research has primarily focused on understanding structure, rather than linking brain dynamics to it. Goal(s): Compare oscillation propagation delays estimated using neuronal avalanches from MEG resting-state data with the underlying white matter structure estimated through tractography. Approach: We characterised the relationship between pathways length and the related propagation delays, using deterministic and probabilistic approaches, and looking at different frequency bands. Results: While higher frequency bands scale proportionally with propagation delays and length, lower frequency bands show constant delays, regardless of tract length, for both deterministic and probabilistic tractography. Impact: This multi-modal approach has the potential to improve understanding of how underlying white matter structure constrains brain [oscillatory] activity. Future research will focus on integrating additional structural and microstructural measurements to inform biophysical models of brain structural and functional connectivity.
Longitudinal Analysis of White Matter Lesions in Multiple Sclerosis using Mixture Modeling at 7 Tesla
Authors: Donnay Corinne , Gaitán María , Griffanti Ludovica , Reich Daniel , Nair Govind
Published: November 2024

Motivation: Analyzing multiple sclerosis (MS) lesions longitudinally is challenging, and requires consistent and robust imaging, processing, and statistical methods. Conventional binary lesion segmentations might overlook significant pathology changes as degeneration is continuous. Goal(s): To track subtle changes in MS lesions using statistically derived metrics. Approach: We introduced a two-component Mixture Model (MM) to track longitudinal changes qT1 with regions of interest (ROIs) and compared it with conventional image metrics. Results: In our longitudinal analysis, the MM approach uncovered changes missed by traditional methods suggesting MM may help capture and understand longitudinal evolution of MS lesions. Impact: Our novel mixture modeling analysis approach may untangle unique aspects of biological processes in MS lesion evolution, offering a valuable alternative to conventional image analysis methods.
Association between white matter hyperintensities and altered cerebral blood flow in maintenance hemodialysis patients: a longitudinal study
Authors: Mingan Li , wenbo Yang , Lijun Song , Boyan Xu , Zhenghan Yang , Hao Wang , Zhenchang Wang
Published: November 2024

Motivation: The relationship between white matter hyperintensity (WMH) and altered cerebral blood flow (CBF) in maintenance hemodialysis patients remains unclear. Goal(s): The study aims to explore the regulation of changes for CBF and its relationship with WMH burden in hemodialysis patients. Approach: Hemodialysis patients were divided into two groups based on whether their CBF decreased after 3-year therapy. The severity of white matter hyperintensity was compared between the two groups. Results: Compared with the increased CBF group, higher burden of deep WMH was found in the decreased CBF group. Impact: This association between WMH and decrased CBF in maintenance hemodialysis be beneficial to the exploration of the complex mechanisms underlying the development of cerebral abnormalities during hemodialysis.
Longitudinal neuroimaging combined with multi-omics reveals cerebral structural and functional changes in COVID-19
Authors: Lizhu Yuerong , Sun Jun , YANG Yu-Xin
Published: November 2024

Motivation: COVID-19's neurological effects remain ambiguous, with limited exploration of neuroimaging changes versus clinical symptoms, especially through pre-SARS-CoV-2 exposure longitudinal imaging, remains less explored. Goal(s): Understand brain change patterns and identify therapeutic targets for post-COVID-19 brain injury and neuropsychiatric effects. Approach: Utilized consistent neuroimaging on patients in acute recovery across two centers. Employed multiple clinical tools to gauge neuropsychiatric manifestations. Blood samples analyzed for protein profiles indicative of inflammation and neural damage. Results: Found significant vulnerability in the limbic lobe, observed contrasting pathological changes in symmetrical brain regions, and highlighted potential genetic and neurotrophic factors influencing neuropsychiatric symptoms post-COVID-19. Impact: This study offers clinicians a clearer path to target COVID-19-related neuropsychiatric symptoms. It prompts further inquiry into genetic influences on brain alterations, enabling tailored therapeutic strategies for affected patients.
Independent Component Analysis in Long Covid during cognitive exertion reveals widespread deficits in BOLD activity
Authors: Barnden Leighton , Baraniuk James , Thapaliya Kiran , Eaton-Fitch Natalie , Inderyas Maira , Marshal-Gradisnik Sonya
Published: November 2024

Motivation: To understand the cognitive deficits of Long Covid (LCov). Goal(s): What are the brain locations with different BOLD activity in LCov?Approach: Two consecutive fMRI were acquired in 19 LCov and 16 healthy controls (HC) with a 7 Tesla scanner during the cognitive color-word Stroop task. Run2 was affected by fatigue induced by Run1. BOLD time series were processed with the CONN toolbox and submitted to independent component analysis (group ICA). Results: ICA detected widespread deficits in LCov activity and sensorimotor excesses. The extent of LCov activity differences supports the hypothesis that global Covid19 infection affects brain-wide BOLD activity and regulatory function. Impact: Our discovery of brain-wide changes in Long Covid BOLD activity supports the mechanism of brain-wide Covid-19 infection inducing cognitive deficits. Research should be directed to therapies that eliminate cerebral infection and facilitate and monitor recovery from virus inflicted damage.
Fully-Automated Segmentation algorithm of Rectal Cancer and mesorectum on Multiparametric MR
Authors: Guo Lili , Fu Kuang , Wang Wenjia
Published: November 2024

Motivation: Developing a fast solution to segment rectal tumors and mesorectal tissue instead of the current manual labeling. Goal(s): The goal was to develop an automated segmentation model using nnU-Net for fully-automated segmentation of rectal cancer and mesorectum on MR images. Approach: The dataset was divided into training and testing sets, and pre-processing steps were conducted to minimize computational burden. The nnU-Net deep learning network was employed to train the model. Results: The Dice similarity coefficients for tumor and mesorectum in both the training and testing sets were as follows: 0.91 (training) and 0.88(testing) for tumor, and 0.93 (training) and 0.89 (testing) for mesorectum. Impact: This study proposes an automatic segmentation scheme for rectal tumor and mesentery using deep learning. It can be used to guide the annotation of new medical images, potentially improving the accuracy of rectal cancer treatment response predictions.
Nipple detection in breast dynamic contrast-enhanced magnetic resonance imaging using reinforcement learning
Authors: Piat Gauthier , Ouadahi Fares , Rouyer Julien
Published: November 2024

Motivation: As the nipple position knowledge becomes part of standardized report, the automatic detection can ease clinician’s workflow. Goal(s): The aim of our work is to accurately detect the position of the nipples in a dynamic contrast-enhanced (DCE) MR image. Approach: A reinforcement learning approach combined with a multi-constructor and multi-centric database enabled to initiate the development of a versatile tool in line with clinical real life. The detection problem was addressed using a Deep Q-Network trained with 248 breast DCE MR images. Results: The nipple positioning error is less than 10 millimeters in most of the breasts tested, i.e. 95/102 breasts. Impact: Nipple detection is a tedious task for clinicians and an arduous one for algorithms. Lesion to nipple distance is valuable information when planning surgery. This study explores the landmark detection domain to automate nipple detection using a reinforcement learning approach.