bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating vascular normalization in orthotopic triple negative breast cancer with metronomic chemotherapy using 3D-UTE-GRASP DCE MRI
Authors: Qayyum Sawwal , Zhang Jin , Aronowitz Eric , Han Myung Shin , Lee Seung Koo , Kim Gene
Published: November 2024

Motivation: Metronomic chemotherapy shows promise as a cost-effective therapy for vascular normalization. However, it is unclear how to determine the optimal biological dose (OBD). Goal(s): Our goal is to use dynamic contrast-enhanced (DCE) MRI and pharmacokinetic analysis for non-invasive measurements of the heterogenous tumor treatment response toward determining the OBD. Approach: The 4T1 murine orthotopic triple negative breast cancer models were assessed longitudinally using two different dosing schemes, daily and intermittent, using cyclophosphamide. Pharmacokinetic and histological analysis (CD31, Ki67) were conducted. Results: The intermittent dosing schedule showed higher Vp, Fp, and Ktrans in all tumor regions indicating possible vascular normalization. Impact: The proposed 3D-UTE-GRASP DCE-MRI method provides a non-invasive platform to assess for optimal biological dose in metronomic chemotherapy. By accurately determining the heterogenous tumor vessel dynamical changes, this platform can be used to enhance treatment response over time.
Free breathing cardiac T2 mapping via single-shot ZOOM-MOLED and deep learning reconstruction
Authors: Dai Chenyang , Zhu Liuhong , Wu Jian , Yang Qinqin , Wu Zhigang , Chen Zhong , Cai Congbo , Cai Shuhui
Published: November 2024

Motivation: Quantitative cardiac magnetic resonance (CMR) imaging has important applications in clinic. However, conventional parametric mapping methods suffer from inherent inefficiencies. Goal(s): To enhance the resolution of reconstructed images, mitigate image distortion and artifacts, and improve the signal-to-noise ratio in quantitative CMR imaging. Approach: A method was proposed which combines single-shot multiple overlapping-echo detachment (MOLED) imaging with outer volume suppression (OVS) and zonal oblique multislice (ZOOM) techniques, and deep learning reconstruction was used for image reconstruction. Results: The results of simulation, phantom, and in vivo healthy volunteer experiments show great performance of the proposed method. Impact: This study developed a cardiac T2 mapping method without requirement of breath-holding or respiratory-gating. It paves the way for real-time dynamic high-resolution cardiac T2 mapping.
Amide Proton Transfer Imaging Has added Value for Predicting Extraprostatic Extension in Prostate Cancer Patients
Authors: Qin Xiaoyan , Mu Ronghua , Deng Kan , Zheng Wei , Peng Yang , Huang Bingqin , Shen Zhiwei , Zhu Xiqi
Published: November 2024

Motivation: Multi-parametric MRI is the most favorable imaging technique for local staging of PCa. Creating a combined model using these parameters would be desirable to improve the assessment of EPE. Goal(s): To verify the diagnostic efficiency of tumor size, LCC, ADC, APT, and their combined models for predicting EPE. Approach: The difference of tumor size, LCC, ADC and APT value between groups were compared. The ROC analysis was used for EPE prediction. Results: APT, ADC, tumor size and the LCC were independent predictors of EPE. The AUC of model III (APT +ADC+LCC+tumor size) were 0.869. Impact: These findings hold crucial clinical significance in the selection of appropriate therapeutic strategies for clinical cases of prostate cancer.
A Novel Renal 3D Saturation Recovery T1 Mapping readout by GRASE (3D-SR-GRASE)
Authors: Zhang Wenyan , Tao Quan , Chen Zelong , Deng Kan , Wu Zhigang , Zhang Yizhe , Zhang Qianqian , Xu Yikai , Feng Yanqiu
Published: November 2024

Motivation: Renal T1 mapping has been explored as a tool to visualize localized and diffuse renal diseases. 2D-MOLLI imaging have limited coverage, and 3D imaging are currently focused on cardiac imaging and with long acquisition time. Goal(s): In this study, we aimed to propose a fast 3D T1 mapping sequence for kidney. Approach: A saturate-recovery(SR) pulse, followed by 3D-GRASE readout, is used for T1 mapping. We also verified its effectiveness in T1 mapping for phantom and normal volunteers. Results: The proposed sequence allows for 3D renal T1 imaging within two minutes and measured T1 value in phantom and volunteers were consensus with 2D-MOLLI. Impact: This SR-GRASE sequence may provide a 3D fast clinical imaging technique for kidney.
KTSSI: Quantitative fascial magnetic resonance imaging
Authors: Zhou Xiaohan , Liang Yan , Liu Wentao , Tang Weinan , Han Dong
Published: November 2024

Motivation: Fascia, a challenging component in MRI due to its rapid signal decay, remains elusive in in vivo imaging under normal physiological conditions. Goal(s): This study introduces an innovative K-T Space Section Imaging-MRI (KTSSI) method, aimed at illuminating the T2* characteristics of fascial tissues. Approach: Through extensive phantom testing and MRI scans of healthy human lower legs using KTSSI, we reveal a new dimension of fascia within the broader MRI domain. Results: Obtained were extensive, continuous 3D reconstructed images of the fascia in healthy individuals, displaying distinct and clear features under normal physiological conditions. Impact: This work reframes enable the imaging of fascia, paving the way for patients with myofascial conditions by enabling early detection and precise evaluation of structural changes. This opens avenues for investigating dynamic anatomical adhesions or structural ruptures.
Mapping fat-water separated R1, R2*, and fat fraction with bipolar multi-echo MP2RAGE
Authors: Pazmino Jorge Campos , Fortin Marc-Antoine , Fortier Véronique , van der Kouwe Andre , Ciobanu Cristian , McNabb Evan , Bider Renée-Claude , Levesque Ives
Published: November 2024

Motivation: Multi-Echo Magnetization Prepared Two Rapid Acquisition of Gradient Echoes (ME-MP2RAGE) can be combined with chemical shift-encoded fat-water separation to simultaneously map fat and water-specific R1. However, long echo times in the multi-echo portion of the technique can lead to poor fat-water separation and compromised accuracy and precision of the estimates. Goal(s): Simultaneous mapping of fat and water-specific R1, R2*, and proton density fat fraction with bipolar ME-MP2RAGE. Approach: Unipolar and bipolar ME-MP2RAGE sequences were compared in simulation and phantom experiments. Results: Numerical simulations and phantom experiments showed that bipolar readouts produce more accurate and precise estimates than unipolar alternatives. Impact: We propose a technique for simultaneous measurement of PDFF, fat and water-specific R1, and R2* combining multi-echo MP2RAGE and fat-water separation. Moreover, we show that bipolar readouts produce more accurate and precise estimates of these parameters using multi-echo MP2RAGE.
3D UTE With Twisted Trajectories
Authors: Carl Michael , Ma Yajun , Du Jiang
Published: November 2024

Motivation: Radial UTE can often be impacted by aliasing artifacts if undersampling is required to achieve a short scantime. More efficient trajectories may alleviate these limitations. Goal(s): Our goal is to study how much aliasing reduction can be achieved in UTE MRI by applying a small amount of spiral twist to the readout trajectory. Approach: In order to add some twist/spiral to the UTE trajectories, we simply added an orthogonal gradient while simultaneously ramping down the radial-out read gradient. Results: Images using a longer, twisted readout trajectory results in less visible aliasing artifacts and increased SNR. Impact: UTE MRI undersampling artifacts were found to be reduced using simple twisted k-space trajectories, hence allowing a reduction in scantime.
Cardiac Simultaneous Multi-Slice Multimapping based on Locally Low-Rank and Sparsity Constraints: Method Development and Validation
Authors: Emu Yixin , Chen Zhuo , Gao Juan , Hu Chenxi
Published: November 2024

Motivation: Simultaneous Multi-Slice (SMS) Multimapping can considerably improve the scan efficiency by acquiring myocardial T1 and T2 maps of 3 short-axis slices in 1 breath-hold. Goal(s): To propose an accurate, precise, and reproducible SMS-Multimapping method. Approach: A locally low-rank and sparsity-based reconstruction algorithm was developed to reduce noise and aliasing artifacts. Validation was performed in phantoms and 10 healthy subjects, where the method was compared with standard MOLLI/bSSFP T2 mapping and Multimapping. Results: Despite the 6-fold reduction of scan time, the proposed method shows good accuracy, reasonable precision, and acceptable reproducibility in its regional myocardial T1 and T2 measurement. Impact: The proposed method transforms a scan of 6 breath-holds down to a single breath-hold scan. Once employed, the method can greatly improve the patient comfort and efficiency of myocardial parametric mapping.
One-Step Image Reconstruction for Cine MRI with a Quadratic Constraint
Authors: Zeng Larry , Li Ya , Ma Xiaodong , Yuan Chun
Published: November 2024

Motivation: In cine MRI, the measurements within each time-frame alone are too noisy for image reconstruction. Some information must be ‘borrowed’ from other time frames and the reconstruction algorithm is a slow iterative procedure. Goal(s): We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction. We derive a non-iterative algorithm to minimize this objective function. Approach: The derivation of the algorithm is based on the calculus of variations. The resultant algorithm is in the form of filtered backprojection. Results: The feasibility of the proposed algorithm is demonstrated with a clinical patient brain study. Impact: Non-iterative reconstruction that minimizes a constrained objective function increases the throughput in healthcare institutions. This translates to reduced healthcare costs. The new reconstruction formula has a closed-form explicit expression of how to incorporate the reference image in dynamic reconstruction.
Compensation of Respiratory Induced Artifacts in the Lumbar Spinal Cord Using a 1D Pre-Acquisition Navigator
Authors: Robison Ryan , O'Grady Kristin , Sweeney Grace , Ganji Sandeep , Johnson Brian , Smith Seth
Published: November 2024

Motivation: Respiration induces artifacts and signal loss in axial multi-echo gradient echo imaging of the lumbar spinal cord. Goal(s): To investigate respiration-induced field shifts in the lumbar cord and to mitigate respiration induced artifacts using a 1D phase navigator. Approach: A 1D phase navigator, added prior to the multi-echo gradient echo readout, was used to measure and provide compensation for respiration-induced and shot-dependent phase shifts. Results: The proposed navigator was effective in measuring field shifts and providing a substantial reduction in artifacts in the lumbar spinal cord. Navigator post-processing was simplified compared to that required for a 1D navigator post-readout. Impact: This work demonstrates, via phantom and in-vivo experiments, self-consistent measurements of respiration-induced field shifts and proposes an approach for their compensation that could be integrated into future spinal cord studies using multi-echo gradient echo acquisitions.
Accelerated Whole-Brain Mapping of Venous Cerebral Blood Volume Using Velocity-Selective Venous-Spin-Labeling With 3D GRASE Encoding
Authors: Heo Youngho , Oh Sungsuk , Lee Hyunyeol
Published: November 2024

Motivation: The VS venous-spin-labeling-prepared 3D TSE method has recently shown promise in whole-brain venous CBV mapping with relative immunity to field variations. Nevertheless, the method’s relatively long scan times limits its application to functional studies involving short-term stimuli. We aimed to develop a highly accelerated technique for CBVv mapping across the entire brain. Goal(s): To reduce imaging time while mitigating inherent artifacts in GRASE imaging. Approach: We employed GRASE encoding with variable refocusing flip angles while subsampling k-space data, followed by compressed sensing based image reconstruction. Results: The proposed technique yields comparable CBVv values across the entire brain, with highly accelerated scan times. Impact: We introduce a scan-time efficient CBVv mapping strategy by means of GRASE encoding with sparse k-space sampling. Upon further evaluation of these issues, the present GRASE-based CBVv mapping method is expected to find various applications in neuroimaging studies.
Precision Diagnosis of BI-RADS4 Breast Lesions: A Promising Approach with DCE and 3D-MIP Parameters
Authors: liang hongbing , zhang lina , ning ning , zhao siqi , li yuanfei , wu yueqi , song qingwei , guan haonan , xie lizhi
Published: November 2024

Motivation: Breast cancer is a significant health concern for women. Accurate diagnosis of BI-RADS4 lesions is challenging, necessitating improved diagnostic indicators. Goal(s): This study aims to enhance BI-RADS4 breast lesion diagnosis using DCE and 3D-MIP parameters, providing more precise insights. Approach: We analyzed various parameters, identified independent factors, and combined vascular diameter difference with Slopemax for optimal diagnosis. Results: The combination demonstrated superior diagnostic efficiency, differentiating benign from malignant lesions effectively. Impact: This approach holds promise for early breast cancer diagnosis and improved patient care, offering clinicians a valuable tool for enhanced precision in BI-RADS4 lesion evaluation.
Reliability and repeatability of texture features extracted from quantitative T1 & T2 of fresh breast tumour specimens at 3T
Authors: Nkonde Kangwa , Cheung Sai , Senn Nicholas , Husain Ehab , Masannat Yazan , He Jiabao
Published: November 2024

Motivation: Quantitative T1/T2 is known to alter in the presence of breast tumours, and texture analysis offers a measure to characterise unique tumour morphology. Goal(s): We aimed to determine the reliability and repeatability of texture features extracted from T1/T2 images across acquisitions. Approach: Five repeated acquisitions of T1/T2 were performed on 20 breast tumours to derive texture features of Mean, Standard deviation, Kurtosis, Skewness, and Entropy. Results: There was excellent reliability and repeatability in all T1 texture features, except moderate reliability in Entropy. There was good to excellent reliability and excellent repeatability for most T2 textures, except Kurtosis and Skewness. Impact: The reliability and repeatability of texture features extracted from relaxation property maps serves as a corner stone towards higher order analysis for breast cancer, to support clinical decision with confidence.
Microcalcification Detection and Differentiation in Breast Cancer using Ultrashort Echo Time (UTE) MRI
Authors: Ayoub Yazan , Cheung Sai Man , Maglan Boddor , Senn Nicholas , Husain Ehab , Masannat Yazan , He Jiabao
Published: November 2024

Motivation: Ultra short echo time (UTE) has been developed to capture the rapid signal decay of short T2* species, to overcome the insensitivity of conventional MRI towards micro-calcification, a central prognostic marker of breast cancer. Goal(s): To examine the degree of calcification in breast tumour specimens using UTE. Approach: The degree of calcification of whole tumour from 20 specimens freshly excised from female patients with breast cancer was derived using dual-echo UTE protocol, with correlation against histological findings. Results: The degree of calcification was significantly different between malignant and non-calcified tissue, with no significant correlation to Ki-67 and NPI scores. Impact: Ultra-short echo time (UTE) enhances the sensitivity to micro-calcifications in the breast, through dual-echo approach to maximise the signal of short T2* species. Clinical implementation of UTE can enhance assessment of microcalcification and improve prognostic value of breast cancer imaging.
Combination of DCE-MRI and NME-DWI via Deep Neural Network for Predicting Breast Cancer Molecular Subtypes
Authors: Ba Zhichang , Zhang Hongxia , Liu Aoyu , Guan Haonan , Zhou Xinxiang , Liu Lu , Nanding Abiyasi , Sang Xiqiao , Kuai Zixiang
Published: November 2024

Motivation: Breast cancer exhibits diverse molecular subtypes with varying responses to treatment. Goal(s): This study aims to explore the potential enhancement of breast cancer molecular subtype prediction by combining DCE and NME-DWI through DNNs. Approach: 475 patients with 480 breast cancers were recruited and classified into molecular subtypes using IHC staining and FISH examination. Manual lesion segmentation and analysis using IVIM, diffusion kurtosis, and stretched exponential models. DNN models for molecular subtype prediction, based on single DCE-MRI or NME-DWI datasets were constructed and compared. Results: DNN classification accuracy significantly varied among the three imaging datasets (P < 0.05), with MP-MRI outperforming DCE-MRI and NME-DWI. Impact: This study's integration of DCE-MRI and NME-DWI through DNNs for breast cancer subtype prediction advances non-invasive genotyping, potentially transforming personalized treatment strategies and improving outcomes in breast cancer patients.
Data-consistent Retrospective Motion Correction and Co-Registration
Authors: Fieseler Michael , Schramm Georg , Nuyts Johan , Schäfers Klaus , Boada Fernando
Published: November 2024

Motivation: Motion correction algorithms based on Image-based co-registration of retrospectively ordered motion states have limited effectiveness for highly accelerated scans. Goal(s): To develop a robust motion correction algorithm for highly accelerated dynamic MRI scans. Approach: We developed an approach that jointly, and data-consistently, estimates motion-corrected images and motion fields. Results: Simulated and experimental results demonstrate that the proposed approach yields improved motion-corrected images at high acceleration factors during dynamic MRI scans. Impact: The proposed approach could remove previously reported limitations on the use of retrospectively re-ordered dynamic MRI scans.
Improved Fat-Water separation with Deep Learning-based ad-hoc MRI reconstruction incorporating spatial smoothing.
Authors: M Ganeshkumar , Kandasamy Devasenathipathy , Sharma Raju , Mehndiratta Amit
Published: November 2024

Motivation: The novel Deep Learning (DL)-based Ad-Hoc Reconstruction (AHR) method for fat-water separation in Multi Echo-Magnetic Resonance Imaging (ME-MRI) has absolute generalizability. It can perform fat-water separation with the ME-MRIs from any anatomical region and views with varied numbers of echoes. Goal(s): This research investigates the fat-water separation performance of spatial smoothing incorporated DL-based AHR method in ME-MRIs with and without noise. Approach: The fat-water separation biophysical model based loss in AHR is added with spatial smoothing constraints. Results: Results demonstrate that incorporating spatial smoothing in AHR improves the fat-water separation performance in ME-MRIs without noise, however, no performance improvements in ME-MRIs containing noise. Impact: The PDFF maps obtained from fat-water separation in Multi Echo-MRI (ME-MRI) are of diagnostic and prognostic value in many diseases. This study investigates the performance of a novel Deep Learning-based Ad-Hoc Reconstruction method with spatial smoothing for fat-water separation.
Accelerated Convergent Reconstruction for MRI with High and Low Frequency
Authors: Luo Chen , Cui Zhuo-xu , Wang Huayu , Xie Taofeng , Jin Qiyu , Chen Guoqing , Liang Dong
Published: November 2024

Motivation: Theoretically, results of general unfolding network are not a convergence point of the ill-posed problem for MRI reconstruction. Goal(s): Our goal was to design an accelerated convergence unfolding network that is easier to approach the convergence point. Approach: Using accelerated gradient descent method as the framework, the proximal gradient descents of MRI high-frequency and low-frequency information are completed in a single iteration, which achieves faster convergence. Results: The reconstructed MRI of our unrolled network performs better than others. Impact: The convergence point can be effectively approximated by accelerating convergence rate, but it is still not guaranteed to be the optimal point, and further work should seek the optimal value.
End-to-end polar analysis software package for radially acquired fMRI
Authors: Haft-Javaherian Mohammad , Zafari-Ghadim Yalda , Nasiraei-Moghaddam Abbas
Published: November 2024

Motivation: Achieving full advantage of radial acquisition and reconstruction by conducting the complete analysis in the polar coordinate system. Goal(s): Implement a comprehensive end-to-end fMRI analysis software package with a graphical user interface. Approach: Radially acquired fMRI was reconstructed natively in the polar coordinate system using the Polar Fourier Transform, followed by utilizing preprocessing steps (motion correction and brain extraction) implemented in the polar coordinate system to perform statistical analysis. Results: The software package performs reconstruction, preprocessing, and statistical analyses of radially acquired fMRI data in the polar coordinate system and is validated using fMRI of 31 healthy subjects. Impact: This software package facilitates the native polar analysis of radially acquired fMRI that increases the specificity and/or improves the spatial resolution, particularly in task-based brain mapping studies with the region of interest considerably smaller than the field of view
MaRGA: a Graphical and Application Interface for the MaRCoS open-source console
Authors: Algarín José Miguel , Guallart-Naval Teresa , Borreguero José , Galve Fernando , Alonso Joseba
Published: November 2024

Motivation: MaRCoS integrates hardware, firmware, and software for MRI scanner control, focusing on system reliability but overlooking user experience. Goal(s): Develop MaRGA (MaRCoS Graphical Application), a user-friendly Graphical User Interface (GUI) for low-field MRI community, ensuring intuitive MaRCoS control and clinical environment compatibility. Approach: Designed MaRGA with simplified panels and updated API, enabling features like DICOM image export, clinical protocol management, and streamlined image reconstructions. Results: Tested MaRGA on 0.2 T and 72 mT scanners in lab and hospital settings, enhancing workflow efficiency and user satisfaction through customizable controls and improved overall experience. Impact: The introduction of MaRGA, a user-friendly Graphical User Interface (GUI) for low-field MRI scanner control, enhances user experience and workflow efficiency with MaRCoS. MaRGA significantly improves the operation of low-field MRI scanners in both laboratory and clinical settings.
Comprehensive raw data collection using a Philips Research Imaging Development Environment (PRIDE) tool
Authors: Ganji Sandeep , Gillen Joseph
Published: November 2024

Motivation: Automate collecting of MRI raw data from the Philips MR scanners. Goal(s): To create a tool that will allow users to extract selected scan data in raw format and save specific scan information for later use. Approach: Using a Philips PRIDE interface to gathers raw data and schedule a job to execute during afterhours on the Scanner Console. Results: The simple tool allows to collect complete raw data in under 3 mins at the end of the scan and associate the data with respective DICOM information for later association or annotation. Impact: Collection and storage of the complete acquisition raw data with associated DICOM information for potential use in the future using a flexible tool with a small footprint.
Image Super-Resolution Using Deep Convolutional Networks Improve the Image quality of Compressed Sensing MRI for Pancreatic DWI.
Authors: Wen Daguang , Zhang Xiaoyong , Xia Chunchao
Published: November 2024

Motivation: Image resolution achieved with compressed sensing was inferior compared to that obtained with sense technique.Current state of the art in Super-Resolution enables enhanced image resolution at a finer level of detail. Goal(s): Objective is to enhance visualization of anatomical details in high-resolution pancreatic DWI by leveraging SR. Approach: In our study, we employed integrating super-resolution convolutional neural network-compressed sensing (SR-CS) algorithm and integrating artiffcial intelligence-compressed sensing (AI-CS) algorithm for the reconstruction of pancreatic HR-DWI raw data. Results: Images with SR-CS generally exhibit superior performance compared to traditional images in terms of tumor border delineation and reduction of background noise from peritoneum and spine. Impact: Current utilization of AI is extensive, while application of SR in medical images remains rare. Utilization of SR allows for execution of MRI within a concise timeframe, while simultaneously considering the aspect of resolution.
Deep Learning-based Super-Resolution Reconstruction for Brain Diffusion-weighted MRI
Authors: Zhang Shuo , Song Qingwei , Lin Liangjie
Published: November 2024

Motivation: A deep learning-constrained algorithm has been integrated into MRI data acquisition and image reconstruction processes, encompassing compressed sensing, image denoising, and resolution upscaling techniques. Nonetheless, limited prospective studies are available that evaluate the application of this algorithm for brain diffusion-weighted imaging. Goal(s): The primary objective of this study was to compare the recently developed deep learning-constrained algorithm with conventional compressed sensing reconstruction. Approach: This study comprehensively assessed images, both qualitatively and quantitatively, employing rigorous methodologies and analytical tools. Results: The results demonstrated that the newly developed deep learning-constrained algorithm significantly enhanced image sharpness while maintaining signal-to-noise ratio, thus advantaging clinical diagnosis. Impact: Deep learning-constrained super-resolution reconstruction leads to a significant increase in image sharpness of brain DWI, which holds potential to improve clinical diagnosis of diseases, such as stroke and tumors.
Deep Learning Reconstructed Reduced Field-of-View Diffusion Weighted Imaging in Rectal Cancer: Comparison of Image Quality
Authors: Tan Yuqi , Ye Zheng , Zhang Miaoqi , Zhang Bo , Xia Chunchao , Li Zhenlin
Published: November 2024

Motivation: Reduced field-of-view DWI (rDWI) can improve the image quality (IQ) and lesion conspicuity in rectal cancer (RC) while reducing signal-to-noise ratio. Deep learning reconstruction (DLR) can denoise images. The feasibility and performance of DLR in rDWI for RC remains unclear. Goal(s): To compare the IQ and apparent diffusion coefficient (ADC) values between DLR-rDWI and noDLR-rDWI in RC. Approach: Objective and subjective IQ analysis were performed. ADC values were calculated. Results of IQ analysis and ADC between DLR-rDWI and noDLR-rDWI were compared. Results: The IQ of DLR-rDWI was better than noDLR-rDWI (except lesion conspicuity, P=0.157). ADC values was not affected by DLR. Impact: DLR-rDWI could be considered for inclusion in routine rectal MRI protocols. However, whether DLR can improve lesion conspicuity in RC should be further investigated with smaller lesions. The ability of DLR-rDWI in diagnosis and prediction for RC could be studied.
Prediction of myelin stainings using 7T MRI and deep learning
Authors: Pittayapong Sutatip , Hametner Simon , Höftberger Romana , Günther Grabner
Published: November 2024

Motivation: Histological examination of the brain provides precise analyses of brain tissue, but requires ex vivo tissue samples. In vivo MRI offers an alternative but still has limitations. Goal(s): Predict histologic images from in vivo MR images. Approach: Utilize deep learning generative models to create brain histological images from multi contrast MR images. Results: The appropriate combination of MRI contrasts can generate myelin histology images. Impact: Generating myelin histological images significantly impacts brain tissue property research by providing ex vivo information. This adaptable technique extends its applicability to various tissue properties, providing broader insights into histology and beyond.
Radiomics for Deep Brain Stimulation outcome prediction using Quantitative Susceptibility Mapping (RadDBS-QSM)
Authors: Roberts Alexandra , Zhang Jinwei , Kim Heejong , Romano Dominick , Akkus Sema , Sabuncu Mert , Li Jianqi , Kopell Brian , Spincemaille Pascal , Wang Yi
Published: November 2024

Motivation: To improve outcome prediction for deep brain stimulation (DBS) surgery using radiomic features on quantitative susceptibility maps (QSMs). Goal(s): To address the inconsistent levodopa challenge test (LCT) prediction for DBS outcomes by describing the target variable, motor symptom improvement, as a weighted sum of QSM radiomic features. Approach: A least absolute shrinkage and selection operator (LASSO) model is implemented, trained, and tested on patient data and known DBS outcomes. Results: Model predictions outperform the conventional LCT prediction and estimate DBS improvement from preoperative motor symptom scores and radiomic features on QSM. Impact: The levodopa challenge test estimates patient response to deep brain stimulation surgery, presenting undesirable side effects and inconsistent outcomes. Radiomic prediction of deep brain surgery outcomes using quantitative susceptibility maps aims to provide a numerical measure of symptom improvement.
Multi-parametric MRI for Evaluating Variations in Structure, Function, and Metabolites in Acute Kidney Injury Induced by Ischemia Reperfusion
Authors: Tao Quan , Zhang Qianqian , An Ziqi , Chen Zelong , Wu Zhigang , Deng Kan , Feng Yanqiu
Published: November 2024

Motivation: There is lack of a comprehensive MRI technique to comprehensively detect the acute kidney injury (AKI) induced by ischemia reperfusion injury (IRI). Goal(s): We aimed to develop the mpMRI for diagnosis of AKI induced by ischemia reperfusion IRI. Approach: The IRI-AKI model of 40-minutes ischemia in rats were established, and mpMRI is conducted at 0, 1, 3, 7, 14, and 28 days. Several MRI indexes signal and their diagnosis performance were compare, respectively. Results: Multi-parametric MRI may shows comprehensive variations in IRI-AKI, and amine-CEST may exhibits the highest accuracy for diagnosis of IRI-AKI. Impact: This may provide guideline for clinical application of renal mpMRI.
Evaluating Glucose Uptake in Brown Adipose Tissue by In-Vivo GlucoCEST MRI
Authors: Vo Van Nhat Minh , Nahardani Ali , Moradi Sara , Lippe Chris , Hoerr Verena
Published: November 2024

Motivation: The project assessed the glucose uptake in brown adipose tissue (BAT) without using ionizing radiation since current methods, such as PET, have safety risks. Goal(s): In a preclinical study we investigated whether chemical exchange saturation transfer MRI (CEST-MRI) could quantify the uptake of exogenous glucose in BAT. Approach: We utilized CEST-MRI to monitor and analyze the glucose uptake in 6 mice following intravenous (i.v.) and intraperitoneal (i.p.) administration of glucose. Results: GlucoCEST MRI successfully detected glucose uptake in BAT and revealed distinct glucose kinetics after i.v. and i.p. administration. Impact: GlucoCEST is a promising radiation-free technique to measure relative glucose uptake in BAT, which can be used to investigate BAT activity e.g. in metabolic diseases. Additionally, it can provide further insight into BAT function and pharmacological activation.
Lipid Biosynthesis as a Biomarker of Metformin Treatment in Renal Tumor Cells Using Stable Isotope Resolved Metabolomics and High Field NMR
Authors: Crooks Daniel , Yang Ye , Lane Andrew , Brender Jeffrey , Krishna Murali , Linehan W. Marston
Published: November 2024

Motivation: NMR-based analyses of lipids can reveal the sources and pathways contributing to lipid biosynthesis in cells grown in the presence of 13C-labeled tracers. Goal(s): Our goal was to determine whether treatment of FLCN-deficient renal cell carcinoma (RCC) cells with the Complex I inhibitor metformin modulated cellular biosynthesis of lipids. Approach: We utilized 1H-13C HSQC NMR analysis of cellular lipids in FLCN-deficient tumor cells to assess incorporation of acetyl groups derived 13C6-glucose or 13C515N2-L-glutamine into cellular lipids during treatment with metformin. Results: We observed a sharp decrease in incorporation of 13C-glucose-derived carbon into lipid acyl chains and cholesterol methyl groups following metformin treatment. Impact: We found that metformin decreased synthesis of lipids from glucose while enhancing lipid synthesis from glutamine in renal tumor cells. These findings demonstrate that targeting Complex I may be a promising therapeutic avenue for treatment and prevention of FLCN-deficient RCC.
Assessment of Hepatic Fat Content and Prediction of Myocardial Fibrosis in Athletes by using Proton Density Fat Fraction Sequence
Authors: Chen Jing , Zheng Xue , Feng Xiaolan , Liu Tao , Wang Li , Zhang Xiao-Yong
Published: November 2024

Motivation: Exploring changes in liver fat content in athletes and its role in predicting late gadolinium enhancement (LGE) of myocardiumGoal(s): To use magnetic resonance imaging-proton density fat fraction(MRI-PDFF) for the quantization of the liver fat content and prediction of LGE in athletes. Approach: Recruitment of athletes and controls for cardiac magnetic resonance(CMR) examination, analysis of liver fat content using MRI-PDFF, and application of logistic regression to construct predictive models for LGE. Results: The liver fat content and mean liver fat fraction were altered in athletes compared with controls. Hepatic fat content can effectively predict LGE after excessive exercise. Impact: The study advanced sports cardiology by identifying hepatic fat content as emerging indicators for predicting LGE in athletes, enhancing training strategies and early detection of myocardial fibrosis.
3D Hepatic MR Elastography at 0.55T
Authors: Darwish Omar , Jeljeli Sami , Di Cio Pierluigi , Kinsella Shawna , Sinkus Ralph , Neji Radhouene
Published: November 2024

Motivation: Expanding hepatic 3D MRE to wide-bore low field MR systems (B0 ≤ 1.0T) can serve as a means of accommodating liver patients with high BMI and/or claustrophobia such as metabolic dysfunction-associated fatty liver disease (MAFLD) patients. Goal(s): Demonstrate the feasibility of 3D MRE at 0.55T in healthy volunteers. Approach: 5 healthy volunteers were scanned at 60Hz mechanical excitation with a Hadamard-encoded 3D MRE sequence at 0.55T and were also scanned with a reference 3D MRE sequence at 3T for comparison. Results: Bland-Altman analysis demonstrated good agreement between the biomechanical parameters retrieved at 0.55T and 3T. Impact: We demonstrated the feasibility of hepatic 3D MRE at 0.55T in healthy volunteers, which paves the pathway for an MRE clinical study in MAFLD patients to evaluate clinical added value.
Evaluating the diagnostic performance of Dixon and MRS based proton density fat fraction (PDFF) in hepatic steatosis
Authors: Cao Ruiyu , Ban Xilei , Li Hongwei , Sun Aiqi , Wu Peng , Xia Mingfeng , Bian Hua , Li Hao , Wang He
Published: November 2024

Motivation: Steatosis is the histopathologic hallmark of NAFLD. Liver histology is currently the standard for hepatic steatosis diagnosis, which is invasive. Several MRI methods have been validated to accurately measure hepatic fat content. Goal(s): To evaluate diagnostic performance of different hepatic fat quantification methods. Approach: We compared hepatic fat content calculated by Dixon MRI and MRS with histology results as reference. Results: The outcomes show that the fat fraction measured by these two methods highly correlated with steatosis degrades measured by histology. Compared with MRS, fat fraction calculated by Dixon MRI performed better diagnostic capacity in hepatic steatosis. Impact: Our study demonstrates that the Dixon-based method outperforms the MRS. The use of whole liver automatic segmentation improves diagnostic efficiency, and its performance is comparable to the ROI-based method, making it a promising hepatic fat fraction detection approach in clinic.
A study on brown adipose tissue using histogram features from fat fraction maps in modify Dixon technique
Authors: Ma Lili , Huang Gang , Ai Kai , Du Yunxia , He Yuqi , Xu Wenxiang
Published: November 2024

Motivation: The recent discovery of brown adipose tissue (BAT) in adults presents new approaches for treating metabolic disorders. Goal(s): Noninvasive methods for distinguishing between BAT and white adipose tissue (WAT) are still under the exploration. Approach: In this study, histogram features of human BAT and WAT were extracted using fat fraction (FF) maps that generated from the modified Dixon (mDIXON) technique. The features were subsequently analyzed and differentiated between the two types of adipose tissue. Results: The results indicated that 16 out of 18 extracted features were statistically significant. Furthermore, in the reproducibility study, four features exhibited strong reproducibility. Impact: This study demonstrated the feasibility of differentiating BAT and WAT by using noninvasive MRI approach. The mDIXON technique allows for BAT's quantification, providing a convenient way for researching BAT's correlation with certain metabolic disorders.
New Dual-Element 13C/1H Endorectal Coil for Improving mpMR-TRUS Guided Fusion Prostate Biopsies With Hyperpolarized C-13 Molecular Imaging
Authors: Gebrezgiabhier Daniel , Carvajal Lucas , Chen Hsin-Yu , Kim Yaewon , Bok Robert , Cooperberg Matthew , Nguyen Hao , Shinohara Katsuto , Okamoto Kimberly , Frost Mary , Wang Zhen , Ohliger Michael , Gordon Jeremy , Larson Peder , Aggarwal Rahul , Vigneron Daniel
Published: November 2024

Motivation: To address the issues with the original dual-element 13C/1H endorectal coil (ERC). Goal(s): We designed and fabricated a novel dual-element 13C/1H ERC, validated with bench testing and then evaluated in 3T MRI studies. Approach: Phantoms were imaged using the new ERC and the original ERC. Acquired data was then analyzed and respective SNR compared. Results: The new ERC demonstrated substantially improved 13C and 1H MRI sensitivity on bench electronic testing. In addition, the new ERC demonstrated substantial improvement in signal-to-noise ratio, and since the coil has successfully been used in hyperpolarized 13C-pyruvate, co-polarized 13C-urea+pyruvate multiparametric MRI patient studies for guiding prostate cancer biopsy. Impact: Hyperpolarized 13C MRI, RF Coils, Metabolic imaging, Molecular imaging, Endorectal coil
Low field (60mT) MRI using flexible coil for prostate imaging
Authors: Song Jae Eun , Sharkey Jeremy , Shokrekhodaei Maryamsadat , Sadinski Meredith , De Matos Gomes Muller , King Scott B. , Nacev Aleksandar
Published: November 2024

Motivation: The low field (60mT) MRI system offers advantages such as affordability and portability. Goal(s): To develop flexible coils for low field (60mT) MRI to improve image quality. Approach: Designing a multi-channel receive coil using flexible body coil technology, allowing improved workflow, close proximity to the patient's body and improved SNR. Results: The flexible coil demonstrated higher SNR in phantom experiment, enhancing image quality and enabling visualization of previously undetected areas in in-vivo experiment. Impact: The advancements in flexible coils have the potential to improve image guided procedures, facilitating accurate targeted biopsies and ultimately improving patient outcomes.
Longitudinal 129Xe MRI Gas-exchange and Exercise Intolerance in Long-COVID
Authors: AlArab Natally , McIntosh Marrissa , Hahn Andrew , Feeley Nicholas , Staab Keegan , Percy Jonathan , Wharff Conner , Sieren Jessica , Comellas Alejandro , Hoffman Eric , Fain Sean
Published: November 2024

Motivation: Long-COVID symptoms are experienced by 10-20% of COVID-19 patients. 129Xe MRI ventilation and gas-exchange measurements may provide insights into long-COVID-19 patients' recovery. Goal(s): Use 129Xe MRI to monitor longitudinal recovery (>1 year following infection) of long-COVID patients. Approach: Thirteen long-COVID participants were evaluated longitudinally using pulmonary function tests, six-minute walk distance (6MWD), quality-of-life, and 129Xe MRI imaging measurements. Results: Improvements in FEV1 and FVC%pred, dyspnea following exercise, and clinically significant improvements in 6MWD were observed. No significant differences in imaging measurements were observed between visits or between COVID and control groups. Dyspnea and MRI gas-exchange were correlated. Impact: 129Xe MRI measurements in long-COVID participants suggest persistent gas-exchange abnormalities and exercise intolerance, offering valuable insights for future management and rehabilitation of these patients.
The diagnostic potential of magnetic resonance fluoroscopy in patients with achalasia
Authors: Wu Chao , Zhao Wei , Zhang Chen , Sun Haoran
Published: November 2024

Motivation: A non-invasive imaging method, such as MR fluoroscopy, was used for treating achalasia patients. Goal(s): To determine whether MR fluoroscopy can diagnose patients with achalasia. Approach: We included 39 achalasia patients and 39 healthy volunteers. MR fluoroscopy was performed to observe the structure of the gastroesophageal junction. Results: We measured his angle, the esophageal width, the width of esophageal hiatus, the sphincter length, the angle between the lower esophagus and the longitudinal axis, and the angle between the lower esophageal sphincter and horizontal axis. The parameters of the patient group were statistically and significantly different from those of control group. Impact: MR fluoroscopy can be effectively used in the clinical diagnosis of cardiac achalasia. The MR imaging method is a non-radiological tool and is used to evaluate anatomical structures.
Determining the Reproducibility and Reliability of 2D- and 4D flow MRI Mitral Valve Regurgitation Quantification Methods
Authors: Safarkhanlo Yasaman , Berto Martina Boscolo , Spano Giancarlo , Schütze Jonathan , Stark Anselm , Bastiaansen Jessica , Gräni Christoph
Published: November 2024

Motivation: Mitral valve regurgitation (MVR) quantification is crucial for diagnosis and treatment of patients with mitral valve disease. While different MRI based MVR quantification methods exist, their correlation with one another and their reproducibility and reliability remains unknown. Goal(s): To determine the reproducibility and reliability of four different 2D- and 4D flow MVR volume quantification methods based on CMR. Approach: The intermethod, inter- and intra-reader agreements between four different methods, 4D-flowAIM, 2D-PCstandard, 2D-PCMV, Volumetric, were compared for patients with severe secondary MVR. Results: Among all techniques, 2D-PCstandard and Volumetric methods were the most reliable ones (ICC>0.99, P-value<0.001). Impact: 2D-PCstandard and Volumetric methods quantify the MVR volume most consistently and further research with diverse MVR types and larger cohorts is needed to establish reliable conclusions for 2D-PCMV and 4D-flowAIM methods.
An evaluation of hemodynamic parameters before and after Ross procedure for Unicuspid Aortic Valve (UAV) using 4D flow MRI
Authors: Zbihley Andrew , Maroun Anthony , Baraboo Justin , Johnson Ethan , Mehta Christopher , Allen Bradley , Markl Michael
Published: November 2024

Motivation: Unicuspid Aortic Valve (UAV) is an important subset of Bicuspid Aortic Valve. We identified a need to include wall shear stress in a larger pre- and post-operative cohort of UAV patients. Goal(s): Our goal was to evaluate the effects of the Ross procedure for UAV patients, specifically evaluating hemodynamic parameters, peak systolic velocity and wall shear stress (WSS), in the ascending aorta (AAo). Approach: We retrospectively examined these hemodynamic parameters in thirteen patients before and after UAV replacement. Results: We found that both peak systolic velocity and WSS in the AAo decreased significantly post-operatively, indicating successful restoration of aortic 3D blood flow dynamics. Impact: Unicuspid Aortic Valve (UAV) is a rare yet important subset of Bicuspid Aortic Valve (BAV). Here, we analyze the hemodynamics of a larger pre- and post-operative UAV cohort with the inclusion of wall shear stress (WSS).
Accelerated Phase Contrast MRI with Use of K-Space Restoration and Resolution Enhancement Generative Adversarial Neural Network
Authors: Morales Manuel , Street Jordan , Rodriguez Jennifer , Johnson Scott , Pierce Patrick , Manning Warren , Nezafat Reza
Published: November 2024

Motivation: Phase-contrast (PC) MRI evaluates blood flow in cardiovascular disease. However, the prolonged scan times limit its efficiency. Goal(s): We sought to develop a highly accelerated PC technique based on omitting high-frequency k-space regions along the phase encoding direction. Approach: A deep learning k-space restoration and enhancement strategy for training (KREST) was developed to improve resolution while maintaining phase information. KREST was trained and tested with PC images from 1600 patients. Results: In a prospective study of 16 patients, KREST reduced breath-hold time relative to parallel imaging (19 vs 6 s). Impact: Our k-space restoration and enhancement strategy enables resolution-enhancement while providing k-space data consistency. Deep learning accelerated phase-contrast imaging showed similarly accurate quantification of peak mean velocity to a standardized parallel imaging method.
Dynamic 2D phase-contrast of the tricuspid valvular flow with automated valve-tracking: patient case studies
Authors: Peters Dana , Lamy Jerome , Xiang Jie , Huber Steffen , Steele Jeremy
Published: November 2024

Motivation: MRI is not capable of measuring tricuspid regurgitant jets, required for diastolic function evaluation. Goal(s): Using a dynamic slice plane which tracked the tricuspid valve, we studied patients with suspected tricuspid regurgitation. Approach: The valve-tracking phase-contrast sequence used deep learning to automatically prescribe a phase-dependent slice plane. Results: Tricuspid regurgitation was measured and tricuspid regurgitant jets could be visualized in patients. Impact: A new automated 2D valve-tracking phase-contrast approach permits visualization of tricuspid regurgitant jets. This will enable evaluation of diastolic function by MRI.
Rotational flow as a marker of left ventricular function between youth and adult T2D subjects
Authors: Park Sungho , Fujiwara Takashi , Enge Danny , Bjornstad Petter , Reusch Jane , Barker Alex
Published: November 2024

Motivation: Rotational flow within the aorta has been associated with cardiovascular disease and ventricular-vascular coupling, but no study has investigated its direct correlation with LV function. Goal(s): This study aims to explore whether the assessment of rotational flow can effectively identify left ventricle dysfunction between youth and adult type 2 diabetes (T2D) subjects. Approach: Correlation between global function and strain changes by CMR and rotational flow indices and pulse wave velocity by 4D flow MRI were evaluated. Results: Adult T2D had significant decrease in vorticity indices with CMR biomarkers, while showing less significance in CMR biomarkers compared to youth T2D. Impact: Vorticity indices are potential biomarkers to assess LV dysfunction and understand ventricular-vascular coupling even in the absence of geometric anomalies within the aorta. A comprehensive examination of rotational flow and LV function is required.