bluuebunny/crossref_metadata_2025 huggingface dataset:
A high current, in-bore, switched capacitor voltage converter with low EMI and high efficiency.
Authors: Schildknecht Christoph , Riegger Daniel , Brunner David
Published: November 2024

Motivation: Due the noise emission of switch mode power supplies, linear regulators are often present in electronics in and around the MR bore, with the related thermal challenges. Goal(s): In this work we present a switched capacitor converter witch is capable of providing high output currents without emitting noise in the MR RF band. Approach: The goal was achieved by controlling the slew rate of the gate source voltage of the switching GaN FETs. Results: High efficiency, low output ripple and no unexpected transient behavior could be measured on the bench. Impact: The presented 10A switched capacitor converter can provide efficiently power to electronics without emitting RF noise around the MR RF band. Enlarging the integration possibilities of high density electronics in and around the MR bore.
In-Ovo MRI: design of a large-scale RF coil model
Authors: Hernandez Daniel , Jeong Yonghwa , Nam Taewoo , Kim Kyoung-Nam
Published: November 2024

Motivation: The poultry industry utilizes MRI to assess egg quality, especially to identify fertilized eggs. Image quality across eggs should be similar and with efficient filling factor. Goal(s): The goal is to design a specialized coil for MRI that can efficiently and accurately scan multiple eggs , providing the same image quality for each egg. Approach: The proposed coil has a multiloop structure. We used electromagnetic simulations to compute the magnetic field and compared the proposed coil with a volume and individual loop coils. Results: Validated through simulations and MR images, the coil displayed the scalability and, enabling the imaging of multiple eggsImpact: The proposed coil design shows better egg per area filling factor efficiency and uniform image quality for each egg and also scalability for high-throughput egg screening. This design promises to enhance multiple egg imaging quality control in the poultry industry.
Automatically Quantitative Intratumoral Susceptibility Signal In Evaluating The FlOG Staging Of Ovarian Cancer Patients
Authors: Hao Li , Liu Ailian , Li Ye , Song Qingling , Shi Yuting , Song Qingwei , Wang Hongkai , Zhuang Mingrui
Published: November 2024

Motivation: Accurate diagnosis and staging of ovarian cancer play a key role in the selection of treatment plan, surgical method and determination of the circumferenceGoal(s): Tumor intratumoral susceptibility signal (ITSS) can reflect the new growth inside the tumor Vascular and bleeding conditions, ITSS have been widely used in many departments Although few studies have applied this technique to ovarian cancerApproach: Automatically quantitative ITSS prediction of clinical FIGO staging of ovarian cancer was performed by using AS (AnatomySketch 1.0) software (Dalian University of Technology)Results: The automatic quantitative ITSS rate was significantly higher in advanced ovarian cancer than in early ovarian cancerImpact: Automatic quantitative ITSS is expected to be applied to the study of ovarian tumors and more sites in the future. ITSS can effectively predict FIGO type of ovarian cancer and provide valuable information for making treatment plan and judging prognosis
Free-breathing 3D whole-heart simultaneous bright- and black-blood anatomical imaging and T1/T2 mapping at 0.55T
Authors: Kokhanovskyi Ivan , Castillo-Passi Carlos , Crabb Michael , Ganter Carl , Kunze Karl , Neji Radhouene , Karampinos Dimitrios , Makowski Marcus , Prieto Claudia , Botnar Rene
Published: November 2024

Motivation: To overcome the limitations of clinical examinations, which require several sequential acquisitions under multiple breath-holds, and to make cardiac MR more accessible and affordable at lower field strength. Goal(s): To develop a novel 3D free-breathing sequence for simultaneous assessment of cardiovascular anatomy via bright- and black-blood imaging and myocardial tissue quantification in an easy to use one-click-scan at 0.55T. Approach: Implementation of a novel iNAV-based 5-heartbeat interleaved sequence (proACTION) with distinct IR and T2 preparation modules and non-rigid motion correction at 0.55T. Results: proACTION provides good delineation of cardiac and vascular structures with accurate joint T1/T2 parametrical mapping in healthy subjects. Impact: Comprehensive 3D whole-heart evaluation of cardiovascular anatomy and tissue characterization with T1/T2 maps can be obtained in an efficient, free-breathing, and easier to use one-click-scan with proACTION at 0.55T.
An AI-based pipeline for automatic image fusion of cardiac CTCA and perfusion MRI
Authors: Jiang Wenting , Ng Ming-Yen , Sin TsunHei , Cao Peng
Published: November 2024

Motivation: The 3D fusion of coronary structure and myocardial blood flow data helps to reduce the misallocation of affected vessels to their associated myocardial territories. Goal(s): An AI-based pipeline has been developed that uses advanced machine learning algorithms to automatically fuse images from cardiac CTCA and perfusion MRI. Approach: The pipeline includes an automatic reorientation of 3D CT coronary angiography and fusion with stress cardiovascular magnetic resonance images. Results: we achieved 3D fusion of CTCA and CMR establishing a correlation between coronary artery stenosis and stress-induced myocardial hypoperfusion. Impact: the pipeline can assist in clinical assessments of coronary artery disease.
Novel iNAV-based 3D Whole-Heart Late Gadolinium Enhancement Low-Field (0.55T) Cardiovascular MRI
Authors: Littlewood Simon , Crabb Michael , Castillo-Passi Carlos , Si Dongyue , Kunze Karl , Prieto Claudia , Chiribiri Amedeo , Botnar René
Published: November 2024

Motivation: 3D whole-heart late gadolinium enhancement imaging has previously been demonstrated at 1.5T, but not at low-field (0.55T). Goal(s): To develop a novel free breathing, whole-heart, late gadolinium enhancement imaging framework at low field. Approach: Patients with known ischaemic heart disease were scanned and results of the proposed 3D sequence were compared with 2D LGE images. Results: There is excellent agreement between the 3D and 2D datasets in the detection of myocardial scar. Impact: Preliminary results demonstrate the feasibility of the proposed framework for comprehensive 3D whole-heart late gadolinium enhancement imaging for the detection of myocardial scar at 0.55T.
Assessing lower back myofascial interface mobility using MR elastography-based slip interface imaging (SII)
Authors: Hojo Emi , Sui Yi , Shan Xiang , Zheng Keni , Rossman Phillip , Waters Tim , Manduca Armando , Powell Garret , An Kai-Nan , Zhao Kristin , Bauer Brent , Ehman Richard , Yin Ziying
Published: November 2024

Motivation: Investigating abnormal myofascial adhesion is crucial for understanding chronic low back pain in myofascial pain syndrome (MPS), necessitating objective, non-invasive imaging methods to characterize myofascial mobility in the lower back. Goal(s): To evaluate the efficacy of MR-Elastography (MRE)-based slip interface imaging (SII) technique for visualizing myofascial mobility in the lower back of healthy volunteers. Approach: A custom-built MRE driver and a new SII biomarker (Dnorm) were introduced for detecting slip interfaces across thoracolumbar fascia and inter-muscular myofascial interfaces. Results: The Dnorm map at a lower MRE frequency successfully provided clear visualization of lumbar slip interfaces, indicating unrestricted mobility in healthy volunteers. Impact: The new SII biomarker enhances visualization of the interface mobility in thoracolumbar fascia and other inter-muscular interfaces in the lower back. This may benefit assessment of myofascial mobility differences between healthy individuals and patients with MPS.
AutoML Radiomics-Based Classification for Opportunistic Osteoporosis Screening with Lumbar Fat and Water using IDEAL-IQ MRI
Authors: Cheng Yung-Yin , Chen Chun-Wen , Liao Chun-Han , Liu Ming-Cheng , Lin Shao-Chieh , Lyu Pin-Sian , Chiu Tzu-Yu , Ou Chen Chung , Liu Yi-Jui
Published: November 2024

Motivation: Could lumbar fat and water MRI be as an opportunistic screening tool?Goal(s): To develop autoML radiomics-Based Classification for osteoporosis prediction using lumbar fat and water MRI. Approach: A TPOP-radiomics classification model was trained using lumbar fat and water images obtained through the IDEAL-IQ method in normal and osteoporosis patients identified by DeXA. Three datasets of radiomics features were used, categorized based on their dimension (2D, 3D, and projection map)Results: Our results indicate that the best model from the AutoML process demonstrated mean sensitivity of 0.745 and mean specificity of 0.758 in distinguishing between normal and osteroporosis. Impact: Because osteoporosis is often considered a 'silent' disease, routine IDEAL-IQ lumbar scans have the potential to serve as an opportunistic screening tool for reducing the risk of fragility fractures, which are associated with morbidity and mortality.
A maze-like metasurface design as an efficient resonator for 7T MRI
Authors: Maurya Santosh K , Tegareh Eiska , Schmidt Rita
Published: November 2024

Motivation: Metamaterial-based designs have the potential to locally increase the RF field and to serve as resonators in MRI. However, many of the structure either include a high dielectric layer substrate or require large amount of lumped elements. Goal(s): Our goal was to design a metamaterial without the need for either. Approach: A novel metasurface was constructed from concentric split-rings alternatingly rotated by 90° - generating a maze-like configuration - which allowed to lower the resonant frequency. Results: The novel maze-like metasurface achieved an RF field increase in the range of x1.5-2 compared to using a surface-coil of the same dimensions. Impact: We demonstrated a new metasurface geometry that provides an efficient resonator at 298 MHz for 7T MRI. This design does not require high dielectric or lumped elements, which offers a simple implementation, a flexible setup and a high efficiency resonator.
A Simulation-based Study of the Cycloid Dipole as an RF Coil Element for 7T MRI
Authors: Alkandari Dheyaa , Wright Steven
Published: November 2024

Motivation: The demand for improving RF coil designs to maximize the potential of high-field MRI continues to grow. Exploring innovative RF coil elements holds the potential to improve RF coil performance and diagnostic image quality. Goal(s): Our goal is to investigate the performance of a cycloid dipole antenna as a possible RF coil element for high-field MRI. Approach: FDTD simulations were performed to compare the performance of a standard half-wavelength dipole at 7 T with two variations of the cycloid dipole. Results: Cycloid dipole exhibits a shorter resonance structure, higher B1+ and B1+/√SAR10g_max efficiencies when compared to the standard dipole antenna. Impact: The study introduces cycloid dipoles as potential MRI coil elements. This opens opportunities for future investigations to optimize cycloid antennas within specific MRI coil designs, improving clinical imaging quality.
Cognitive Performance and Brain Connectivity in High-Contact and Low-Contact Sport Athletes
Authors: Karimpoor Mahta , Taghavi Hossein Moein , Georgiadis Marios , Towns Jessica , Cecchi Nicholas , Mills Brian , Phouksouvath Narvin , Goubran Maged , Mouchawar Nicole , Sami Sohrab , Wintermark Max , Grant Gerald , Camarillo David , Zeineh Michael
Published: November 2024

Motivation: Repetitive head impact in contact sports is linked to long-term cognitive sequelae, but the complexities of these changes remain unclear. Goal(s): Determine potential relationships between resting-state functional connectivity (rsFC) and cognitive performance differential between high- and low-contact sports. Approach: We assessed baseline rsFC and cognitive performance in PAC-12 athletes using rsfMRI and the ImPACT test. Results: Enhanced ImPACT visual-motor-speed performance was present in low-contact sports and associated with increased connectivity between attentional networks and sensorimotor/visual/auditory regions. High-contact sports showed less connectivity between these motor and auditory regions, but more connectivity between these motor and visual regions. Impact: This research sheds light on how repetitive head impacts in contact sports affect cognitive function and brain connectivity.
Cardiac and respiratory self-gating based on PCA of selected points from coil arrays
Authors: Yang Wenchao , Liu Wenjian , Wang Dong , Ouyang Rongzhen , Hu Liwei , Zhong Yumin , Qi Haikun , Hu Peng
Published: November 2024

Motivation: ECG-gating for cardiac MR Imaging may fail, especially at high field, and the conventional self-gating method is insufficient to effectively extract the cardiac signal in 3D cardiac MR cine with high precision (previous precision 20-30ms). Goal(s): Our goal was to achieved a reliable cardiac self-gating technique with the precision of 10ms level. Approach: We proposed a two-step selective PCA self-gating method by first selecting the heart beating or respiration sensitive points and then performing PCA. Results: The proposed method achieved a temporal precision of 11ms for 3D cardiac cine images. Impact: The proposed selective PCA self-gating technique can be applied in poor ECG-gating MR scans, such as patients with hairy chests or obesity, as well as in high-field environments, with a high level of precision down to 11ms.
Sonic DL Cardiac Cine MRI at 3T: Comparison with Conventional Segmented Cine MRI
Authors: Sun Bin
Published: November 2024

Motivation: This study aimed to explore the feasibility and accuracy of Sonic DL cardiac magnetic resonance cine technology. Goal(s): We aimed to assess the performance of Sonic DL cine MRI at 3T for left ventricular (LV) volume and mass measurement, especially patients with arrhythmia and/or difficulty in breath-holding. Approach: 48 patients were consecutively enrolled. EDV, ESV, SV, EF, and LV mass were measured. The agreement and correlation of the parameters were assessed. Image quality was evaluated and structure visibility rating. Results: Good agreements and correlations were found between the techniques for measuring left ventricular function. Impact: Sonic DL cardiac cine MRI allowed the assessment of LV volume with high accuracy and showed a significantly better image quality.
CMR-based left ventricular strain reflects the therapeutic effect of stem cells in chronic ischemic heart disease
Authors: Mu Dan , liu jinbang , Zhang He , Wang Dongjin , Zhang Bing , Yue Xiuzgeng , Zhao Xiance
Published: November 2024

Motivation: CMR left ventricular strain analysis is a crucial tool for assessing myocardial status, capable of identifying and evaluating regional myocardial dysfunction caused by coronary artery disease. Goal(s): This study aims to evaluate the efficacy of cellular therapy in patients with chronic ischemic heart disease using left ventricular strain indices. Approach: 38 patients scheduled for coronary artery bypass grafting were randomly assigned to receive cellular therapy or serve as controls, followed by CMR imaging and strain analysis of various left ventricular views. Results: Preliminary results indicate improvements in some CMR-derived strain indices in the cellular therapy group post-treatment, especially notable at 6 months post-operation. Impact: This study provides new insights into the assessment of cellular therapy efficacy using CMR left ventricular strain indices, offering a more profound understanding and evaluation method for cellular therapy in patients with chronic ischemic heart disease.
Cardiovascular assessment of diastolic dysfunction in people living with the HIV: correlation with markers of disease activity
Authors: Zheng Yue , Ding Haibo , Liu Ting
Published: November 2024

Motivation: People living with HIV are at increased risk of cardiovascular disease compared with healthy people. Goal(s): To explore the extent of diastolic atrial and left ventricular dysfunction in PLWH by CMR in correlation with clinical markers of disease activity. Approach: 101 PLWH and 62 healthy volunteers were recruited for this study in China. Both left atrial (LA) and LV strain and strain rate were calculated using CMR feature tracking. Results: PLWH had a larger LAVImax, LAVImin and LAVIpre-a as compared to healthy volunteers. The LA reservoir, conduit and booster pump function were all impaired in PLWH. Impact: The prevalence of diastolic dysfunction as well as asymptomatic systolicabnormalities is observed in HIV patients.
FRACTURE-Angiography: simultaneous acquisition of bone imaging and angiography
Authors: Kurosawa Ryuna , Yokota Hajime , Sada Takayuki , Hanada Koichi , Ito Ryo , Nitta Keisuke , Yamagishi Yoshiki , Sato Hirotaka , Matsumoto Koji , Maki Satoshi , Namiki Takashi , Yoneyama Masami , Masuda Yoshitada , Uno Takashi
Published: November 2024

Motivation: In preoperative cervical spine assessment, precise visualization of the vertebral artery (VA) course is of paramount importance. We present a new sequence called FRACTURE-Angiography. Goal(s): The purpose is to evaluate the clinical applicability of FRACTURE-Angiography compared to FRACTURE and TOF-MRA. Approach: Both quantitative and qualitative evaluations were performed. In the quantitative evaluations, we assessed the depiction ability of the VA and bone tissue based on the contrast ratio with background tissue. The qualitative evaluations for 3D-fusion images were conducted from the perspectives of bone morphology and VA course. Results: FRACTURE-Angiography could image arterial signals and bone morphology simultaneously and satisfy clinical requirements. Impact: FRACTURE-Angiography allows simultaneous acquisition of bone tissue and arterial images in a single imaging session. As a result, it has the advantage of shortening scan time and minimizing the gap between scans.
Radiomic Features Outperform Clinical Metrics in Distinguishing Femoroacetabular Impingement Patients from Healthy Subjects
Authors: Montin Eros , Kijowski Richard , Youm Thomas , Lattanzi Riccardo
Published: November 2024

Motivation: Radiomics could differentiate the symptomatic hip from the asymptomatic contralateral hip in patients with femoroacetabular impingement (FAI). This study investigates its potential in distinguishing FAI patients from healthy subjects. Goal(s): To compare the diagnostic performance of radiomic features and clinical metrics in FAI diagnosis. Approach: We used 3D Dixon MRI data (10 healthy subjects and 10 FAI patients). We trained machine learning models on radiomic features extracted from MRI to classify subjects as healthy or FAI. Models were trained also on clinical metrics for comparison. Results: Radiomic features accurately identified FAI patients without errors (100% accuracy). Clinical metrics achieved 74% accuracy. Impact: Radiomic features exhibited a remarkable diagnostic performance, accurately identifying all FAI patients and healthy subjects. This study shows the promise of radiomics to enable automated FAI diagnosis.
Prediction of Backfill Progression at the Sacroiliac Joint in Patients with Axial Spondyloarthritis using a radiomics method
Authors: Cui Jia , Li Boya , Guo Zikang , Qu Jin , Zhang Ying , Shen Zhiwei , Lei Xinwei
Published: November 2024

Motivation: Identifying patients with a backfill progression is crucial for predicting clinical prognosis and adjusting treatment approaches in the disease process. Goal(s): This study aimed to extract radiomics features for the sacroiliac joint on MRI images in patients with axSpA to predict backfill progression within one year. Approach: This retrospective study analyzed 257 patients diagnosed with axSpA. The radiomics and clinical models were combined to construct a nomogram model through multivariable logistic regression analysis. Results: Seven radiomics features were extracted to generate a Rad-score. The AUCs of the radiomics, clinical, and nomogram models in the training cohort were 0.90, 0.78 and 0.93, respectively. Impact: The built radiomics-based nomogram has good predictive value for structural progression in patients with axial spondyloarthritis.
Emotional regulation mediates the protective role of resting-state brain activity against depression symptoms in late adolescence
Authors: Lan Huan , Zuo Chao , Chen Li , Wang Song , Gong Qiyong
Published: November 2024

Motivation: The neural correlation between emotional regulation and adolescent depressive symptoms has not yet been elucidated. Goal(s): Our goal was to identify the neural substrates of emotional regulation ability (ERA) and its association with depressive symptoms in adolescents. Approach: We conducted whole-brain correlation, prediction and mediate analyses with resting-state fMRI and behavioral measurements data. Results: The results indicated that ERA was associated with brain activity in right ventromedial prefrontal cortex (VMPFC) and cuneus. Additionally, ERA mediated the link between spontaneous activity of VMPFC and depressive symptoms. Impact: Emotional regulation ability may indirectly modulate depressive symptoms in adolescents through affecting neural activity in the VMPFC, which may provide some neurobiological implications for early intervention of adolescent depression.
Regional glutamine levels and cognition in patients with schizophrenia and healthy control subjects
Authors: Barker Peter , Senapati Dillip , Etyemez Semra , Özdemir Ípek , Yoon Mark , Kamath Vidyulata , Coughlin Jennifer
Published: November 2024

Motivation: To better understand the neurochemical correlates of cognitive impairment in subjects with schizophrenia and healthy control subjects. Goal(s): Are regional brain metabolite levels and peripheral markers correlated with cognition in subjects with schizophrenia?Approach: Regional brain metabolism using 7T MRS, detailed neuropsychological testing, and peripheral markers from venipuncture were obtained in 12 subjects with schizophrenia and 9 healthy control subjects. Results: In all subjects, significant positive correlations were found between regional glutamine (Gln) levels and blood ammonia levels, and, in subjects with schizophrenia, regional brain Gln levels were negatively correlated with measures of cognition. Impact: These preliminary data support the hypothesized role of aberrant Gln metabolism as one of the factors associated with CI in schizophrenia, possibly by perturbation of the glutamate/GABA-glutamine neurotransmitter cycle.
Longitudinal assessment of brain functional connectivity in depressed patients according to resting-state fMRI
Authors: Qiu Zi-You , Chen Chin-Hung , Tsai Yuan-Hsiung , Weng Jun-Cheng
Published: November 2024

Motivation: Given that suicidal ideation (SI) is closely related to social development, it is important to understand the associations between network function and SI (or the non-suicidal ideation, NS) in patients with depression. Goal(s): We aim to investigate brain function changes in depressed patients with SI and NS between baseline (Time 1, TP1) and follow-up (Time 2, TP2; after one year of therapy). Approach: Paired t-tests, repeated-measure ANCOVA, and network-based statistical analysis were used. Results: We found differences in functional activity after treatment, the results surrounded the DMN region in each group. NBS revealed significantly increased functional interconnections of subnetworks after treatment. Impact: Our findings provide more information about potential neural biomarkers of various depressive disorders.
Weak supervision in multi-coil accelerated MR image reconstruction
Authors: Atalik Arda , Chopra Sumit , Sodickson Daniel
Published: November 2024

Motivation: In training-data-limited settings, weak supervision –cooperatively utilizing under-sampled and fully-sampled datasets– can be advantageous. Goal(s): To compare weakly-supervised multi-coil Magnetic Resonance (MR) image reconstruction against reconstruction using only under-sampled or fully-sampled datasets in high- and low-data regimes. Approach: Pretrain a Variational Network (VarNet) in a self-supervised manner by minimizing L1 loss in k-space using a 4x under-sampled dataset. Transfer the pre-trained weights to another VarNet and fine-tune it using a smaller, fully sampled dataset by optimizing MS-SSIM loss in image space. Results: We demonstrate improvements in reconstruction quality in the high-data regime as well as enhanced robustness of reconstruction in the low-data regime. Impact: Multi-coil MR image reconstruction exploiting both under-sampled and fully-sampled datasets is achievable with transfer learning and fine-tuning. Our proposed methodology can provide improved reconstruction quality and robustness.
TransGRAPPA: Self-supervised Transformer Network for k-Space Interpolation
Authors: Huang Wenqi , Spieker Veronika , Pan Jiazhen , Rueckert Daniel , Hammernik Kerstin
Published: November 2024

Motivation: Addressing limitations in parallel imaging, particularly GRAPPA’s challenges like noise amplification and dependence on linear k-space value combinations. Goal(s): To enhance k-space interpolation accuracy with a transformer network, thereby improving the quality of clinical imaging. Approach: We employ a novel self-supervised transformer network with an attention mechanism - TransGRAPPA, exploiting latent features for nonlinear interpolation of missing k-space points. Results: TransGRAPPA outperforms GRAPPA and RAKI in terms of NRMSE, PSNR, SSIM, and noise reduction, showcasing enhanced capabilities on fastMRI’s multi-coil knee dataset. Impact: The study presents a innovative reconstruction method using transformer network to explore k-space point relationships with limited training data, offering potential improvements in MR image quality and scan speed, and more efficient and accurate diagnostics in medical imaging.
Cardiac protocol including 1H 3T MRI and 31P MRSI 7T with a dipole array coil
Authors: Karkouri Jabrane , Watson Will , Weir-McCall Jonathan , Hoole Stephen , Klomp Dennis , Rodgers Christopher
Published: November 2024

Motivation: 31­P heart applications can be used to monitor cardiac energetics, treatment response in vivo and metabolic inflexibility, a key feature of the failing heart. Goal(s): We present here a 7T and 3T protocol for 31­P heart application, including the validation of a dipole array coil design. Approach: We evaluated the performance of the coil at 7T with B1 maps and through in vivo scans of 8 healthy with a long 31P CSI protocol, and tested the 3T protocol on 5. Results: Results show spectra of excellent quality. PCr/gATP ratios lie within the expected range and B1+ maps show good uniformity. Impact: This coil design has the potential of lifting the current limitations associated with the wider use of 31­P cardiac MRSI to study the heart energetics. It can also help the diagnosis and the design of new drugs in the future.
Myocardial tissue characterization by CMR for the evaluation of heart failure with preserved ejection fraction in hypertrophic cardiomyopathy.
Authors: Ma Xuan , Zhao Shihua
Published: November 2024

Motivation: The association between myocardial tissue characteristics detected by cardiac magnetic resonance (CMR) and heart failure with preserved ejection fraction (HFpEF) in hypertrophic cardiomyopathy (HCM) remains unclear. Goal(s): We sought to evaluate the role of myocardial tissue characteristics detected by CMR in the identification of HFpEF in HCM. Approach: CMR was used to access tissue characteristics including native T1 values, extracellular volume fraction (ECV) and indexed ECV (iECV). Results: Native T1 was a sensitive biomarker independently associated with the diagnosis of HFpEF-HCM. Impact: The inclusion of myocardial tissue characteristics by cardiac magnetic resonance in the diagnostic algorithms of heart failure with preserved ejection fraction in patients with hypertrophic cardiomyopathy should be considered in clinical practice and future studies.
Deep Learning Automated Segmentation of the Left Ventricle for Spin-Echo Cardiac Diffusion Tensor Imaging (cDTI)
Authors: Hannum Ariel , Le Thu , Cork Tyler , Ennis Daniel
Published: November 2024

Motivation: Segmentation is central to cDTI post-processing, but remains subjective, time-intensive, and observer-dependent. Faster methods are needed. Goal(s): To develop and validate a U-Net for automating and standardizing left ventricle segmentations for cDTI. Our target was for U-net generated masks to yield cDTI metric maps within 5% of ground-truth and Dice scores comparable to a human reader. Approach: We developed a U-Net to automatically segment cDTI data then compared generated masks to expert annotations. Results: Median Dice score was 0.79 with cDTI metrics within 5% of ground truth. A multiple-reader study demonstrated the need for further generalization of datasets at different resolutions. Impact: An automated U-Net approach to cardiac DTI segmentation of the left ventricle minimizes segmentation variability, reduces processing time, and preserves cDTI metric measurement accuracy.
The Goldilocks zone for 3T MRS studies using semi-LASER: Determining the optimal balance between repetition time and scan time using FSL-MRS
Authors: Ensworth Alex , Barlow Laura , Kozlowski Piotr , MacMillan Erin , Laule Cornelia
Published: November 2024

Motivation: A short TR is often used in clinical MRS brain studies, leading to T1-weighting of metabolites and inaccurate T1 correction. Goal(s): To determine the optimal balance between scan time and TR that minimizes T1-weighting effects when using semi-LASER MRS. Approach: SNR and metabolite concentrations were compared for TRs of 2, 5 and 8s using FSL-MRS. Results: A TR of 5s provides a good balance of scan time, SNR and signal recovery. For a similar scan time, TR of 2s leads to incomplete signal recovery and thus heavy T1 weighting, while a TR of 8s results in complete signal recovery but reduced SNR. Impact: For MRS studies using semi-LASER, our work informs scientists and clinicians on the issues of using a short TR, and recommends the optimal scan parameters to use while implementing the newly available FSL-MRS analysis package.
Artifact Simulation Toolbox for GABA-Edited Magnetic Resonance Spectroscopy
Authors: Bugler Hanna , Berto Rodrigo , Souza Roberto , Harris Ashley
Published: November 2024

Motivation: GABA-edited Magnetic Resonance Spectroscopy (MRS) is a valuable tool used to measure GABA. However, it suffers from low signal to noise ratio. Machine learning has been recently proposed to overcome these challenges but accessing the large amount of in vivo data necessary for training can be difficult. Goal(s): To create a GABA-edited MRS artifact toolbox. Approach: We developed an open-access python toolbox to simulate four common artifacts (ghosting, eddy current effects, lipid contamination and phase/frequency shifts) in GABA-edited MRS. Results: The toolbox will support machine learning algorithm development by complementing existing simulation software and allow for flexible user inputs for data personalization. Impact: Our open-access python toolbox can be used to simulate spurious echoes, eddy currents, lipid contamination and motion artifacts to provide realistic and representative GABA-edited MRS data. This can be used for methods development such as training machine learning algorithms.
Breast tumor segmentation network based on local attention
Authors: Han Binze , Yang Long , Zhang Heng , Liu Zhou , Wang Meng , Ren Ya , Yang Qian , Cui Wei , Li Ye , Liang Dong , Liu Xin , Zheng Hairong , Zhang Na
Published: November 2024

Motivation: Accurate segmentation of the lesion region is the first step toward early diagnosis. The transformer, on the other hand, has very competitive performance but also extremely high computational complexity. Goal(s): Finding an efficient and computationally inexpensive method is currently a great challenge for the application of transformers in medical image segmentation. Approach: We adopt the shift local self-attention method to extract features, which reduces the computational complexity while obtaining very high segmentation accuracy. Results: Experimental results on a dataset comprising 130 breast tumor cases demonstrate that the proposed network accurately segments breast tumors, surpassing the accuracy of many other convolution-based or transformer-based networks. Impact: This study may inspire scientists to create simpler, efficient components for reduced self-attention computational cost while preserving long-range modeling. The achievement in high-precision segmentation can ease clinicians' workload by reducing image annotation.
Usefulness of Super-Resolution Deep Learning-Based Reconstruction on High-Resolution 3D T2WI for Evaluation of the Internal Auditory Canal
Authors: Uetani Hiroyuki , Nakaura Takeshi , Iwashita Koya , Morita Kosuke , Yamashita Yuichi , Saito Takumi , Matsuo Kensei , Hirai Toshinori
Published: November 2024

Motivation: There are no reports on the usefulness of high-resolution three-dimensional T2-weighted imaging (HR-3D T2WI) using super-resolution deep learning-based reconstruction (SR-DLR) technique. Goal(s): We aimed to determine whether a novel SR-DLR technique can improve the image quality of HR-3D T2WI for assessing the IAC and inner ear. Approach: We qualitatively assessed the image quality of HR-3D T2WI with and without SR-DLR for the visualization of detailed structures of the IAC and inner ear. Results: SR-DLR was shown to significantly improve the image quality of HR-3D T2WI in visualizing nerves in the IAC and inner ear compared to conventional HR-3D T2WI without SR-DLR. Impact: High-resolution three-dimensional T2-weighted imaging with super-resolution deep learning-based reconstruction can improve the visualization of detailed structures of the internal auditory canal and inner ear without extended acquisition time.
White matter alterations in brain fog: A Long-Covid study
Authors: Rolandi Nicolò , Ricciardi Antonio , Grosso Elena , Shatila Madiha , Yiannakas Marios , Prados Ferran , Kanber Baris , Wingrove Jed , Grussu Francesco , Battiston Marco , Samson Rebecca , Tur Carmen , Palesi Fulvia , D'Angelo Egidio , Wheeler-Kingshott Claudia Gandini
Published: November 2024

Motivation: The symptoms of brain fog include problems with concentration, memory, attention, which result in difficulties with communication. This can make it extremely difficult for an individual to carry out daily tasks and responsibilities as well as maintain relationships deteriorating their quality of life. Goal(s): To investigate white matter alteration in Long-COVID. Approach: Voxel-wise analysis of core white matter voxels using advanced MRI metrics and neuropsychological scores. Results: Results highlight promising perspective for further investigations and potential clinical interpretation of Long-COVID syndromesImpact: The addition of MRI enables a more thorough exploration of the diverse cognitive dimensions affected in individuals experiencing brain fog and perhaps the possibility to understanding the involvement of WM alterations as either a risk factor or consequence of Long-COVID.
Neurochemical Alterations Caused by Persistent COVID-19-Induced Anosmia: Probing Orbitofrontal Cortex Metabolites and Potential Biomarker
Authors: Nemati Shadman , Monsef Abbas , Dogahe Mohammad Haghani , Karimzad Sahand , Abbaspour Elahe
Published: November 2024

Motivation: Olfactory impairments caused by COVID-19 have been addressed in neuroimaging findings over the past years. However, long-term complications on brain orbitofrontal cortex (OFC) needs to be further investigated. Goal(s): Our goal was to assess metabolites level change in the brain OFC region in COVID-induced anosmia subjects in comparison to healthy population. Approach: 54 subjects categorized into control, short- and long-term anosmia groups were studied using single voxel MRS. Metabolite level alterations of their brain OFC region were investigated. Results: We found that NAA, Cho, and Cr levels in brain OFC region decreased as COVID-induced anosmia duration and severity increased. Impact: The demonstrated results of alteration in brain metabolites level influenced by the severity of COVID-induced anosmia highlights MRS as a robust assessment tool for physicians to better investigate olfactory function impairment in the brain orbitofrontal cortex.
Deep Learning-Based Automated Kidney and Cortex Segmentation from Non-contrast T1-weighted Images
Authors: xiong lianqiu , Huang Gang , Jiang Shanshan , Zhu Yi , zou caixia , pan nini , shi liuyan
Published: November 2024

Motivation: In the realm of kidney imaging, the precise measurement of kidney volumes, including total, cortical, and medullary volumes, is of significant clinical importance, but manual segmentation is time-consuming and impractical. Goal(s): To develop a fully automated deep learning-based segmentation method for segmenting the entire kidney and internal structures in MR images. Approach: Utilized a 3D nnU-Net deep learning model trained with non-contrast-enhanced T1-weight MR images from 40 volunteers, validated against manual segmentation. Results: The automated method strongly correlated with manual measurements (Pearson’s > 0.9) and achieved Dice coefficients of 0.96 for the whole kidney and 0.84 for the cortex on the test set. Impact: This deep learning approach offers rapid, precise, and replicable kidney volume analysis, enhancing both research and clinical care.
An automated end-to-end deep learning reconstruction and quantification workflow for fast quantitative DCE-MRI
Authors: Jing Juntong , Mekhanik Anthony , Murray Victor , Cohen Ouri , Otazo Ricardo
Published: November 2024

Motivation: Despite extensive research and promising initial results, quantitative dynamic contrast-enhanced (DCE) MRI is marginal in clinical practice, due to lack of automation and low reproducibility. Goal(s): Introduce an end-to-end deep learning approach for an automated and more reproducible DCE-MRI pipeline. Approach: Two networks, one reconstructing undersampled k-t data via Movienet and the other estimating perfusion and MR parameters, were merged into a unified, automated pipeline. The approach was tested on a volunteer and a patient with cervical cancer. Results: Automated processing yielded images in under 2 seconds, comparable in quality to GRASP and providing multiparametric mapping of perfusion and MR from one acquisition. Impact: The proposed fast automated data processing pipeline including deep learning reconstruction and quantification can be an important clinical tool to exploit the information from DCE-MRI to improve tumor diagnosis and treatment response evaluation.
Evaluation of the fairness and effectiveness of nnU-Net on multi-organ segmentation
Authors: Li Qing , Li Yan , Sun Longyu , Sun Mengting , Liu Meng , Hu Xumei , Zhang Xinyu , Xia Xueqin , Wang Shuo , Chu Yinghua , Wang Chengyan
Published: November 2024

Motivation: A systematic analysis of the segmentation effectiveness for fairness helps enhance the effectiveness of artificial intelligence(AI) model, which has not been done before. Goal(s): This study aims to compile statistics the relation between the segmentation effectiveness and aging, gender as well as anatomical regions. Approach: The nnU-Net model is used for organ segmentation while the DICE was computed to evaluate the relation between the effectiveness with aging and gender and the heatmap was used to visualize the spatial error distribution regarding anatomical regions. Results: The result demonstrates variations in nnU-Net's effectiveness within subgroups, highlighting the significance of attention mechanisms for segmentation model enhancement. Impact: This study comprehensively evaluated the fairness and effectiveness of nnU-Net across multiple organs within the body. An analysis was conducted to investigate the relationship between segmentation errors and age, gender as well as anatomical regions for organ segmentation.
In vivo T1 and T2 mapping of human knee at 0.05 Tesla
Authors: Yang Shiqi , Su Shi , Ding Ye , Zhao Yujiao , Wu Ed
Published: November 2024

Motivation: To study knee tissue properties at Ultra-low-field (ULF) for sequence design/optimization, enabling ULF MRI for wide-ranging applications. Goal(s): To measure the T2 and T1 values of various tissues in vivo human knee at 0.05T. Approach: Multiple TE and TR measurements were conducted on a home-built and RF shielding-free 0.05T MRI scanner for T2 and T1 mapping through pixel-wise numerical fitting. Results: Phantom results exhibited a linear relationship between the Gadolinium concentration and relaxation rate, demonstrating the feasibility of mapping procedure. Additionally, the T2 and T1 values of cartilage, tendon, fat, and skeletal muscle in human knee were estimated and reported. Impact: The estimated Gadolinium T2 and T1 relaxivities at 0.05 Tesla are significantly higher than those at 1.5T and 3.0T, guiding the usage of contrast agent dose. Moreover, T2 and T1 mapping of musculoskeletal tissues can facilitate sequence design/optimization.
Automatic Estimation of Neonatal Ventricles-to-Brain Volume Ratio using AI for Monitoring Hydrocephalus
Authors: Farkash Gil , Onikul Alexey , Shimshovitz Asaf , Blecher-Segev Hila , Pratt Li-tal , Ben-David Eli , Zharkov Elena
Published: November 2024

Motivation: To propose a new approach for managing hydrocephalus in neonates based on neonatal MRI and AI-based brain ventricle volume quantitation, brain parenchyma volume and ventricle-to-brain volumes ratio. Goal(s): To evaluate the robustness of quantitative measurements of ventricle and brain volumes using AI-based algorithms, on scans acquired on a 1 Tesla permanent magnet neonatal MRI. Approach: The performance of three AI-based segmentation algorithms was evaluated using linear correlations and Intersection over Union (IoU) score between ground truth and predictions. Results: Results show high linear correlations between ground truth and algorithm predictions, validating the use of these volumetric measurements to monitor hydrocephalus longitudinally. Impact: An AI based method for segmenting neonatal MRI images may provide volumetric quantitation and enable fast and accurate decision making on surgical intervention in preterm infants with hydrocephalus.
Edited MRS of the Infant Brain on 28 Scanners
Authors: Murali-Manohar Saipavitra , Zöllner Helge J. , Davies-Jenkins Christopher W. , Gudmundson Aaron T. , Hui Steve C.N. , Song Yulu , Gagoski Borjan , Tisdall M. Dylan , Saleh Muhammad G. , Weldon Kimberly B. , Rosenberg Jens T. , Noeske Ralph , Clarke William T. , Oeltzschner Georg , Wisnowski Jessica L. , Edden Richard A.E.
Published: November 2024

Motivation: The Healthy Brain and Child Development (HBCD) study is a longitudinal, multi-vendor, multi-site study of early brain development, which will enroll ~7,500 infants. HBCD includes MRS within the imaging protocol. Goal(s): The goal of this abstract is to present HBCD MRS pilot data, and identify any vendor and site differences in MRS data quality and measured metabolite concentrations. Approach: HBCD pilot MRS data were successfully acquired on 28 scanners, and analyzed using Osprey 2.5.0, to examine vendor and site differences. Results: ANOVA results show minimal vendor and site differences which is encouraging for such a large-scale multi-site, multi-vendor study. Impact: HBCD is an NIH-funded multicenter study of brain development across the first decade of life. It is the largest ever study to incorporate MRS. In this abstract, we present in vivo data demonstrating MRS performance across vendor and site.
19F-Magnetic Resonance Spectroscopy to evaluate antidepressant exposure & patient-level factors affecting adolescent brain disposition
Authors: Stancil Stephani , Leeder J. , Lee Phil , Brooks William , Tumberger John , Bartkoski Michael , Hunsinger Frank , Carrothers Kerry , Choi In-Young
Published: November 2024

Motivation: Medication response in adolescent depression is unpredictable and relationships between dose, brain concentrations and clinical response are unknown. Goal(s): 19F-MRS is uniquely suited to study pediatric brain disposition, as it’s non-invasive, non-radiolabeled and less than minimal risk. Approach: Youth (n=52) aged 12-21 taking fluoxetine completed 19F-MRS at 3T. Results: Brain fluoxetine concentrations exceeded plasma concentrations by 9 to 304-fold. Dose-normalized brain concentrations varied 13-fold, explained by plasma concentration and dose with small contributions from BMI, CYP2D6 and ABCB1. 19F-MRS is a valuable tool for studying pediatric brain disposition of fluorine-containing medications and enables inquiry into patient factors that impact brain exposure and response. Impact: In vivo 19F-MRS measures brain concentrations of fluorine-containing medications and enables inquiry into individual-level factors contributing to brain disposition. This approach fills a critical gap in pediatric drug development, especially where other imaging modalities (e.g., PET) are not feasible.
Diffusion tensor cardiovascular magnetic resonance with monopolar spin-echo at ultra-high gradient strength Connectom scanner
Authors: Paul Shubhajit , Ferreira Pedro , Evans John , Escobar Camila , Fasano Fabrizio , Pennell Dudley , Nielles-Vallespin Sonia , Scott Andrew
Published: November 2024

Motivation: Spin-echo (SE) diffusion tensor cardiovascular magnetic resonance (DT-CMR) imaging with monopolar diffusion encoding scheme is limited by bulk motion induced signal loss. Goal(s): Utilization of ultrahigh gradient-strengths to substantially reduce the echo-time (TE) in monopolar SE DT-CMR. Approach: A monopolar SE DT-CMR pulse-sequence was developed. An in-vivo study at ultra-high gradient-strength (180mT/m, Connectom scanner) for diastolic cardiac phases was conducted. Results: With ultra-high gradient strength, it was possible to obtain reasonable DT-CMR data with monopolar SE in 60% of subjects. To our knowledge this is the first report of SE DT-CMR with monopolar diffusion encoding utilizing the ultra-high gradient-strength of the Connectom scanner. Impact: The ability to acquire monopolar SE using ultra-high diffusion gradient strengths and the associated drastic reductions in TE may provide substantial increase in imaging efficiency for DT-CMR acquired in diastolic cardiac phases, a key step towards clinical translation.
Submillimeter in vivo human brain diffusion MRI at 500 mT/m with concurrent field monitoring
Authors: Ramos-Llordén Gabriel , Mahmutovic Mirsad , Park Daniel J. , Maffei Chiara , Ma Yixin , Lee Hong-Hsi , Wald Lawrence L. , Witzel Thomas , Keil Boris , Huang Susie Y.
Published: November 2024

Motivation: High-fidelity, artifact-free diffusion MRI (dMRI) in high-performance gradient systems requires more advanced encoding and reconstruction approaches than those widely used. Goal(s): To achieve ghosting- and eddy current distortion-free in vivo submillimeter human brain dMRI with concurrent field monitoring. Approach: A 16-ch clip on field probe system was integrated onto custom-built 72ch to map high-order field perturbations during the acquisition. SENSE-based reconstruction was informed with the monitored phase evolution as expressed in a 3rd-order spherical harmonic model. Results: Concurrent field monitoring reconstruction reduces non-linear Nyquist ghosting and geometric distortions generated by high-order eddy currents from ultra-strong diffusion gradients. Impact: We expect concurrent field monitoring to become essential in achieving high-quality image reconstruction as the adoption of high-performance gradients systems grows and image acquisition strategies evolve with more sophisticated image encodings.