bluuebunny/crossref_metadata_2025 huggingface dataset:
A (k,t)-RAKI Method for Interpolating Sparse Data in Accelerated MRSI Acquisitions
Authors: Zhang Yunrui , Zhao Ruiyang , Wang Zepeng
Published: November 2024

Motivation: To further accelerate high-resolution MRSI acquisitions leveraging parallel imaging. Goal(s): While standard parallel imaging techniques such as (k,t)-GRAPPA can interpolate the sparsely sampled (k,t)-space in MRSI, learning-based nonlinear interpolation has demonstrated better performance in parallel MRI. But these methods have not effectively utilized the time/free induction decay (FID) dimension, which should be leveraged to improve interpolation accuracy. Approach: We adapted and extended the RAKI method by incorporating the FID dimension, via a 3D, complex-valued convolutional network, for MRSI reconstruction. Results: Our method effectively reconstructed data for different undersampling designs in in vivo MRSI, leading to improved subsequent spatiospectral processing results. Impact: We presented a self-supervised learning-based (k,t)-space interpolation method, (k,t)-RAKI, that is useful for further accelerating MRSI acquisition, in combination with subspace methods.
Frequency-selective inversion nulling ultra-short echo time (FINUTE) MRI for direct detection of lipids of the myelin bilayer
Authors: Swain Anshuman , Soni Narayan , Wilson Neil , Reddy Ravinder
Published: November 2024

Motivation: Recent studies have shown the effects of lipid dyshomeostasis and demyelination in the pathology of neurodegenerative diseases, especially early-onset Alzheimer’s disease. Consequently, imaging methods to monitor these changes are necessary. Goal(s): This study uses a novel sequence, termed FINUTE, to image short T2 lipids primarily associated with the myelin bilayer. Approach: Simulations and experiments on ex-vivo spinal cord specimens are performed for validation of methodology and applied in-vivo to assess changes in myelination in a mouse model of AD. Results: Results demonstrate FINUTE’s sensitivity to myelin lipids, with statistically significant white matter(corpus callosum) and visually-apparent gray matter(hippocampus) changes present in AD animals. Impact: FINUTE presents a non-invasive MR-imaging technique that is sensitive to lipids primarily in the myelin bilayer as well as in gray matter, thus providing a method for assessing myelination and lipid dyshomeostasis in neurodegenerative diseases such as AD.
Orientation independent quantification of macromolecular proton fraction in tissues with suppression of residual dipolar coupling
Authors: Gao Zijian , Yu Ziqiang , Zhou Ziqin , Hou Jian , Jiang Baiyan , ONG Michael Tim-yun , Chen Weitian
Published: November 2024

Motivation: The residual dipolar coupling (RDC) can lead to the orientation-dependent measurements in ordered tissues in MRI, potentially confounding their clinical applications. Goal(s): We demonstrate the potential confounding effect from tissue orientation in quantitative magnetization transfer can be suppressed by using a new technique Macromolecular Proton Fraction Mapping based on Spin-Lock (MPFSL). Approach: Applying MPFSL, we can adjust both the resonance frequency offset and the amplitude of spin-lock radiofrequency pulse to achieve a strong effective spin-lock field to suppress RDC, eliminating orientation-dependency of MPF measurement. Human knee specimen experiments conducted verified this finding. Results: The MPF measured using MPFSL shows insensitivity to tissue orientations. Impact: Spin-lock based quantitative magnetization transfer imaging can achieve orientation-independent quantification, thus having potential applications in characterization of highly-ordered tissues such as cartilage and myelin.
Aberrant activations associated with developmental dyslexia and READ1 deletion induced by visual/attentive tasks
Authors: Giubergia Alice , Mascheretti Sara , Arrigoni Filippo , Toraldo Alessio , Andreola Chiara , Villa Martina , Lampis Valentina , Giorda Roberto , Villa Marco , Peruzzo Denis
Published: November 2024

Motivation: Developmental Dyslexia (DD) is a complex and heritable neurodevelopmental disorder with heterogeneous genotype-phenotype pathways. Goal(s): Utilise fMRI as a bridge between genetic factors (DD-candidate risk genes) and behavioral traits (proficiency in reading skills). Approach: A GLM was used to test for relationships between reading proficiency, genetic mutation, and neural activations of two visual-attentive tasks. Results: A genetic vulnerability to alterations in neural activation was found in the ventral attentive and salient networks during reading-related stimuli in subjects with poor reading proficiency. Impact: Functional MRI has shown to be a valuable mediator linking genotype to phenotype, possibly leading to the optimization of criteria to diagnose Developmental Dyslexia and the early identification of children with a genetically driven susceptibility.
Altered dynamics of global cortical depth connectivity in depression
Authors: Pais-Roldán Patricia , Ramkiran Shukti , Yun Seong Dae , Rajkumar Ravichandran , Hagen Jana , Okla Areej Al , Veselinovic Tanja , Schnellbächer Gereon , Neuner* Irene , Shah* N. Jon
Published: November 2024

Motivation: A previous own study in healthy volunteers indicated that global laminar connectivity is highly dynamic, suggesting that it could be sensitive to altered brain conditions. Goal(s): Does global laminar connectivity change in depression? Approach: We acquired high-resolution fMRI data from patients before and after treatment and conducted a dynamic connectivity analysis focused on cortical depth. Results: The prevalence of the depth-connectivity states co-evolved with the psychometric scores of patients. Impact: The presented results may motivate other researchers working on laminar fMRI to average across ROIs and evaluate the effect of diverse brain conditions on the global component of depth-dependent connectivity, whose potential relevance is suggested by our preliminary studies.
Hyperactive Cerebellum in Alzheimer’s Disease
Authors: Elyan Rommy , Ahmed Biyar , Karunanayaka Prasanna
Published: November 2024

Motivation: Cerebellar involvement in Alzheimer’s disease (AD) has not been studied to the extent that cortical neuropathological changes have been. Historical and recent histopathological literature demonstrates cerebellar AD pathology while functional investigations have demonstrated disrupted intrinsic cortical – cerebellar connectivity in AD. Goal(s): Investigate metabolic activity and functional connectivity of the cerebellum with the default mode network, dorsal attention network, and primary olfactory cortex. Approach: Characterizing the cerebellum’s metabolic activity using 18F-fluorodeoxyglucose positron data from the Alzheimer’s Disease Neuroimaging Initiative. Results: In contrast to known parietal and temporal lobe FDG hypo-metabolism in AD, significant FDG hyper-metabolism was found in the cerebellum. Impact: Results show that resting state functional connectivity of cerebellar regions (that show hyper FDG metabolic activity) is impaired across brain-wide networks. Future work focusing on inhibitory control of the cerebellum as a potential pathway of AD pathogenesis is warranted.
Towards a multi-parametric MRI-based myelin marker in the developing mouse brain
Authors: Lee Choong Heon , Minteer Jennifer , Liang Zifei , Kim Yongsoo , Zhang Jiangyang
Published: November 2024

Motivation: Although several myelin markers have been introduced using MRI, their ability to accurately detect myelin has been limited in sensitivity and specificity. Goal(s): MP-MRI shows promise in improving myelin mapping, but validating its effectiveness remains a challenge. Our aim is to create a MP-MRI indicator and verify its accuracy through 3D myelin histology. Approach: We compared myelin histology in MOBP-eGFP mouse brains, which exhibit enhanced myelination with various MRI markers in the same subjects. Results: We observed varying degrees of correlation between MRI markers and MOBP signals in different brain regions. Employing PLSR analysis revealed that MP-MRI has potential to enhance myelin mapping. Impact: The integration of multiple MRI markers in multiparametric MRI has the potential to improve our capacity for mapping myelin in the brain. A direct biomarker of myelin would be highly impactful for management of patients with MS and de/dysmyelinating disorders.
Mapping glymphatic solute transportation through the perivascular space of hippocampal arterioles with 14 Tesla MRI
Authors: Zhou Xiaoqing , Man Weitao , Liu Xiaochen , Jiang Yuanyuan , Hike David , Cid Lidia Gomez , Choi Sangcheon , Lin Changrun , Yu Xin
Published: November 2024

Motivation: The perivascular space (PVS) plays a crucial role in facilitating the clearance of waste products and the exchange of cerebrospinal fluid and interstitial fluid in the central nervous system. Goal(s): However, the limited depth penetration of current imaging methods impedes the study of glymphatic dynamics in deep brain regions. Approach: In this study, we introduced an ultra-high-resolution dynamic contrast-enhanced MRI mapping approach based on single-vessel multi-gradient-echo methods. Results: This technique allowed the differentiation of penetrating arterioles and venules from adjacent parenchymal tissue voxels and enabled the detection of Gd-enhanced signals coupled to PVS of penetrating arterioles in the deep cortex and hippocampus. Impact: The study revealed significant PVS-specific Gd signal enhancements, shedding light on glymphatic function in deep brain regions. These findings advance our understanding of brain-wide glymphatic dynamics and impaired waste clearance, warranting further exploration of their clinical relevance and therapeutic applications.
Charting vascular network architecture in primate brain using ferumoxytol-weighted laminar MRI
Authors: Autio Joonas , Kimura Ikko , Ose Takayuki , Matsumoto Yuki , Ohno Masahiro , Urushibata Yuta , Ikeda Takuro , Glasser Matthew , Van Essen David , Hayashi Takuya
Published: November 2024

Motivation: Although the brain's vascular network plays a crucial role in supplying oxygen and glucose while removing metabolic by-products to meet the high energy demands of neural information processing, our understanding of the vascular network architecture in the primate brain remains limited. Goal(s): To address this issue, our study aims to explore the variability of the vascular network and its relationship to underlying neuroanatomy. Approach: We investigate brain vascularity in macaque monkeys using ferumoxytol-weighted laminar MRI. Results: We demonstrate that vascularity exhibits 3-fold variation across brain regions, moderate variability across cortical layers, distinct translaminar clusters, and strong association with neuron and synaptic densities. Impact: Laminar ferumoxytol-weighted MRI shows considerable potential to delineate pial vessel network, intracortical feeding arteries and draining veins and density of capillary networks. The capillary density exhibits close association with the underlying neuroanatomy.
Comparison of White Matter Maturation Rates in Young Rhesus Macaques and Humans
Authors: Allen Carly , Dean Douglas , Moody Jason , DiPiero Marissa , Aggarwal Nakul , Kalin Ned , Alexander Andrew , Kecskemeti Steve
Published: November 2024

Motivation: Non-human primates are thought to develop 3-4 times faster than humans based on sexual maturity and death; however, there has been a lack of quantitative data to support this ratio to describe brain development. Goal(s): Our goal was to find a quantitative relationship between the rate of white matter myelination in rhesus macaques and humans. Approach: We compared rates of change in quantitative relaxometry MRI T1 values in six ROIs for rhesus macaques and human infants. Results: We found a ratio ranging from 4.7 to 6.2 in the ROIs, corresponding to 4.7-6.2 times faster white matter myelination in rhesus macaques than humans. Impact: By providing a quantitative approach to comparing early-life rhesus macaques white matter development with human infants, research that relates rhesus macaques and human brain development can make a more informed comparison, assisting researchers in translating results between species.
Spatio-Angular Noise2Noise for Self-Supervised Denoising of Diffusion MRI Data
Authors: Jiang Haotian , Zhang Shu , Wen Xuyun , Cui Hui , Lu Jun , Rekik Islem , Ma* Jiquan , Chen* Geng
Published: November 2024

Motivation: Diffusion MRI (DMRI) suffers from heavy noise. The noise issue reduces the accuracy and reliability of the derived diffusion metrics. Goal(s): Existing Deep Learning (DL) methods for DMRI denoising usually rely on training with paired noisy-clean data, which are unavailable in a clinical setting. Therefore, we propose a self-supervised DL denoising method, called Spatio-Angular Noise2Noise, for DMRI denoising. Approach: We stem from the fact that a network trained with paired noisy data can capture the essential information of underlying clean data for noise reduction. Results: Extensive experiments on simulated and real datasets demonstrate the superiority of SAN2N over existing DMRI denoising methods. Impact: SAN2N can reduce the noise effectively and improve the quality of fiber ODFs and tractography.
Simultaneously multi-parameter mapping via SSFP multiple overlapping‑echo acquisition and deep learning reconstruction
Authors: Chen Weikun , Lin Qing , Yao Qiaoli , Zhu Liuhong , Lin Liangjie , Wang Jiazheng , Chen Zhong , Cai Shuhui , Cai Congbo
Published: November 2024

Motivation: Multi-parametric quantitative magnetic resonance imaging provides a comprehensive and detailed characterization of tissue properties, enhancing the diagnostic accuracy and potential for scientific research. However, the long acquisition time limits its widespread application. Goal(s): To provide a method that can quickly realize multi-parametric quantitative magnetic resonance imaging. Approach: We designed a fast multi-parametric quantitative magnetic resonance imaging method which combines balanced steady-state free precession sequence with multiple overlapping echo detachment imaging technique. Results: Experimental results show that the proposed method can simultaneously obtain accurate T1, T2, T2*, proton density (PD), B0, and B1 parametric maps. Impact: The proposed method can simultaneously obtain accurate T1, T2, T2*, PD, B0, and B1 maps without distortion or artifacts, and no registration is needed. It has great potential for clinical application.
3D/4D Ultrashort Echo Time Balanced-SSFP MR Lung Images Reconstructed Using XD-GRASP-Pro
Authors: Garrison William , Miller Zachary , Mugler John , Cai Jing , Miller G
Published: November 2024

Motivation: Obtaining high-quality images of the lung using proton MRI is challenging due to breathing motion and the short T2* and low proton density of lung parenchyma. Goal(s): Our goal was to demonstrate a free-breathing proton lung MRI approach that maximizes parenchyma and vessel signal in the lungs. Approach: This method combines a 3D ultra-short echo time (UTE) balanced steady-state free precession (bSSFP) pulse sequence with a GRASP-Pro-based reconstruction algorithm applied to respiratory phase-binned data. Results: Image quality was markedly better for SSFP images than for spoiled images, and end-of-exhalation frames reconstructed from 4D images compared favorably with respiratory-triggered images. Impact: A UTE bSSFP radial pulse sequence combined with temporally-constrained reconstruction produces high-signal, high-resolution lung images at end-of-exhalation collected during free breathing. While non-end-of-exhalation reconstruction was less effective, a similar reconstruction algorithm that incorporates motion fields could improve results.
Spatiotemporal CBF dynamics underlies emergence of limbic-sensorimotor-association cortical gradient and adaptive behavior in human infancy
Authors: Ouyang Minhui , Detre John , Sindabizera Kay , Kuschner Emily , Edgar J. Christopher , Huang Hao
Published: November 2024

Motivation: Infant cerebral blood flow (CBF) delivers nutrients to meet the brain’s energy demand for the fastest period of brain development across lifespan. Goal(s): The presented study delineates the organizing principle of whole-brain CBF dynamics during infancy. Approach: We optimized a state-of-the-art pseudo-continuous-arterial-spin-labeled (pCASL) sequence to obtain high-resolution spatiotemporal dynamics of infant CBF at isotropic 2.5mm. Results: We revealed infant physiological heterogeneity and found the emergence of the limbic-sensorimotor-association cortical gradient based on CBF. Infant regional CBF changes were also associated with their improved real-world developmental functioning. These normative charts of infant CBF can serve as atlases for research and clinical care. Impact: Capitalizing on a 3D multi-shot stack-of-spirals pCASL, we acquired the highest-resolution infant CBF maps available to date, discovered the emergence of the limbic-sensorimotor-association cortical gradient in infancy, and provide a standardized reference for infant CBF.
Cardiac Magnetic Resonance Cine Images derived-Radiomics for the Prediction of Event Free Survival in Patients with Acute Myocardial Infarction
Authors: A Xin , Zhang Ying , Chen Yundai
Published: November 2024

Motivation: Prognostic value of radiomic features extracted from CMR cine image remains to be investigated. Goal(s): To evaluate the prognostic value of radiomic features derived from cine images in patients with ST-segment elevation myocardial infarction (STEMI). Approach: Radiomic features were extracted from CMR cine images on STEMI patients, and LASSO -Cox regression used to select predictive features for MACE. Cox regression was applied to build models. Results: RAD score provided an incremental prognostic value above baseline clinical factors and LVEF (C-index 0.78 vs 0.69; p=0.002) and outperformed the addition of CMR markers of infarct injury (C-index: 0.78 vs 0.69, p<0.001). Impact: Radiomic features provide incremental prognostic value to clinical and infarct size in the prediction of MACE, which would promote the development of the prognostic assessment with non-contrast enhanced CMR.
Impact of jugular vein ligation on cerebrospinal fluid clearance from G-lymphatic system in mice
Authors: Ruze Anthony , Mouton Laura , Singhabahu Ruchith , Gottschalk Joshua , Spajer Myriam , Thomas Jean-Léon , Lenck Stéphanie , Santin Mathieu
Published: November 2024

Motivation: Cerebral venous outflow abnormalities have been linked to various neurological disorders, necessitating a detailed understanding of their impact on brain and lymphatic perfusion. This study aimed to investigate the G-lymphatic system change following bilateral jugular vein ligation (JVL) in mice. Goal(s): Deeper understanding of the venous system's role in CNS fluid homeostasis. Approach: JVL was performed in mice. 2D-TOF, DCE-FLASH and 3D-MGE imaging were acquired at baseline, 2, 7 and 14-days post-surgery. Quantitative analysis was used to assess changes in lymphatic flow, brain volumetry. Results: JVL induced hypertension, bigger brain and veinous system. The permeability in the brain reduced before returning to baseline. Impact: Our study demonstrated progressive alterations in cerebral blood flow in mice following jugular vein ligation, highlighting the utility of MRI for studying the G-lymphatic system in brain. These findings contribute to a better understanding of cerebrovascular changes in living conditions.
Using Real Time Phase contrast MRI to investigate CSF oscillations and aqueductal pressure gradients during free breathing
Authors: LIU Pan , Owashi Kimi , Capel Cyrille , Metanbou Serge , Balédent Olivier
Published: November 2024

Motivation: CSF dynamics is complex and regulates intracranial pressure. Pressure difference dynamics between the third and fourth ventricles (ΔPt) drives CSF oscillations in the aqueduct. MRI can quantify aqueduct anatomy and CSF oscillations. Goal(s): To quantify ΔPt during free-breathing by combining MRI anatomical imaging with real-time phase-contrast MRI. Approach: We developed a dedicated software to obtain: CSF flows dynamics Q(t), morphology of the aqueduct, its flow resistance (R) and ΔPt which equal R·Qt. Cardiac and breathing contributions to ΔPt were investigated in volunteers. Results: Contributions to ΔPt were 12.3 Pa and 9.5 Pa from cardiac and breathing respectively. Impact: Dedicated post-processing of real-time phase-contrast MRI allows quantification of CSF oscillations in the aqueduct and the pressure gradient between the third and fourth ventricles. Furthermore, continuous flow acquisition allows calculation of the cardiac and breathing influence on the pressure gradient.
Toward Task-Based Reconstruction: Evaluating Relationships Between Reconstruction and Object Detection Performance
Authors: Konovalova Natalia , Tolpadi Aniket , Bhattacharjee Rupsa , Luitjens Johanna , Gassert Felix , Giesler Paula , Majumdar Sharmila , Pedoia Valentina
Published: November 2024

Motivation: Traditional medical image reconstruction emphasizes standard metrics, potentially overlooking optimization for downstream tasks like segmentation and anomaly detection. Goal(s): Our study investigates the relationship between standard reconstruction and object detection metrics. Approach: We trained a Faster R-CNN detector for meniscal anomalies, addressing class imbalance and implementing a custom detection-specific augmentation protocol. Results: Evaluation on reconstructed datasets revealed that reconstruction quality was associated with true predictions but had a limited impact on overall detection performance, while boxes-based reconstruction metrics showed no correlation with prediction outcomes. These findings underscore the importance of considering associations between standard reconstruction and downstream task metrics when optimizing end-to-end pipelines. Impact: Evaluation of standard reconstruction metrics, sliced by object detection outcomes, revealed a significant association between reconstruction and detection performance, emphasizing the utility of this approach in assessing task-based reconstruction.
Graph kernel assisted robust individual and group level functional brain parcellation (GRAFP)
Authors: Mohapatra Sovesh , Ouyang Minhui , Peng Qinmu , Huang Hao
Published: November 2024

Motivation: Various rs-fMRI studies highlight the need for accurate delineation of different brain functional networks (FNs) to carry out precise therapeutic interventions in the individuals. Goal(s): To develop a novel zero-shot non-linear graph kernel-assisted approach for enhanced functional brain parcellation at individual and group levels. Approach: Utilization of Wavelet, Fourier, and Hilbert transformations for feature extraction from BOLD signals, and a propagation attribute graph kernel to capture non-linear temporo-spatial connectivity, using k-means clustering. Results: The kernel-based approach outperforms static FC matrix parcellations, achieving higher accuracy in network delineation in both individual and group level, as evidenced by Dice and Jaccard scores. Impact: The study introduced graph kernel-based method for functional brain parcellation, which improved the accuracy of functional network delineation in rs-fMRI data, surpassing traditional static functional connectivity approaches in both individual and group level, as validated by Dice and Jaccard metrics.
Generic and Robust Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations
Authors: Kuppens Daan , Barbieri Sebastiano , Rauh Susanne , Gurney-Champion Oliver
Published: November 2024

Motivation: Tissue properties are estimated from MRI data using bio-physical models that relate MRI signal to underlying tissue properties via quantitative MRI parameters. Deep learning can improve parameter estimation, but needs retraining for different acquisition protocols, hindering implementation. Goal(s): Implement a deep learning algorithm able to estimate quantitative MRI parameters for multiple quantitative MRI applications, irrespective of acquisition protocol. Approach: Neural controlled differential equations (NCDEs) overcome this limitation as they are independent of the configuration of input data. Results: NCDEs have improved performance compared to least squares minimization in estimating quantitative MRI parameters when SNR is low or when the parameter has low sensitivity. Impact: Neural controlled differential equations are a generic purpose tool for parameter estimation in quantitative MRI that outperform least squares minimization in quantitative MRI parameter estimation, irrespective of acquisition protocol or quantitative MRI application.
Enhanced motion artifact simulator for structural MRI with MP-RAGE sequence
Authors: Wu Tianqi , Sokolska Magdalena , Thomas David , Grech-Sollars Matthew , Zhang Hui
Published: November 2024

Motivation: Motion compromises the utility of structural MRI with MP-RAGE sequence, a workhorse of quantitative neuroimaging research. Recent interest in deep learning-based mitigating solutions, and the scarcity of motion-corrupted data, motivates the need for realistic data simulation. Unfortunately, existing open-source simulators fail to consider important features in real-world acquisitions, including variations in phase-encoding direction, multi-coil acquisition and GRAPPA parallel imaging, resulting in less realistic simulations. Goal(s): We aim to develop a more realistic motion artifact simulator for MP-RAGE structural MRI. Approach: We extend TorchIO, an existing simulation framework, to support aforementioned features. Results: The comparison between simulations demonstrated the importance of including these features. Impact: The proposed simulation framework can be used to generate more realistic motion-corrupted MRI data from clean images. These data can be served as training sets for deep learning algorithms in motion artifact related applications.
Detunable Wireless Litzcage Coil for Human Head MRI at 1.5T
Authors: Zhu Haoqin , Lang Michael L. , Yang Yijin , Martin Melanie , Zhang Gong , Zhang Qiang , Chen Yuanyuan , Yan Xinqiang
Published: November 2024

Motivation: Detuning wireless volume coils is challenging due to their complex structure, multiple resonant modes and multiple detuning circuits. Goal(s): Developing an efficient method to geometrically decouple from the body coilApproach: Designing an inductive birdcage coil featuring a figure-of-eight conductor pattern within the rungs, conducting volunteer and phantom image for compare its performance with the body coil and a receive array. Results: The wireless Litzcage coil offers ~3.9 times higher SNR than the body coil. A 10% boost in the central area, a 21% reduction at the surface, and similar head image quality compared to a commercial 12-channel Head coil. Impact: Applies to 0.55T, 3.0T, and 7T MRI systems, and expands to extremity, breast and body imaging. Simplifies coil design, improves detuning, and lowers costs. Lightweight and user-friendly, enabling MRI-guided therapy and streamlined clinical processes.
Prediction of Low Quality ADC Maps from T2 Scans
Authors: Brender Jeffrey , Ota Mitsuki , Krishna Murali , Ford Joshua , Choyke Peter , Turkbey Ismail
Published: November 2024

Motivation: ADC maps are an essential tool for early prostate cancer detection but are often uninterpretable due to imaging artifactsGoal(s): Detect problems early in the imaging procedure using T2 images to predict the future quality of the ADC mapApproach: Constructed a multisite corpus of 486 patients imaged at both the NIH and outside. Investigated the influence of acquisition parameters on image quality and the predictive power of neural networks and simple anatomy measurements from the T2 imageResults: ADC image quality can be predicted from the T2 image using either a neural network approach or measurement of the rectal cross-sectionImpact: The probability of a low quality, uninterpretable ADC maps can be inferred early in the imaging process, allowing corrective action (e.g. removal of gas by a muscle relaxant) to be employed
Resting-state changes along the cortical depth detected during evolution of major depressive disorder
Authors: Pais-Roldán Patricia , Yun Seong Dae , Ramkiran Shukti , Rajkumar Ravichandran , Hagen Jana , Okla Areej Al , Veselinovic Tanja , Schnellbächer Gereon , Neuner* Irene , Shah* N. Jon
Published: November 2024

Motivation: The relative contribution of each cortical depth to the network disturbances coupled with depression remains unexplored. Goal(s): We aim to identify changes in connectivity along the cortical thickness during depression recovery. Approach: We use high-resolution, large-coverage EPIK to functionally map the brain of patients before and after treatment and perform cortical-depth specific analysis of network connectivity. Results: Changes in connectivity linked to depression treatment were observed at multiple depths of the cortex in two resting-state networks. Impact: The demonstration that network connectivity does not change homogeneously in a patient population along the cortical depth suggests the importance of adding this variable to the analysis of psychiatric disorders to improve understanding of the mechanisms behind network disturbances.
Cognition-related connectome gradient dysfunctions of thalamus and basal ganglia in drug-naïve first-episode major depressive disorder
Authors: Zhang Qian , Zhao Youjin , Zhang Aoxiang , Chen Lizhou , Gong Qiyong
Published: November 2024

Motivation: The continuous spatial patterns of inter-region connectivity within the subcortical network still remain less well-understood in MDD. Goal(s): Using functional gradient mapping, a novel approach to identify hierarchical organization of functional networks, we aim to evaluate multiscale subcortical gradients in MDD and their association with cognition. Approach: Subcortical gradient alterations at the global-, system-, and subregion-levels and their relation to neuropsychological functioning were assessed in MDD patients relative to healthy controls. Results: Principal gradient values were lower in thalamic and limbic systems but higher in basal ganglia in MDD. Interactions between thalamic and basal ganglia gradient alterations were implicated in MDD-related memory impairments. Impact: Multiscale subcortical gradient alterations can enhance our understanding of MDD-related hierarchical disturbances in subcortical function and may provide useful clinical biomarkers for cognitive impairments in MDD.
Disrupted brain functional connectome gradient in social anxiety disorder
Authors: Zhang Xun , Gong Qiyong
Published: November 2024

Motivation: Although discrete macroscale functional network abnormalities were observed in social anxiety disorder (SAD), the alterations of continuous spatial patterns of functional connectomes remain unknown. Goal(s): We aimed to use a novel method to characterize aberrant patterns of connectome gradients in SAD patients. Approach: We applied diffusion map embedding to characterize functional connectome gradients and investigated between-group differences of global and regional topological features and their clinical relevance. Results: Globally, SAD patients demonstrated decreased explanation ratio, narrower gradient range and less spatial variation in the principal gradient. Regionally, SAD group showed increased gradients in the sensorimotor networks and decreased in the default mode network. Impact: Our findings of internally clinically-relevant disrupted hierarchy patterns of functional connectomes could add further insights into the neurobiological underpinnings of SAD, and may advance the development of objective biomarkers for early diagnosis, targeted intervention, and therapeutic efficacy evaluation in SAD.
Dynamic Estimation of Respiration-Induced B0 Inhomogeneities in OSSI fMRI: A Novel Framework Using FIDNavs and SENSE Maps
Authors: Salifu Mariama , Noll Douglas
Published: November 2024

Motivation: In OSSI fMRI, temporal fluctuations in the B0 field, predominantly resulting from respiration, can induce changes to the steady state, subsequently diminishing the temporal signal-to-noise ratio (tSNR)Goal(s): Our objective is to develop an efficient technique for estimating respiration-induced B0 variations in OSSI fMRIApproach: We have used Free Induction Decay (FID) frequency offset to estimate the first-order field inhomogeneities. A novel element in our approach lies in adopting a spatial encoding strategy for these FIDs, drawing on the geometric centroids of each coil's sensitivity profileResults: Our initial findings indicates comparable results between our FIDNavs method and image-based field map method. Impact: This approach allows for a rapid measurement of B0 variations, thus facilitating faster real-time corrections. This method bypasses the lengthy process of calibration or the need for reference images.
Sequence Adaptive B1+ and B0 Field-imperfections Estimation (SAFE) for enhanced MRF quantification
Authors: Gao Mengze , Cao Xiaozhi , Abraham Daniel , Zhou Zihan , Setsompop Kawin
Published: November 2024

Motivation: B1+ and B0 field-inhomogeneities can significantly reduce accuracy and robustness of MRF’s quantitative parameter estimates. Additional B1+ and B0 calibration scans can mitigate this but add scan time and cannot be applied retrospectively to previously collected data. Goal(s): Here, we proposed a calibration-free sequence-adaptive deep-learning framework, to estimate and correct for B1+ and B0 effects of any MRF sequence. Approach: We demonstrate its capability on arbitrary MRF sequences at 3T, where no training data were previously obtained. Results: Such approach can be applied to any previously-acquired and future MRF-scans. The flexibility in directly applying this framework to other quantitative sequences is also highlighted. Impact: Proposed method can estimate B1+ and B0 maps without calibration scan and be applied to arbitrary MRF sequence without new training data. It can be used retrospectively to improve quality of parameter maps of any previously-acquired or future MRF data.
High-Fidelity ASL Perfusion Imaging Using Unsuppressed Water Signals in MR Spectroscopic Imaging
Authors: Guo Rong , Shao Xingfeng , Li Yudu , Zhao Yibo , Jin Wen , Li Yao , Wang Danny , Sutton Brad , Liang Zhi-Pei
Published: November 2024

Motivation: ASL and MRSI experiments are currently performed using different sequences, and EPI-based ASL methods suffer from spatial distortion and limited SNR. Goal(s): To develop a water unsuppressed MRSI based imaging method for high-fidelity ASL-based perfusion imaging. Approach: The SPICE sequence was integrated with a PASL module for ASL acquisition, and a GS model-based method was used for image reconstruction. Results: The proposed method achieved ASL at 2×2×2 mm3 resolution and MRSI at 2×3×3 mm3 within 9 minutes in total. Compared with typical EPI-based methods, the resulting ASL images were free from spatial distortion, and had adequate SNR within a short scan time. Impact: This work presents a new method for high-fidelity ASL-based perfusion imaging combining with MRSI-based metabolic imaging. With further development, it may provide a powerful brain imaging tool for both functional studies and clinical applications.
Axon diameter mapping in the living human brain with ultra-high gradient diffusion MRI using 500 mT/m gradient strength
Authors: Ma Yixin , Lee Hong-Hsi , Lee Hansol , Ramos-Llordén Gabriel , Chan Kowk Shing , Huang Susie
Published: November 2024

Motivation: Noninvasive quantification of axon diameter in the living human brain offers valuable insights into the mesoscopic organization of white matter. Current methods for mapping axon diameter using diffusion MRI are limited by gradient strength. Goal(s): To evaluate the sensitivity of axon diameter mapping to small diameter axons on the Connectome 2.0 scanner (Gmax=500mT/m) compared to the original Connectome scanner (Gmax=300mT/m). Approach: The AxCaliber-SMT model was fitted to diffusion MRI data in 10 healthy subjects scanned on Connectome 2.0 and Connectome 1.0. Results: Median axon diameter in the corticospinal tract was 2.63um on Connectome 2.0 and 4.00um on Connectome 1.0. Impact: Connectome 2.0 pushes the resolution limit and signal-to-noise ratio of axonal diameter mapping, allowing for greater sensitivity toward small diameter axons at the individual level for a variety of neuroscientific and clinical applications.
An MRF approach for Simultaneous T1- and PRFS-based 3D MR-Thermometry
Authors: Gutt Moritz , Horstmann Dominik , Wacker Frank , Hensen Bennet , Gutberlet Marcel
Published: November 2024

Motivation: The classical PRFS-based approach to MR-thermometry cannot be used in adipose tissue and is vulnerable to susceptibility artifacts. Nonetheless, the PRFS-based method is quite accurate in aqueous tissue when no severe susceptibility artifacts occur. Goal(s): A simultaneous measurement of T1 could be used to account for susceptibility artifacts and perform thermometry in adipose tissue. Approach: An MRF sequence was designed to measure T1 and the PRF at the same time. It was tested during a microwave ablation on a liver phantom. Results: The PRFS-based temperature maps had a higher temperature accuracy while the T1-based temperature maps performed better in predicting the ablation zone. Impact: It was shown that simultaneous T1- and PRFS-based 3D-Thermometry is possible using MRF. While the T1 proved to be more robust to susceptibility-induced errors, the PRF had a better temperature accuracy. A combined approach could provide a more accurate MR-thermometry.
Real-time automatic multipoint temperature regulation during MRI-guided Laser-induced Thermotherapy (MR-LITT)
Authors: Desclides Manon , Ozenne Valéry , Bour Pierre , Machinet Guillaume , Pierre Christophe , Chemouny Stéphane , Quesson Bruno
Published: November 2024

Motivation: Current Laser devices used during MR-guided LITT can use single or multiple fibers to create coagulation necrosis, but do not provide opportunities for precise temperature control in tissue. Goal(s): We present an automatic control algorithm combined with a multi-source laser that allows the temperature to be forced to follow predefined temperature profiles. Approach: Fast, multi-slice thermometric data are processed on the fly to achieved efficient volumetric temperature regulation of multiple laser sources simultaneously. Results: We offer a precise and rapid volumetric temperature control solution combined with multi-source LITT to create conformal ablation volumes larger than those achieved with a single fiber. Impact: Automatic volumetric temperature regulation of multisource LITT combined with real-time multislice MRI thermometry allows better control of local thermotherapies in soft tissues.
Low-intensity focused ultrasound with continuous theta burst stimulation induces human primary motor cortex functional connectivity changes
Authors: Yang Wei-Chih , Chen Kai-Hsiang , Kuo Yih-Chih , Dong Yan-Siou , Chen Gin-Shin , Shih Yao-Chia
Published: November 2024

Motivation: Combining low-intensity transcranial focused ultrasound stimulation (TUS) akin to continuous theta burst stimulation (cTBS) setting (ctbTUS) with cTBS over M1 can be a potential strengthening non-invasive neuromodulatory method. Goal(s): To understand the neuroplasticity in response to ctbTUS or simultaneous ctbTUS+cTBS. Approach: Resting-state fMRI with seed-based analysis with seeds of M1 and its first dorsal interosseous (FDI) muscle representation (M1FDI) was used to assess functional connectivity (FC) changes due to cTBS, ctbTUS, or ctbTUS+cTBS. Results: We replicated M1-FC degradations in ipsilateral sensorimotor regions due to cTBS, and verified the potential synergic effect of ctbTUS+cTBS on M1-FC decreases in supplementary motor area. Impact: Our study is the first to use resting-state fMRI to investigate FC changes within motor network due to either cTBS, ctbTUS, or ctbTUS+cTBS stimulations on left M1. The results help understand the potential of ctbTUS+cTBS to be a novel therapy.
Resting-State Functional Quantitative Susceptibility Mapping (rsfQSM)
Authors: Nassar Jannette , Kiersnowski Oliver , Fuchs Patrick , Weil Rimona , Shmueli Karin
Published: November 2024

Motivation: Task-based functional Quantitative Susceptibility Mapping (fQSM) shows more localized brain activations than fMRI. Resting-state fMRI reveals brain connectivity networks but resting-state analysis of QSM has not yet been performed and may provide complementary information. Goal(s): To perform a resting-state functional analysis using QSM (rsfQSM) and compare it to rsfMRI, focusing on the Default Mode Network (DMN). Approach: We used seed-based and ICA-based analyses for rsfQSM and assessed the similarity of the DMN to that in rsfMRI with quantitative metrics. Results: The DMN was detected in rsfQSM with spatial similarities to the DMN in rsfMRI. rsfQSM showed weaker and less extensive functional connectivity. Impact: We computed resting-state functional connectivity from magnetic susceptibility maps for the first time, revealing similarities in the default-mode network compared to rsfMRI. This paves the way for new QSM-based explorations of brain function to potentially deepen understanding of neurological diseases.
Functional connectome through the human life span
Authors: Sun Lianglong , Zhao Tengda , Liang Xinyuan , Xia Mingrui , Li Qiongling , Liao Xuhong , Gong Gaolang , Wang Qian , Pang Chenxuan , Yu Qian , He Yong
Published: November 2024

Motivation: The normative developmental and aging trajectory of the functional connectome in the human brain remains unknown. Goal(s): To establish the normative growth trajectory of functional connectome from the largest, quality-controlled multimodal neuroimaging dataset. Approach: We aggregated 33,809 task-free fMRI scans from 32,328 individuals aged 32 postmenstrual weeks to 80 years from 119 global sites, and quantified lifespan growth charts using generalized additive models for location, scale, and shape (GAMLSS). Results: We uncovered nonlinear connectome growth at the whole cortex, system, and regional levels, identified critical developmental inflection points, and demonstrated substantial individual heterogeneities in patients with ASD and patients with MDD. Impact: Our findings elucidate for the first time the lifespan evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neuropsychiatric disorders.
Deep Learning-based Disambiguation for Multiple AD Radiotracers using PET/MRI
Authors: Kumar Ashwin , Kim Donghoon , Mormino Elizabeth , Chaudhari Akshay , Young Christina , Chen Kevin , Khalighi Mehdi , Zaharchuk Greg
Published: November 2024

Motivation: AD patients must undergo repeated visits for amyloid and tau radiotracer imaging, leading to high costs and dose concerns due to PET's inability to simultaneously acquire multiple radiotracers during a single session. Goal(s): Using PET/MRI scans, we used deep learning to create separate amyloid and tau PET images from a simulated combined dual-tracer image. Approach: We simulated a combined amyloid-tau image by blending co-registered list-mode data and employed a 2.5D U-Net architecture for effective separation. Results: Mixed-dose models, incorporating physics-inspired data augmentation and MR information, exhibited enhanced anatomical preservation and reduced variability in quantitative metrics. Impact: The demonstrated separation of a simulated combined amyloid and tau PET/MRI study into its individual components using DL may allow for simultaneous injection of multiple radiotracers in a single acquisition, streamlining the imaging process for AD patients.
Preliminary investigation of BOLD dependence on EEG-TMS using a closed-loop TMS-EEG-fMRI setup
Authors: Laurinoja Joonas , Hassan Umair , Nyrhinen Mikko , Makkonen Matilda , Lioumis Pantelis , Lin Fa-Hsuan , Zrenner Christoph , Ilmoniemi Risto , Aydogan Dogu Baran
Published: November 2024

Motivation: The motivation for this research study is to improve the efficacy of transcranial magnetic stimulation. Goal(s): The specific goals of this study are to establish a closed-loop TMS-EEG-fMRI system and to investigate brain state-dependent EEG-TMS responses in relation to concurrent fMRI measurements. Approach: 150 single TMS pulses are delivered while monitoring TMS-elicited network activity using interleaved fMRI acquisition. Data processing involves extracting EEG phase information, preprocessing of fMRI data, and statistical analysis using SPM12. Results: Significantly increased fMRI signal was detected in the M1 and SMA under specific EEG phase conditions. These results illustrate the relationship between TMS, EEG phases, and BOLD responsesImpact: The results of this study have important implications for the field of non-invasive brain stimulation and neuroimaging. The development of a closed-loop TMS-EEG-fMRI system holds the potential to revolutionize the treatment of various brain disorders by personalizing TMS interventions.
Cross-validating magnetic resonance elastography and ultrasound time-harmonic elastography of the brain by using a 3D optical tracker
Authors: Chandía Stefan Klemmer , Schattenfroh Jakob , Brinker Spencer , Tzschätzsch Heiko , Meyer Tom , Sack Ingolf
Published: November 2024

Motivation: Magnetic resonance elastography (MRE) and ultrasound time-harmonic elastography (USE-THE) have not been cross-validated yet. Since their results are in 3D and 2D, respectively, aligning them is difficult. Goal(s): To cross-validate MRE and USE-THE in the brain based on a common atlas space. Approach: An optical system tracked the position of fiducial markers derived from MRE during USE-THE measurements. Consequently, the resulting spatial alignment of both measurements allowed direct comparison. Results: Stiffness was averaged over the whole field-of-view and over five anatomical regions. Globally, agreement was good (ICC=0.6982) and regionally, it was acceptable based on a Wilcoxon signed test (p>0.05). Impact: Agreement between cerebral MRE and USE will facilitate multi-modal neural tissue characterization. Combined MRE-USE could benefit from high spatial resolution of MRE and high temporal resolution of USE-THE.
Magnetic Particle Imaging goes clinical routine? – first step to human-sized MPI-guided intervention in realtime
Authors: Vogel Patrick , Rückert Martin , Günther Johanna , Reichl Teresa , Kampf Thomas , Bley Thorsten , Behr Volker , Herz Stefan
Published: November 2024

Motivation: The gold-standard for guiding minimally invasive cardiovascular interventions is X-ray (digital subtraction angiography - DSA). Can we reduce the radiation exposure for clinical staff and patients?Goal(s): The use of alternative radiation-free imaging methods providing all necessary features can reduce the radiation exposure dramatically. Approach: The imaging modality Magnetic Particle Imaging (MPI) uses iron-oxide-based nanoparticles as tracer for realtime visualization of dynamic processes. In a first step, this technique could be used to support clinical DSA treatment. Results: In a first study, a lightweight and portable human-sized MPI scanner has been built and successfully tested under realistic conditions with vascular phantoms within a catheter-lab. Impact: First simultaneous MPI/DSA hybrid imaging in human-sized phantoms demonstrates the feasibility of scaling-up the MPI technology. With a clinical approved tracer, MPI could be ready for clinical routine.
3D-TOF MRA at 5.0T MR:Visualization of Superior Cerebellar Artery
Authors: Tian Ning , Gan Jie , Yu Dan , Yin Dong , Jiang Sen , Yu Lei
Published: November 2024

Motivation: To improve non-invasive visualization of the superior cerebellar artery (SCA) for better clinical outcomes. Goal(s): To assess the feasibility of using 3D-TOF MRA at 5.0 T MR for detailed imaging of the SCA. Approach: Retrospective analysis of high-resolution 5.0T MR images from patients with suspected cerebrovascular diseases, focusing on the SCA's anatomical details. Results: The study confirmed that 5.0T MRA provides accurate SCA imaging, consistent with anatomical and CTA results, crucial for diagnosing and managing related cerebrovascular conditions. Impact: The study provides a new non-invasive benchmark for SCA imaging, potentially reducing iatrogenic risks in neurosurgery and informing the etiology of trigeminal neuralgia, paving the way for safer surgical practices and targeted treatments.