bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Changes in Quantitative MRI with Time in Muscle Denervation of the Lower Extremities
Authors: Akerman Michelle , Igbinoba Zenas , Urban Casey , Lan Ranqing , Sneag Darryl , Tan Ek
Published: November 2024

Motivation: Quantitative muscle MRI (qMRI) metrics (T2, diffusion diameter, and fat fraction (FF)) are sensitive to tissue microstructure, and altered in denervated muscle. However, the time-dependencies of these metrics as they relate to denervated muscle have not yet been analyzed in humans. Goal(s): Assess patterns of qMRI changes in the lower extremity in denervated muscle. Approach: Muscles from 24 lower extremity exams (23 patients) were categorized as non-denervated or denervated (chronically- or acutely-involved) using electromyography findings. Results: Increased T2 in denervated muscles, and increased FF in chronically-involved muscles, and alternating patterns of diffusion diameter with time. Impact: Quantitative MRI changes in lower extremity denervated muscles may complement peripheral nerve MRI and electromyography by providing tissue sensitive information relevant to the extent of disease at specific timepoints from initial injury.
Application of 5 diffusion models in bladder cancer staging based on the date of diffusion spectrum imaging
Authors: Xu Chunmiao , Zhang Xiaoxian , Chen Xuejun , Wang Shaoyu
Published: November 2024

Motivation: The pathological grade of bladder cancer is closely related to the choice of treatment and the prognosis1. Diffusion spectrum imaging (DSI) is a newly developed model, which is helpful in distinguish benign and malignant tumors2. Goal(s): This study was to explore the quantitative parameter from DSI in differentiating pathology grade of bladder cancer. Approach: The differences of DSI quantitative parameter between high-grade and low-grade lesions and the differentiation performance of the indices were evaluated . Results: Quantitative parameters of DSI could effectively distinguish pathology grade of bladder cancer, and AUC ranged from 0.790 to 0.960. Impact: The quantitative parameters obtained from Diffusion spectrum imaging are more stable and can predict the pathological grade of bladder cancer better than traditional ADC.
Comparison of MUSE-DWI and Conventional DWI in the Application of Invasive Breast Cancer and Malignancy Grade Prediction: A Comparative Study
Authors: WANG WEICHENG , DOU bowen , zhao Wenjing , fang longjiang , Chu yujing , Pylypenko Dmytro
Published: November 2024

Motivation: MUSE-DWI was used to better display breast cancer and histological grade prediction.Goal(s): This study aim to compare MUSE-DWI and conventional DWI for evaluating invasive breast cancer lesions, focusing on ADC values for preoperative histological grading. Approach: It included 63 confirmed lesions, assessed for qualitative parameters like sharpness, artifacts, and distortion, and quantitative measures including SNR and ADC. The results demonstrated that MUSE-DWI significantly reduces artifacts and distortions, enhancing image quality. Moreover, it showed higher diagnostic efficacy in the preoperative histological grading of breast cancer. Results: MUSE-DWI was superior to SS-EPI-DWI in image display and histological grade prediction. Impact: Compared with SS-EPI-DWI, MUSE-DWI can display the lesions of invasive breast cancer more intuitively, and it has higher robustness to the histological grade of invasive breast cancer.
The analysis of kidney diffusion patterns with non-linear least square method in AKI
Authors: Mei Yingjie , Guo Yihao , Wu Shuyu , Wu Zhigang , Luo Wei , Tan Xiangliang , Wang Guangyi , Liu Zaiyi
Published: November 2024

Motivation: Diffusion components and the initial values must be specified in advance in IVIM, which might not be sensible in tissues with complicated diffusion characteristics. Goal(s): To reveal the changes of diffusion patterns of kidney in acute kidney injury (AKI). Approach: Non-negative least squares (NNLS) method shown to derive the number of compartments from the data, rather than to impose it in the analysis of diffusion signals was employed. Results: The volume fraction of tubular or/and vascular decreased significantly and restricted tissue water diffusion was detected in AKI. Impact: Our results suggest that NNLS model is potentially a valuable tool for accurate description of diffusion in kidney.
A Computational Investigation of DSC-MRI Signals From 3D Tissue Structures with Varied Cellular Features
Authors: Patel Reshmi , Semmineh Natenael , Quarles C.
Published: November 2024

Motivation: Dynamic susceptibility contrast (DSC) MRI is a robust method for imaging brain tumors, and there is potential to glean more clinically useful data than is obtained with standard-of-care DSC-MRI. Goal(s): We aimed to systematically investigate the effect of varied cellular features on the difference in DSC-MRI-derived ΔR2* time curves to evaluate the feasibility of recovering these features in real tissue. Approach: We generated 3D tissue structures of ellipsoids (determined by specified parameters and randomly distributed) and applied the finite difference finite perturber method to compute ΔR2*. Results: In general, ΔR2* increased then plateaued as cell volume fraction, aspect ratio, and size increased. Impact: We simulated T2*-weighted DSC-MRI signal for 3D tissue structures with varied cellular features to evaluate the feasibility of recovering these features in real tissue. Results suggested that cell volume fraction, aspect ratio, and size may be identifiable biomarkers.
Comparing R2* and QSM at 9.4T for the ability to detect increased deoxyhemoglobin (hypoxia) in the mouse brain
Authors: Makarowski Ty , Sun Hongfu , Dunn Jeff
Published: November 2024

Motivation: Investigating R2* and QSM for deoxyhemoglobin detection is vital for diagnosing and understanding diseases where tissue oxygenation is frequently compromised. Goal(s): To evaluate R2* against QSM for their ability to detect deoxyhemoglobin changes in a controlled hypoxic environment using a mouse model. Approach: Employ a graded hypoxia protocol in naïve, female C57Bl/6 mice, capturing 3D MGE images at various oxygen levels (30%, 15% and 10%) to measure R2* and QSM responses. Results: R2* demonstrated significant sensitivity to hypoxia in brain regions, particularly the hippocampus, unlike QSM, suggesting its potential as a superior hypoxia biomarker. Impact: This study reveals R2* relaxometry's superior sensitivity to the detection of changes in deoxyhemoglobin over QSM, potentially improving early detection and monitoring of hypoxia-related diseases, such as Multiple Sclerosis, and informing future clinical imaging protocols.
Analysis of Iron Accumulation in MAPT- and C9orf72-associated Frontotemporal Lobar Degeneration: QSM, T2*-w MRI, and Histology
Authors: Prinse Fieke , Giannini Lucia , Bulk Marjolein , Suidgeest Ernst , Dijkstra Kyra , van Buuren Renee , Dopper Elise , Seelaar Harro , van der Weerd Louise
Published: November 2024

Motivation: Ex-vivo histology is the most common method to assess iron accumulation in frontotemporal lobar degeneration, but in vivo assessment is crucial to unravel disease mechanisms. Goal(s): This study aims to assess the distribution and severity of iron accumulation post-mortem using susceptibility MRI and compare this to histological data. Approach: We analyzed postmortem tissue of 5 MAPT-FTLD and 2 C9orf72-FTLD cases using a histological iron staining, T2*-weighted MRI, and QSM maps. Results: We found that histology, susceptibility MRI, and QSM show good correspondence of iron distribution in FTLD brain tissue. However, sharp details are better seen on T2*-weighted MRI, and U-fibers on QSM maps. Impact: Our study showed that susceptibility-based imaging can be used to visualize iron accumulation in FTLD; with T2*-weighted MRI and QSM showing complementary spatial information. Therefore, these two methods should be used parallel and not independent of each other.
Repeatability of susceptibility separation methods in brain at 3 T
Authors: Naji Nashwan , Snyder Jeff , Seres Peter , Beaulieu Christian , Wilman Alan
Published: November 2024

Motivation: Susceptibility separation methods aim to separate co-existing myelin and iron contributions. However, their repeatability has not been investigated. Goal(s): Evaluating repeatability of existing separation methods in brain and comparing their performance. Approach: Three methods (χ-Sep, χ-SepNet, and APART) were applied to 3T scan-rescan data of 21 healthy subjects, and the resultant dia- and paramagnetic maps were evaluated in white and deep gray matter regions. Results: Reliability varied by method and region, with many regions showing moderate to good reliability. Average repeatability coefficients were 4 ppb and 8 ppb in white matter and iron-rich deep gray regions, respectively. Impact: Susceptibility separation methods showed moderate to good reliability in most brain regions, and sub-voxel changes around 5 ppb might be error. Comparing values reported using different methods might not be straightforward, as the difference between measurements could exceed 15 ppb.
Glymphatic dysfunction in non-dialysis, hemodialysis and peritoneal dialysis patients with ESRD is associated with cognitive decline
Authors: Hao Wang , lijun Song , Wenbo Yang , Boyan Xu , Zhenchang Wang
Published: November 2024

Motivation: The glymphatic function has not yet been explored in non-dialysis,HD and PD patients with ESRD. Goal(s): Our goal was to explore the pattern of glymphatic function in ESRD patients and its relationship with cognitive decline. Approach: Diffusion tensor imaging along the perivascular space (DTI-ALPS) index methods was used to investigating brain glymphatic dysfunction in ESRD patients with non-dialysis, HD and PD patients using. The relationship between Montreal Cognitive Assessment (MoCA) and changes in DTI-ALPS index was measured. Results: Compared with HD and PD, ESRD patients with non-dialysis showed lower DTI-ALPS index.Changed DTI-ALPS index associated with cognitive decline in ESRD patients with non-dialysis. Impact: Our findings reveal a greater degree of aberrant glymphatic functionality in ESRD patients with non-dialysis than HD and PD, which may offer new insights to the effectiveness of dialysis treatment.
Evaluation of Imaging Difference in Glymphatic System between Motor Symptoms and Levodopa Responsiveness of Parkinson's Disease
Authors: Deng Jinhuan , Lin Fan , Deng Kan , Wu Peng , Chan Queenie
Published: November 2024

Motivation: Growing evidence has shown that glymphatic dysfunction is closely linked to Parkinson’s disease(PD), yet its imaging in glymphatic system with motor symptoms remains unclear. Goal(s): Using three different imaging metrics to validate the association of the glymphatic system with motor symptoms before and after administration of exogenous levodopa, and levodopa responsiveness in PD. Approach: The calculation of DTI-ALPS index, the automated quantification of PVSs of basal ganglia region (BG-PVSs) and choroid plexus volume (CPV) based on MRI. Results: When DTI-ALPS index decreases and BG-PVSs and CPV increase, motor symptom gets worsen and levodopa effectiveness diminishes. Significant linear correlations were observed (CPV-DTI-ALPS, CPV-PVSs, DTI-ALPS-PVSs). Impact: This study employed three distinct imaging metrics (DTI-ALPS index, automated PVSs quantification, and CPV) to provide a more comprehensive characterization of the glymphatic system, affirming a correlation between glymphatic dysfunction and motor symptoms in Parkinson's patients.
Dynamic distortion correction of ME-EPI using learning-based single-scan multi-echo blip up-down acquisition (ME-BUDA)
Authors: Ge Nuowei , Yang Qinqin , Wu Zejun , Bao Jianfeng , Wu Zhigang , Cai Congbo , Cai Shuhui
Published: November 2024

Motivation: Multi-echo (ME) fMRI approaches based on ME-EPI acquisition achieve higher BOLD sensitivity and reproducibility than traditional EPI. However, ME-EPI suffers from severe image distortion. Goal(s): To develop a technique to correct ME-EPI distortion artifacts in single scan. Approach: We developed a deep learning-based technique to correct ME-EPI distortion artifacts using single-scan multi-echo blip up-down acquisition (ME-BUDA). The proposed method was suitable for both spin- and gradient-echo-based EPI and was validated in simulation, human brain and additional dynamic imaging experiments. Results: For simulation experiment, the PSNR and SSIM were 33.31 and 0.98, respectively. For in vivo dynamic imaging, the temporal SNR increased by 75%. Impact: The ME-BUDA method can reliably correct the geometric distortion of dynamic ME-EPI images without additional information, ensuring the distortion-free, real-time, and high-quality ME-fMRI analysis of important function regions.
Leveraging Compressed Sensing for Improvement of FIDDLE Image Quality Rather Than for Acquisition Speed
Authors: Rehwald Wolfgang , Pang Jianing , Rojas Rafael , Swanson Julie , Wendell David , Pirela Sherilyn , Dement Jeana , Klem Igor , Kim Raymond
Published: November 2024

Motivation: Imperfect breath holding and cardiac arrhythmia create chest wall and cardiac ghosting in conventional segmented dark-blood LGE images (FIDDLE) often rendering them non-clinical. Goal(s): We aimed to apply compressed sensing ‘CS’ as the solution to this problem, to acquire FIDDLE images without ghosting, even in challenging patients. Approach: CS can acquire multiple high-spatial and excellent-temporal resolution single shots that intrinsically never display ghosting artifacts. Sparsity is created along the shot dimension, enabling CS to reconstruct the generally not-so-sparse FIDDLE images. Single shot averaging further improves SNR. Results: The CS FIDDLE images show high SNR and no ghosting. They should simplify clinical imaging. Impact: The CS FIDDLE method should improve clinical CMR image quality and alleviate the need for repeated acquisitions due to poor breath holding. It also enables using CS for the acquisition of single still-frame images with intrinsically higher SNR.
A deep-learning-based framework for spark artifacts detection and correction
Authors: Tong Li , Wang Puwei , Zhu Lei , Qin Shucheng , Wang Zhenkui
Published: November 2024

Motivation: The occasional occurrence of spark artifacts in MRI could significantly hinder diagnosis. Previous whole K-space segmentation methods are unstable and require stringent intensity normalization. Goal(s): In this study, we aim to improve the accuracy and stability of spark identification, especially for sparks with low intensities and near the K-space center. Approach: We propose a two-step deep learning-based framework consisting of spark patch classification and patch-level spark segmentation, which are further corrected by ESPIRiT. Results: The proposed methods are demonstrated to be effective and robust on various imaging protocols and body parts for different degrees of spark artifacts. Impact: Incidental spark artifacts in MRI can significantly hinder diagnosis. We developed a deep-learning-based two-step framework for robust spark detection and correction, which has been validated to be effective on a variety of imaging protocols for different degrees of spark artifacts.
A deep-learning-based Signal-to-Noise Ratio (SNR) adaptive uniformity correction method
Authors: Tong Li , Wang Puwei , Wang Zhenkui
Published: November 2024

Motivation: Intensity normalization in MRI is crucial for consistent image analysis. However, naïve uniformity correction (UC) using pre-collected coil sensitivity distribution may over-compensate low-SNR regions and reduce visual quality. Goal(s): This study aims to develop an SNR-adaptive UC method to prevent over-compensation in low-SNR regions. Approach: We propose using a deep network to learn an SNR-aware uniformity correction map by suppressing over-compensation on low-SNR regions. During training, the original uniformity correction map is used to guide the weighing between consistency loss and over-compensation suppression loss. Results: The proposed method has been demonstrated to effectively suppress over-compensation on low-SNR regions in various head imaging protocols. Impact: The proposed method can improve MRI image quality by adaptively compensating for intensity variations based on the noise level in different regions. It may lead to more accurate diagnoses and better identification of subtle changes in MRI images.
Motion Correction in Multi-shot Acquisitions by Removal of Motion-ridden Shots to fill with Unrolled DL Reconstruction
Authors: Goel Megha , Chatterjee Sudhanya , Rajamani Sajith , Ramanna Sudhir , Shankpal Preetham , C Florintina , Agarwal Harsh , Shaik Imam , Joel Suresh
Published: November 2024

Motivation: Motion is the primary reason for artifacts in MRI. Goal(s): The proposed method is an attempt at solving motion correction problem for 2D-acquisitions by dropping motion-corrupt sections of k-space to be reconstructed in a fashion similar to under-sampled reconstruction by an unrolled DL framework. Approach: The estimation of motion-corrupt shots is proposed using: (a) camera tracking, (b) data relationships between channels, (c) navigator shots. Using these methods to find the dominant pose and outlier shots, reconstruction using an unrolled DL network would fill in for the corrupt k-space shots . Results: The method shows significant motion correction for T1/T2 FSE/FLAIR sequences. Impact: The proposed solution has the potential to save tens of thousands of dollars per year per scanner. Breaking up the problem into separate sub-problems can be investigated further, along with the various detection methods mentioned.
Motion correction with subspace-based self-navigation for combined angiography, structural and perfusion imaging using ASL
Authors: Shen Qijia , Wu Wenchuan , Woods Joseph , Chiew Mark , Ji Yang , Okell Thomas
Published: November 2024

Motivation: Perfusion and angiographic images using arterial spin labeling (ASL) are particularly susceptible to head motion. Goal(s): To correct motion for Combined Angiography, Structural and Perfusion using Radial Imaging and ASL (CASPRIA) and reduce motion induced aliasing and blurriness for angiographic, perfusion and structural imaging. Approach: 3D navigators are reconstructed after each ASL preparation using subspace to account for varying contrast. These are used to correct the raw data for motion. A joint label and control reconstruction was formulated to generate motion corrected perfusion and angiographic images. Results: Motion induced artefacts and blurriness were greatly reduced in angiographic, structural and perfusion data. Impact: Motion robustness of CASPRIA sequence was improved, facilitating future clinical application with less cooperative patients.
Motion Tracking inside the MRI scanner using gradient artifacts in EEG-fMRI
Authors: Rezaei-Dastjerdehei Mohammadreza , LeVan Pierre
Published: November 2024

Motivation: Motion tracking in EEG-fMRI has been a challenging area of research in recent years, with existing approaches frequently suffering from limitations in spatial and temporal resolution or requiring additional hardware or calibration scans. Goal(s): We aim to introduce a motion-tracking approach by modelling the gradient artifacts induced in EEG recordings during EEG-fMRI studies. Approach: We introduce an algorithm tailored for detecting rigid and non-rigid head motion in EEG-fMRI data and aim to assess its performance by comparing it with camera-based motion detection techniques. Results: We have demonstrated the capability of our algorithm to accurately identify motion in EEG-fMRI. Impact: Our method shows potential across a range of uses, such as enhancing EEG data quality, especially in the context of reducing motion-related artifacts in EEG-fMRI studies.
Simultaneous Contrast-Free 3D Aortic Lumen and Vessel Wall Imaging at 0.55T at systole and diastole
Authors: Paredes Matías , Castillo-Passi Carlos , Kunze Karl , Botnar Rene , Prieto Claudia
Published: November 2024

Motivation: Bright-blood and black-blood imaging are relevant for assessing aortic pathologies. Research on aortic imaging at 0.55T which could potentially make MRI more accessible and affordable is scarce. Goal(s): To evaluate the feasibility of a novel non-contrast enhanced simultaneous bright- and black-blood aorta imaging at 0.55T at systole and diastole. Approach: Five healthy volunteers were scanned at 0.55T with the proposed accelerated and non-rigid motion-compensated sequence (iT2prep-BOOST). Adiabatic, MLEV4 and MLEV8 T2-preparation pulses were compared. Results: Good image quality was obtained for simultaneous acquisition of 3D bright- and black-blood aorta imaging at 0.55T at systole and diastole with the proposed iT2prep-BOOST and MLEV8 T2-preparation. Impact: The proposed approach enables 3D simultaneous bright- and black-blood aorta imaging at 0.55T during a fast free-breathing scan and thus shows promise for the detection of different aortic diseases, potentially making aortic MRI more accessible and affordable.
Quantitative and Qualitative Correlation of 0.55T MRI to CT for Normal Anatomic Structures and Common Pulmonary Pathologies
Authors: Tang Felicia , Chen Timothy , Ebrahimzadeh Sayedomid , Fields Brandon , Liu Jonathan , Lee Yoo Jin , Yen Adam , Bowers Kiara , Schonour Brandon , Su Pan , Larson Peder , Yang Yang , Sohn Jae Ho
Published: November 2024

Motivation: Although MRI has had low adoption in lung imaging due to susceptibility artifacts, limiting its utility in pulmonary parenchymal imaging, low-field MRI (0.55T) has potential to address those limitations. Goal(s): However, its thoracic diagnostic capabilities remain indeterminate, so our goal was to compare its ability to detect common lung pathologies to chest CT and provide comparable quantitative measurements. Approach: Structures and pathologies were measured with both modalities, and two radiologists identified lung pathologies with MRI only. Results: Results indicated that readers were able to detect pathologies using 0.55T MRI, serving as a first step in exploring 0.55T MRI as an alternative modality. Impact: Our study revealed potential for 0.55T MRI as an emerging tool for MR-based anatomic evaluation of the lung, and its limitations. This can expand lung imaging options and potentially provide better tissue characterization for diagnoses like lung cancer.
Cardiac MRF for Simultaneous T1, T2 and Fat-Fraction Quantification at 0.55T
Authors: Pedraza Diego , Castillo-Passi Carlos , Araya Nicole , Velasco Carlos , Botnar René , Prieto Claudia
Published: November 2024

Motivation: Cardiac MRF is a powerful imaging-technique that allows for comprehensive myocardial tissue characterization in a single-scan and has been proposed at 1.5T and 3T. However, cMRF has not been demonstrated at lower-field yet. Goal(s): Investigate the feasibility of a Dixon-cMRF sequence for simultaneous T1, T2 and fat-fraction quantification at 0.55T. Approach: Dual-echo spoiled-GRE-acquisition with varying IR-T2-preparation pulses. Experiments were performed on standardized phantoms and with 5 healthy volunteers and compared with spin-echo references. Results: T1, T2 and fat-fraction Dixon-cMRF at 0.55T was tested with phantoms and with healthy subjects, showing good agreement with reference values in phantom and promising results in healthy subjects. Impact: The simultaneous quantification of T1, T2 and fat-fraction at 0.55T in a single cardiac-MRF of 15s could provide an alternative to higher field scanners, allowing for a more accessible way to assess cardiovascular disease.
Initial Experience Using 0.55T MRI for Detection of Liver Metastases in NET Patients
Authors: Remick Isabelle , Ohliger Michael , Hong Cheng , Yang Yang , Heath Courtney Lawhn , Su Pan , Itriago-Leon Pedro , Bergsland Emily , Hope Thomas
Published: November 2024

Motivation: As assessment of liver metastases requires multiple imaging modalities, it is essential to compare diagnostic capabilities and patient experiences of the low-cost 0.55T MRI to conventional imaging techniques. Goal(s): We analyzed the sensitivity for neuroendocrine tumor metastases detection of gadoxetate-enhanced 0.55T MRI to 68Ga-DOTATATE PET/CT and 3.0T MRI while evaluating patient experienceApproach: Patients were imaged on 0.55T MRI with 68Ga-DOTATATE PET/CT and/or 3.0T MRI for comparison. Sound pressure levels (SPLmax) were compared between 0.55T and 3.0T. Results: Hepatobiliary phase imaging at 0.55T showed increased detection rates over 68Ga-DOTATATE PET/CT. SPLmax of 0.55T was significantly lower. Patients found the 0.55T MRI less stressful. Impact: Routine imaging of patients with neuroendocrine tumor metastases is feasible at 0.55T MRI. Low-field MR imaging has the potential to improve patient experience and accessibility without sacrificing diagnostic capability.
Multi-Channel PROPELLER-MRI Acceleration using NUFFT Compressed Sensing at Mid-Field MRI of 0.5T
Authors: Jain Nitin , Das Rajdeep , Agarwal Harsh , Rajamani Sajith , Venkatesan Ramesh
Published: November 2024

Motivation: Mid-field MRI have lower SNR so data acquisition is associated with longer data acquisition time. Therefore, develop fast imaging technique with motion robust data acquisition with minimal SNR penalty due to fast imaging. Goal(s): Develop a robust image reconstruction technique for compressed sensing (CS) accelerated PROPELLER acquisitions. Approach: A new iterative reconstruction technique based on NUFTT and CS for PROPELLER acquisitions. Results: MRI imaging of ISMRM-NIST phantom and volunteer scan were acquired and reconstructed with minimal under-sampling artifacts such as haze and streaks with PROPELLER acceleration. Impact: Compressed sense accelerated PROPELLER can acquire high quality motion robust MRI images at mid-field MRI. Proposed MR image reconstruction technique for compressed sensing accelerated PROPELLER technique can enable acquisitions requiring longer scan time due to SNR.
In vivo Breast T1 Mapping at Ultra-Low Field (6.5 mT): Variable Flip Angle Method
Authors: Shen Sheng , Koonjoo Neha , Saksena Mansi , Ogier Stephen , Boele Thomas , Keenan Kathryn , Rosen Matthew
Published: November 2024

Motivation: The fractional T1 differences between healthy and abnormal tissue are significant larger in the ultra-low-field (ULF) regime (<10 mT) compared to high field. Goal(s): Despite the challenges of imaging at ULF (predominately low SNR and spatial-temporal resolution), we demonstrate in vivo T1 mapping in the breast at 6.5 mT in 43 minutes. Approach: A variable flip angle (VFA) method with B1 correction was used. Results: T1 mapping of CuSO4 solutions showed an average T1 deviation <7% compared to reference T1 measurements. Breast phantom T1 mapping was also performed. Finally, this method was applied on two healthy female volunteers. Impact: This work explores ultra-low field T1 mapping as potential biomarker for low-cost breast imaging. We demonstrate the feasibility of quantitative T1 mapping of the human breast in healthy female volunteers at 6.5 mT using a variable flip angle method.
Point-wise k-space evaluation for spatial encoding magnetic fields for magnet optimizations
Authors: Liang Tingou , Yang Junqi , Li Bing Keong , Li Erping , Yu Wenwei , Huang Shao Ying
Published: November 2024

Motivation: The current optimizations of permanent magnet array (PMA) designs are guided by checking field properties, not reflecting the quality of reconstructed images. Goal(s): We aim to propose indicating parameters for the encoding capability of spatial encoding magnetic fields (SEMs) to guide PMA designs. Approach: Local k-spaces are pushed to be point-wise. The coverage area of the point-wise k-spaces between the spokes of the maximum and minimum angles is calculated to indicate the encoding capability. Results: The proposed method is fast, enlarging the optimization space, resulting in SEMs having superior encoding capability with stronger field, higher gradient, and lower NRMSE of the resultant images. Impact: The proposed point-wise k-space evaluation enlarges the solution space for the PMA optimizations thus significantly improves the performances of the outcomes, i.e., SEMs having superior encoding capability with higher field strength and higher gradient compared to that from conventional approachs.
Improved Tx Efficiency in Mock Transcranial MRgFUS with Modified Transfer Medium & Transducer Ground at 3T: Improved Results with Updated Phantom
Authors: Lakshmanan Karthik , Walczyk Jerzy , Carluccio Giuseppe , Collins Christopher
Published: November 2024

Motivation: In MRI at 3T, the typical configuration of MR-guided focused Ultrasound (MRgFUS) results in a dark band through the brain in MRI. Goal(s): We introduce an approach to significantly improving MRI in the whole brain in addition to removing the dark band artifact, demonstrating here with an improved phantom for better results. Approach: An improved phantom for experimental validation of our method was developed by using a spheroidal compartment rather than a hemispherical compartment to represent the head. Results: Transmit Efficiency was improved by more than a factor of 4 on average in the ROI using our proposed method. Impact: By strategically adjusting electric permittivity of the transfer medium and slotting the transducer ground plane, transmit efficiency of MRI in transcranial MRgFUS can be improved by a factor of up to 4 while also eliminating a well-known dark band.
Extrapolated-B1-corrected Variable Flip Angle T1 Mapping in Cortical Bone with a Phase-Sensitive Method
Authors: Chen Sheng , Gilbo Yekaterina , Sporkin Helen , Fielden Samuel , Allen Steven , Mugler John , Miller G. , Meyer Craig
Published: November 2024

Motivation: Unintended heating of the skull and nearby soft tissue during transcranial MR-guided Focused Ultrasound surgery needs to be monitored. However, T1-based thermometry in cortical bone may be biased with variable flip angles. Goal(s): Our goal was to correct flip angles to improve the T1 mapping accuracy in cortical bone. Approach: In phantom and human studies, B1 maps of soft tissue were measured with a phase-sensitive method, extrapolating from which B1 maps of bone were generated and were used to correct flip angles for T1 mapping. Results: Improved accuracy and homogeneity of T1 maps were demonstrated as validation. Impact: Extrapolated-B1 correction with a phase-sensitive method should improve accuracy and homogeneity of T1 maps in cortical bone and is promising in monitoring unintended heating in the skull and nearby brain tissue during transcranial MR-guided Focused Ultrasound surgery.
Cardiac MR-thermometry with integrated catheter drift detection for guidance of ventricular tachycardia ablation
Authors: Rogers Charlotte , Mooiweer Ronald , Shankar Rohini Vidya , Tripp Donovan , Razavi Reza , Botnar René , Roujol Sébastien
Published: November 2024

Motivation: MR-thermometry is a promising approach for real-time monitoring of lesion formation during MRI-guided cardiac ablation. However, ablation catheters can potentially drift during ablation and lead to inaccurate lesion formation. Goal(s): To develop a cardiac MR-thermometry sequence with integrated catheter drift detection. Approach: Continuous active tracking modules were added between the cardiac triggered acquisitions of a cardiac MR-thermometry sequence. Low-pass temporal filtering of the active tracking signal was then applied to remove cardiac and respiratory components and estimate catheter drift. This approach was evaluated in a phantom. Results: This study showed that catheter drift detection is possible within active tracking in an MR-thermometry sequence. Impact: This study demonstrates the potential for simultaneous catheter drift detection and cardiac MR-thermometry, which may improve the safety of the procedure and the accuracy of lesion formation. Further evaluation in-vivo is now warranted.
MRI-guided histotripsy targeting using MR-thermometry and MR-ARFI
Authors: Gupta Dinank , Kaovasia Tarana , Allen Steven , Hall Timothy , Xu Zhen , Noll Douglas
Published: November 2024

Motivation: Transcranial histotripsy requires pre-therapy targeting to ensure treatment at the intended region of interest. MR-ARFI and MR-Thermometry are used for targeting HIFU treatments, but are not tested for targeting of transcranial histotripsy treatments since they use different ultrasound treatment parameters. Goal(s): We evaluate the accuracy of MR-thermometry and MR-ARFI for targeting histotripsy treatments in ex-vivo tissues. Approach: Low intensity MR-thermometry and MR-ARFI were done prior to histotripsy treatment on bovine brain tissues. The lesion location was compared with the peak temperature/displacement to quantify targeting error. Results: Both MR-thermometry and MR-ARFI can perform accurate targeting of histotripsy treatments with mean errors of 2mm. Impact: Transcranial histotripsy is a promising non-invasive treatment method that requires pre-treatment targeting to ensure treatment delivery at the desired location. We showed that both low temperature MR-thermometry and MR-ARFI can be used to accurately estimate histotripsy treatment location.
Systematic Automated Evaluation of Needle Artifacts at 0.55 T, 1.5 T, and 3 T
Authors: Dong Fang , Faust Jonas , Maier Florian
Published: November 2024

Motivation: Numerous studies have investigated the appearance of MRI-compatible needles for interventional MRI. Needle artifacts were evaluated manually, which is a time-consuming process and prone to inter-reader deviations. Goal(s): Our goal was to introduce an automated method for evaluating needle artifact diameter, aiming to simplify artifact assessment. Approach: An automatic evaluation of needle artifacts was implemented and validated by conducting a systematic investigation of needle artifacts in a phantom study. Results: A comprehensive chart of needle artifact diameter for various image parameters was generated automatically, serving as a tool for needle comparison. The results indicate excellent algorithm reliability. Impact: The proposed tool allows for a systematic characterization of needle artifact size with high reliability and efficiency, which could be used to guide the correct choice of needle in different use cases (balance between artifact and lesion visibility)
Optimizing catheter based pulse application for intra-Arterial-Spin-Labeling in coronary arteries
Authors: Spreter Felix , Reiss Simon , Fischer Johannes , Özen Ali , Maier Alexander , Bock Michael
Published: November 2024

Motivation: Intra-Arterial-Spin Labeling (iASL) could offer an alternative for myocardial perfusion measurements without the use of contrast agents by labeling blood with a catheter transmit RF-coil. Goal(s): To study the parameters influencing the iASL labeling efficiency inside the artery to improve the SNR. Approach: The complex iASL process is investigated with simulations and in-vitro measurements for different coil geometries (solenoid, loop), driving currents, coil orientations relative to the magnetic field, and blood flow velocities. Results: The simulations were in good agreement with measurements, show a maximal mean flip angle created by the labeling pulse of 105°, and a threshold behavior for the transmit current. Impact: The improvement of the labeling process inside coronary arteries started in this study, is an important step towards making ASL a viable method for myocardial perfusion quantification.
Time-Frequency Multiplexed Wideband Array Beam-Forming Enhances Thermal Magnetic Resonance Theranostics of Brain Tumors
Authors: Saha Nandita , Kuehne Andre , Niendorf Thoralf
Published: November 2024

Motivation: Thermal magnetic resonance theranostics combines diagnostic MRI with targeted thermal therapy with an integrated radiofrequency applicator. Precise RF dosimetry is crucial for real-time treatment planning. Goal(s): Our goal is to evaluate a time-frequency multiplexing wideband RF beamforming method for precise targeting of small and large deep-seated brain tumors for Thermal Magnetic Resonance theranostics. Approach: We employed a multi-vector field shaping algorithm for optimizing RF channel settings of the RF applicator. Results: With time-frequency multiplex excitations, we achieved precise SAR10g targeting in the tumor volume while minimizing RF exposure to healthy tissues. Our study advances thermal magnetic resonance theranostics efficacy promising improved outcomes. Impact: Our approach of utilizing horse-shoe shaped RF applicator comprised of wideband SGBT dipole antenna can be conveniently adapted to individual patient's tumor position and geometry while maintaining the efficiency and quality of RF heating for ThermalMR theranostics of brain tumors.
Interactions and heating time-course of cerebral aneurysm flow diverters during scanning at 7 Tesla
Authors: Igarashi Suguru , Chida Kohei , Matsuda Tsuyoshi , Takeda Kota , Hayakawa Susumu , Tsutsui Shota , Fujiwara Shunrou , Kubo Yoshitaka , Sasaki Makoto , Ogasawara Kuniaki
Published: November 2024

Motivation: Adverse interactions with static magnetic fields (e.g., displacement force and torque) and radiofrequency-induced heating during MRI have been resolved for 3T MR systems, but have yet to be assessed for 7T MRI. Goal(s): The present study aimed to assess displacement force and torque in the 7T static magnetic field and to clarify radiofrequency-induced heating during 7T MRI for two types of FDs. Approach: This study was conducted based on the ASTM standards. Results: Magnetic field interactions and heating on FDs during 7T MRI are acceptable from a safety perspective. Impact: This study based on ASTM standards showed magnetic field interactions and heating on FDs during 7T MRI are acceptable from a safety perspective.
Deep Learning-based Distortion Correction of Diffusion-weighted Imaging
Authors: Zhang Kuan , In Myung-Ho , Campeau Norbert , Erickson Bradley , Shu Yunhong
Published: November 2024

Motivation: Diffusion-weighted imaging (DWI) is typically based on single-shot echo-planar imaging (EPI), which is prone to magnetic field inhomogeneities-induced artifacts, such as geometric distortion and blurring. The multi-shot diffusion sequence, DIADEM, employing a dual spin-warp (SW) and EPI phase-encoding strategies, can produce distortion-free images at the cost of extended scan times. Goal(s): We proposed a deep learning-based distortion correction method for conventional DWI, using DIADEM as reference. Approach: The 3D neural network was trained to learn the mapping between the projections of the point-spread-function, PSF H(y,s) along the EPI phase-encoding (y) direction and the PSF-encoding (s) direction, respectively. Results: It demonstrated reduced geometric distortion. Impact: Conventional DWI sequence suffers from distortion caused by susceptibility. We proposed a deep learning-based distortion correction method, leveraging distortion-free DIADEM images as reference. Our method was demonstrated to reduce geometric distortion and imaging blurring without distortion calibration.
Alternating unrolling network using jointly low-rank and sparse tensor prior for accelerating dynamic MRI
Authors: Zhang Yinghao , Hu Yue
Published: November 2024

Motivation: The unrolling networks that combine low-rank (LR) and sparse priors have the potential to enhance the reconstruction performance. However, the underlying iterative algorithm for solving the model of joint LR and sparse constraint is complicated, resulting in redundant network structure. Goal(s): To propose a simple yet effective alternating unrolling framework that exploits jointly LR and sparse prior for robust reconstruction of highly accelerated dynamic MRI data. Approach: Instead of strictly unrolling the iterative algorithm, we propose a novel "DC-LowRank-DC-Sparse" alternating framework. Results: The proposed network (AlteRS-Net) outperforms the SOTA unrolling networks regarding both visualization and quantitative evaluation of PSNR and SSIM. Impact: A novel alternating framework for unrolling network of jointly low-rank and sparse prior is established for accelerating dynamic MRI. This alternating concept could serve as an inspiration for the design of unrolling networks that combine other priors in various applications.
A deep learning based super-resolution technique for MR image reconstruction in BLADE sequence
Authors: Pan Hang , Lan Nan
Published: November 2024

Motivation: Conventional super-resolution techniques are not applicable to magnetic resonance images reconstructed from BLADE sequences, where four corners of the k-space are missing. Goal(s): When BLADE data are fed into a common super-resolution model targeting ordinary Cartesian k-space data, strong Gibbs rings appear due to the truncation of k-space. On this basis, we propose a deep learning-based method specifically for the super-resolution task with BLADE data. Approach: We mainly used the Residual Density Network (RDN) and designed the downsampling method based on the characteristics of BLADE data. Results: Experimental results show that our model is able to predict high-resolution MR images with fewer artifacts. Impact: By applying our RDN-based model specifically adapted to BLADE data, the image matrix size can be increased by a factor of 2 to produce sharper images without increasing acquisition time.
The effect of fasting on renal phase contrast and arterial spin labelling
Authors: Alhummiany Bashair , Buckley David L. , Shelley David , Sharma Kanishka , Sourbron Steven
Published: November 2024

Motivation: Variations in dietary conditions can impact renal blood flow (RBF), but it is currently unknown whether fasting overnight can affect the measurement. A recent consensus for phase contrast (PC) advises against fasting, but similar consensus for arterial spin labelling (ASL) was not reached. Other laboratory tests might require fasting, leading to variability in preparation for MRI. It is therefore critical to understand whether fasting affects the measurementGoal(s): This study investigates the effect of fasting compared to the recommended MRI preparation. Approach: ASL and PC acquired in healthy volunteers. Results: No significant difference between fasting and consensus-preparation was found for RBF and perfusion. Impact: A strict control for diet may not be required for MRI studies measuring renal blood flow and perfusion using phase contrast and arterial spin labelling.
Virtual elastography based on an intravoxel incoherent motion for assessing chronic kidney disease
Authors: Chen Yueyao , Qi Ruirui , Liu Wenxi , Liang Qiumei , Luo Peiyin , Li Junfeng , Chen Qiuyi , Pan Jingtong , Qu Feifei , Qin Haodong , Wu Yanglei , Meng Fanqi , Lyu Hanqing
Published: November 2024

Motivation: Various b values of shifted apparent diffusion coefficients (sADC) and virtual magnetic resonance elastography (vMRE) were not validated for renal stiffness. Hence, a new method was required for assessing chronic kidney disease (CKD) noninvasively. Goal(s): To investigate the relationship between sADC and vMRE and the clinical indicators and diagnostic efficacy of CKD. Approach: The μdiff generated with sADC was used to quantify renal stiffness. The data were analyzed using Spearman, partial correlation, Mann–Whitney U test, and receiver-operating characteristic curves. Results: sADC and vMRE were effective in assessing renal function and diagnosing CKD, but distinctly at various b values. Impact: This study provides a reference b value for sADC and vMRE and suggests that vMRE could be used as a new noninvasive technique to assess chronic kidney disease.
Non-contrast assessment of pulmonary perfusion using pulsed arterial spin labeling on a 0.55T scanner
Authors: Javed Ahsan , Ramasawmy Rajiv , Bruce Christopher , Wang Haiyan , Campbell-Washburn Adrienne
Published: November 2024

Motivation: Pulmonary perfusion imaging requires ionizing radiation (CT) or gadolinium-based contrast agents (MR) and therefore cannot be used on all patients.Goal(s): We propose an easy-to-prescribe non-contrast pulmonary perfusion imaging method to improve the diagnosis and monitoring of pulmonary hypertension.Approach: We designed a free-breathing arterial spin labeling imaging sequence that is compatible with whole-lung coverage at 0.55T. We demonstrate this method in healthy volunteers and a swine model. Results: We measured 11.55±4.09% and 7.76±2.62% ASL signals using inversion and saturation labeling which was comparable between breath-held and free-breathing scans. Perfusion defects were clearly visualized in the swine model. Impact: Our method should enable qualitative assessment of non-contrast pulmonary perfusion in patients who are contraindicated for gadolinium-based contrasts or who need frequent monitoring of pulmonary perfusion. Our method would contribute to enabling contrast-free comprehensive pulmonary exams at 0.55T.
A Preliminary Study of 3D Dynamic Enhanced MRI for Evaluation of the Vascular Architecture of Solid Solitary Pulmonary Nodules in the Lung
Authors: fu liang , ding haiming , zhang huiting , li kai
Published: November 2024

Motivation: DCE-MRI were used to valuate the vascular construction of solid solitary nodules (SPN) to help the qualitative clinical diagnosis. Goal(s): To evaluate the value of DCE-MRI in the vascular architecture of solid SPN. Approach: 32 patients with SPN underwent chest DCE-MRI. Pathological specimens and vascular structural parameter MVD and MPI were evaluated by immunohistochemical markers CD31, VEGF, and SMA. Results: Ktrans and Ve from DCE-MRI had significant differences between benign and malignant SPN, and high diagnostic efficacy with AUC of 0.893 and 0.880. Ktrans and Kep were significantly positively correlated with CD31-MVD and VEGF, while negatively correlated with MPI. Impact: Dynamic enhancement Magnetic resonance imaging can be used as an effective auxiliary means to distinguish benign and malignant pulmonary nodules.
Noise-induced Variability Quantification in Deep Learning-Based MRI Reconstructions
Authors: Dalmaz Onat , Desai Arjun , Chaudhari Akshay , Hargreaves Brian
Published: November 2024

Motivation: While noise propagation in linear imaging methods like SENSE is well-studied, similar analysis is not common in deep learning-based MRI reconstructions. Goal(s): Evaluate, characterize, and compare noise propagation in deep learning-based and linear MRI reconstruction under varying conditions. Approach: We uses Monte Carlo simulations to empirically analyze mean and variance of knee MRI images reconstructed by SENSE and deep learning methods. Results: SENSE yields unstructured, relatively-uniform noise distribution, while deep learning methods produce anatomically structured noise with substantial variability across tissues, acceleration factors, and noise levels. Noise-aware deep learning reconstruction shows more uniform noise propagation and reduced tissue-specific variability. Impact: Elucidating noise propagation in deep MRI reconstructions could direct algorithm refinement, optimizing image quality and reliability for clinical application. Simply reconstructing noise-propagation maps in routine protocols may help in image interpretation.
DeepSepSTI: Improved Susceptibility Tensor Reconstruction by Anisotropic Susceptibility Source Separation
Authors: Fang Zhenghan , Shin Hyeong-Geol , Dewey Blake , Calabresi Peter , van Zijl Peter , Sulam Jeremias , Li Xu
Published: November 2024

Motivation: Magnetic susceptibility source separation has potential for characterizing pathological tissue changes in disease. However, existing source separation methods assume isotropic susceptibility, ignoring anisotropy in white matter. Goal(s): To develop a method for anisotropic susceptibility source separation for better susceptibility tensor reconstruction. Approach: The paramagnetic susceptibility, modeled by an isotropic scalar, and the diamagnetic susceptibility, modeled by an anisotropic tensor, are jointly estimated in each voxel from local frequency and R2’ measurements using a deep learning model, named DeepSepSTI. Results: DeepSepSTI shows generally improved estimation of susceptibility tensors, anisotropy and PEV than DeepSTI. DeepSepSTI can better describe tissue characteristics in multiple sclerosis lesions. Impact: The proposed DeepSepSTI approach may help better measure changes in iron, myelin, and susceptibility anisotropy in various neurological diseases such as multiple sclerosis, potentially providing improved biomarkers for better characterization of disease stage and progression.