bluuebunny/crossref_metadata_2025 huggingface dataset:
Detecting magnetization exchange between human brain tissue and CSF compartments using selective parenchyma spin labeling and CSF imaging
Authors: Kim Dahan , Huang Yujia , Liu Jiaen
Published: November 2024

Motivation: While challenging in humans, measuring fluid exchange between the brain parenchyma tissue and CSF compartments is essential for understanding the role of CSF-mediated metabolic waste clearance in neurodegeneration. Goal(s): We demonstrate the feasibility of detecting such fluid exchange in human brains, unaffected by CSF-flow and partial-volume artifacts. Approach: Free-water spins inside parenchyma were selectively saturated and labeled by magnetization transfer, and subsequent partial saturations were quantified within CSF compartments. Results: We found 3.6% saturation in subarachnoid space (SAS), significant saturation difference between SAS and lateral ventricles (1.3%), and higher saturations in slow-flowing, narrow compartments (e.g. SAS and longitudinal fissure) than larger ventricle spaces. Impact: We demonstrated feasibility of detecting fluid exchange between brain parenchyma and CSF compartments in human brains through selective parenchyma saturation and CSF saturation quantification. Measuring such exchange is important for understanding the role of CSF-mediated metabolic waste clearance in neurodegeneration.
Sleep and Cardiovascular Risk Variables Predict Perivascular Space Morphological Alterations in the Aging Brain
Authors: Zhang Hedong , Robles Carlos , Kim Andrew , Shao Xingfeng , Kang Kyung Wook , Kim Jiyoung , Oh Yoon Sang , Trang Abigail , Lee Emily , Jo Hyunjin , Moon Yeonsil , Kim Hosung , Chai Yaqiong
Published: November 2024

Motivation: Enlarged perivascular space (PVS) has been brought into attention in aging populations. However, which cardiovascular risk factors contribute to enlarged PVS are not well understood. Goal(s): This study aims to quantify PVS morphology and investigate which cardiovascular risk factors contribute the PVS deformity in aging populations. Approach: We employed random forest to predict PVS morphological changes using 9 cardiovascular risk factors and computed the importance index for all predictive factors. Results: Our findings highlighted the significant role of sleep quality, being the best predictor to PVS count, linearity, and diameter. Cardiovascular risk factors such as triglycerides best predicted PVS tortuosity. Impact: Our study is the first to investigate which cardiovascular risk factors are predictive of atypical PVS morphology. Our discovery provides valuable insights into the mechanism underlying PVS deformity and their subsequent impact on glymphatic system and cerebral vascular diseases.
Thin slice positive source QSM improves deep learning based paramagnetic rim detection in multiple sclerosis lesions
Authors: Luu Ha Manh , Gauthier Susan , Kovanlikaya Ilhami , Wang Yi , Spincemaille Pascal , Sisman Mert , Nguyen Thanh
Published: November 2024

Motivation: Rim lesions are important subset of chronic active MS lesions that show strong correlation to patient disability. Rim identification by experts is time consuming. Goal(s): Develop tool for supporting the expert in Rim identification using 1 mm QSM. Approach: We developed an automated deep learning-based network for PRL detection on thin-slice 1mm QSMp. We evaluated the improvement in performance compared with networks trained using 1mm QSM and 3mm QSMp. Results: Use of high-resolution positive susceptibility source maps improves detection of Rim in MS patients compared to 1mm QSM and 3mm QSMp. The network does not require a precise QSM lesion mask to operate. Impact: Using the Deep learning for detecting rim on 1mm QSMp, enabling reducing workload for human in detecting rim.
A Data-Driven Subspace Reconstruction for Distortion-Free Diffusion-Relaxometry Echo Planar Time-Resolved Imaging
Authors: Dai Erpeng , McNab Jennifer
Published: November 2024

Motivation: The subspace-based reconstruction is an SNR-efficient approach for distortion-free diffusion-relaxometry MRI with highly under-sampled echo-planar time-resolved acquisition (EPTI), in which the needed bases can be estimated from simulations. However, the simulations may not be able to fully capture the signal evolution in complex human tissue. Goal(s): To improve the subspace-based EPTI reconstruction by estimating the bases from acquired calibration data. Approach: The efficacy of the new data-driven subspace reconstruction was evaluated with in vivo EPTI experiments. Results: High-resolution, under-sampled EPTI images are reliably reconstructed using the data-driven subspace reconstruction. Impact: Our study presents a new data-driven approach for estimating the bases for the subspace-based echo-planar time-resolved imaging (EPTI) reconstruction, which may better reflect the underlying microstructure than the numerical simulation and further facilitate studies with diffusion-relaxometry MRI.
Unprecedented SNR Efficiency in Prostate DWI By Combining Ultra-Strong Gradients and Spiral Readouts
Authors: Molendowska Malwina , Müller Lars , Fasano Fabrizio , Jones Derek , Tax Chantal , Engel Maria
Published: November 2024

Motivation: Prostate DWI with high b-values holds promise for microstructural tissue characterization but is notoriously SNR-deprived. Goal(s): (i) To boost the SNR of prostate DWI; (ii) to reduce artefacts resulting from scanner imperfections that are exacerbated by the methods used to increase the SNR. Approach: Spirals and strong gradients (≤300mT/m) are used to attain short TEs and thus high SNR. An expanded encoding model including measured static and dynamic fields is deployed to obtain high image quality. Results: The approach is demonstrated in a healthy subject and a patient diagnosed with prostate cancer. It delivers higher SNR and improved cancerous lesion conspicuity. Impact: We provide the demonstration of prostate DWI with ultra-strong gradients and spiral readouts. Using high b-values and short echo times enhances lesion conspicuity and holds potential for early and non-invasive disease detection.
Improved SLIPEN (iSLIPEN) for Three-Dimensional Multi-slab Diffusion-Weighted Imaging by Partial Fourier and Prior Information
Authors: Xu Xiaorui , Chen Shihui , Liang Liyuan , Yuan Chenglang , Xiong Hailin , Chang Hing-Chiu
Published: November 2024

Motivation: SLIPEN is a promising technique to obtain 3D multi-slab DWI without suffering slab boundary artifacts. However, its performance is degraded when encountering limited signal SNR. Goal(s): An improved SLIPEN is desired to achieve robust perfomance regardless of limited signal SNR. Approach: Partial Fourier was applied to design an optimized sampling pattern and prior information was also incorporated into the model to improve the performance. Results: The improved SLIPEN could achieve comparable results to gold standard for in-vivo DWI images and DTI maps, with the need of only one third of gold standard data. Impact: 3D isotropic high-resolution DWI without suffering from slab boundary artifacts can be robustly achieved by our method with the use of 2D navigator, therefore benefiting the neuroscience study in evaluating crossing and kissing fibers.
Self-navigated 3D multi-slab EPI for SNR-efficient high-resolution diffusion MRI
Authors: Li Ziyu , Miller Karla , Chen Xi , Chiew Mark , Wu Wenchuan
Published: November 2024

Motivation: 3D multi-slab EPI achieves superior SNR efficiency for high-resolution diffusion MRI but requires navigators for phase correction, which increase scan time and SAR. Goal(s): To eliminate the requirement for navigators in 3D multi-slab diffusion MRI. Approach: 3D imaging is intrinsically highly segmented, making self-navigation challenging. Our optimized multi-shot sampling facilitates self-navigation by ensuring each shot intersects with kz=0 plane. The overall sampling pattern’s overlap and gaps are also minimized. A structured low-rank reconstruction is leveraged to reconstruct 2D phase maps from these intersections for phase correction. Results: Compared to navigated imaging our self-navigated method achieves comparable image quality with 31.4% shorter scan time. Impact: By removing the need for navigation, our method enables 3D multi-slab diffusion MRI to efficiently achieve TRs with near-optimal SNR efficiency. This approach may permit wider adoption of high-resolution diffusion MRI for basic and clinical neuroscience.
Visual Pathway Delineation via Correlation-Constrained Feature Decomposition and Consistency-based Sample Selection
Authors: Diakite Alou , Li Cheng , Xie Lei , Feng Yuanjing , Han Hua , Zheng Hairong , Wang Shanshan
Published: November 2024

Motivation: Accurate segmentation of visual pathway (VP) in multi-parametric MRI is crucial for reliable diagnosis of visual disorders. However, existing methods face challenges due to complex multi-parametric MRI relationships and limited labeled training data. Goal(s): The goal is to improve automatic VP delineation by developing a new framework that handles complex multi-parametric MRI relationships and incorporates unlabeled data. Approach: Our framework incorporates a correlation-constrained feature decomposition module to better exploit multi-parametric MRI information and a consistency-based sample selection method for more effective semi-supervised learning. Results: Experiments on the HCP dataset show that the proposed framework achieved superior VP delineation performance compared to state-of-the-art approaches. Impact: The results of this study could have a significant impact on scientists, clinicians, and patients by improving the understanding of the human visual system and enhancing the diagnosis accuracy of visual pathway disorders.
CF-VCENet: Coarse-to-Fine Vascular Connectivity Enhancement Network for Hepatic Vessel Segmentation in MR Images
Authors: Zhao Ziqi , Li Wentao , Ding Xiaoyi , Shao Guoliang , Sun Jianqi , Xu Lisa X.
Published: November 2024

Motivation: Vessel location must be pinpointed for precise avoidance during probe insertion for liver ablation. Goal(s): Our goal was to segment the hepatic vessel from MR images and to ensure the connectivity of the segmentation results. Approach: Hepatic vessel MR images were obtained from the records of 105 patients. Coarse-to-fine vascular connectivity enhancement algorithm was trained and tested using a five-fold cross-validation method. Results: Results demonstrated that our two-stage algorithm improved the connectivity of vessel segmentation results, with the dice coefficient increasing by up to 1.8% compared to the initial segmentation. Impact: Accurate segmentation results and enhanced connectivity provide a basis for hepatic vessel location and modeling. The results can assist doctors in preoperative planning while reducing the risk of damage to normal tissue in patients.
Active Gradient Guidance Based Susceptibility and Magnitude Information Complete Network for Basal Ganglia Segmentation
Authors: Xi Jiaxiu , Bao Lijun
Published: November 2024

Motivation: Accurate segmentation of basal ganglia is a crucial prerequisite for subsequent clinical practice and research. The boundaries of BG remain challenging to segment especially when dealing with data affected by severe artifacts. Goal(s): This work aims to propose an automatic BG segmentation method with radiologist comparable accuracy and high inference speed. Approach: An active gradient guidance-based susceptibility and magnitude information complete network(AGNet). With newly designed modules, AGNet can efficiently capture the inter-slice information and exploit it as attention guidance to facilitate the segmentation process. Results: AGNet has superior segment accuracy over existing methods with ADSC=0.874 and AHD=2.010, especially near boundaries of target VOI. Impact: The proposed model achieves more accurate segmentation at the boundary contour. Automatic and precise segmentation of basal ganglia is a prerequisite for the quantification of tissue magnetic susceptibility analysis and can serve as a fundamental tool for neurodegenerative disease research.
A 72-Channel Head Coil with an Integrated 16-Channel Field Camera for the Connectome 2.0 Scanner
Authors: Mahmutovic Mirsad , Shrestha Manisha , Ramos-Llordén Gabriel , Scholz Alina , Kirsch John , Wald Lawrence , Möller Harald , Mekkaoui Choukri , Huang Susie , Keil Boris
Published: November 2024

Motivation: Diffusion MRI utilizing ultra-high performance gradients for high b-value in vivo brain images still suffers from low SNR and increased eddy currents artifacts. Goal(s): To construct a high-density coil array with an integrated field monitoring system. To enhance SNR and parallel image encoding, while capturing 3rd-order field dynamics. Approach: Utilizing simulations, 3D printing technology, and radiofrequency electronics to construct a 72-channel head coil and incorporate a field monitoring system. Optimization of the combined system to operate jointly in a space-constraint MRI gradient coil environment. Results: High-resolution, high b-value diffusion in vivo imaging with greatly minimized image artefacts. Impact: The constructed 72-channel head coil along with the new Connectome 2.0 scanner will enable the investigation of new microstructure features and connectivity in the living human brain.
The Impacts of High Permittivity Materials on Various Multichannel Transceiver Arrays for Human Head Imaging at 10.5 Tesla
Authors: Waks Matt , Grant Andrea , Sadeghi-Tarakameh Alireza , Jungst Steve , Lagore Russell , DelaBarre Lance , Rupprecht Sebastian , Yang Qing , Lanagan Michael , Eryaman Yigitcan , Adriany Gregor , Ugurbil Kamil
Published: November 2024

Motivation: Since RF power requirements increase with operating frequency, SAR levels at UHF represent practical limitations. Here we evaluate possible improvements in overall transmit efficiency and SNR of array coils for the human head at 10.5T through the utilization of high permittivity materials. Goal(s): Our goal was to evaluate the impact of high permittivity materials (HPM) on the transmit efficiency and SNR for various transceiver array designs. Approach: We experimentally evaluated four multichannel transceiver arrays of different architectures with and without a formfitting HPM former. Results: The HPM coil former achieved improvements in transmit efficiency and SNR compared to a typical polycarbonate coil former. Impact: Incorporating high permittivity dielectric materials into the design and fabrication of pTx-capable transceiver array coils demonstrated improved transmit efficiency and SNR. This technology has the potential to improve imaging and spectroscopic applications in the human head at 10.5T and beyond.
A 60-channel high-density flexible receive array for pediatric abdominal MRI
Authors: Lee Wonje , Stickle Yunjeong , Follante Clyve , Grafendorfer Thomas , Yang Taeyoung , Robb Fraser , Zhang Fan , Scott Greig , Pauly John , Vasanawala Shreyas , Syed Ali
Published: November 2024

Motivation: Conventional MRI coils offer suboptimal parallel imaging performance for young children. Goal(s): Our goal was to enhance imaging acceleration by dedicated flexible high-density coil design for pediatric patients at 3T. Approach: We design, construct, and evaluate a highly flexible small element dense array constituted by dual turn loops with minimum inter-component interference layout design. Results: Both phantom and in-vivo studies demonstrated superior parallel imaging performance using the proposed coil. Impact: A dedicated high-channel count coil that allows highly localized coil sensitivities by minimum interference layout design may benefit small pediatric patients.
Molecular MRI of neuroinflammation using a redox-active iron complex
Authors: Zhang Chunxiang , Zhang Can , Gale Eric , Zhou Iris
Published: November 2024

Motivation: Neuroinflammation is a critical pathophysiological process implicated in the development of neurodegenerative disorders. Goal(s): Imaging to detect, monitor, and surveil neuroinflammatory processes could profoundly improve how patients suffering neurodegenerative diseases are diagnosed and managed. Approach: We evaluated brain imaging with the oxidatively activated contrast agent, Fe-PyC3A, as a proxy for inflammatory microglial activity in a mouse model of lipopolysaccharide(LPS)-induced neuroinflammation. Results: Fe-PyC3A generated significantly greater enhancement in LPS-treated mice than in saline-treated controls, correlating with immunohistochemical quantification of microglial activation. Imaging using Gd-DOTA as negative control probe and NOX-2 deficient mice as loss of function control links Fe-PyC3A enhancement with reactive microglial activity. Impact: MRI using oxidatively activated probes as a potential marker to detect and quantify neuroinflammatory processes could profoundly improve how patients suffering neurodegenerative diseases are diagnosed and managed.
T1 relaxometry or EPR signal intensity – Which is best for quantifying iron oxide nanoparticles in tissues non-destructively?
Authors: Kantesaria Saurin , Tang Xueyan , Suddarth Steven , Pasek-Allen Jacqueline , Namsrai Bat-Erdene , Goswitz Arjun , Hintz Mikaela , Bischof John , Garwood Michael
Published: November 2024

Motivation: Currently there is no low-cost method to nondestructively quantify iron oxide nanoparticles (IONPs) in tissue across a wide concentration range (0.05-100 mg Fe/mL). Goal(s): Our lab has developed a low-cost, LOngitudinally Detected Electron Paramagnetic Resonance (LOD-EPR) system. This work aims to evaluate LOD-EPR IONP quantification accuracy. Approach: We compare IONP Fe quantification accuracy of R1 (=1/T1) from MR relaxometry versus LOD-EPR signal in solution and IONP-perfused rat kidney sections used in cryopreservation. Results: LOD-EPR signal vs Fe concentration is linear in 0.05-10 mg Fe/mL IONP solutions and in IONP-perfused tissue, whereas R1 vs Fe concentration is linear in solution but not in tissue. Impact: Accurate quantification of IONPs in tissues at room temperature can be done using low-cost, benchtop LOD-EPR. Our primary application is in IONP rewarming of cryopreserved organs, however other applications such as dosimetry and oxygen sensing should also be possible.
Identification of transcriptomic signatures associated with cortical thinning in neuromyelitis optica spectrum disorder
Authors: Guo Min , Zhuo Zhizheng , Wu Minghao , Sun Jun , Yang Yu-Xin , Duan Yunyun , Liu Yaou
Published: November 2024

Motivation: Determining the potential transcriptomic signatures driving cortical thinning in neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS). Goal(s): To compare the cortical atrophy patterns and the underlying molecular mechanisms between NMOSD and MS. Approach: A partial least squares (PLS) regression model was used to associate the CTh alteration profile with the expression of genes from the Allen Human Brain Atlas (AHBA) database, then Metascape analysis was performed to identify the functional biological processes. Results: Distinct cortical atrophy patterns and underlying cell signaling pathways were observed in NMOSD and MS. Impact: The distinct cortical atrophy patterns will help in differential diagnosis of NOMOSD and MS. The identified genes and signaling pathways will help understand the pathological mechanism of both diseases and provide potential therapeutic targets.
In vivo assessment of astrocyte reactivity in patients with progressive supranuclear palsy
Authors: Hirata Kosei , Matsuoka Kiwamu , Tagai Kenji , Endo Hironobu , Tatebe Harutsugu , Ono Maiko , Kokubo Naomi , Kataoka Yuko , Oyama Asaka , Shinoto Hitoshi , Takahata Keisuke , Obata Takayuki , Dehghani Masoumeh , Near Jamie , Kawamura Kazunari , Zhang Ming-Rong , Shimada Hitoshi , Shimizu Hiroshi , Shimizu Hiroshi , Yokota Takanori , Tokuda Takahiko , Higuchi Makoto , Takado Yuhei
Published: November 2024

Motivation: Although astrocytic pathology is a pathological hallmark of progressive supranuclear palsy (PSP), the role of astrocytes in the pathophysiology of PSP is not fully understood. Goal(s): This study aimed to evaluate astrocyte reactivity in vivo in patients with PSP. Approach: Astrocyte reactivity was assessed by magnetic resonance spectroscopy and plasma biomarkers, which were verified via tau-PET and histopathological analysis. Results: Our results suggest that, in the anterior cingulate cortex, astrocyte reactivity precedes pronounced tau deposition and neurodegenerative processes and modulates brain function in PSP. Elevated myo-inositol was associated with high lactate levels, suggesting a link between reactive astrocytes and brain energy metabolism changes. Impact: This study assessed astrocyte reactivity in vivo using magnetic resonance spectroscopy and plasma biomarkers, providing insights into the involvement of astrocytes in the pathogenesis of progressive supranuclear palsy.
A Potential Substitution for Gadolinium in Brachial Plexus Magnetic Resonance Neurography: Deep Learning-Based Virtual Enhancement.
Authors: Liang Weiqiang , Li Yi , Ju Guangliang , Liang Xiaoyun , Zhang Jing
Published: November 2024

Motivation: Contrast-enhanced Magnetic Resonance Neurography (MRN) improves visualization of brachial plexus, but gadolinium risks limit clinical use. To reduce reliance on gadolinium contrast in brachial plexus (BP) MRN, we explore deep learning's potential for virtual enhancement. Goal(s): To investigate the feasibility of virtually enhancing brachial plexus MRN without gadolinium. Approach: An image enhancement network based on 2.5D U-Net was trained to generate virtually enhanced BP images from non-enhancement BP images, achieving high image quality and nerve visualization. Results: The virtual enhancement BP images showed comparable vascular suppression and image quality to gadolinium-enhanced images, demonstrating the potential for gadolinium substitution in brachial plexus MRN. Impact: This work opens the door to safer and more accessible BP MRN by reducing reliance on gadolinium. It may lead to broader clinical adoption and facilitate research on non-contrast imaging methods, benefiting both clinicians and patients.
Impact of Spinal Cord Injury (SCI) level on Cortical Reorganization
Authors: Ismaila Lukman , Farahani Farzad , Sadowsky Cristina , Sair Haris , Pekar James , Choe Ann
Published: November 2024

Motivation: We aimed to fill the knowledge gap regarding the impact of spinal cord injury (SCI) level on cortical reorganization. Goal(s): We sought to investigate cortical reorganization patterns in chronic SCI patients, specifically differentiating between cervical and thoracic injuries. Approach: Employing graph theory analysis of functional connectivity, we analyzed data from 32 chronic SCI patients and 32 healthy controls. Results: Significant alterations in somatomotor and visual networks in SCI cohort was observed. Notably, those with thoracic injuries exhibited more pronounced functional segregation within the somatomotor network, dividing it into dorsolateral and paramedian SMN regions and a ventrolateral SMN region. Impact: Our findings on the influence of SCI level on brain reorganization may impact clinicians, researchers, and rehabilitation specialists, guiding tailored interventions and raising new questions about optimizing SCI recovery.
Phase jolt: Second spatial derivative of phase images is a new contrast that offers many benefits for SWI type processing
Authors: Gulban Omer Faruk , Deistung Andreas , Tse Desmond Ho Yan , Bollmann Saskia , Huber Renzo , Goebel Rainer , Kay Kendrick , Ivanov Dimo
Published: November 2024

Motivation: Unlike magnitude images, even simple averaging is difficult with phase images, because of the circular nature of phase, spanning 2pi radians range. Goal(s): In our research that uses mesoscopic imaging (< 0.5 mm isotropic) at 7 T, we need to average multiple acquisitions to increase SNR. Being unable to average straightforwardly together with the lack of natural zero point is a critical constraint. Approach: To address this problem, we propose to operate on the magnitude of the second spatial derivative of phase images - called “phase jolt”. Results: Our results show phase jolt offers benefits for processing associated with SWI imaging. Impact: Phase jolt is an easy to implement new contrast where vessels and non brain tissue are highlighted and background bias field is mitigated. Therefore, phase jolt images have potential to be impactful in any setting where phase images are used.
Alternating low-rank tensor reconstruction for more precise and repeatable multiparametric mapping with Cardiovascular MR Multitasking
Authors: Cao Tianle , Mao Xianglun , Kwan Alan , Berman Daniel , Xie Yibin , Li Debiao , Christodoulou Anthony
Published: November 2024

Motivation: While MR Multitasking shows initial promise as a free-breathing, non-ECG approach for multiparametric CMR, its precision and repeatability still require further improvement to match the widely adopted clinical protocols. Goal(s): To improve precision and repeatability of multiparametric mapping by cardiovascular MR Multitasking. Approach: A novel low-rank tensor reconstruction strategy was developed to improve the reconstruction performance. Numerical simulations and in-vivo studies on healthy volunteers and cardiomyopathy patients were used to evaluate the proposed technique. Results: Compared to conventional recontruction, the proposed approach showed lower RMSE in numerical simulations, and improved precision by ~20% and repeatability by ~30% in in-vivo studies. Impact: The improved cardiovascular MR Multitasking has the potential to be an efficient and subject friendly (free-breathing, non-ECG) alternative for diagnosis of CMR patients whose T1 and T2 changes are greater than 100 ms and 2 ms, e.g., amyloidosis patients.
High-Fidelity Intravoxel Incoherent Motion (HIFIVIM) Parameter Mapping Using Locally Low-Rank with Temporal Subspace Constraint
Authors: Finkelstein Alan , Liao Congyu , Cao Xiaozhi , Mani Merry , Schifitto Giovanni , Zhong Jianhui
Published: November 2024

Motivation: Intravoxel incoherent motion (IVIM) is a measure in MRI to quantify tissue perfusion. However, clinical applications are limited by noisy parameter estimates for the perfusion fraction (f) and pseudodiffusion coefficient (D*). Goal(s): We sought to improve IVIM parameter estimation using a model-based reconstructionApproach: We combined locally low-rank (LLR) and temporal subspace constraints to reliably perform joint reconstruction of IVIM images before fitting while correcting shot-to-shot phase variations between each b-value. Results: Our method resulted in smoother signal decay curves before fitting and improved the estimation of IVIM parameter maps with less noise and fewer outliers. Impact: A model-based reconstruction with low rank and temporal constraints improved IVIM image reconstruction, reducing noise and outliers in parameter estimates. Spline interpolation further facilitated reliable estimation of IVIM maps from just 5 b-values, benefiting clinical situations like stroke.
Proximal Gradient Decent Network for Respiratory-Correlated Four-Dimensional Abdominal MR Fingerprinting Reconstruction (PGDN-RC-4DMRF)
Authors: Wang Lu , Liu Chenyang , Zhi Shaohua , Ren Ge , Li Tian , Cao Peng , Cai Jing
Published: November 2024

Motivation: Four-dimensional MR fingerprinting (4D-MRF) has the potential to improve precision and efficacy in abdominal radiotherapy (RT). However, the long reconstruction time of the state-of-the-art reconstruction method, compress-sensed-based respiratory-correlated 4D-MRF (CS-RC-4DMRF), limits its clinical application. Goal(s): The study aims to develop a novel method to reduce the reconstruction time of CS-RC-4DMRF. Approach: We developed PGDN-RC-4DMRF by integrating a deep proximal gradient descent network (PGDN) into 4D-MRF. Tumor motion tracking accuracy, tissue quantification accuracy, and image quality were evaluated. Results: The proposed PGDN-RC-4DMRF method reduce the reconstruction time by a factor of 120, decreasing it from 8 min/slice to 4 s/slice while maintaining other metrics. Impact: The improvement in the reconstruction speed of 4D-MRF through PGDN-RC-4DMRF may enhance the practicality of 4D-MRF in clinical settings for clinicians and potentially benefit RT outcomes for patients.
Non-invasive high-resolution in vivo pH mapping in brain tumors by 31P‑informed deepCEST MRI
Authors: Schüre Jan-Rüdiger , Rajput Junaid , Steidl Eike , Shrestha Manoj , Deichmann Ralf , Hattingen Elke , Fabian Moritz , Maier Andreas , Nagel Armin , Zaiss Moritz
Published: November 2024

Motivation: The pH value is an important biomarker for many diseases. MRI-based 3D pH mapping for clinical routine would be an enormous benefit for diagnostics. Goal(s): Prediction of intracellular 31P-pHi maps from 1H APTw-CEST MRI data using a voxel-wise neural network, aiming to improve brain tumor imaging. Approach: Fifteen glioblastoma patients underwent 3T MRI with both APTw-CEST and 31P-MRS. A neural network trained on 11 patients data to correlate APTw-CEST features with 31P-derived pHi values, tested on 4 additional patients. Results: The neural network's pHi predictions closely matched 31P-pHi maps, showing potential for high-resolution, non-invasive pHi mapping in brain tumors. Impact: High resolution pH imaging for better diagnosis of diseases (inflammation, stroke, tumor) and therapy monitoring in clinical routine.
Non-invasive mapping of brown adipose tissue activity with MRI
Authors: Cai Zimeng , Zhong Qiaoling , Feng Yanqiu , Wu Zhigang , Liang Changhong , Liew Chong Wee , Kazak Lawrence , Cypess Aaron , Liu Zaiyi , Cai Kejia
Published: November 2024

Motivation: Through non-shivering thermogenesis, brown adipose tissue (BAT) plays a critical and beneficial role in obesity and metabolic diseases. Goal(s): In this study, we developed non-invasive creatine CEST (CrCEST) MRI of adipose tissues for mapping BAT activity in both rodents and humans given to creatine’s important role in bioenergetics. Approach: We observed by CrCEST MRI that the changes in BAT activity in rats and human after drug administration and/or cold exposure were in good agreement with traditional 18F-FDG PET/CT imaging. Results: The results of this study demonstrated CrCEST MRI as an endogenous, non-invasive, and radiation-free method for in vivo mapping of BAT activity. Impact: In this study, endogenous CrCEST MRI of adipose tissues was developed and found to serve as an imaging biomarker for BAT activity, the diagnosis of metabolic diseases, and the evaluation of new therapeutic strategies in a longitudinal and non-invasive means.
Highly Accelerated CEST Imaging with Stack-of-stars Acquisition using Unsupervised Implicit Neural Representation Networks
Authors: Liu Bei , She Huajun , Du Yiping
Published: November 2024

Motivation: Reduction of scan time in CEST imaging is clinically meaningful. Goal(s): Our goal is to develop an undersampled reconstruction algorithm to help vastly reduce the acquisition time. Approach: A novel unsupervised deep-learning based algorithm is proposed to accelerate steady-state pulsed CEST imaging with golden-angle stack-of-stars trajectory using mixed-feature hash encoding implicit neural representation. Additionally, Imaging quality is further improved using the explicit prior knowledge of weighted joint sparsity in subtle structural features of CEST image domain. The low rankness and sparsity in the Z‐spectra domain are used to reduce acquisition time. Results: It is possible to achieve a 30-fold acceleration for CEST imaging. Impact: An unsupervised deep-learning algorithm is proposed to accelerate steady-state pulsed CEST imaging with golden-angle stack-of-stars trajectory using mixed-feature hash encoding implicit neural representation and weighted joint sparsity. It can vastly reduce the acquisition time and has potential for clinical applications.
High-Resolution Reduced FOV Renal Chemical Exchange Saturation Transfer MRI Using orthogonal RF pulses
Authors: Zhang Qianqian , Chen Zelong , Wu Zhigang , Deng Kan , Tao Quan , Zhang Wenyan , Zhang Yizhe , Xu Yikai , Feng Yanqiu
Published: November 2024

Motivation: Long scanning time and low resolution limit the chemical exchange saturation transfer (CEST) clinical translation. Goal(s): We aimed to develop a high-resolution renal reduced field of view CEST (rCEST) technique to reduce scanning time. Approach: The rFOV based on orthogonal RF pulses in combination with conventional CEST module was performed on a volunteer and compared this technique with full-size FOV CEST (fCEST). Results: Compared to fCEST, rCEST has shorter scanning time, higher image quality, and better saturation efficiency at the same image resolution. Impact: The rCEST technique may have potential for clinical applications requiring high resolution and metabolic renal CEST-MR image.
Assessment of neoadjuvant immunochemotherapeutic response for bladder carcinoma using amide proton transfer weighted MRI: a feasibility study
Authors: Kong Lingmin , Cai Qian , Chen Yanling , Cao Wenxin , Weng Bei , Guo Yan , Wang Huanjun
Published: November 2024

Motivation: To accurately predict bladder cancer patient neoadjuvant treatment responses is essential and urgent. Goal(s): To investigate the feasibility of amide proton transfer weighted (APTw) and diffusion weighted MRI in evaluating the response of neoadjuvant therapy for bladder cancer. Approach: Histogram analysis features were extracted from pre- and post-treatment APTw and apparent diffusion coefficient (ADC) map. Results: Several imaging biomarkers derived from pretreatment imaging were statistical significant between pathological complete response (pCR, no residual tumor) and non-pCR group (P < 0.05 for all). For the pCR group, APTw values markedly decreased while ADC values noticeably increased at post-treatment MRI (P < 0.05 for all). Impact: This work establishes that APTw MRI holds promise to evaluate bladder cancer tumor responses to neoadjuvant immunochemotherapy and may be used to guide personalized precision therapy in future.
PET-MR compatible CEST method for imaging of Alzheimer’s Disease.
Authors: Leforestier Rodolphe , Xia Ding , Feng Li , Ferreira-Atuesta Carolina , Xu Ziwei , Hedden Trey , Xu Xiang
Published: November 2024

Motivation: Current methods of assessing Alzheimer's disease, such as PET scans, are expensive, involve exposure to radiation and have limited resolution. Goal(s): We aim to demonstrate the applicability a novel CEST MRI method to measure the relayed Nuclear Overhauser effect, which may be sensitive to amyloid-β aggregates. Approach: We have developed and tested a radially sampled CEST sequence (ssGraspCEST) that can be acquired on hybrid PET-MRI systems. Results: MCI and AD patients appeared to have narrower distributions of LDNOE and ∆ST(-3.6) and higher values. However, due to the limited sample size at this time, no significant differences were observed between the two groups. Impact: We demonstrated the implementation of a fast, motion-robust CEST method, fully compatible with hybrid PET-MRI systems and particularly suitable for imaging elderly participants who cannot hold still during the scan, which may be useful in future for detecting pathological aggregates.
Probabilistic Template Matching for Detection of Language Network with resting-state fMRI in Patients with Brain Tumors
Authors: Teo Jian Ming , Kumar Vinodh , Lee Jina , Eldaya Rami , Hou Ping , Noll Kyle , Ferguson Sherise , Prabhu Sujit , Wintermark Max , Liu Ho-Ling
Published: November 2024

Motivation: Automated detection of resting-state language network with independent components analysis (ICA) of brain tumor patients is challenging. Goal(s): Develop an algorithm to detect the language network with ICA guided by a probabilistic overlap map (POM). Approach: POM was generated from sentence completion presurgical fMRI of 283 patients. Probabilistic template matching performs a direct search over probability thresholds and component numbers. Independent dataset of 28 patients was used for testing in comparison to an existing method. Results: Recommended ICA components from our algorithm agreed better with tb-fMRI language localizations, demonstrating significantly higher Dice coefficients and Pearson correlation scores in left hemisphere primary language areas. Impact: The proposed method can improve the accuracy of automated detection of rs-fMRI language network. This may benefit presurgical evaluation for patients whose tumors are adjacent to language areas but have limited tb-fMRI.
Longitudinal resting-state network changes in treatment-resistant OCD patients following MR-guided Focused Ultrasound Capsulotomy
Authors: Rockel Conrad , Clark Darren , Pichardo Samuel , Girgis Fady , Adams Beverly , Kiss Zelma , Pike G
Published: November 2024

Motivation: MR-guided focused ultrasound capsulotomy is a surgical procedure to treat intractable OCD. While demonstrating clinical success, the mechanisms of symptom decrease are poorly understood. Goal(s): This study sought to explore how intrinsic brain networks change following surgery. Approach: Seed-based resting state fMRI was used to analyze intrinsic networks in a group of 6 OCD patients prior to and following surgery, along with a matched control group. Results: Prior to surgery, OCD patients showed greater connectivity within internally-focused networks, and less connectivity in those involved in external cognition. One year following surgery, these connectivity differences were substantially reduced relative to controls. Impact: This study will appeal to neuroscientists interested in resting-state networks involved with OCD, as well as in how these networks change following a MRgFUS surgical procedure which produced substantial clinical improvement.
Disrupted functional connectivity architectures of neural circuits in obsessive-compulsive disorder
Authors: Cao Lingxiao , Li Hailong , Jiang Jiaxin , Li Bin , Chai Shuangwei , Zhou Huan , Gong Qiyong , Huang Xiaoqi
Published: November 2024

Motivation: The mechanistic understanding of dysfunctional neural circuits involved in obsessive-compulsive disorder (OCD) is incomplete. Goal(s): To replicate previous findings in an independent data set and replenish mechanisms of changes in functional connectivity architectures within neurocircuitry of OCD using resting-state fMRI. Approach: Network-based statistical analysis on a brain network incorporating functionally parcellated regions of interest defined by clustering technique was used. Results: Hyperconnectivity were detected in the fronto-pallidal, fronto-thalamic, basal ganglia-thalamic, intra-thalamic, and thalamo-amygdala connections in OCD patients compared with healthy controls. Impact: We depict the neurocircuitry model of OCD pathophysiology through the functional network connectivity perspective and extend it by providing the importance of intra-thalamic and thalamo-amygdala connections in OCD. These findings add mechanistic insights to the dysfunctional neural circuits in OCD.
Single-timepoint dynamic functional connectivity patterns in temporal lobe epilepsy
Authors: Sainburg Lucas , Rogers Baxter , Chang Catie , Englot Dario , Morgan Victoria
Published: November 2024

Motivation: Epileptic tissue generates interictal spikes between seizures, which are used to localize the epileptic focus clinically. Goal(s): We aimed to detect dynamic functional connectivity (FC) patterns in resting-state fMRI data that may be related to interictal spikes. Approach: We detected whole-brain dynamic FC patterns at timepoints that had FC characteristics similar to epileptic spikes in both healthy controls and patients with temporal lobe epilepsy (TLE). Results: We found three dynamic FC patterns, one of which occurred more in TLE than in controls and the occurrence of which was related to clinical measures of epilepsy severity. Impact: These results suggest the potential clinical utility of fMRI-based dynamic FC to detect interictal spikes. Future studies can evaluate the correspondence of these dynamic FC patterns to interictal spikes using simultaneous electrophysiology and fMRI.
Imaging small intracortical blood vessels at 64 μm in-plane resolution in macaque monkey brain in vivo using a large-bore 7T MRI scanner
Authors: Wang Jianbao , Ma Yuhan , Liu Yipeng , Lin Libo , Berman Avery , Bollmann Saskia , Polimeni Jonathan , Roe Anna
Published: November 2024

Motivation: Hemodynamics of the cerebral cortex are shaped by vascular architecture; however, it remains challenging to study the small intracortical vascular anatomy in vivo. Goal(s): To test whether intracortical arterioles can be detected in vivo in non-human primates at 7 Tesla using a conventional human MRI scanner, and to study the organization of arterials and venules. Approach: After conducting time-of-flight (TOF) contrast simulations, optimized TOF-MRA images from macaques were acquired using a 7T large-bore MRI scanner with 64-μm in-plane resolution. Results: Intracortical arterioles and venules were reliably imaged and exhibited cortical area-specific differences in distribution. Imaging times were as fast as 10 minutes. Impact: Using a standard human 7T MRI scanner, we illustrate that micron-scale intracortical arterioles are detectable non-invasively in vivo in primates. We suggest similar methods can be used to study human microvascular organization in health and disease.
Neuroimaging of Serotonergic and Psychedelic Agonist Drug Challenges in Non-Human Primates
Authors: Bagdasarian Ande , Larsen Kristian , Fisher Patrick , Hansen Hanne , Wey Hsiao-Ying
Published: November 2024

Motivation: Acute effects of psychedelic drugs are under-reported in neuroimaging studies, warranting further investigation of their immediate pharmacology to explore the potential to monitor treatment response with imaging. Goal(s): Our goal was to assess acute impacts of serotonergic (psychedelic and non-psychedelic) agonists on hemodynamics in non-human primates (NHP). Approach: Pharmacological-MRI (phMRI) was used to measure cerebral blood volume (CBV) changes by psilocybin, lisuride and 25CN-NBOH. Results: Psilocybin and lisuride induced bi-phasic hemodynamic response, whereas 25CN-NBOH was monophasic. Bi-phasic phenomena may be due to non-selectivity of agonist drugs. Elevated CBV at higher psilocybin doses persists longitudinally, while lisuride and 25CN-NBOH modulations trend toward baseline. Impact: Bi-phasic signal profiles and downstream impacts to cerebral hemodynamics may reflect non-selective targeting of psilocybin and lisuride, highlighting the sensitivity of phMRI in drug evaluation.
Unsupervised deep learning for denoising diffusion-weighted images with noise-correction loss functions
Authors: Chen Yunwei , Zhang Zhicheng , Feng Yanqiu , Zhang Xinyuan
Published: November 2024

Motivation: Since the noisy magnitude MR data generally follows Rician distribution, using the noisy images and network’s output to construct unsupervised learning’s loss function for denoising will lead to a biased estimation, especially for DW images which suffers from the lower SNR. Goal(s): To address the noise bias issue. Approach: We proposed two noise-correction loss functions for unsupervised denoising of DW images, based on DIP and the characteristics of Rician distribution. Results: The experimental results on simulated and in-vivo data demonstrated that the proposed loss functions effectively corrected the signal-dependent noise bias and improved the accuracy of unsupervised learning-based DW images denoising method. Impact: Firstly, we proposed two noise-correction loss functions and validate their effectiveness in denoising DW images. Secondly, the proposed loss functions are not limited to DW images and can be directly applied to other modality MR images.
Neighborhood-attention models for incorporating spatial information in deep learning parameter estimation applied to IVIM
Authors: Kaandorp Misha , Zijlstra Frank , Karimi Davood , Gholipour Ali , While Peter
Published: November 2024

Motivation: Conventional model-fitting approaches neglect spatial information. Recent work showed promise in using convolutional neural networks (CNNs) trained on spatially-correlated synthetic data. However, the convergence rate remained suboptimal, and the spatial extent was limited. Goal(s): To improve estimator performance by utilizing transformer networks and training on larger receptive-fields. Approach: Transformers with self-attention and neighborhood-attention with increased receptive-field were trained on spatially-correlated synthetic data (IVIM), and evaluated quantitatively using novel fractal-noise maps and in-vivo scans. Results: Transformers excelled in integrating spatial information over CNNs. The application of larger receptive-fields with neighborhood-attention effectively leveraged correlated signal information from nearby voxels, leading to improved estimator performance. Impact: The improved parameter estimation from neighborhood-attention models trained on synthetic data brings challenging ill-posed signal analysis problems, like IVIM, closer to clinical implementation. Additionally, the novel fractal-noise maps provide spatially-correlated ground truths, permitting new approaches to quantitative medical image analysis.
Gradient-Free Frequency Encoded MRI
Authors: Srinivas Sai Abitha , Glenn Antonio , Vaughn Christopher , Griswold Mark , Grissom William
Published: November 2024

Motivation: Eliminating conventional gradients can help miniaturize and lower costs of MRI significantly. No method using RF-gradients has been able to achieve frequency encoding, the fastest encoding mechanism in MRI. Goal(s): Develop a Simultaneous-Transmit-and-Receive (STAR) system and perform RF Frequency encoding using the Bloch Siegert shift. Approach: A novel injection transformer, 2MHz/47.5mT RF coil setup and pulse sequence was developed to enable STAR to prevent the RF encoding signal from overwhelming the receiver while frequency encoding MR signal without conventional gradients. Results: The novel STAR system achieved 99.75% cancellation of RF encoding signal, enabling the first-ever acquisition of frequency encoded MR images using RF-gradients. Impact: We have demonstrated, for the first time ever, frequency encoded MRI using RF field gradients in place of conventional B0 gradients. This is a fundamental requirement to make RF encoded-MR imaging as fast as conventional gradient encoding.
Three-Dimensional Balanced Steady State Free Precession Ultra-short Echo Time MRI for Multiple Contrasts Whole Brain Imaging
Authors: Shen Xin , Caverzasi Eduardo , Yang Yang , Liu Xiaoxi , Green Ari , Henry Roland , Emir Uzay , Larson Peder
Published: November 2024

Motivation: Typical ultra-short echo time (UTE) sequences lack of meaningful contrast for long T2 components, and lack of straightforward method to derive images with only ultra-short T2 (uT2) components. Goal(s): To develop a novel high-resolution fast UTE MRI sequence, potentially for myelin imaging. Approach: The sequence was developed based on combining balanced steady-state free precession (bSSFP) and UTE techniques, together with a 3D rosette dual-echo k-space trajectory. Results: The sequence provides PD contrast in both echo times (TEs) and enables easy separation of uT2 components by subtraction between two TEs, which is sensitive to MS patients’ lesions. Impact: The fast and high-resolution (0.94 mm isotropic resolution under three minutes) dual-echo bSSFP UTE sequence provides both structural information (PD contrast) and uT2 components imaging for myelin quantification (by subtraction). It has great potential aiding diagnosis of multiple sclerosis patients.