bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating scout and guidance line-based retrospective motion correction into a 3D deep learning reconstruction for fast and robust brain MRI
Authors: Polak Daniel , Nickel Marcel Dominik , Splitthoff Daniel Nicolas , Deck Jeanette , Clifford Bryan , Huang Yantu , Lo Wei-Ching , Huang Susie Y. , Conklin John , Wald Lawrence L. , Cauley Stephen F.
Published: November 2024

Motivation: Rising medical imaging utilization and increasing use of automated support systems demand high-quality, fast, and reproducible/robust MRI techniques. Despite rapid scanning afforded by deep learning, motion remains a common source of artifacts. Goal(s): Integrate retrospective motion correction into a deep learning reconstruction to facilitate high-quality, fast, and motion-robust brain imaging. Approach: Scout and guidance line-based motion correction was implemented into MPRAGE, SPACE and SWI to enable rapid motion trajectory estimation. A data-consistency driven neural network reconstruction was adapted to perform network regularized motion correction. Results: Improved SNR and reduced motion artifacts are demonstrated in vivo using 4-6-fold accelerated scans with instructed subject motion. Impact: Retrospective motion correction was integrated into a deep learning reconstruction to facilitate fast and motion-robust 3D brain imaging across T1, T2, T2 FLAIR and T2*/SWI. This should add clinical value to routine brain exams and emerging neuro-degenerative screening protocols (ARIA).
Contrast-Optimized Basis Functions for Self-Navigated Motion Correction in 3D quantitative MRI
Authors: Flassbeck Sebastian , Marchetto Elisa , Mao Andrew , Assländer Jakob
Published: November 2024

Motivation: Motion-induced artifacts are a significant barrier to achieving clinically acceptable image quality for multi-compartment quantitative MRI techniques, e.g. a 2-pool magnetization transfer model. Goal(s): To develop a self-navigating approach to estimating motion parameters in an MR-fingerprinting-like acquisition. Approach: We optimize a subspace that maximizes the contrast-to-noise ratio between brain parenchyma and cerebrospinal fluid for a low-resolution, time-segmented low-rank reconstruction used to estimate motion. Results: Compared to the typical SVD basis, the contrast-optimized basis improves the smoothness of the motion estimates and the apparent resolution of the reconstructed coefficient images and quantitative maps. Impact: The proposed retrospective, self-navigating motion correction technique does not require any sequence modifications and/or additional scan time. It can therefore be applied to many quantitative MRI techniques where the signal's variation over time can be well-described in a low-rank subspace.
Spiral T1w-Dixon-VIBE for high resolution abdominal imaging at 0.55T
Authors: Tasdelen Bilal , Lee Nam , Cui Sophia , Nayak Krishna
Published: November 2024

Motivation: Breath-held abdominal fat-suppressed imaging is challenging at mid- and low-field strengths (<1.5T). Fat saturation often fails due to the short T1 of lipid; and Cartesian Dixon imaging provides poor spatial resolution due to the need for long ∆TE, due to the smaller ∆f between water and lipid. Goal(s): Breath-held fat-suppressed high-resolution volumetric abdominal imaging with T1 contrast. Approach: Stack-of-Spirals Dixon imaging, with estimation and compensation for phase due to concomitant fields Results: We demonstrate that spiral Dixon imaging at 0.55T makes excellent use of the required ∆TE, improving SNR efficiency and spatial resolution (1.7x1.7x5.0mm3) compared Cartesian Dixon (3.5x3.5x5.0mm3), within a 17-second breath-hold. Impact: We demonstrate that spiral Dixon single breath-hold volumetric imaging is an attractive alternative to existing Cartesian-based methods for volumetric single breath-hold fat-suppressed imaging at 0.55T, as it simultaneously provides high-resolution and excellent fat-suppression.
Free-Breathing Stack-of-Stars Look-Locker T1-mapping with Whole Liver Coverage
Authors: Goerke Ute , Shih Shu-Fu , Ahanonu Eze , Wu Holden , Deshpande Vibhas , Bilgin Ali , Majeed Waqas , Altbach Maria
Published: November 2024

Motivation: Many patients cannot hold their breath as required on standard protocols for abdominal imagingGoal(s): We develop a new new free-breathing Look-Locker T1-mapping method with whole liver coverage. Approach: The new free-breathing Look-Locker T1-mapping method employs a pilot tone signal for detecting the respiratory state. This signal is used to reconstruct motion-corrected T1-weighted images, which are used to calculate T1-maps. Results: Robust T1-maps are obtained covering the whole liver obtained from 6 min free-breathing scan. Impact: A new free-breathing Look-Locker T1-mapping method with whole liver coverage has been developed for patients who are not able to hold their breath as required in standard protocols.
Clinical Value of 4D Flow MRI in Assessing High-Risk Esophagogastric Varices: A Prospective Study
Authors: Zhang Qian , Wu Mingfeng , Zhu Yi , Jiang Ke , Wang Rongpin
Published: November 2024

Motivation: The pursuit of less invasive diagnostic methods to gauge portal hypertension and the associated risk of variceal bleeding in cirrhosis patients. Goal(s): To determine the effectiveness of hemodynamic parameters derived from 4D flow MRI for the non-invasive assessment of portal hypertension and to stratify the risk of variceal bleeding in patients with cirrhosis. Approach: Utilizing hemodynamic parameters from 4D flow MRI to profile portal circulation. Results: Results showed significant differences in FFC and maximum splenic blood flow between low-risk and high-risk patients. Moreover, the combination of FFC and maximum splenic blood yielded high diagnostic accuracy. Impact: Demonstrating the utility of 4D flow MRI in evaluating portal hypertension and variceal bleeding risk.
Quantitative Assessment of Geometric Distortions in MRI-Linac Sequences for Enhanced Radiotherapy Planning
Authors: Kaffey Zaphanlene , Mulder Sam , McDonald Brigid , Wahid Kareem , Attia Serageldin , O'Connell Nicole , Thill Dan , Dresner Alex , Christodouleas John , Naser Mohammed , Fuller Clifton , McDonald Brigid
Published: November 2024

Motivation: Geometric distortion in MRI-Linac sequences remains insufficiently characterized, impacting the precision of radiotherapy treatment planning. This study aims to quantify such distortions in EPI, TSE, and SPLICE sequences. Goal(s): The goal of this study is to quantitatively assess and compare geometric distortion across three common MRI-Linac sequences using deformable image registration and DICE score analysis. Approach: An in vivo study employed patient T2 and DWI B0 scans. Deformable image registration was conducted using ADMIRE and Elekta-based software, generating deformation vector fields. A Python algorithm calculated RMS values. Results: The sequences exhibited distinct DSC scores and RMS distortions, revealing registration effectiveness and sequence-dependent variability. Impact: These findings set the stage for future research on minimizing distortions in MRI-Linac sequences. The developed Python algorithm could be adapted for real-time monitoring, advancing the precision and safety of MRI-guided radiotherapy.
Local SAR comparison of leg positioning in 16-channel proton/sodium dipole/loop array for 7T MRI
Authors: Wu Menglu , Winfield Jessica , Lally Pete , Ipek Ozlem
Published: November 2024

Motivation: Sodium(23Na)/proton(1H) MRI of the extremities have great potential in diagnosis and treatment of musculoskeletal conditions and oncology applications (e.g.soft-tissue sarcomas). Goal(s): Assessing the performance of a novel 16-channel 1H/23Na MRI coil across varied leg positions and establish safe RF power limits for clinical applications. Approach: Electromagnetic simulations to analyse coil performance in four leg positions. SAR10g levels were compared across configurations while maintaining B1+ field efficacy. Results: The coil showed consistent B1+ performance across all tested positions. The highest SAR levels occurred with calf-to-coil contact, aligning with predictions. Safe RF power limits were established, supporting the coil's clinical potential for extremity imagingImpact: This study validates an innovative 16-channel 1H/23Na coil, setting benchmarks for safe RF power limits, and enhancing disease characterisation, enabling clinical research in musculoskeletal pathologies and soft-tissue sarcoma in the extremities.
SAR safety procedure for self-built pTx human head RF array coils at 9.4T
Authors: Glang Felix , Bosch Dario , Solomakha Georgiy , Bause Jonas , Avdievich Nikolai , Scheffler Klaus
Published: November 2024

Motivation: Ensuring subject safety, in particular to limit tissue heating, is a critical aspect of self-developed pTx RF array coils for UHF applications. Goal(s): Establishing a dependable workflow for accurate simulation, data processing and realization of online supervision of power deposition. Approach: The workflow relies on cross-comparisons of EM simulation results and intermediate processing steps based on representative excitation modes, and on comparison of measured and simulated field maps. Results: Consistency was achieved in all cross-comparison steps. Residual discrepancies between measured and simulated B1+ maps require further investigation, but their safety implications can be addressed by an appropriate safety factor. Impact: A reliable workflow for EM simulation, subsequent data processing, and realization of online SAR monitoring for home-built RF human head array coils at 9.4T is presented. This is an essential building block to ensure subject safety in experimental UHF studies.
Opening new horizons with the first human brain in vivo experiments at 11.7T
Authors: Mauconduit Franck , Gras Vincent , Amadon Alexis , Massire Aurelien , LeSter Caroline , Le Bihan Denis , Luong Michel , Bottlaender Michel , Vignaud Alexandre , Boulant Nicolas
Published: November 2024

Motivation: Ultra-high magnetic field MRI offers new opportunities due to its higher SNR and CNR. Goal(s): After receiving the authorization for scanning 20 adult healthy volunteers on the whole-body Iseult MRI scanner, we performed a preliminary MRI investigation to acquire the first brain images at 11.7T. Approach: Using a homemade multi-transmit multi-receive head coil and parallel transmission, 3D anatomical images were acquired with multiple sequences and tissue contrasts at high resolution. Results: In this study, high quality whole brain images acquired at 11.7T on the Iseult MRI scanner are presented for the first time to the MR community. Impact: Showing for the first time in vivo brain images acquired at 11.7T on the whole-body Iseult MRI scanner, this study reveals first potential and challenges of such systems to the ultra-high field MR community.
Unbiased Neural Networks for Quantitative MRI Parameter Estimation
Authors: Mao Andrew , Flassbeck Sebastian , Assländer Jakob
Published: November 2024

Motivation: Neural-network (NN)-based estimators trained with the mean-squared error criterion have a non-negligible bias which impedes inter-method comparability and the clinical adoption of quantitative MRI methods. Goal(s): To develop fast, accurate, precise, and reproducible quantitative MRI estimators that are reliable in the face of pathology. Approach: We explicitly penalize the bias of the NN's estimates during training and study the resulting NN's bias and variance properties for a magnetization transfer model. Results: The proposed method reduces the NN's variable bias throughout parameter space, achieves a variance close to the theoretical minimum, and shows excellent concordance with parameter maps estimated using non-linear least-squares in vivo. Impact: NNs trained with the proposed strategy are approximately minimum variance unbiased estimators and are therefore well-suited for the development, validation, and translation of new quantitative biomarkers, particularly for multi-compartment biophysical models such as magnetization transfer or diffusion in white matter.
Towards a Standard Model of Diffusion in White Matter with Phase and Relaxation – A Monte-Carlo Study
Authors: Sandgaard Anders , Kiselev Valerij , Shemesh Noam , Jespersen Sune
Published: November 2024

Motivation: Improving parameter estimation for the standard model of diffusion in white matter (SM) by modelling the subsequent decay of the spin-echo of the dMRI signal. Goal(s): To numerically validate SMPR - an extension of SM incorporating orientation-dependent, susceptibility related relaxation rates and Larmor frequency shifts of the spin echo decay of the dMRI signal. Approach: To perform Monte-Carlo (MC) simulations in orientationally dispersed, non-exchanging bundles of hollow magnetized cylinders, simulate a standard PGSE signal and its spin echo decay, and compare against the SMPR model. Results: SMPR is in agreement with the MC simulations in both phase and signal magnitude. Impact: Orientation-dependent susceptibility effects may improve parameter estimation of the Standard Model of diffusion in white matter and enable rotation-free mapping of susceptibility-related parameters.
Biventricular Myocardial Kinetic Energy Distribution in Patients With Repaired Tetralogy of Fallot
Authors: Hsu Shih-En , Wu Ming-Ting , Weng Ken-Pen , Peng Hsu-Hsia
Published: November 2024

Motivation: Patients with repaired Tetralogy of Fallot (rTOF) have varied cardiac structures, yet there's a current lack of analysis on their cardiac kinetic energy. Goal(s): We aim to assess myocardial kinetic energy (KE) differences between patients and normal groups. Approach: We utilized tissue phase mapping images combined with MATLAB programs to calculate myocardial kinetic energy. Results: The results revealed differences in myocardial kinetic energy values between patients and normal groups. Besides, significant variations were observed in the proportional values across three directions, along with notable differences in the KE systolic-to-diastolic ratio of the right ventricle. Impact: Differential myocardial kinetic energy serves as a novel indicator for evaluating cardiac function in rTOF patients. It aids in early detection of cardiac abnormalities, potentially identifying the optimal timing for pulmonary valve replacement surgery.
In vivo STEAM and motion compensated spin echo diffusion tensor CMR in multiple cardiac phases: The effect of field strength
Authors: Scott Andrew , Wen Ke , Luo Yaqing , Huang Jiahao , Gover Simon , Soundarajan Rajkumar , Ferreira Pedro , Pennell Dudley , Nielles-Vallespin Sonia
Published: November 2024

Motivation: Diffusion tensor cardiovascular magnetic resonance (DT-CMR) studies described in the literature have almost uniquely been performed at 3T while 1.5T scanners are more widely available. Goal(s): To compare the performance and microstructural parameters available from stimulated echo (STEAM) and motion compensated spin echo (MCSE) DT-CMR sequences at 1.5T and 3T. Approach: DT-CMR was performed in 20 healthy volunteers using both sequences at both field strengths at peak systole and end diastole. Results: MCSE and STEAM sequences are effective at both 1.5T and 3T. STEAM benefits from the increased SNR available at 3T. Impact: DT-CMR studies should consider making use of 1.5T hardware where access to 3T scanners is more difficult particularly where MCSE sequences are to be used with systolic triggering.
Memory-efficient and robust model-based deep learning using non-montone monotone operator learning (MnM-MOL)
Authors: John Maneesh , Chand Jyothi Rikhab , Jacob Mathews
Published: November 2024

Motivation: The high memory demand of model-based deep learning algorithms restricts their application in large-scale (eg., 3D/4D) applications. Moreover, their robustness to input perturbations is not well-studied. Goal(s): To realize a memory efficient MoDL framework with similar theoretical guarantees as compressed sensing methods, while offering state-of-the-art performance. Approach: We introduce a memory-efficient deep equilibrium framework with theoretical guarantees on uniqueness, convergence, and robustness. Results: The proposed scheme offers comparable performance to state of the art methods, while being 10 times more memory-efficient. Additionally, the proposed scheme is significantly more robust to Gaussian and adversarial input perturbations. Impact: The proposed approach results in greater than 10x reduction in memory demand, which enables the application of MoDL algorithms in large-scale (3D/4D) applications. The theoretically guaranteed robustness of the proposed algorithm reduces the error amplification in highly under-sampled settings.
A framework for abnormality detection in developing white matter in utero, applied to fetuses with Congenital Heart Disease
Authors: Wilson Sian , Cromb Daniel , Karolis Vyacheslav , Christiaens Daan , Uus Alena , Macleod Russell , Price Anthony , Hajnal Joseph , Edwards A. , O'Muircheartaigh Jonathan , Tournier Jacques-Donald , Counsell Serena
Published: November 2024

Motivation: In utero neurodevelopment is complex and not well understood, particularly in fetuses with Congenital Heart Disease. Goal(s): Normatively model microstructural maturation in transient fetal compartmentsApproach: Diffusion MRI was acquired in a healthy control cohort of 235 fetuses (22–37 weeks gestation). White matter bundles were estimated and divided into cross-sections. Gaussian Process Regression models were fit to diffusion metrics in each cross-section, and Z-scores calculated along the tract for 26 fetuses with CHD. Results: We observe gradients of change, highlighting abnormal regions along the white matter unique to each subject. We did not find consistent patterns or associations with a specific diagnosis. Impact: We establish normative trajectories in diffusion MR signal at the level of individual fetal brain compartments that reflect developing microstructure, improving understanding of dynamic fetal brain development and allowing us to predict deviations from the norm.
Simultaneous Water-Specific T1 and Fat Fraction Mapping of the Liver using Look-Locker Dixon MRI
Authors: Greer Joshua , Manhard Mary-Kate , Lanier Matt , Dillman Jonathan , Pednekar Amol
Published: November 2024

Motivation: Hepatic tissue architecture and water-fat content change concurrently with liver disease progression. Simultaneous measurement of water-specific T1 (T1-W) and proton density fat fraction (PDFF) can serve as a quantitative metric for assessment of liver disease. Goal(s): To develop and validate a Look-Locker multi-echo Dixon (LLmDIXON) technique to simultaneously measure T1-W and PDFF in a single breath-hold. Approach: Simultaneous T1-W and PDFF measurements were obtained using LLmDIXON and reference sequences in a phantom (0-40 % PDFF) and four volunteers (4.0-18.2% PDFF). Results: The LLmDixon-based T1-W and PDFF values agreed with simulations and reference sequences in a phantom, and provided comparable PDFF values in volunteers. Impact: LLmDixon provides simultaneous measurement of water-specific T1 and PDFF in a single 15s breath hold. This technique has the potential to characterize liver disease, where both cellular architecture and fat content can concurrently change as disease progresses.
R2* Mapping of Extreme Hepatic Iron Overload Using Free-Breathing UTE Sequence
Authors: Peng Fei , Luo Chaotian , Cui Wei , Tang Cheng , Peng Peng
Published: November 2024

Motivation: Existing liver iron quantification methods are inadequate for extreme iron deposition, hindering effective guidance for iron chelation therapy. Goal(s): Evaluate the practicality of a free-breathing, single-echo UTE sequence with varying echo times for multiple acquisitions in assessing severe hepatic iron overload. Approach: A 3.0T UTE sequence with rigid-based motion correction was used to assess hepatic R2* in nine thalassemia patients, and compared with LIC from Ferriscan and R2* from a 1.5T GRE sequence. Results: UTE-R2* correlated well with GRE-R2* and Ferriscan-LIC, and could differ hepatic iron content in patients whose Ferriscan-LIC or GRE-R2* reach to upper limit. Impact: An imaging strategy utilizing a free-breathing, single-echo UTE sequence with variable echo times for multiple acquisitions, combined with rigid-based motion correction, could be employed to evaluate extreme hepatic iron deposition.
Application of Intratumoral and Peritumoral Multimodal MRI in Predicting HER-2 Expression in Breast Cancer
Authors: Feng Wen , Lei Junqiang , Xiong Yuhui , Ji Kun , Dang Wencheng , Li Jianlin , Gao Yuling
Published: November 2024

Motivation: Human epidermal growth factor receptor-2(HER-2) was a proto-oncogene, and its overexpression was closely associated with the development and prognosis of breast cancer. Goal(s): To investigate predictive value of intratumoral and peritumoral multimodal magnetic resonance imaging (MRI) before surgery for the expression level of HER-2 in breast cancer. Approach: The parameters, including apparent diffusion coefficient (ADC), tissue-diffusivity (Dt), pseudo-diffusivity (Dp), perfusion fraction(f), relaxation rate(R2*), fat-fraction (FF), the relaxation value longitudinal relaxation time(T1), transverse relaxation time(T2) and proton density(PD) were used to predict the expression level of HER-2 in breast cancer. Results: MUSE-Dt-peritumoral predicted HER-2 with the highest AUC(0.724, P=0.017). Impact: There were few studies involving intratumoral and peritumoral multimodal MRI to predict HER-2 in breast cancer. The result was that peritumoral parameters had a momentous part in predictive performance beyond expectation, especially non-invasive techniques which were easy to implement clinically.
Explaining MRI radiomics-based detection of prostate cancer using clinical concepts
Authors: Segre Rebecca , Nketiah Gabriel , Nael Axel , Sunoqrot Mohammed , Bathen Tone , Elschot Mattijs
Published: November 2024

Motivation: Clinical use of computer-aided diagnosis systems for prostate cancer is currently hindered by their internal complexity. Explainability tools can give insight into the functioning of these machine learning (ML) models. Goal(s): Our goal was to supplement the predictions of an MRI radiomics-based ML model for prostate cancer detection with explanations based on clinical concepts currently used in radiological assessment. Approach: We clustered correlating MRI radiomics features into groups representing clinical concepts underlying the PI-RADS system. We used SHAP analysis to explain the importance of these concepts in each predicted lesion. Results: Explainability based on clinical concepts gives insight into ML model predictions. Impact: Our machine learning pipeline combines accurate prostate cancer detection on MRI with intrinsic explainability, potentially resulting in an easier integration into clinical use.
Accelerating Low-Field Prostate DWI: Self-Supervised Denoising for Rapid Scan Acquisition
Authors: Pfaff Laura , Darwish Omar , Eichner Cornelius , Wagner Fabian , Thies Mareike , Vysotskaya Nastassia , Weiland Elisabeth , Benkert Thomas , Nickel Marcel Dominik , Wuerfl Tobias , Maier Andreas
Published: November 2024

Motivation: Diffusion-weighted imaging (DWI) is crucial for lesion detection but suffers from inherently low signal-to-noise ratio (SNR), especially in low-field settings. Goal(s): The goal of this work is to accelerate low-field prostate DWI, reducing the number of image repetitions and scan time while maintaining image quality. Approach: We present a self-supervised denoising method employing Stein's unbiased risk estimator (SURE) and a physics-based noise model and evaluate the denoising results without relying on ground-truth data. Results: Our method excels in preserving image content, outperforming other denoising techniques. This allows a substantial reduction in scan time, making it a promising advancement in low-field DWI. Impact: Our proposed denoising approach accelerates low-field prostate DWI via self-supervised denoising, improving scan efficiency without compromising image quality. We further demonstrate how to employ a physics-based noise model to evaluate denoising performance in the absence of noise-free ground-truth data.
Longitudinal Assessment of Denervated Muscles in Parsonage-Turner Syndrome with Quantitative MRI
Authors: Campbell Gracyn , Li Tim , Lan Ranqing , Tan Ek , Sneag Darryl
Published: November 2024

Motivation: Parsonage-Turner syndrome (PTS) is a spontaneous peripheral neuropathy affecting upper extremity nerves and leading to severe muscle denervation. Quantitative MRI (qMRI) can objectively evaluate the degree of denervation and muscle recovery from PTS over time. Goal(s): To characterize PTS-related muscle denervation using qMRI biomarkers and to assess longitudinal changes. Approach: In 21 PTS subjects at up to four timepoints, the associations of T2, apartment fiber diameter (AFD), fat fraction (FF), and muscle volume with electromyography and muscle function were analyzed. Results: Associations between qMRI biomarkers reflect severity of muscle denervation in PTS. Recovery, involving reduced edema and increased atrophy, may follow non-linear patterns. Impact: Quantitative MRI biomarkers including T2 mapping, apparent fiber diameter, fat fraction, and muscle volumetry correlate with electrodiagnostic and functional assessments of denervation and muscle function impairment in Parsonage-Turner syndrome (PTS), and they can longitudinally characterize PTS-related changes.
Towards Integrating 3D Fetal Brain Slice-to-Volume Reconstruction in a 0.55T Scanner Environment with Gadgetron
Authors: Silva Sara Neves , Uus Alena , Verdera Jordina Aviles , Payette Kelly , Hall Megan , Colford Kathleen , McElroy Sarah , Tomi-Tricot Raphael , Deprez Maria , Hajnal Joseph , Rutherford Mary , Story Lisa , Hutter Jana
Published: November 2024

Motivation: Fetal MRI is an important tool for antenatal diagnosis, allowing to assess appropriate growth with T2-weighted TSE sequences. Involuntary fetal motion is frozen in-plane with single-shot sequences, but 3D inconsistencies remain and are currently mostly addressed with offline slice-to-volume reconstruction. Goal(s): The goal of this work is to integrate slice-to-volume reconstruction into a clinical fetal low-field scan. Approach: A Gadgetron-based real-time pipeline including quality control, decision support, 3D reconstruction and transfer back to the scanner was implemented. Results: The steps of the pipeline were successfully tested in-vivo in low-field fetal MRI. Impact: The complete integration of Slice-to-Volume reconstruction into the normal clinical workflow and the resulting availability of high resolution 3D volumes during the scan overcomes challenges and current barriers of fetal MRI.
Improved parallel imaging with N-periodic spatial banding patterns in bSSFP
Authors: Huo Zimu , Garcia-Foncillas Lorena , Balaji Krithika , Mendoza Michael , Bangerter Neal , Lally Peter
Published: November 2024

Motivation: This research explores the potential for temporally varying N-periodic bSSFP banding artifacts as a new dimension alongside coils for parallel imaging. Goal(s): Our goal is to leverage the temporally varying spatial modulation of a 2-periodic bSSFP acquisition to improve parallel imaging performance over a straightforward bSSFP approach. Approach: We optimize imaging parameters using computational simulations and validate our methodology through in-vivo experiments in brain. Results: Our findings demonstrate that the banding artifacts from 2-periodic bSSFP can serve as additional spatial encoding information in parallel imaging applications to reduce scan time. Impact: Periodically varying bSSFP banding patterns can be exploited to achieve improved parallel imaging performance, creating opportunities for new experimental designs in accelerated imaging.
Isotropic 3D Sub-millimeter MRI of the Vocal Fold Oscillation with Sub-millisecond Temporal Resolution
Authors: Fischer Johannes , Mehr Kian Tadjalli , Traser Louisa , Richter Bernhard , Bock Michael
Published: November 2024

Motivation: Several diseases influence the human vocal fold oscillation which can currently only be studied with superficial stroboscopic imaging. Goal(s): We aim to develop a technique that allows the full characterization of the vocal fold oscillation with sub-millisecond sub-millimeter resolution. Approach: ZTE MRI allows to freeze sub-ms dynamic signal changes in k-space. With synchronization data from a microphone, we retrospectively gate ZTE MRI data of the larynx acquired during singing using a total variation constraint in the time domain to reconstruct the vocal fold motion. Results: 3D vocal fold oscillations can be visualized with ultra-high spatial (0.8mm) and temporal (670μs) resolution. Impact: This work aims to improve the understanding of the VF oscillation under various physiological and pathological conditions, and might have applications in 3D dynamic MRI of other oscillatory body motions.
L2C-FNN: Longitudinal to Cross-sectional Feedforward Neural Network for generalizable AD-dementia progression prediction
Authors: Zhang Chen , An Lijun , Wulan Naren , Nguyen Kim-Ngan , Orban Csaba , Chen Pansheng , Chen Christopher , Zhou Juan Helen , Thomas Yeo B. T.
Published: November 2024

Motivation: Current longitudinal AD-dementia progression prediction studies lack cross-cohort evaluation, raising concerns about the clinical applicability of prediction models. Goal(s): Our goal was to develop a generalizable ML algorithm, L2C-FNN, and assess its generalizability across entirely distinct test cohorts. Approach: L2C-FNN and baseline models were trained solely on ADNI and subsequently evaluated on AIBL, MACC, and OASIS. Multimodal biomarkers were leveraged for forecasting future clinical diagnosis, cognition, and ventricle volume. Results: Our algorithm compares favorably against strong baseline models across all test datasets, confirming its superior generalizability. Impact: The demonstrated potential for improved generalizability in L2C-FNN signifies progress toward enhancing AI prediction models for clinical application. This underscores the continued need for cross-cohort evaluation in future AD-dementia progression modeling studies.
Evaluation of the glymphatic system activity during sleep-wake states through quantitative CSF measurement using a three-pool water model
Authors: Lee Gawon , Oh Se-Hong
Published: November 2024

Motivation: The glymphatic system plays a crucial role in brain waste clearance, and dysfunction has been linked to neurodegenerative diseases like Alzheimer's Disease. Understanding this system is essential for advancing our knowledge of brain health. Goal(s): We aim to develop a non-invasive method to assess glymphatic activity in the human brain. Approach: We utilize a quantitative CSF measurement technique with a three-pool model and multi-echo spin-echo images. Results: Significant variations in glymphatic activity were observed across different brain regions and found to be influenced by sleep. Impact: Our method can potentially reveal sleep-influenced glymphatic activity variations, enabling early Alzheimer's Disease diagnosis.
Distinct Effects of Respiratory Depth and Frequency on CSF Flow
Authors: Banks Makaila , Fisher Harrison , Ashenagar Baarbod , Gomez Daniel , Polimeni Jonathan , Napadow Vitaly , Lewis Laura
Published: November 2024

Motivation: The flow of cerebrospinal fluid (CSF) is essential for maintenance of brain function. Goal(s): We aimed to understand the effects of respiration on CSF flow dynamics by quantitatively testing the change in CSF flow across varying paced breathing frequencies. Approach: Using flow-sensitive fMRI, phase contrast imaging, and physiological recordings, we measured changes in CSF flow and velocity during a visually guided paced breathing task. Results: We examined CSF flow across breath frequencies ranging from 0.1 Hz to 0.25 Hz, and found that slower frequencies of breathing increase CSF flow, independent of breath depth. Impact: Our results demonstrate that key features of human respiration, its timing and its depth, induce separate effects on CSF flow. Our identification of respiratory frequency as a modulator of CSF flow provides an accessible mechanism to modulate CSF flow.
Deep Learning Combination of FLAIR and T2W for Improved TSC Lesion Detection
Authors: Lin Ling , Zhou Yihang , Lin Rongbo , Jiang Dian , Zhao Xia , Zhao Cailei , Liang Dong , Liao Jianxiang , Hu Zhanqi , Wang Haifeng
Published: November 2024

Motivation: This study seeks to address the challenge of limited visibility of periventricular lesions in Tuberous Sclerosis Complex (TSC). Goal(s): Develop FLAIR3, a deep neural network, for adaptive fusion of T2w and FLAIR images in TSC patients to improve lesion detection. Approach: The study adopts a dual-stream U-Net network with a pre-fusion module and employs spatial and channel fusion weight for feature fusion. Gradient loss and segmentation annotations are utilized to generate fusion images with clear textures and improved contrast. Results: The fused image, FLAIR3, demonstrates enhanced lesion contrast and outperforms T2w and FLAIR images in lesion segmentation. Impact: The enhanced lesion visualization provided by FLAIR3 can aid doctors in accurately identifying and diagnosing cortical tubers, improving the overall epilepsy diagnosis and treatment in TSC patients. This work improves the accuracy of automatic tuber segmentation.
Automatic spinal cord segmentation: Generalization across MR parameters, sites, vendors and pathologies
Authors: Bedard Sandrine , Enamundram Naga , Kaptan Merve , Eippert Falk , Kinany Nawal , Ricchi Ilaria , Van De Ville Dimitri , Freund Patrick , Hupp Markus , Lee Lisa , Traboulsee Anthony , Tam Roger , Prat Alexandre , Vavasour Zachary , Kolind Shannon , Oh Jiwon , Aigner Christoph , Cohen-Adad Julien
Published: November 2024

Motivation: Spinal cord cross-sectional area (CSA) is an important biomarker for neurodegenerative and traumatic diseases. However, CSA measurements vary across MRI contrasts and imaging protocols, limiting its use in multi-center studies. Goal(s): The goal is to evaluate CSA variability using a novel contrast-agnostic segmentation method. Approach: We compared this method to the Spinal Cord Toolbox's DeepSeg, analyzing CSA across different sites, and MRI vendors. Additionally, we compared the segmentations in diverse datasets and pathologies. Results: The contrast-agnostic segmentation showed lower CSA variability, and superior performance in most cases, except for intramedullary cord compression, where the Spinal Cord Toolbox's DeepSeg was more accurate. Impact: The contrast-agnostic method yields reliable spinal cord CSA measurements, independent of MRI contrasts and vendors. This, combined with a soft segmentation output, can potentially detect subtle spinal cord atrophy in prospective multi-center cohorts.
Functional Kinematic Assessment of the Wrist Using Volumetric Dynamic MRI
Authors: Abbas Batool , Zi Ruoxun , Block Kai Tobias , Petchprapa Catherine , Fishbaugh James , Gerig Guido , Lattanzi Riccardo
Published: November 2024

Motivation: Dynamic imaging can be useful for the evaluation of wrist instability. Goal(s): To propose a semi-automatic approach for carpal bones segmentation on 3D dynamic wrist MRI to enable kinematic assessment. Approach: We segmented carpal bones on a high-resolution 3D static MRI, registered it to a template created from the dynamic frames, and transferred back the segmentations onto individual 3D dynamic volumes. Bones surfaces were reconstructed and the reproducibility of motion patterns was assessed on repeated scans. Results: Our proposed image processing and visualization pipeline enables semi-automatic segmentation of carpal bones and provides a framework for qualitative and quantitative analysis of wrist kinematics. Impact: This work demonstrates semi-automatic segmentation of real-time dynamic MRI of the wrist to extract carpal bones motion. It could be used for quantitative kinematic analysis to detect and characterize wrist abnormalities.
DeepGrasp-Quant: A General Framework for Deep Learning-Enabled Quantitative Imaging Based on Golden-Angle Radial Sparse Parallel MRI
Authors: Pei Haoyang , Chen Jingjia , Huang Yuhui , Xu Xiang , Xia Ding , Wang Yao , Liu Fang , Chandarana Hersh , Sodickson Daniel , Feng Li
Published: November 2024

Motivation: Quantitative MRI typically involves a multi-step imaging pipeline from data acquisition to parameter estimation. Deep learning holds great promise to improve and streamline the entire workflow for quantitative MRI. Goal(s): This work presents a general deep learning-based rapid quantitative MRI framework, called DeepGrasp-Quant, for efficient and accurate quantification of MRI parameters based on Golden-angle RAdial Sparse Parallel (GRASP) MRI. Approach: DeepGrasp-Quant was designed with cascaded deep learning modules for reconstruction and parameter fitting, enabling direct estimation of MR parameters from undersampled images. Results: Two examples of DeepGrasp-Quant (DeepGrasp-T1 and DeepGrasp-T1-Dixon) were demonstrated for rapid accurate T1 mapping of the brain and the liver. Impact: DeepGrasp-Quant is expected to be a promising technique for efficient and accurate quantification of MRI parameters from highly-accelerated free-breathing data acquisition. In addition to T1 mapping, it can also be integrated with other quantitative MRI methods for different clinical applications.
Aberrant brain structural–functional connectivity coupling related to cognitive impairment in different cerebral small vessel disease burden
Authors: Zhang Xinyue , Liang Changhu , Feng Mengmeng , Xin Haotian , Gao Yian , Sui Chaofan , Wang Na , Zhang Nan , Wen Hongwei , Guo Lingfei
Published: November 2024

Motivation: The impact of different cerebral small vessel disease (CSVD) burden on brain structural and functional connectivity coupling and their correlation with neurocognitive outcomes remain largely unknown. Goal(s): To explore the alterations of structural and functional connection network (SC-FC) coupling in the whole brain and different functional modules of patients with different CSVD burden compared with healthy controls. Approach: Diffusion tensor imaging (DTI) and Resting-state blood-oxygen-level-dependent (BOLD) fMRI techniques were used to analyze structural and functional brain connections. Results: Severe CSVD burden patients exhibited significantly decreased whole-brain SC-FC coupling, reduced modular SC-FC coupling and associated with impairment of cognitive outcomes. Impact: SC-FC coupling might provide a more sensitive neuroimaging biomarker of CSVD burden as well as new insights into the pathophysiologic mechanisms of the clinical development of CSVD.
Evaluation of an MR Anatomically Guided PET Reconstruction in Characterizing Multiple Sclerosis Lesions
Authors: Wang Yujie , Ying Chunwei , Brier Matthew , Li Xinzhou , Faul David , Benzinger Tammie , An Hongyu
Published: November 2024

Motivation: Bowsher CNN, an MRI anatomic-guided PET reconstruction method, can provide high-resolution PET images. It is unknown how it may affect lesion characterization in MS patients. Goal(s): Evaluate PET signal without or with Bowsher CNN in various MS lesions. Approach: FLAIR images defined WMH lesions and NAWM. WMH lesions were further separated into “T1-hypo” and “T1-iso” sub-categories based on T1 intensity. 18F-FDG SUVs were obtained from various lesion ROIs. Results: The SUV differences between WMH and NAWM and between T1-hypo and T1-iso lesions became lower and higher, respectively, after applying Bowsher CNN. Impact: Bowsher CNN PET reconstruction results in high-resolution PET images. SUV differences between WMH and NAWM became smaller, while the SUV differences between T1-hypo and T1-iso, two WMH subcategories, were larger after applying Bowsher CNN.
Subwavelength dielectric waveguide for human head travelling-wave MRI at 7T
Authors: Gao Yang , Liu Tong , Hong Tao , Jiang Wen , Zhang Xiaotong
Published: November 2024

Motivation: Radiative excitation (e.g., travelling-wave, TW) has strength in large coverage and low SAR. It’s well compatibility with single-channel (clinical-mode) makes it promising as whole-body excitation solution at UHF. But it has apparent weakness in efficiency. Goal(s): Improve excitation efficiency as well as homogeneity of TW MRI under clinical-mode. Approach: Subwavelength dielectric waveguide was designed to enhance excitation efficiency as well as homogeneity through mode conversion, power-focusing, wave-impedance-matching and phase-velocity-matching. Results: The excitation efficiency was improved by 114% over brain compared to classic TW . SAR efficiency was 10.8% higher than birdcage. The B1+ RMSE in brain was reduced by 21.9% compared to birdcage. Impact: Our results offered insights into the design of new generation TW MRI excitation systems at UHF. The improved TW MRI systems operated under single channel may hold promises to whole-body imaging at UHF in clinical scenarios.
Dynamic 3D Thermometry in Moving Tissue using Accelerated Stack-of-Radial MRI and an Image-Navigated Multi-Baseline PRF Method
Authors: Dai Qing , Shih Shu-Fu , Curiel Omar , Chiang Jason , Lu David , Tsao Tsu-Chin , Wu Holden
Published: November 2024

Motivation: MRI thermometry faces challenges in moving tissues: intra- and inter-scan motion, limited spatio-temporal resolution, and constrained spatial coverage. These obstacles result in temperature mis-calculations, compromising treatment safety and efficacy. Goal(s): To develop an image-navigated 3D thermometry method to simultaneously track respiratory motion and temperature in moving tissue. Approach: A stack-of-radial sequence was combined with compressed sensing reconstruction to obtain dynamic 3D images. An image-navigated multi-baseline proton resonance frequency shift (PRF) method was developed to generate motion-resolved temperature maps with tissue tracking. Results: The proposed method achieved 24-30 slice coverage with a temporal resolution <1 second/volume and mean absolute error <2 degrees during motion. Impact: The proposed method could improve the safety and efficacy of MRI-guided thermal therapies through reliable temperature monitoring in moving tissues. The capability to simultaneously track motion and temperature evolution enables feedback control, including focused ultrasound beam steering in moving organs.
Quantifying Rotational Correlation Time in Clinical MRI Scanners: A Novel Framework for Enhanced Tissue Characterization
Authors: Deng Shengwen , Zhao Walter , Jordan David , Flask Chris , Griswold Mark , Badve Chaitra , Ma Dan
Published: November 2024

Motivation: This study exploits the underexplored potential of paramagnetic relaxation enhancement (PRE) in clinical MR scanners to characterize molecular interactions and tissue microenvironments in vivo, leveraging Gadolinium-based contrast agents (GBCAs). Goal(s): Develop and validate methodology for estimating Gadolinium-based contrast agent (GBCA) correlation time via relaxivity ratio measurements at 1.5 and 3 Tesla. Approach: Applying relaxation models, we devised a dictionary-matching framework correlating GBCA relaxivities with correlation times, and validated our methods using phantom experiments. Results: Our framework accurately estimates GBCA correlation times at a single field strength showing <5% error (1.5T to 3T) and <11% (3T to 1.5T) in cross-field relaxivity predictions. Impact: This framework leverages MR Relaxometry for precise estimation of GBCA rotational correlation time at single field strengths, offering insights in tissue characteristics. There is significant potential to improve tumor imaging and diagnosis through insights into pH, viscosity, and protein interactions .
Characterization of a Pseudo-Tissue Liver Flow Phantom for Use in Magnetic Resonance Elastography Validation Experiments
Authors: Rice James , Volety Srijyotsna , Lee Wonhyeok , Eriten Melih , Hernando Diego , Roldan-Alzate Alejandro
Published: November 2024

Motivation: MRE is utilized to assess tissue stiffness in vivo, however, robust validation in tissue-mimicking phantoms is needed. Goal(s): Create hydrogel liver phantoms of varying stiffness, characterize them with MRE and compare MRE with a mechanical reference standard. Utilize pulsatile flow to mimic cardiac motion. Approach: Flow phantoms of varying stiffness were created. Stiffness from mechanical test was compared to MRE. Cardiac tagging visualized motion inside each phantom. Results: MRE shear stiffness showed agreement with indenter stiffness and cardiac motion decreased with stiffness. Impact: Advances in MRE have led to its increasing use to determine tissue stiffness in vivo, however, robust validation in tissue mimicking phantoms has yet to be achieved. The proposed methodology may help to assess the quantitative performance of MRE.
Multimodal surface coils for low-field MR imaging
Authors: Zhao Yunkun , Bhosale Aditya , Zhang Xiaoliang
Published: November 2024

Motivation: By the need to address the limitations of low-field MRI, such as low SNR and insensitive frequency tuning. Goal(s): We proposed a design of multimodal surface coil that can enhance the B1 efficiency while reducing the associated electric field. Approach: Through both electromagnetic simulation and bench testing, the performance of this novel coil design technique was evaluated and compared with the conventional surface coil and solenoid coil. Results: The results affirmed the superior performance of the proposed multimodal surface coil design in terms of B1 efficiency and frequency tuning over the surface coil and solenoid coil at the low field of 0.5T. Impact: The proposed multimodal surface coil design improves B1 efficiency compared with the conventional surface coil and solenoid coil at 0.5T. It also mitigates frequency tuning challenges and has the potential to enhance the quality of low-field MRI in clinical diagnosis.
Feasibility of Detecting White Matter Perfusion using Arterial Spin Labeling in Patients with Sickle Cell Disease
Authors: Richerson Wesley , Aumann Megan , Song Alex , Eisma Jarrod , Davis Samantha , Milner Lauren , Jordan Lori , Donahue Manus
Published: November 2024

Motivation: Accurate white matter (WM) perfusion quantification is difficult but likely critical for assessing infarct risk in Sickle Cell Disease (SCD). Goal(s): To evaluate the feasibility of detecting regional WM perfusion using arterial spin labeling (ASL) under conditions of high perfusion and reduced bolus arrival time (BAT) in SCD patients. Approach: A multi-inversion time (TI; range=200-3200 ms), pulsed ASL sequence was applied to quantify perfusion detectability in SCD (n=35) and healthy (n=15) participants. Results: WM perfusion was significantly detected for TI=800-1800 ms in SCD patients. BAT in SCD was more closely related to hematocrit (rho=0.43; p=0.01) than was WM perfusion (rho=-0.13; p=0.47). Impact: We provide evidence in support of perfusion detection with ASL in SCD patients, which is attributable to higher perfusion and reduced BAT.
Effects of Diffusion Time-dependent Tractography Focused on Skeletal Muscles
Authors: Kandori Keiya , Hata Junichi , Oshiro Hinako , Kubo Natsumi , Yoshimaru Daisuke , Okano Hideyuki
Published: November 2024

Motivation: In the skeletal muscles, the effects of varying diffusion times have rarely been investigated, and to what extent they are affected is unclear. Goal(s): This study aimed to determine the effect of diffusion time on skeletal muscle delineation and anisotropy. Approach: Tensor analysis and tractography measurements were performed on the hind legs of mice to investigate the relationship between diffusion time and myofiber delineation and anisotropy in skeletal muscles. Results: Longer diffusion times allowed us to assess diffusion movements within muscle fibers and capture the precise organization of the skeletal muscles. Impact: The effect of varying diffusion times on skeletal muscle myofibers was clarified. The results suggested that this method could be applied to human skeletal muscles for the examination of intramuscular tissues.