bluuebunny/crossref_metadata_2025 huggingface dataset:
MRI4All: A Week-Long Hackathon for the Development of an Open-Source Ultra-Low-Field MRI System
Authors: Srinivas Sai Abitha , Alon Leeor , Alipour Akbar , Artiges Anais , Block Kai Tobias , Boada Fernando , Bratner Doug , Brown Ryan , Chen Jingjia , Ciancia Vito , Cooley Clarissa , Dutt Tarun , Garrett David , Geethanath Sairam , Gruber Bernhard , Gupta Dinank , Ianniello Carlotta , Icke Ilknur , Jordanova Kalina , de Moura Hector Lise , Lui Yvonne , Mao Andrew , Martin Jonathan , Monga Anmol , Musipatla Amritha , Nandi Shounak , Purchase Aaron , Rubio Thiago , Saimbhi Amanpreet , Samardzija Anja , Sappo Charlotte , Shakar Greg , Shang Yun , Short Jeff , Sodickson Daniel , Stockmann Jason , Stoebner Zach , Sun Heng , Teleanu Florin , Theilenberg Sebastian , Tibrewala Radhika , Verdone Antonio , Verghese George , Wiggins Roy , Xin Bingyu , Yang Guang , Zhang Chengtong , Zhang Horace , Zi Ruoxun , Lattanzi Riccardo , Krassnig-Plass Nora , Lakshmanan Karthik , Kiran Kranthi , Umapathy Lavanya , Chen Luoyao , Nwigwe Alex
Published: November 2024

Motivation: To break the accessibility barrier of high-field MRI, we demonstrate that hardware and software systems necessary for an affordable MRI system, can be designed and constructed within a week using open-source tools and conventional 3D printing approaches. Goal(s): To illustrate the realization of an ultra low field MRI system fully operational using open source toolsApproach: Over the course of a week, researchers across the USA have assembled to build the main magnet, field homogenization, gradient, radio-frequency (RF), and software systems needed for the creation of MRI. Results: We present, for the first time, a community-driven open-source MRI system built within a week. Impact: to introduce a community-driven open-source MRI low-field systems have the capability to widely democratize MRI throughout the community and the world.
Efficacy of gadopiclenol in contrast-enhanced MRI of the liver: a post-hoc analysis
Authors: Lee Jeong Min
Published: November 2024

Motivation: Gadolinium dose reduction while maintaining MRI diagnostic efficacy is crucial. Goal(s): Compare gadopiclenol (0.05 mmol/kg) and gadobutrol (0.1 mmol/kg) in liver MRI. Approach: Post-hoc analysis on patients with liver lesions from the PROMISE phase III study (N=66). Lesion visualization was qualitatively (border delineation, internal morphology, contrast enhancement) and quantitatively (enhancement percentage, lesion-to-background ratio) evaluated by three blinded readers. Three additional readers assessed diagnostic preference. Results: Gadopiclenol was non-inferior to gadobutrol for all qualitative visualization parameters and all readers. Quantitative parameters did not differ between the two GBCAs. Readers had in most cases no preference between images with the two GBCAs. Impact: The reduction in the injected gadolinium dose achieved with gadopiclenol may be particularly important in patients undergoing multiple contrast-enhanced MRI examinations. This will also reduce the amount of gadolinium released into wastewater systems, limiting any potential ecological impact.
Acceleration of T2* mapping on an MR Linac using a self-supervised convolutional neural network.
Authors: Ugwudike Albert , Zhang Zehuan , Bano Wajiha , Tree Alison , Luk Wayne , Wetscherek Andreas
Published: November 2024

Motivation: T2* mapping could inform biologically-adaptive MR-guided radiotherapy, but requires improvement in processing time and precision for clinical implementation. Goal(s): To accelerate intravoxel field inhomogeneity correction and generation of T2* maps. Approach: We developed a physics-informed self-supervised convolutional neural network for whole volume T2* mapping of complex multi-echo data from an MR Linac. Bias in T2* estimation is accounted for by calculating the additional signal decay from 3D derivatives of the field inhomogeneity map. Results: Our model generates T2* parameter maps 30% faster than an existing time-efficient algorithm. Resulting T2* maps are less affected by noise compared to the reference. Impact: Our AI-based algorithm is a step towards integration of whole volume T2* mapping for hypoxia assessment into clinical MR-guided radiotherapy workflows. It could enable real-time mapping of dynamic changes, for example during an oxygen challenge and enable biologically adaptive radiotherapy.
Capturing Internal Target Motion with Breathing Variability Using 3D Dynamic Lung MRI
Authors: Liang Xiao , Pan Li , Nevo Erez , Roys Steve , Soomro Hussain , Gullapalli Rao , Sawant Amit , Ernst Thomas , Zhuo Jiachen
Published: November 2024

Motivation: To develop an MRI technique that captures cycle-to-cycle variability and differential motion between inhalation and exhalation to enable more accurate treatment planning and real-time beam adaptation. Goal(s): To address the challenge of acquiring sufficient volumetric data for reconstruction of 3D dynamic lung MRI while maintaining adequate spatiotemporal resolution for radiation therapy guidance. Approach: We utilized golden angle stack-of-star acquisition and labeled each view with the breathing state captured by a surface tracking system for sharing views with similar breathing states. Results: 3D dynamic lung imaging captured cycle-to-cycle variability and respiratory hysteresis with a nominal temporal resolution of 60.6ms per volume. Impact: The 3D dynamic lung imaging captured cycle-to-cycle variability and respiratory hysteresis with a nominal temporal resolution of 60.6ms. It can provide more accurate motion information than 4D-MRI for radiotherapy guidance, avoiding interplay between the tumor target and organs at risk.
Transformer-Based Automatic Pipeline for 3D Needle Localization on Intra-Procedural 3D MRI
Authors: Zhou Wenqi , Li Xinzhou , Zabihollahy Fatemeh , Lu David , Wu Holden
Published: November 2024

Motivation: Needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions, but current manual methods are time-consuming. Goal(s): To develop a transformer-based pipeline for accurate and rapid automatic 3D needle localization on intra-procedural 3D MRI. Approach: The proposed pipeline adopted a coarse-to-fine segmentation strategy by combining 3D and 2D shifted window (Swin) Transformer networks. The performance was evaluated in pre-clinical pig datasets and compared with human-annotated references. Results: Computation time was 6 sec/volume. The median 3D needle tip and axis localization errors were 1.48 mm (1.09 pixels) and 0.98°, which were comparable to human-level accuracy. Impact: The automatic transformer-based pipeline developed in this work achieved rapid (~6s) and accurate pixel-level 3D needle localization on intra-procedural 3D MRI. This new pipeline has the potential to improve MRI-guided percutaneous interventions.
An Algorithm using Artifact Features for Needle Tip Localization in Interventional MRI
Authors: Hong Shijie , He Zhao , Yang Guang-Zhong , Feng Yuan
Published: November 2024

Motivation: Needle tip localization is crucial for accurate and safe image-guided intervention, especially for real-time interventional MRI. Goal(s): To develop an algorithm that utilizes artifact features of the needle tip as prior information for needle tip localization. Approach: Combines target tracking and template matching techniques for accurate needle tip localization. Results: The algorithm's performance has been evaluated using both simulation and physical models. Validation results demonstrate that the algorithm enables fast identification, stable tracking, and highly precise needle tip localization. Impact: This needle tip localization method, leveraging artifact features as prior information, opens up new possibilities for the development of needle localization and tracking algorithms based on artifacts.
Enhanced Real-Time iCMR Device Visualization Using GRAPPA and DnCNN Denoising at Low Field
Authors: Liu Yixuan , Ding Yu , Liu Yingmin , Chen Chong , Jin Ning , Krafft Axel , Maier Florian , Armstrong Aimee , Ahmad Rizwan , Simonetti Orlando
Published: November 2024

Motivation: It is challenging to achieve the spatial and temporal resolutions required for real-time interventional device visualization using low-field scanners with limited gradient performance. Goal(s): The objective of this study is to develop a novel post-processing method capable of delivering high temporal and spatial resolution images in real-time. Approach: We developed a method that sequentially combines GRAPPA with a DnCNN denoising network to provide highly accelerated acquisition with low-latency reconstruction. The network was trained using the OCMR dataset and evaluated using pre-clinical data. Results: The network effectively suppressed noise with minimal latency, while preserving the original features of the image. Impact: This method could enhance the speed and quality of real-time interventional imaging at low field, making it easier for the interventionalist to visually track devices and deploy stents and other devices.
7 Tesla 31P Birdcage / 16-channel 1H Loop and Dipole Array integrated with Parallel Transmit System
Authors: Zhang Bei , Geraedts Tom , Prins Wim , Gohl Conrad , van den Berg Bart-Jan , Sanders Paul , Dimitrov Ivan , Plattel Geert-Jan , Lowrance Daniel , van der Meulen Peter , Henning Anke
Published: November 2024

Motivation: Integrating multinuclear applications into parallel transmit system (PTx) at ultra-high field MRI systems will provide uniform transmit field and good SNR for both proton and the x-nuclei. Goal(s): Design, build and integrate a 7T 31P/1H head array into a 7T PTx system that supports multinuclear applications. Approach: Use 8 loops and 8 folded dipoles as 1H transceivers, and a birdcage as 31P transceiver, for 31P/1H MRS and MRI in a 7T PTx systemResults: Phantom and in vivo experimental results show that the coil can provide homogeneous and good SNR signals for both 31P and 1H in ROIImpact: Elevating multinuclear studies with 7T parallel transmit system, providing uniform transmit fields and good receive sensitivity profile for both proton and x-nuclei in ROI. A potential game-changer for metabolic studies in body applications at ultra-high fields, advancing medical research.
Estimating Variations in SAR Calculations due to Within-Scan Patient Motion Using cGANs for Parallel RF Transmission at Ultrahigh Field MRI
Authors: Blanter Katherine , Plumley Alix , Malik Shaihan , Kopanoglu Emre
Published: November 2024

Motivation: Specific absorption rate (SAR), a proxy measure for tissue heating, is affected by patient motion. SAR safety factors during MRI scanning are intentionally overconservative. Goal(s): While designed to ensure patient safety, overconservativeness impedes the utility of scanning with parallel-transmit (pTx) 7T MRI. We aim to relieve pTx MRI from overconservativeness while maintaining patient safety. Approach: We used deep learning to predict the location of hot-spots during head motion and applied them to a pTx design method which considers patient motion. Results: We report that hot-spots are overcalculated almost 1.5-fold when the degree of motion is not included compared to when it is. Impact: Deep learning-estimated local specific absorption rate (SAR) variations caused by patient motion may be combined with within-scan motion tracking and subject-specific SAR models to create personalized SAR supervision for patients who cannot remain still for high-performance scanning while ensuring patient-safety.
A 48-channel multi-coil shim array for B0 inhomogeneities correction in the NHP brain at 7T.
Authors: Djaballah Elias , Uthayakumar Anojan , Bouchet Martin , Kalouguine André , Amadon Alexis , ZHU Qi
Published: November 2024

Motivation: Functional MRI faces challenges due to B0 field inhomogeneities, which are amplified in non-human primate studies, especially at ultra-high fields. Goal(s): Our aim was to develop a Multi-Coil Array (MCA) specifically designed for whole brain shimming of non-human primates. Approach: A semi-heuristic approach was used to design an MCA, based on the Principal Components Analysis of subject-optimal stream functions. The MCA was then constructed and used to image an in-vivo NHP brain. Results: The designed MCA effectively reduced B0 inhomogeneities in the primate brain, resulting in significant improvements in B0 homogenization and enhanced image quality in functional MRI images at 7T. Impact: The development of a Multi-Coil Shim Array designed specifically for non-human primates significantly improves functional MRI image quality by effectively reducing B0 inhomogeneities. This advancement could pave the way for more accurate and detailed primate brain studies at ultra-high fields.
Ultrashort echo time quantitative magnetization transfer (UTE-qMT) MRI distinguishes human diabetic bones from healthy ones
Authors: Shin Soo Hyun , Moazamian Dina , Suprana Arya , Fu Eddie , Jerban Saeed , Jang Hyungseok , Ginsberg Charles , Bukata Susan , Ma Yajun , Chang Eric , Du Jiang
Published: November 2024

Motivation: There is no standardized method to probe bone quality, a key determinant of bone fracture risk of type 2 diabetes patients. Goal(s): We tested whether UTE quantitative MT (UTE-qMT) imaging and UTE-based water pool measurement can distinguish diabetic bones from healthy ones. Approach: Twenty-two ex vivo human diabetic bones and 13 healthy ones were scanned with UTE-MT, proton density UTE, and inversion recovery UTE sequences to measure qMT parameters and fractions of pore and bound water pools. Results: The proton exchange rates from UTE-qMT showed a significant decrease in diabetic bones. Impact: The proton exchange rate measured via UTE-qMT can distinguish diabetic bones from healthy ones. UTE-qMT may provide insight into molecular-scale bone quality that explains the increased fracture risk in type 2 diabetes patients despite the increased bone mineral density.
Denoising of 3D Fast Spin Echo Magnetic Resonance Imaging Using Multi-channel Three-dimensional Convolutional Neural Network
Authors: ZHAO Shutian , XIAO Fan , Griffith James , CHEN Weitian
Published: November 2024

Motivation: Three-dimensional (3D) Fast Spin Echo (FSE) magnetic resonance imaging (MRI) can be acquired with high spatial resolution but at a cost of reduced signal-to-noise ratio (SNR). Deep-learning methods are promising for denoising in MRI. Goal(s): The existing 3D denoising convolutional neural networks (CNNs) can be further improved with the sturcture to extract high dimensional features. Approach: We developed a deep-learning approach based on multi-channel 3D CNN to utilize inherent noise information embedded in multiple number-of-excitation (NEX) acquisition. Results: The proposed method achieves improved denoising performance compared to the current state-of-the-art denoising methods in both slice-by-slice 2D and 3D metrics of PSNR and SSIM. Impact: The proposed network can realize a denoised effect with details well preserved for clinically achievable 2-NEX MR images. This shows great potential for 3D MRI, fast imaging, and low-feild MRI that demanding for noise suppression.
A Pilot Study of Insert Nonlinear Diffusion Gradient Coil on Calf Imaging
Authors: Zhang Horace , Elsaid Nahla , Nixon Terence , Constable R. Todd , Sinusas Albert , Galiana Gigi
Published: November 2024

Motivation: A flexible light-weight nonlinear gradient coil was recently proposed and the feasibility for diffusion imaging is to be studied. Goal(s): To get EPI imaging on calf with the presence of the nonlinear diffusion gradient coil Approach: We design the experiment, processing pipeline, and an ADC map is shown as preliminary quantitative validation. Results: This study demonstrates the feasibility of diffusion imaging using an insert diffusion gradient coil. Impact: This study demonstrates the feasibility of diffusion imaging using an insert diffusion gradient coil, paving the way for further application of muscle and nerve imaging on the lower extremities with high gradient strength.
Few-shot Learning Approach for Differentiation of Atypical Parkinsonian Syndromes Using Susceptibility Weighted Imaging
Authors: Choi Won June , Bo Jin Hwang , Lee Jae-Hyeok , Gahm Jin Kyu
Published: November 2024

Motivation: Recent research indicates that various atypical Parkinsonian syndromes (APSs) exhibit distinct and subtle patterns of iron accumulation in the globus pallidus and putamen, typically detected through susceptibility-weighted imaging (SWI). Goal(s): We propose a novel automated framework for distinguishing between APSs, specifically MSA-P and PSP, in SWI allowing the model to learn from a small amount of labeled data. Approach: We combined T1-weighted and SWI to create a Hybrid Contrast Image, facilitating precise registration. Furthermore, we used Hyperbolic Few-shot contrastive learning for similarity-based. Results: The model achieved a balanced accuracy of approximately 94.29%, demonstrating its superior robustness compared to other models and distance metrics. Impact: Our proposed approach demonstrated the potential to classify specific APS with high performance using a small amount of labeled data. Furthermore, it can be extended to apply not only to binary-classification of specific APS but also to the entire APS.
Longitudinal assessment of autologous knee chondrocyte implantation using DL T2 Mapping and DOSMA framework
Authors: Carretero Laura , Fung Maggie , Nunes Bruno , Bhattacharjee Rupsa , Pedoia Valentina , Majumdar Sharmila , Chaudhari Akshay , Desai Arjun , Kogan Feliks , Rodríguez Elena , López-Alcorocho Juan Manuel , Sánchez Eugenia , Guillén Isabel , Guillén Pedro , Wiesinger Florian , Malpica Norberto , Padrón Mario
Published: November 2024

Motivation: Clinical adoption of quantitative MRI for cartilage repair monitoring is hindered by a lack of standardization in acquisition and tedious image analysis. Goal(s): Our goal was to longitudinally assess high-density autologous chondrocyte implantation (HD-ACI) in the knee using a fast and robust DL T2 mapping technique, correlating with clinical outcome. Approach: 15 HD-ACI patients (treated in femoral/patellar compartments) were longitudinally imaged and processed with a semi-automated pipeline, enabling a standardized regional analysis at a layer level. Results: DL T2 map reflected longitudinal significant changes in deep layer. Significant T2 decrease in femoral HD-ACI within the first follow-up year, correlated with good clinical progression. Impact: The demonstrated feasibility of DL T2 mapping coupled with a semi-automatic analysis to monitor changes after HD-ACI repair, allows for further investigation of the underlying biology of quantitative findings; advancing its adoption as cartilage healing biomarker in the clinical setting.
Reproducibility of tailored and universal non-selective excitation pulses at 7T for human cardiac body imaging: A 3-year and an inter-day study
Authors: Alarcón Manuel Sánchez , Dietrich Sebastian , Bassenge Jean , Schulz-Menger Jeanette , Schmitter Sebastian , Aigner Christoph
Published: November 2024

Motivation: Addressing the issue of reduced spatial variability in flip angle (FA) patterns in ultra-high field 3D imaging of the human heart for inter-year and inter-day studies, ensuring a high level of reproducibility. Goal(s): Find the correct RF parallel transmission (pTx) excitation scheme that reduces FA spatial variability in 7T 3D imaging of the human heart for long-term and short-term studies. Approach: Default, tailored pulses (TP), and pre-computed universal pulses (UP) were evaluated to optimize FA homogeneity in B1+ datasets across three years. Results: The study highlights UPs' robustness in managing FA variations across subjects and coil placements in 3D body imaging at 7T. Impact: This study confirms pre-computed UPs' suitability for 7T cardiac flip angle homogenization. Different MRI operators maintained consistent RF performance across three years and inter-day tests, with no significative differences in scans at various coil positions for both tests.
Quantitative Abdominal Sodium MRI Combined with 32-Channel Proton pTx MRI at 7T in a Large Field-of-View
Authors: Scheipers Anna , Orzada Stephan , Grimm Johannes , Losch Jana , Fiedler Thomas , Nagel Armin , Schmitter Sebastian , Ladd Mark , Platt Tanja
Published: November 2024

Motivation: 23Na MRI enables the quantification of the tissue sodium concentration. A large field-of-view is beneficial for abdominal MRI, especially if several organs are of interest. Due to lower resolution compared to 1H MRI, 23Na MRI is less suited for segmentation. Goal(s): To combine large field-of-view 1H and quantitative abdominal 23Na MRI in the same position at 7T. Approach: Employing a custom-built 23Na radiofrequency coil and reference vial setup together with a 32-channel proton pTx array to allow dual-nuclei MRI in the same position. Results: Combination of large field-of-view 1H and quantitative 23Na MRI of the human torso is feasible at 7T in ≤42min. Impact: This work shows the feasibility of combined 1H and 23Na imaging at 7T in a large field-of-view both under free breathing, laying the ground work for an accurate evaluation of the tissue sodium concentration in several organs at once.
Motion-robust high-resolution multi-echo 3D gradient echo imaging of the human brain at 10.5 tesla using 80 receive channels
Authors: Liu Jiaen , van Gelderen Peter , de Zwart Jacobus , Duyn Jeff , Grant Andrea , Auerbach Edward , Waks Matt , Lagore Russell , Delabarre Lance , Tarakameh Alireza Sadeghi , Eryaman Yigitcan , Adriany Gregor , Ugurbil Kamil , Wu Xiaoping
Published: November 2024

Motivation: There is an increasing interest in T2*-related contrast at ultrahigh field for increased signal-to-noise and contrast-to-noise ratios. Goal(s): To demonstrate the feasibility and utility of high-resolution T2*-weighted brain MRI at 10.5 tesla by combining a motion-robust multi-echo gradient-echo method with a high-channel-count RF coil. Approach: Images were collected at 0.5-mm isotropic resolution using a custom 80-channel receive (80Rx) coil and used for quantitative R2* and susceptibility mapping. Results: Our method effectively eliminated artifacts from motion, producing quality images and multi-parametric maps. Parallel imaging performance was improved using the 80Rx coil relative to the commercial 7-tesla Nova 32Rx coil. Impact: The demonstrated feasibility and utility of motion-robust high-resolution multi-echo gradient echo imaging in humans at 10.5 tesla may shed light on future optimal implementation of anatomic T2*-weighted brain MRI at ultrahigh field, paving the way for many neuroscience applications.
Remarkably enhanced B1 and SNR with uHDC ceramics integrated with novel RF transreceiver array for 2H, 17O, and 1H imaging of human brain at 10.5T
Authors: Soon Soo Han , Waks Matt , Li Xin , Wiesner Hannes , Zhu Xiao-Hong , Chen Wei
Published: November 2024

Motivation: 2H and 17O MRSI are useful to study brain energy metabolism, however, have low imaging sensitivity. Goal(s): To develop a RF coil engineering solution offering superior performance for human brain 1H MRI, 2H and 17O MRSI at UHF. Approach: We constructed a novel RF transreceiver array coil, which can operate at 1H, 2H and 17O resonant frequencies at 10.5T. The integration of ultrahigh dielectric constant (uHDC) ceramics enhanced RF transmission field (B1+) and SNR. Results: The new array coil functioned well for performing multinuclear imaging, and the integrated uHDC technology remarkably enhanced B1+ and SNR for performing 2H and 17O MRSI. Impact: In this study, we introduce and demonstrate an advanced RF array coil integrated with the uHDC material enabling imaging of three important nuclei (1H, 2H and 17O) signals with superior performance aiming for human brain applications at UHF of 10.5T.
Bebop-EPI (BEeping BOld Pulse sequence) – employing inherent acquisition acoustics to generate auditory stimuli for auditory fMRI
Authors: Schmidt Rita , Seginer Amir
Published: November 2024

Motivation: With improved scanning methods and SNR, auditory response studies in functional MRI require well-defined stimuli but are encumbered by the acoustic noise from the acquisition gradients and by the temporal inaccuracy of the external audio source. Goal(s): Our goal was to use the acoustic noise generated by the MRI gradients to circumvent an external source for auditory fMRI. Approach: We implemented BEBOP (BEeping BOld Pulse sequence) EPI which enables varying the echo spacing, and thus pitch, per slice and per repetition and so provides a platform for auditory fMRI. Results: An fMRI feasibility study at 7T was successfully implemented, measuring auditory-motor responses. Impact: We demonstrated a new approach that simultaneously generates auditory stimuli and measures their BOLD response. The new approach offers high temporal accuracy of the auditory tasks due to the MRI gradients’ high temporal precision.
Improved across-scanner reproducibility using vendor-agnostic diffusion sequences
Authors: Liu Qiang , Ning Lipeng , Shaik Imam Ahmed , Gagoski Borjan , Bilgic Berkin , Grissom William , Nielsen Jon-Fredrik , Zaitsev Maxim , Rathi Yogesh
Published: November 2024

Motivation: The reproducibility of diffusion MRI (dMRI) data collected at multiple sites can be affected by differences between MRI scanners, especially scanners from different manufacturers. Goal(s): To develop vendor-neutral dMRI pulse sequences using our Pulseq development platform and reduce the inter-scanner variability between scanners from different vendors. Approach: Using a diffusion phantom and with three human subjects, we tested inter-scanner variability using Pulseq and vendor-specific product sequences. We report inter-scanner variations using standard error for mean diffusivity and fractional anisotropy. Results: Pulseq sequence yielded dramatically better results (>2x reduction in variability) enhancing the reliability of dMRI measurements across scanners. Impact: The vendor-neutral Pulseq-diffusion sequence has the potential to harmonize data acquisition and improve the robustness of diffusion MRI, making it an invaluable tool for advancing multi-site studies.
Harnessing QA/QC protocols for diffusion MRI neuroimaging workflows with MRIQC
Authors: Gomez Teresa , Chen Yibei , Provins Céline , Markiewicz Christopher , Rokem Ariel , Esteban Oscar
Published: November 2024

Motivation: Reliable neuroimaging pipelines require the implementation of robust QA/QC protocols. Goal(s): Developing an extension of MRIQC for the QA/QC of diffusion MRI data. Approach: We build on MRIQC's infrastructure to generate individual visual reports of dMRI images and define new image quality metrics (IQMs). Results: We developed a minimal processing pipeline for whole-brain dMRI data of human adults. The processing pipeline generates individual visual reports for the QA of unprocessed inputs. The pipeline also extracts IQMs to train automated decision-making, following MRIQC's established pattern. Impact: MRIQC is a widely-adopted tool for the QA/QC of unprocessed MRI data. However, support for dMRI was previously lacking. This MRIQC extension will improve QA/QC of dMRI by bringing it to the highest standards and will facilitate the implementation of rigorous protocols in multimodal neuroimaging.
Integrated Registration and Harmonization Framework for Quantitative T2-weighted MRI Analysis following Prostate Cancer Radiotherapy
Authors: Zacharaki Evangelia , Breto Adrian , Algohary Ahmad , Wallaengen Veronica , Punnen Sanoj , Abramowitz Matthew , Pollack Alan , Stoyanova Radka
Published: November 2024

Motivation: The reliable evaluation of T2-weighted MRI (T2w) signal change in prostate cancer following radiotherapy (RT) is challenging due to deformations (physiological and RT-related) and scanner/protocol acquisition variability. Goal(s): To develop an automated and reproducible methodology for quantification of T2w signal change in longitudinal studies following RT. Approach: The methodology includes T2w image intensity harmonization and deformable registration of post-RT to pre-RT images for automated detection of prostate, peripheral zone and tumor volume. Results: The repeatability in T2w intensity estimation improved following the automatic registration relative to manual contours; and the quantitative changes of T2w reached significance when pre- and post-RT series were compared. Impact: The developed methodology allows to automatically detect ROIs in post-RT MRI exams, reduces data acquisition-related variation and improves imaging features’ repeatability, thereby enables the quantitative characterization of RT-induced changes in T2w.
Testing the Quantitative Imaging Biomarkers Alliance (QIBA) PDFF Profile in the Liver: Results from 416 Scanners at 1.5T and 3T
Authors: Siu Adrienne , Solywoda Mary Jean , Davis Tom , Robson Matthew , Salvati Roberto
Published: November 2024

Motivation: The Quantitative Imaging Biomarkers Alliance (QIBA) PDFF Profile describes the expected performance of an imaging technique when measuring PDFF. However, the expected performance in phantoms was determined in one phantom on 27 scanners and may not be applicable widely. Goal(s): We tested the hypothesis that the QIBA PDFF bias criteria (mean:within ±5.0%, maximum:within ±7.0% (percentage points)) cannot be attained at scale with multiple phantoms on >400 scanners. Approach: We calculated the QIBA PDFF criteria using phantom data from 416 scanners across three vendors at 1.5T and 3T. Results: All six combinations of scanner vendor and field strength passed the QIBA PDFF criteria. Impact: The hypothesis that the QIBA PDFF bias criteria cannot be maintained with multiple phantoms on >400 scanners was disproven in a novel dataset with 416 scanners, strongly suggesting that it is possible to achieve this level of performance at scale.
Imaging glutamine utilization in a prostate cancer xenograft model
Authors: Hodo Yuki , Tressler Caitlin , Ghaemi Behnaz , Webster Aliyah , Li Yuguo , Pomper Martin , Bulte Jeff , van Zijl Peter , Thomas Aline
Published: November 2024

Motivation: MRI agents that can monitor abnormal glutamine utilization, a hallmark of many aggressive cancers, are not clinically available. Goal(s): We investigated the utility of glutamine as a chemical exchange saturation transfer (CEST) agent to evaluate its utilization. Approach: Phantoms revealed contrast differences between glutamine and its metabolic products. Dynamic CEST images (in vivo) were acquired in 2 prostate cancer xenograft models after intravenous injection of glutamine. MALDI (matrix-assisted laser desorption/ionization) images of the same tumors (ex vivo) were collected for validation. Results: CEST and MALDI images could distinguish prostate tumors derived from cell lines with known differences in glutamine utilization. Impact: The potential of CEST (chemical exchange saturation transfer) MRI to evaluate glutamine utilization was evaluated in preclinical prostate cancer models (DU-145 and LNCaP). CEST enhancement images upon infusion of glutamine could distinguish tumors that differed in glutamine utilization.
Magnetic resonance imaging of macrophage response to radiation therapy
Authors: Yang Harrison , Howerton Brock , Marti Francesc , Adatorwovor Reuben , Chapelin Fanny
Published: November 2024

Motivation: Cellular response to cancer treatment is difficult to track in real time. Standard practice involves immunostaining of a biopsied tumor, but this is severely limited by a number of factors. Goal(s): Non-invasive imaging methods such as MRI could obviate the need for biopsies and serve as a biomarker of radiation therapy efficacy. Approach: This study aimed to observe macrophage response in a mouse model by use of a fluorine nanoemulsion and 19F MRI. Results: It was shown that macrophage recruitment can be quantified through MRI. Moreover, the findings suggest that macrophage response to radiation therapy is dependent on several factors including tumor origin. Impact: Our results demonstrate the potential of 19F MRI to non-invasively track macrophages during radiation therapy and its prognostic value with regards to tumor growth. This technique will be extremely beneficial in future analysis of inflammation’s role in tumor recurrence.
Acceleration of Magnetic Resonance Elastography using a Novel Distributed Encoding Technique
Authors: Kramer Mary , Cerjanic Alex , McGarry Matthew , Johnson Curtis
Published: November 2024

Motivation: Magnetic resonance elastography (MRE) data quality is susceptible to poor data quality from subject motion and long scan times. Goal(s): A novel sampling technique and estimation scheme was developed and implemented to improve flexibility and acquisition time of MRE. Approach: The technique utilizes non-traditional sampling directions in an optimized encoding matrix to collect data efficiently to be used in a novel algorithm for estimating harmonic displacement fields. This allows for acquisition acceleration or flexibility in the data sampled to be rejected in post-processing if it is distorted. Results: Scans were acquired 2.3x faster than standard methods with 95.2% multiscale structural image similarity. Impact: A novel sampling and estimation scheme demonstrated here can be used to improve the application of magnetic resonance elastography. This is accomplished through prospective reduction in sampling, reducing acquisition time, and retrospective volume rejection, circumventing distortion introduced by subject motion.
Data-Driven Analysis of Brain Tissue Mechanics using Magnetic Resonance Elastography and Non-Negative Matrix Factorization
Authors: Diano Alexa , Bailey Olivia , Kramer Mary , Twohy Kyra , Johnson Curtis
Published: November 2024

Motivation: There exists a need for a comprehensive method to analyze regional brain tissue mechanics that accounts for variability across subject populations. Goal(s): Here we aimed to implement a multivariate data-driven technique to capture brain mechanical properties across a wide population while preserving small-scale differences between subjects. Approach: Non-negative matrix factorization was used to reduce mechanical properties derived from magnetic resonance elastography (MRE) into a low-dimensional form to generate unconfined regions of the brain that demonstrate high covariance across all subjects. Results: This technique was able to capture recognizable anatomical regions in the brain without structural input to determine weightings on the population average. Impact: This low-dimensional representation of brain tissue mechanics acquired from non-negative matrix factorization and MRE will help define baseline properties that accurately represent a wide range of subject populations while minimizing variability across imaging studies and contributing to improved statistical models.
In Vivo Glutamate CEST MR Fingerprinting (GluCEST-MRF)
Authors: Martinez Jessica , Otazo Ricardo , Cohen Ouri
Published: November 2024

Motivation: To obtain quantitative glutamate CEST and MT maps in the brain with higher resolution than spectroscopic imaging. Goal(s): To develop a CEST-MRF pulse sequence and deep learning reconstruction approach for rapid quantitative glutamate imaging. Approach: CEST-MRF pulse sequence with an acquisition schedule optimized by deep learning was developed to measure glutamate exchange rate and volume fractions. Quantitative maps were obtained using a neural network trained on physics-derived signals. Results: The proposed approach yields water T1 and T2 relaxation maps, glutamate exchange and volume fraction maps and the semi-solid exchange and volume fraction maps in a scan time of less than 2 minutes. Impact: The proposed quantitative glutamate-sensitive CEST-MRF technique can lead to improved diagnosis and treatment response evaluation in patients with brain tumors given that glutamate dysregulation is a key aspect of tumor growth.
Simultaneous T1 and T2 mapping of the brain with accelerated QuantoRAGE using optimized sequence parameters and fast neural network fitting
Authors: Nguyên Tâm , Hilbert Tom , Marques José , Açikgöz Berk , Kreis Roland , Bastiaansen Jessica , Kober Tobias , Bonanno Gabriele
Published: November 2024

Motivation: T1 and T2 relaxometry provide valuable information for early pathology detection but require long scan and fitting times for high-resolution whole-brain mapping. Goal(s): To reduce acquisition and map generation times for simultaneous T1 and T2 mapping. Approach: The proposed accelerated sequence uses two scans instead of the original four, with parameters optimized using the Cramér-Rao lower bound (CRLB). A neural network fast fitting model is employed to drastically reduce parameter quantification times. Results: The optimized technique reduced total acquisition time from 18:20 to 9:10 minutes and fitting time from several hours to 2 min for the entire brain. Impact: Using QuantoRAGE, simultaneous T1 and T2 relaxometry of the whole brain with high isotropic resolution can be acquired in 9 minutes with quantitative maps generated within few seconds per slice. Both aspects bring quantitative MRI closer to clinical applications.
Magnetization transfer explains most variablity of T1-estimates in the MRI literature
Authors: Assländer Jakob
Published: November 2024

Motivation: T1-estimates vary substantially throughout the literature. Goal(s): To provide evidence that magnetization transfer (MT) explains most of this variability. Approach: We simulated 16 literature T1-mapping approaches with an MT model and fitted a T1-value to each simulated dataset. We then modified a global set of MT parameters to best explain the T1-variability. Results: We found that MT explains 71% of the literature's T1-variability. The largest reduction and minimal Bayesian and Akaike information criteria were achieved when incorporating two recent advances in MT modeling: describing the semi-solid pool's spin dynamics with the generalized Bloch model and removing commonly-used constraints on the semi-solid pool's T1. Impact: Our results suggest that T1 should be considered a semi-quantitative metric in biological tissue, meaning comparisons between different T1-mapping methods and validations in doped-water phantoms are of limited value.
Accelerated Preclinical UHF Abdominal T1 Mapping using Novel Rosette Ultrashort Echo Time (PETALUTE)
Authors: Lipka Alexandra , Sawiak Stephen , Shen Xin , Emir Uzay , Özen Ali , Chiew Mark , Speth Joseph , Chan Deng-Yuan , Jiang Zhen , Tamer Gregory , Scarpelli Matthew
Published: November 2024

Motivation: Well established techniques for fast 3D T1 mapping with cartesian/radial trajectories are prone to respiratory artifacts.Previously established non-cartesian sequences have mitigated the influence of motion artifacts, though still suffer from long measurement times. Goal(s): Implementation of a novel 3D dual-echo rosette k-space trajectory for preclinical UTE MRI(PETALUTE) for abdominal imaging of both anatomical and quantitative T1 measurements and retrospective 4-fold acceleration. Approach: PETALUTE(resolution 0.24x0.24x0.24mm3,accelerated scan-time 2:15min) acquisition for T1 mapping via variable flip angle method and evaluation of T1 values and acceleration effects. Results: High-resolution non-gated abdominal imaging with the ability to clearly distinguish anatomy and T1 values,that did not deprecate when accelerated. Impact: Well established methods for T1 mapping using cartesian/radial trajectories suffer from motion artifacts due to long acquisition duration.PETALUTE,a novel 3D dual-echo rosette k-space trajectory for preclinical UTE-MRI,is able to generate high-resolution non-gated abdominal anatomical images and T1 mapping in ~2min.
2D T1, T2, T2* and PDFF mapping in the kidney with rosette MRF using Hermitian low-rank and dictionary-patch based regularization
Authors: Cruz Gastao , Cummings Evan , Griesler Tom , Hamilton Jesse , Gulani Vikas , Davenport Matthew , Seiberlich Nicole
Published: November 2024

Motivation: Subjective qualitative T2-weighted, T1-weighted (with and without contrast) and fat suppressed images are currently used to characterize renal masses. Characterization could be improved and standardized by using objective, generalizable, quantiative criteria. Goal(s): In this work, 2D single-breathhold, high-resolution T1/T2/T2*/PDFF mapping rosette MRF is deployed for kidney tissue characterization. Approach: A novel MRF reconstruction is introduced to enable reduced MRF data collection time, incorporating separate low-rank models along the TE and TR domains, Hermitian symmetry via virtual coils, and a dictionary-patch based regularization. Results: In vivo results in healthy subjects demonstrate 2D 1x1x5 mm3 T1/T2/T2*/PDFF MRF kidney mapping in a single breath-hold. Impact: Simultaneous mapping of T1/T2/T2*/PDFF in the kidney in a single high-resolution breath-hold scan via the proposed MRF approach is feasible. This technique could bolster traditional pre-/post- contrast renal mass protocols with objective characterization methods.
Multinuclear fingerprinting (MNF): high-resolution simultaneous proton/sodium MR fingerprinting
Authors: Rodriguez Gonzalo , O’Donnell Lauren , Yu Zidan , Cloos Martijn , Madelin Guillaume
Published: November 2024

Motivation: Develop a method for high-resolution multinuclear fingerprinting (MNF). Goal(s): Generate high-resolution multi-parametric maps of proton and sodium nuclei. Approach: The method consists of two steps: 1- Simultaneous acquisition of 1H/23Na MR fingerprinting (MRF) data resulting in high-resolution 1H maps and low-resolution 23Na maps 2- Application of a super-resolution algorithm to match the in-plane resolution of 23Na maps to the in-plane high-resolution of the 1H maps. Results: Multinuclear fingerprinting (MNF) can generate high-resolution 1H density, T1, and T2 maps and 23Na density, T1, T2long, and T2short maps in brain from simultaneous 1H/23Na MRF data acquired at 7 T in 21 min. Impact: This method provides a novel approach towards the investigation of sodium maps as biomarkers for neurological diseases.
Robust motion- and $$$\delta B_0$$$ -correction for high-resolution QSM at 7T
Authors: Brackenier Yannick , Casella Chiara , Cordero-Grande Lucilio , Tomi-Tricot Raphael , Bridgen Philippa , Setsompop Kawin , Malik Shaihan , Hajnal Joseph
Published: November 2024

Motivation: Quantitative susceptibility mapping (QSM) provides valuable clinical information and is widely used, especially at ultra-high field (7T). Due to long echo times, QSM acquisitions are extra sensitive to the changes in B0 ($$$\delta\textbf{B}_0$$$), such as those secondary to motion. Goal(s): To provide purely data-driven motion and $$$\delta\textbf{B}_0$$$ correction for QSM. Approach: We use the self-navigated DISORDER k-space re-ordering, originally proposed for motion correction, to additionally estimate $$$\delta\textbf{B}_0$$$. Within-scan motion and $$$\delta\textbf{B}_0$$$ are then retrospectively corrected during image reconstruction. Results: We show improved reconstruction in all 5 scanned volunteers when additionally correcting $$$\delta\textbf{B}_0$$$. This directly improves QSM. Impact: The proposed method can result in improved image quality when scanning in presence of motion and , e.g. due to heavy breathing. Combining this approach with an optimized QSM protocol will provide motion- and -robust QSM.
Improving Reproducibility in Quantitative 4D Flow MRI Using AI-Driven Fully-Automated Processing and Analysis
Authors: Johnson Ethan , Yang Kai , Weiss Elizabeth , Jarvis Kelly , Berhane Haben , Sodhi Aparna , Rigsby Cynthia , Markl Michael
Published: November 2024

Motivation: Reproducibility is fundamentally an issue for quantitative MRI, and any human intervention required for processing can be a significant source of variability. Goal(s): This study aims to improve reproducibility in quantitative 4D flow MRI by removing all human input from processing, using AI-driven tools. Approach: Hemodynamic parameters quantified by a fully automated neural-network-based processing tool for 4D flow MRI were compared to quantifications performed by two sets of human observers. Results: Moderate but appreciable limits of agreement were observed between quantifications performed by different human observers. Quantified values from fully-automated processing were comparable to those from humans, but all inter-observer variability was eliminated. Impact: This study offers a stable baseline for improving measurement reliability in quantitative 4D flow MRI by removing all manual human inputs required.
A validated computational model of diffusion tensor imaging including cyclical strain and permeability
Authors: Alemany Ignasi , Nielles-Vallespin Sonia , Ferreira Pedro F. , Pennell Dudley J. , Scott Andrew D. , Doorly Denis J.
Published: November 2024

Motivation: To investigate the effects of strain on diffusion where existing studies are limited to isotropic unrestricted media. Goal(s): The aim of this study is to develop and validate a novel methodology that extends the classic Monte Carlo random walk algorithm to incorporate the effects of strain within complex media. Approach: Strain is included in the MCRW simulations displacing the geometry and the particles in each time step and is validated against established finite volume (FV) methods and an analytical solution for free diffusion. Results: We demonstrate the ability to assess changes in the diffusion tensor due to cyclical strain and long diffusion times. Impact: The updated MCRW model offers new capabilities for quantifying strain-induced biases in diffusion tensor CMR metrics enabling clinicians to more accurately interpret microstructural changes, particularly in patients with pathological alterations.
FlowSim: a blood flow simulator for histology-informed diffusion MRI micro-vasculature mapping in cancer
Authors: Voronova Anna , Grigoriou Athanasios , Bernatowicz Kinga , Simonetti Sara , Serna Garazi , Roson Núria , Escobar Manuel , Vieito Maria , Nuciforo Paolo , Toledo Rodrigo , Garralda Elena , Sala-Llonch Roser , Palombo Marco , Perez-Lopez Raquel , Grussu Francesco
Published: November 2024

Motivation: Open-source software for simulating diffusion MRI (dMRI) signals arising from micro-vascular perfusion is needed to inform the development of new techniques for non-invasive vascular characterization. Goal(s): To present FlowSim, a micro-vasculature perfusion dMRI signal simulator, demonstrating its utility for in vivo vascular property estimation. Approach: FlowSim estimates blood velocities in all segments of custom vascular networks. These are used to calculate spin trajectories in the presence of arbitrary diffusion-encoding gradients. Results: FlowSim synthesizes dMRI signals from realistic vascular networks reconstructed from histology. These can be used to inform the estimation of capillary blood velocity distributions in vivo, showcased herein in cancer. Impact: We present FlowSim, a simulator of diffusion MRI (dMRI) signals arising from micro-vasculature perfusion. FlowSim synthesizes dMRI signals from realistic vascular networks reconstructed from histology, and informs the estimation of new microvasculature metrics in vivo, needed, for example, in cancer.
Tuneable Digital Phantoms for Grey Matter Modelling
Authors: Aird-Rossiter Charlie , Kanari Lida , Cuntz Herman , Jones Derek , Palombo Marco
Published: November 2024

Motivation: There are several generators of white matter phantoms that have been developed in recent years and have significant potential in developing and validating diffusion MRI techniques through computational simulation. However, no such generator has been proposed for grey matter phantoms. Goal(s): We aim to provide a means of generating grey matter phantoms compatible with diffusion MRI simulations. Approach: Combing the network growth presented in the Contextual Fibre Growth (ConFiG) algorithm with the generative method of topological neuro synthesis (TNS), to create non intersecting morphologically realistic cellular structures. Results: We can show that our algorithm can generate non-intersecting realistic voxels of grey matter. Impact: We have developed a highly versatile algorithm, ConCeG, which can generate realistic digital phantoms of GM. These phantoms are ready to be incorporated into dMRI simulators, such as Camino, DiSimPy and MCDS for testing and validating diffusion MRI techniques