bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Network-based Classification of Aortic Stenosis Severity and Velocity Inlet Prediction from Cine 2D Flow MRI
Authors: Wolkerstorfer Gloria , Dirix Pietro , Buoso Stefano , Kozerke Sebastian
Published: November 2024

Motivation: Imaging stenotic aortic valves using cine 2D and 4D Flow-MRI is compromised by flow-related image artefacts, making estimation of the effective orifice area challenging. Goal(s): To estimate aortic valve orifice area and inlet velocity profiles from 2D PC-MRI slices, acquired downstream of the aortic valve. Approach: Synthetic 2D PC-MRI slices were generated from personalized synthetic flow simulations of pulsatile flow in realistic stenosed aortae. Two U-Nets were trained to predict valvular orifice and inlet velocity profiles. Results: This work demonstrates that classification of aortic stenosis and prediction of peak systolic velocities from synthetic 2D PC-MRI slices acquired downstream of the valve is possible. Impact: Our work indicates that aortic valvular orifice area and inlet velocity profiles can indeed be predicted from a few cine 2D PC-MRI slices acquired downstream of the valve. The approach potentially enables time-efficient standard imaging using a few breathheld scans as available on all clinical MR systems.
Rapid 3D slab-selective MR elastography using interleaved motion encoding
Authors: Tripp Donovan , Darwish Omar , Prieto Claudia , Botnar René , Sinkus Ralph , Neji Radhouene
Published: November 2024

Motivation: Most current volumetric 3D MRE sequences are restricted to 2D slice acquisitions, but we propose a novel sequence for rapid 3D slab-selective MRE. Goal(s): To demonstrate the feasilbility of a 3D slab-selective MRE sequence with an interleaved motion encoding scheme. Approach: The proposed 3D MRE sequence allows the measurement of different wave offsets and motion encodings for a 3D slab in a single measurement with a constant repetition time, minimising total acquisition time. Results: We show initial results of the proposed technique in a phantom and for a single breathhold 3D liver MRE in a healthy subject. Impact: The proposed method can be applied for effiicient 3D high-resolution MRE. Applications include liver fibrosis and inflammation staging, but the sequence may also be used for brain MRE.
Regional Correlation of Stiffness and Perfusion in the Human Brain at 7T MRI through MR Elastography and Arterial Spin Labeling Techniques
Authors: Neher Caitlin , Triolo Em , Kurt Mehmet
Published: November 2024

Motivation: We are motivated to understand the impact of blood flow on the mechanical properties of brain tissue for applications in neurodegenerative pathophysiology. Goal(s): Our goal was to establish a novel postprocessing framework for correlation of structural and functional properties characterized by MR elastography (MRE) and pulsed arterial spin labeling (PASL). Approach: We obtained MRE and PASL in 8 healthy controls, segmented the brain, and conducted regional correlation analyses of elastograms and perfusion maps. Results: After successful data processing and validation, we found significant inverse correlations in the cortical gray matter, some cortex regions, as well as a similar nonsignificant trend in other regions. Impact: These study results, which show a perfusion–stiffness relationship in some brain regions, point to an underlying biological mechanism relating vasculature and viscoelastic properties; however, this research direction needs further investigation, more subjects, and improved ASL techniques to strengthen regional analysis.
Assessment of renal function with arterial spin labeling and intravoxel incoherent motion in type 2 diabetic patients
Authors: Wang Qian , Guo Jinxia , Xia Pu , Xu Cheng
Published: November 2024

Motivation: Kidney injury could be occurred in the early stages of DM. Goal(s): We aimed to evaluate the diagnostic values of ASL and IVIM for distinguishing early kidney dysfunction in T2DM. Approach: All subjects were performed ASL and IVIM scans. Results: The results demonstrated that cortical RBF, f values and medullary D, f values were lower in the DM group with normal level of albumin-to-creatinine rate (ACR) than in control group, and f is the optimal index for differentiating the DM from DKD and control, indicating that ASL and IVIM could be used to evaluate kidney impairment of T2DM. Impact: When early kidney injury in T2DM could be evaluated with ASL and IVIM,early clinical intervention can be implemented, significantly delaying or preventing the progression of DKD and greatly improving the prognosis for patients with DKD.
Utilizing the human connectome project to quantify gray matter microstructural decline and cognitive correlates in healthy aging using MAP-MRI
Authors: Singh Kavita , Barsoum Stephanie , Schilling Kurt , An Yang , Benjamini Dan
Published: November 2024

Motivation: The mean apparent propagator (MAP)-MRI model, free from biophysical assumptions, shows high sensitivity to gray matter (GM) microstructural changes. Yet, its capacity to predict age-related cognitive and behavioral changes is uncharted. Goal(s): To profile MAP-MRI based microstructural/volumetric changes in normal aging and its cognitive correlates. Approach: Utilizing the HCP-Aging diffusion and cognitive datasets from 707 unimpaired participants, we investigated age associations in 56 GM regions and their cognitive correlates. Results: MAP-MRI identified unique age-related patterns in GM regions, linked to memory and executive function decline, limbic network stability; suggesting potential for MAP-MRI in predicting age-related cognitive, behavioral, and microstructural changes. Impact: MAP-MRI identified unique age-related patterns in GM regions, linked to memory and executive function decline, limbic network stability; suggesting potential for MAP-MRI in predicting age-related cognitive, behavioral, and microstructural changes.
Aberrant Functional Connectivity Patterns in the Anterior Cingulate Cortex Subregions of Irritable Bowel Syndrome with Depressive Symptoms
Authors: Tang Ruoyu , Jin Yihan , Xu Kuanghui , Chen Xiaofei , Zhang Yong , Li Jie
Published: November 2024

Motivation: Atrophy and hyperactivity of the anterior cingulate gyrus (ACC) are key drivers of irritable bowel syndrome (IBS) and its psychiatric comorbidity. Goal(s): Resting-state fMRI was performed to observe the functional connectivity (FC) patterns of ACC subregions in IBS with depressive symptoms patients to explore the potential neural mechanism of IBS and its comorbidity depression. Approach: Seed-based whole-brain FC analysis was performed and distinct subregions of ACC showed different whole-brain connectivity patterns in IBS patients. Results: The aberrant FC within the emotional arousal network, salience network and executive network may be characteristic neurobiological markers of IBS with comorbidity depression. Impact: The aberrant FC within the emotional arousal network may be a characteristic neurobiological marker of IBS with comorbidity depression. In addition, the abnormal FC between the salience network and the executive network may be the underlying neural mechanism of IBS.
Cross Mood and Anxiety Disorders Connectome Landscape of Dysconnectivity
Authors: Jacob Yael , Morris Laurel , Balchandani Priti , Murrough James
Published: November 2024

Motivation: Mood and anxiety disorders have high comorbidity and overlapping symptoms which makes diagnosis and treatment challenging. Identification of shared network mechanisms that underlie these disorders is needed. However, most networks are studied in only one disorder at a time. Goal(s): We aim to explore how brain network features reveal differences as well as commonalities across mood and anxiety disorders.Approach: Here we conducted a trans-diagnostic approach motivated by a recent theory of cross-disorder ‘connectome landscape’ which delineates optimal and suboptimal network organization. Results: We empirically tested this novel concept for the first time, observing connectome landscape perturbations in anxiety and PTSD patients. Impact: Identification of distinct or shared network mechanisms that underlie mood and anxiety disorders is greatly needed. Empirically testing the connectome landscape theory, we uncover unique network organization related to depression or anxiety, indicating that anxiety manifests as more global dysconnectivity.
Computational Fluid Dynamics Of Bladder Voiding Using 3D Dynamic MRI
Authors: Shahid Labib , Gonzalez-Pereira Juan Pablo , Johnson Cody , Bushman Wade , Roldan-Alzate Alejandro
Published: November 2024

Motivation: Catheter-based urodynamic studies to assess bladder dysfunction are invasive and provide inadequate biomechanical information. MRI-based computational fluid dynamics (CFD) has demonstrated potential to uncover these features not evident from catheterization. Goal(s): Develop and implement a computational methodology to non-invasively assess urodynamics. Approach: Acquire 3D dynamic MRI of bladder voiding. Use the images to execute subject-specific CFD simulations of the bladder and urethra. Calculate existing urological nomograms and energy expended to quantify bladder function using the MRI and CFD results. Results: The healthy subject showed unobstructed bladder outlet and normal contractility. We calculated the energy expended to void bladder for the first time. Impact: A method using MRI-based computational fluid dynamics was developed to simulate bladder voiding. Results show successful quantification of urine flow dynamics. This method shows potential to overcome limitations of current invasive catheter-based urodynamic studies.
Creating Digital Twins of Solid Tumors: Insights from Dynamic Contrast-Enhanced MRI
Authors: Salavati Hooman , Ceelen Wim , Debbaut Charlotte , Pullens Pim
Published: November 2024

Motivation: Prediction of cancer therapy outcomes is a paramount objective in oncology, closely tied to the integration of novel biomarkers into clinical practice. Goal(s): The goal of creating digital twins of solid tumors is to equip oncologists with a comprehensive replica of the tumor, allowing them to make well-informed decisions. Approach: In the development of digital twins for solid tumors, we introduce a multidisciplinary approach that essentially combines quantitative MRI and computational modeling. Results: The image-based model yields a comprehensive representation of tumor perfusion, providing a map of elevated interstitial fluid pressure, which holds significant potential as a biomarker in oncology. Impact: Cancer therapy's success is not guaranteed, with potential serious side effects. Our aim is to offer a robust digital tumor replica for evaluating numerous treatment options, identifying the optimal plan while minimizing adverse effects.
Hepatic 5D flow: An Effective Acquisition and Reconstruction Scheme for Portal Vein
Authors: Cao Ruiyu , Li Shaohang , Li Hongwei , Chu Ying-Hua , Sun Aiqi , Jin Ning , Yan Xu , Wu Yunzhu , Splitthoff Daniel , Li Hao , Wang He
Published: November 2024

Motivation: 4D flow imaging in the liver suffers from long acquisition time and inefficient motion control. Goal(s): Address the challenges of prolonged acquisition time and significant motion artifacts in hepatic 4D flow imaging. Approach: We collected data from all respiratory states without a diaphragm navigator, and retrospectively reconstructed respiratory-resolved 5D flow using simultaneously recorded breathing signal. Results: This scheme reduced the acquisition time from over 10 minutes to 6-8 minutes, while maintaining consistent image quality with few motion artifacts. High quantitative correlation in hepatic hemodynamic results was found between the results from prospectively navigated data and retrospectively binned data. Impact: The proposed hepatic 5D flow scheme achieved high image quality and quantitative metrics, compared with those of diaphragm navigated results. This scheme can effectively shorten the acquisition time to 6-8 minutes and mitigate motion artifacts.
Grey and white matter plasticity during motor-skill learning: a longitudinal diffusion MRI study
Authors: Emmenegger Tim , Schading-Sassenhausen Simon , David Gergely , Killeen Tim , Freund Patrick
Published: November 2024

Motivation: MRI studies have demonstrated plastic changes in grey and white matter (GM/WM) during motor skill learning. However, diffusion magnetic resonance imaging (dMRI) might provide additional complementary information in contrast to multi-parametric mapping (MPM), which has been investigated previously. Goal(s): To investigate training-induced neuroplasticity using dMRI and contextualize them to the MPM findings. Approach: Acquisition of longitudinal dMRI and MPM during motor skill learning. Results: We observed overlapping changes in dMRI and MPM metrics following motor skill learning. dMRI was thereby able to capture additional changes within the WM, whereas within the GM, some findings were unique to the MPM protocol. Impact: dMRI and MPM metrics are sensitive to motor skill learning-induced changes in GM and WM. To combine the two methodologies advances our capability in detecting neuroplasticity changes and might be beneficial for patient rehabilitation.
Fluid mechanics based quantitative transport mapping network for predicting gene expression of nasopharyngeal carcinoma (NPC) patients
Authors: Zhang Qihao , Romano Dominick , Weppner Ben , Nguyen Thanh , Spincemaille Pascal , Wang Yi
Published: November 2024

Motivation: To use fluid-mechanics based deep learning method to predict perfusion parameters from dynamic imagesGoal(s): We propose to explore the possibility to use neural network trained on simulated data from fluid mechanics simulation to analyze dynamic medical images. Approach: We use quantitative transport mapping network (QTMnet), which is trained on simulated concentration propagation profile generated from constrained constructive optimization (CCO) and transport equation-based tracer propagation simulation, to predict perfusion parameters including flow rate, permeability, vasculature volume, from DCE MRI images. Results: QTMnet predict perfusion parameters accurately in simulation study and can distinguish different gene expression group patients comparing with using traditional kinetics model. Impact: Proposed QTMnet method can be used to predict different perfusion parameters related to dynamic images accurately and automatically without usage of arterial input function.
Ultrafast breast MRI in differentiating high-grade from benign and low-grade malignant breast lesions
Authors: Li Yang , Liu Haifa , Wang Qi , Xu Qian , Wang Mengzhu , Grimm Robert , Qi Mingwei
Published: November 2024

Motivation: Ultrafast (UF)-DCE MRI is a novel approach to obtain kinetic information very early after enhancement, which promises improved capabilities in differentiating malignant from benign lesions of breast cancers. Goal(s): The early hemodynamic characteristics of lesions using breast UF-DCE MRI were systematically investigated to evaluate the value of the relevant kinetic parameters in the diagnosis of different grades of breast cancer. Approach: The kinetic parameters of UF-DCE MRI were calculated to differentiate the different grades of breast cancer. Results: The kinetic parameters of UF-DCE MRI can be used to distinguish high-grade from benign and low-grade breast cancer. Impact: Breast ultrafast DCE MRI was used to explore the early hemodynamic characteristics of the lesions and evaluate the value of the relevant dynamic parameters in the diagnosis of different grades of breast cancer.
Caffeine reduces cerebrovascular reactivity in addition to lowering basal perfusion
Authors: Sankaralayam Dinil Sasi , Hu Zhiyi , Xu Cuimei , Jiang Dengrong , Liu Peiying , Moghekar Abhay , Lu Hanzhang
Published: November 2024

Motivation: Caffeine, one of the widely used psychoactive substances is known to reduce basal cerebral blood flow (CBF). However, its effect on vasodilatory capacity has not been characterizedGoal(s): To evaluate the impact of Caffein on cerebrovascular reactivity (CVR)Approach: 8 healthy caffeine-naïve volunteers were scanned for baseline (pre-caffeine) and post-Caffeine CVR measurements using BOLD MRI and phase-contrast MRI (PC)-MRI during normal air breathing and hypercapnia using 5% CO2 enriched gas mixtureResults: There was a significant reduction in blood-flux (BF) during room-air (p=0.002) and hypercapnia (p=0.0015) post caffeine administration (variation=33.7% and 41.3% respectively). PC-CVR and BOLD-CVR were reduced by 32.7%(p=0.006) and 22.5%(p=0.006) respectivelyImpact: This study's findings provide valuable insights into the impact of caffeine on cerebrovascular reactivity (CVR), revealing a significant reduction after caffeine intake. Findings would be beneficial in reducing the inter-subject variability of CVR by improving the sensitivity in detecting abnormalities.
Quantifying Spatial Variations of Cardiac-Induced Volumetric Strain Using DENSE MRI: Insight from an Observational Study
Authors: van Hulst Ellen , Báez-Yañez Mario , Adams Ayodeji , Biessels Geert Jan , Zwanenburg Jacobus
Published: November 2024

Motivation: The heartbeat causes deformations and volumetric strain in the surrounding brain tissue which can be observed using Displacement Encoding with Stimulated Echoes (DENSE) MRI. Local variations in volumetric strain reveal both expansion and compression in individual voxels or regions. Goal(s): To offer insights into the heterogeneous patterns seen in volumetric strain maps. Approach: Volumetric strain data of nine subjects was included and clustered (k-means) into four clusters. Results: Both expanding and compressing clusters were found in all subjects. Compressing clusters were mostly found at the periphery of the brain and possibly reflect structures facilitating fluid movement (sulci and veins). Impact: Clustering volumetric strain data into individual clusters with similar voxels reveals distinct volumetric strain profiles in DENSE data. Potentially, these clusters can be used to cleanup DENSE data from fluid-related artifacts to make the data specifically reflect brain tissue strains.
Design of a novel double-tuned RF coil system for 1H/13C MR imaging at 7T
Authors: Du Feng , Li Nan , Zhou Jie , Wang Zhe , Zhang Xiaoliang , Zheng Hairong , Li Ye
Published: November 2024

Motivation: Hyperpolarized 13C MR imaging is of particular interest in cancer applications such as tumor staging and monitoring treatment response as it provides unique real-time metabolic information. Goal(s): This work is to develop a novel double-tuned RF coil that can achieve uniform excitation and highly sensitive acquisition for 1H/13C MR imaging at 7T. Approach: The numerical electromagnetic simulation was utilized to evaluate the feasibility and performance in s-parameters and B1+ field distributions. The bench tests were conducted to further validate the performance. Results: These simulated and measured results indicated that the development of an efficient 1H/13C RF coil for MR imaging at 7T. Impact: A novel double-tuned RF coil system that can achieve uniform excitation and highly sensitive acquisition for 1H/13C MR imaging at 7T was developed. This coil system has the potential to be used for hyperpolarized 13C MRI at ultra-high field.
Measurement of awake rats CSF pulsation using EPI-based resting-state fMRI data
Authors: Shin Dongho , Kim Jun-Hee , Park Sung-Hong
Published: November 2024

Motivation: This research aims to explore the relationship between CSF dynamics and BOLD signals using EPI-based resting-state fMRI data from an open database of rat models. Goal(s): Rodents and humans are compared regarding CSF dynamics and the BOLD signal. Approach: The study computes temporal correlations between CSF pulse, CSF edge, and the BOLD signal. Results: While in resting state, both CSFpulse and CSFedge indices were correlated with global BOLD, exhibiting a stronger correlation for CSFedge and varying peak correlations at -1s, -10s, and +11s. The temporal correlation between CSF dynamics and global BOLD indicates differences in CSF physiology in humans compared to smaller animals. Impact: The study results imply differing correlation coefficients between CSF dynamics and the BOLD signal, suggesting promising pathways for deeper investigations into brain CSF dynamics in small animal models and neuroscientific advancements using EPI-based fMRI database.
DTI/DKI Biomarkers of Chronic mild Traumatic Brain Injury
Authors: Lee Donghoon , Meabon James
Published: November 2024

Motivation: Imaging biomarkers accurately diagnosing and monitoring treatment response for chronic mild Traumatic Brain Injury (mTBI) are needed. Goal(s): This study aimed to experimentally validate and determine the performance of MRI biomarkers for monitoring chronic repetitive mild traumatic brain injury (mTBI). Approach: We used diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) to assess white matter injury in mouse brains with chronic mTBI and compared results with those for age-matched control brains. Results: Reduction in fractional anisotropy and increase of axial kurtosis were observed in the medulla of mTBI brains compared to the parameters in the same region of control brains. Impact: It is new to monitor DTI and DKI parameters as noninvasive biomarkers in the brain with chronic mTBI.
MR Elastography as a Potential Imaging Biomarker and Non-Invasive Method for Diagnosing Spontaneous Intracranial Hypotension
Authors: Mark Ian , Karki Pragalv , Cutsforth-Gregory Jeremy , Brinjikji Waleed , Madhavan Ajay , Messina Steven , Cogswell Petrice , Chen John , Ehman Richard , Huston John , Murphy Matthew
Published: November 2024

Motivation: Spontaneous intracranial hypotension (SIH) is a debilitating disease with a normal brain MRI in 20% of cases. Goal(s): Our goal was to use MR elastography (MRE) to identify unique viscoelastic patterns in SIH patients. Approach: We performed brain MRE in 15 SIH patients and compared their mechanical properties to 65 healthy controls. Results: SIH patients exhibited significant differences in both stiffness and damping ratio compared to healthy controls. Impact: We demonstrate MRE as a potential imaging biomarker and a non-invasive method for diagnosing SIH, including patients with a normal brain MRI.
B1 SHIM CALIBRATION USING 1D ENCODED B1 DATA
Authors: Wheaton Andrew , Dannels Wayne
Published: November 2024

Motivation: To develop a method for fast per-patient calibration of B1 shim parameters. Goal(s): To reduce scan time for per-patient B1 shimming calibration to improve patient throughput. Approach: A key insight is that 1D projections acquired with specific projection orientations are sufficient to capture B1 distribution patterns. By comparing a pair of orthogonal B1 projections in the brain or by measuring average B1 amplitude of a pair of ROIs in a single projection across the breast, left-right B1 symmetry can be measured. Results: Optimal B1 shim settings can be determined with a total time < 1 second as confirmed by B1 maps. Impact: The proposed method for per-patient B1 shimming calibration using 1D B1 projections instead of 2D B1 maps can quickly calibrate B1 shimming parameters in less than one second.
7T MRI Coils: Streamline Approach in Analysis of Coil Coupling
Authors: Vliem Jules , Zivkovic Irena
Published: November 2024

Motivation: To gain a better understanding of electromagnetic (EM) interactions in RF coil designs by visualizing their EM flow. Goal(s): Identifying the dominant coupling mechanism in different coil types through visualization of electric and magnetic fields and power flow. Approach: Simulating conventional, shielded-coaxial-cable (SCC), twisted pair coils, and square loops (self-decoupled coils) to visualize their EM fields using streamlines. Results: Diverse coupling behaviors are observed among the coil types, each demonstrating unique dominant mechanisms. A high resemblance in the EM flow between the self-decoupled coil and the SCC and twisted pair coils was found. Impact: Identifying the dominant coupling mechanism in different coil designs with streamlines can help in adjusting the coil design for maximum interelement decoupling when placed in an array configuration.
Optimizing RF Coil Design to Minimize RF Interference in MR-Guided Microwave Liver Ablations at 1.5T
Authors: Hernandez Daniel , In Myung-Ho , Kim Kyoung-Nam
Published: November 2024

Motivation: Clinical MRI-guided microwave ablations often suffer from noise due to electromagnetic interference (EMI) between ablation probes and imaging coils. Instead of modifying the clinical microwave ablation system that could compromise FDA-approval, we explore alternative coil designs to mitigate the noise. Goal(s): Minimize EMI between the microwave ablation probes and imaging coils during clinical MR-guided microwave ablations. Approach: We applied a band-pass filter, studying the impact of coil size, and investigating efficient coil combinations to reduce interference. Results: A band-pass filter led to a 89% improvement in field uniformity. Also employing smaller coils can mitigate the ripple effects induced by the ablation probe. Impact: Our study addresses the critical need to reduce electromagnetic interference (EMI) between microwave ablation probes and imaging coils during clinical MR-guided microwave ablations at 1.5T. Motivated by the interference challenges in current clinical setups, we develop methods to mitigate EMI.
A Comparison of FLASH-based Volumetric B1+ Mapping Methods in Phantom at 7 Tesla
Authors: Kent James , Liebig Patrick , de Buck Matthijs , Valkovič Ladislav , Dragonu Iulius , Hess Aaron
Published: November 2024

Motivation: Fast and accurate B1+ mapping is critical for parallel transmission in ultra-high field MRI, but several options exist, and which is the most optimal is unknown. Goal(s): To evaluate three FLASH-based volumetric B1+ mapping methods; 2D SatTFL, 3D SA2RAGE and 3D Sandwich. Approach: We acquired fully sampled absolute B1+ maps at 7T in a realistic human head phantom across multiple transmission voltages to establish a ground truth and assess the dynamic range of each method. Results: SA2RAGE and Sandwich both enable low-power non-selective RF pulses and maintain accuracy for low B1+ regions. Sandwich has a 60% shorter acquisition time than SA2RAGE. Impact: This study will help to inform a choice of B1+ mapping sequences when imaging at ultrahigh field.
A Novel 30-Channel Ultra-flexible Phased-Array for High-Resolution and Parallel Imaging Optimized MR Hand/Wrist/Brachial Plexus Imaging at 3T
Authors: STICKLE YUN JEONG , Follante Clyve , Aspy Canyon , Blankenship Seth , Yang Tae-Young , Thomas Tony , Fung Maggie , Wen Yan , Robb Fraser , Tan Ek Tsoon , Sneag Darryl
Published: November 2024

Motivation: Conventional hand/wrist coils have larger loop sizes and limited number of elements, resulting in in-sufficient SNR and acceleration capability for imaging small anatomic structures. Goal(s): To develop a small flexible coil for hand/wrist, which improves spatial resolution, SNR and acceleration with flexibility for brachial plexus imaging as well when combined with other coils. Approach: A 30-Channel parallel imaging optimized coil was built with the small flexible dual loop, high impedance internal cable baluns, exceptionally low noise preamplifiers and highly flexible mechanical materials. Results: This study shows higher SNR and improved acceleration capabilities for results for this novel ultra-flexible coil compared to conventional coils. Impact: This novel coil design provides comfortable fitting, high-resolution and higher acceleration for in-vivo 3T hand/wrist/unilateral brachial plexus imaging.
White matter-engaged multilayer network for evaluation of functional deficits in Alzheimer’s disease
Authors: Xu Lyuan , Zu Zhongliang , Gao Yurui , Li Muwei , Schilling Kurt , Choi Soyoung , Anderson Adam , Gore John , Ding Zhaohua
Published: November 2024

Motivation: The role of white matter (WM) in the functional connectivity within brain networks has not been well studied. Goal(s): Our goal was to use a high-order graph model to comprehensively analyze brain functional networks that engage WM. Approach: We constructed multilayer networks and analyzed network parameters in the brains of subjects with Alzheimer’s disease (AD). Results: Multilayer network analysis showed increased sensitivity for detecting significant deterioration in functional connectivity (FC) in AD. Impact: Multilayer networks allow more comprehensive understanding of structure-function relations within the whole brain and may provide deeper insight into the pathophysiology of degenerative brain disease.
Detection and Correction of Spurious Motion Within Overlapped Multi-Slice Prostate T2-Weighted Acquisitions
Authors: Borisch Eric , Kazemi Armita , Grimm Roger , Rossman Phillip , Riederer Stephen
Published: November 2024

Motivation: Motion frequently impairs T2 weighted prostate imaging; in the multi-pass acquisitions that are common this results in an objectionable stair-step artifact, and can lead to additional scans and increased exam time. Goal(s): Reduce the impact of motion occurring in a subset of the multi-pass acquisition. Approach: Automatic detection of motion (through a mutual-information metric) coupled with replacement of corrupted slices via averaging of neighbors. In the described case, adjacent slices are intentionally overlapped, leading to reasonable results from this approach. Results: Improvements are clearly visible in both motion-controlled phantom and a subset of volunteer examinations. Impact: The ability to automatically repair a portion of motion-corrupted exams may enable reduction of supplemental / repeat scans, improving overall exam times. The described technique is not computationally complex, and could be performed inline after scan completion.
Predictive value of Intravoxel incoherent motion diffusion-weighted MR imaging in different expression states of HER2 in breast cancer
Authors: Zhao Siqi , Zhang Lina , Li Yuanfei , Wu Yueqi , Ning Ning , Liang Hongbing , Xie Lizhi , Guan Haonan , Song Qingwei , Liu Ailian
Published: November 2024

Motivation: This study aimed to predict HER2 expression states in breast cancer patients using IVIM imaging, offering valuable guidance for anti-HER2 treatment. Goal(s): To categorize patients into HER2-positive, HER2-low, and HER2-zero groups, analyze IVIM parameters, and assess their relationship with clinicopathological features. Approach: 67 breast cancer patients were retrospectively analyzed, with IVIM imaging and data collection. Statistical tests were employed to compare the groups. Results: While no significant differences emerged in clinicopathological features, ADCfast values differed significantly. Both HER2-positive and HER2-low subgroups exhibited higher ADCfast values than HER2-zero cases. ADC, ADCslow, and f showed no significant variations. Impact: This study demonstrates that ADCfast can predict HER2 expression noninvasively, assisting in personalized treatment planning and prognosis assessment for breast cancer patients pre-surgery, providing valuable insights for clinical decision-making.
Objective Depression Diagnosis derived from Effective Connectivity through Dynamic Causal Modelling
Authors: Schielen Sjir , Stepanov Dmitrii , Cîrstian Ramona , Aldenkamp Albert , Zinger Svitlana
Published: November 2024

Motivation: The diagnosis of major depressive disorder (MDD) currently involves subjectivity, but an objective test based on a measurement is desired. Goal(s): To obtain effective connections between brain networks from functional MRI that both allow MDD to be diagnosed and offer clinically relevant insight. Approach: Stochastic Dynamic Causal Modelling is applied to the time series of resting-state networks. The most discriminative connections are found through Bayesian Model Reduction and Chi-Square feature selection. These connections are used for classification using machine learning. Results: Eight clinically relevant effective connections result in 94% leave-one-out cross-validation accuracy, which resulted in 100% accuracy on a separate test set. Impact: The discriminative ability of the eight resulting effective connections aid understanding of MDD's pathophysiology. Furthermore, the results may inspire researchers to investigate the eight most discriminative connections on other datasets, which can lead to an objective diagnostic biomarker for MDD.
Feasibility of echo asymmetry and least squares estimation (IDEAL-IQ) in differentiation of atypical spinal hemangiomas from metastases
Authors: Wang Qizheng , Xu Ke , Ji Xiaoxi , Lang Ning
Published: November 2024

Motivation: It is common for patients with primary tumors to find abnormal signals in the spine, which may be initially reported as “metastases cannot be rule out”. For these cases, differential diagnosis has a significant impact on patient staging and management, which may result in misdiagnosis or additional imaging, ultimately biopsy, and unnecessary costs. Goal(s): To investigate chemical shift-encoded sequence (IDEAL-IQ) for differential diagnosis of spinal tumors. Approach: Single-center prospective study. Results: This work highlights the benefits of adding proton density fat fraction (PDFF) maps yield from IDEAL-IQ to improve diagnostic accuracy of spinal metastases and hemangiomas without contrast agents. Impact: IDEAL-IQ provides reliable quantification of spinal tumor bone marrow infiltration pattern in clinical settings, which is comparable to the quantitative parameters of DCE-MRI. It may be a valuable tool for providing information for early differential diagnosis in a non-invasive way.
Efficient and Complete Fat Suppression in 2-point Dixon MRI for Improved Qualitative and Quantitative Assessment of Lumbar Plexus
Authors: Lin Sheng Qing , Udayakumar Durga , Chhabra Avneesh , Madhuranthakam Ananth
Published: November 2024

Motivation: The use of 2-point Dixon is prevalent for fat/water separation in MRI, but suffers from incomplete fat suppression, leading to residual fat signal in the water image. We have previously developed a “Darkfat” post-processing technique that can reduce this residual signal. Goal(s): This retrospective study aims to evaluate Darkfat processing in clinical lumbar plexus images. Approach: Retrospective 2-point T2-weighted lumbar images from 30 patients were processed using Darkfat and evaluated through qualitative and quantitative assessment. Results: Water-only images from Darkfat processing had significantly better fat suppression (P<0.0001), and subjectively better image quality (P<0.005) compared to original water images from 2-point T2-weighted Dixon acquisition. Impact: Darkfat image processing significantly improves fat suppression in clinical 2-point T2-weighted lumbar images enabling enhanced anatomical visualization. This could potentially improve pathological visualization.
Evaluation of the change in magnetic susceptibility values of knee joint cartilage in patients with osteoarthritis using UTE-QSM
Authors: Li Jing , Xiang Shaoxin , Wang Xianqi , Tian Xiaohong , Ji Bing , Hu Shanshan , Zhang Ming , Yang Yu Xin , Wei Hongjiang , Chen Wei
Published: November 2024

Motivation: Quantitative susceptibility mapping (QSM) may be a useful tool for studying the characteristics of collagen fibers in knee cartilage.The susceptibility quantification using GRE with fat saturation and relatively long TE may be further improved using UTE-QSM. Goal(s): To measure the change in susceptibility values of knee cartilage in patients with different grades of OA using UTE-QSM. Approach: A total of 13 knees from 10 patients who underwent both X-ray and MRI-UTE were enrolled. Results: Our results show that in the posterior regions of the medial femoral condyle and lateral femoral condyle, the magnetic susceptibility value significantly decreases with the increase of OA grade. Impact: UTE-QSM can promote osteoarthrologists and radiologists to better understand knee OA from different dimensions, and can provide more imaging evidence for monitoring the progress of OA, formulating treatment plans, and evaluating treatment effects.
A systematic automated post-processing approach for quantitative analysis of 3D T1ρ knee MRI
Authors: Zhong Junru , Yao Yongcheng , Xiao Fan , Ong Michael Tim-Yun , Ho Kevin Ki-Wai , Chan Queenie , Griffith James , Chen Weitian
Published: November 2024

Motivation: To address the global healthcare challenge of knee osteoarthritis. Goal(s): Develop and validate an automated post-processing method for quantitative 3D T1ρ knee imaging analysis. The proposed post-processing pipeline accelerates the process while preserving a user-friendly and clinical-related output. Approach: We proposed a post-processing pipeline that combines parcellation, ROIs selection, T1rho fitting, and regionally averaged outputs. We evaluated our approach on 30 OA patients and 10 healthy controls. Results: The proposed post-processing approach achieved satisfactory performance on automatic ROI selection compared to the manually labelled ROIs and provided quantitative T1ρ analysis with clinical promise. Impact: Our proposed pipeline enables automated post-processing for T1ρ imaging with deep learning, pushing this promising technique to the clinics to provide sensitive and quantitative knee OA diagnostics.
MRI metrics can help explain the loss of functional strength in aging
Authors: Hall Mary , Vainberg Yael , Asay Jessica , Hicks Jennifer , Muccini Julie , Gold Garry , Mazzoli Valentina
Published: November 2024

Motivation: There is a need to investigate the relationship between age-related muscle atrophy and functional strength. Goal(s): To explore the relationship between volumes of individual knee extensor muscles relative to total volume of the quadriceps as measured by MRI and sit to stand performance. Approach: Participants performed a sit to stand test while being recorded by a markerless motion capture system and underwent an MRI exam that included a Dixon scan, which was used to calculate muscle volumes in the quadriceps. Results: There were correlations between age and vastus intermedius and vastus lateralis volume. Rectus femoris volume was correlated with sit to stand performance. Impact: We utilized a novel experimental design using smartphone-based markerless motion capture and MRI metrics to study the relationship between functional strength and age-related muscle atrophy. This work could inform design of physical therapy programs for the elderly.
Muscle Kinetics on Diffusion-weighted Imaging during Plantar Flexion for Assessing Sex Differences in Age-related Muscle Quality
Authors: Zhang Xinyue , Xiang Pei , Deng Kan , Zhang Zhaohui
Published: November 2024

Motivation: The exercise-tailored diffusion-weighted imaging (DWI) protocol has never been implemented to assess sex differences in age-related muscle quality in the healthy population. Goal(s): To investigate the feasibility of muscle kinetics on DWI during exercise for assessing sex differences in age-related muscle quality. Approach: This study recruited 87 healthy participants with 174 legs imaged and assessed muscle kinetics on DWI during exercise for assessing sex differences in age-related muscle quality. Results: Males and females showed different age-related pattern with muscle kinetics on DWI during plantar flexion. Impact: An exercise-tailored MR protocol can be implemented for assessing the muscle quality.
Quantitative MRI assessment of knee joint cartilage in pediatric hemophilic arthropathy using automated cartilage segmentation technique
Authors: Kuang Yangying , Lai Hua , Raithel Esther , Wu Yunzhu
Published: November 2024

Motivation: To offer a quantitative imaging marker for monitoring of hemophilic joints. Goal(s): To assess knee joint cartilage changes in children with hemophilic arthropathy(HA) using automated segmentation and explore their connection with Hemophilia Joint Health Scores(HJHS). Approach: MRI were conducted on children with HA and healthy children using advanced techniques and automated cartilage segmentation to evaluate knee joint cartilage and their associations with HJHS. Results: Significant differences in T1 and T2* values were found between HA and healthy controls, with positive correlations between T1 values in specific regions and HJHS, along with negative correlations between cartilage volume in specific regions and HJHS. Impact: MRI techniques such as T1 mapping and T2* mapping hold promise for quantitatively assessing early-stage knee joint cartilage damage in HA, and show identifiable correlations with HJHS.
Ultrashort Echo Time and Fast Field Echo Imaging and Processing for Spine Bone Imaging in Spondylolysis
Authors: Vucevic Diana , Yamashita Yuichi , Malis Vadim , Mesa Anya , Achar Suraj , Miyazaki Mitsue , Bae Won
Published: November 2024

Motivation: Fracture of pars interarticularis is a common injury in adolescent athletes, currently requiring CT scan for accurate diagnosis. Goal(s): Advance MR imaging to depict spinal bone with high fidelity. Approach: Two techniques utilizing multiecho ultrashort echo time (UTE) and field echo (FE) with simple post-processing were developed to image lumbar spinal bone. SNR and CNR were determined, and clinical utility was assessed in patients. Results: Improvements in visual quality and bone contrast were achieved using multiecho processing as opposed to a single echo inversion. Both UTE and FE techniques provided good bone contrast, although FE provide significantly better resolution and bone-muscle contrast. Impact: This study advances MR imaging of the pars interarticularis for evaluation of spondylolysis. We demonstrated clinical feasibility in a patient with a pars defect, depicted with clarity with the techniques described here.
The Quantitative Parameters Derived from IDEAL-IQ in the Lumbar Vertebrae of Healthy Children: A Pilot Study of Bone Development
Authors: Yang Jie , Sun Hui-miao , Yang Hong , Hu Lei , Niu Jin-liang
Published: November 2024

Motivation: Early childhood bone development affects that of bone disease in adolescence and adulthood. Many diseases can affect the cancellous bone or bone marrow. Therefore, it is of great significance to quantify the bone development of healthy children. Goal(s): To quantify the normal bone development and provide a basis for further studies focusing on diseases involving lumbar vertebrae. Approach: This study was conducted to quantify the fat and cancellous bone content of lumbar vertebrae in healthy children based on IDEAL-IQ. Results: As the age increased, the average PDFF and R2* both increased significantly. No association was found between the gender and PDFF, R2*. Impact: As the age increased, the average PDFF and R2* of lumbar vertebrae both increased significantly in healthy children. These findings will probably improve our understanding of the bone development and enable differential diagnosis other diseases of children’s bone.
Impact of rTMS on the glymphatic system in patients with first-episode depression before and after treatment
Authors: Laiyang Ma , Wenjing Huang , Wanjun Hu , Jing Zhang , Xiong Yuhui
Published: November 2024

Motivation: The neuropathological mechanisms of repetitive transcranial magnetic stimulation (rTMS) for the treatment of depression are unclear. Goal(s): The aim of this study was to explore the effects of rTMS on the brain glymphatic system using Diffusion MR Technique in patients with first-episode depression before and after treatment. Approach: Diffusion tensor image analysis along the perivascular space (DTI-ALPS) as a non-invasive method for evaluating the activity of the glymphatic system in human brain by using diffusion images. Results: The left ALPS index of patients with first-episode depression is lower than that of healthy people, and it is increased after rTMS treatment. Impact: This study demonstrated the DTI-ALPS method to assess lymphatic system activity in first-episode depression patients before and after rTMS treatment. The abnormality of ALPS index may provide a potential biomarker for explaining depression, and rTMS can cause changes in ALPS.
Synthetic high-b-value MUSE DWI in preoperative differentiation of high-grade glioma from low-grade glioma
Authors: Chen ZiYang , Liu Weiyin , Du EnFu , Chen Wen , Tong Ru
Published: November 2024

Motivation: High-b-value diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) with b value = 3000 s/mm2 are independent predictors of overall survival. Goal(s): To explore the feasibility of synthetic high-b-value DWI and ADC values in diagnosis of glioma using actually scanned ones as standard reference. Approach: To assess scanned and synthetic multiple high-b-value MUSE DWI and ADC of 5 patients with low-grade glioma and 3 patients with high-grade glioma. Results: All synthetic high-b-value DWIs had superior image quality and diagnostic efficacy of glioma to all scanned DWIs. The scanned and synthetic ADC were significantly different between different b values. Impact: Synthetic high-b-value MUSE DWI can provide better image quality and diagnostic efficiency of grading glioma without consuming extra scan time, encouraging us to promote the utility of setting up synthetic high-b-value MUSE DWI as routine.
In Vivo Imaging of Tumor Metabolic Heterogeneity Using [1-13C]Pyruvate-d3 Hyperpolarized By Reversible Exchange With Parahydrogen
Authors: Petersen Stefan , Groß Philipp , Nagel Luca , Willing Robert , Heß Lisa , Mitschke Julia , Klemm Nicole , Müller Christoph , Knecht Stephan , Weigt Moritz , Bock Michael , von Elverfeldt Dominik , Zaitsev Maxim , Chekmenev Eduard , Hövener Jan-Bernd , Martins André , Schilling Franz , Reinheckel Thomas , Schmidt Andreas
Published: November 2024

Motivation: Hyperpolarized [1-13C]pyruvate MRI is promising for studying cancer metabolism and assessing early therapy response but requires high-throughput and less complex hyperpolarization techniques for wide availability. Goal(s): Demonstrating metabolic imaging in a genetic mouse model of metastasizing breast cancer (MMTV-PyMT) using purified [1-13C]-pyruvate-d3 hyperpolarized via parahydrogen-based Signal Amplification By Reversible Exchange (SABRE). Approach: Our rapid (6 min) and efficient hyperpolarization method yielded highly-polarized (>10%) [1-13C]-pyruvate-d3 in safe aqueous solutions. Results: Administered to two PyMT-mice, 13C chemical shift imaging detected the injected pyruvate and metabolized [1-13C]-lactate. Analysis revealed elevated lactate levels in tumors compared to healthy breast tissue, highlighting tumor compartments with distinct metabolic profiles. Impact: We showcase our rapid, cost-effective SABRE hyperpolarization approach, yielding safe, highly-polarized pyruvate for inaugural cancer metabolic investigations. This innovation expands high-throughput preclinical HP-MRI research, enabling comprehensive exploration of tumor biology, metabolic processes, and therapeutic responses in cancer.
Analysis of 31P chemical-shift signatures of high-energy phosphates in glioma patients measured at 7 Tesla
Authors: Franke Vanessa L. , Seng Bela , Platek Justyna , Weckesser Nina , Schlemmer Heinz-Peter , Paech Daniel , Ladd Mark E. , Bachert Peter , Korzowski Andreas
Published: November 2024

Motivation: The detailed characterization of tumor micro-environment can be supported by 31P MRSI enabling the non-invasive determination of pH and magnesium ion content (Mg). Goal(s): The aim of this study was to investigate whether a discrimination between different glioma micro-environments might be possible based on the differences in 31P chemical-shift signatures. Approach: For this purpose, 31P MRSI datasets from 12 patients with glioma acquired at 7T were analyzed and used to estimate the underlying pH and Mg values. Results: For the analyzed cohort, different trends in 31P chemical-shift signatures, as well as in pH and Mg values were observed for different tumor subtypes. Impact: The analysis of 31P chemical-shift signatures in glioma patients could potentially be used for stratifying tumor subtypes, and might help in the characterization of tumor microenvironments, e.g. by determining potential biomarkers such as pH and the magnesium ion content.