bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting pathological status of prostate cancer patients – Examining the value and leading features in MRI Radiomics
Authors: Isaksson Lars , Summers Paul , Pepa Matteo , Zaffaroni Mattia , Vincini Maria , Corrao Giulia , Mazzola Giovanni , Rotondi Marco , Raimondi Sara , Gandini Sara , Volpe Stefania , Haron Zaharudin , Alessi Sarah , Pricolo Paola , Mistretta Francesco , Luzzago Stefano , Cattani Federico , Musi Gennaro , De Cobelli Ottavio , Cremonesi Marta , Orecchia Roberto , Marvaso Giulia , Jereczek-Fossa Barbara , Petralia Giuseppe
Published: August 2023

The risk of patients being under- or overtreated during radiotherapy depends heavily on the pre-treatment assessment. Prediction models for surgical margin status, pathological lymph nodes, pathological tumor stage and ISUP grade group were formed using clinical and radiological features alone and together with whole-prostate radiomic features in 100 patients who proceeded to prostatectomy after multiparametric-MRI. The addition of radiomics features significantly improved AUC for the prediction models. The leading radiomic features differed between the different models.
Radiomic Features Measured with Multiparametric Magnetic Resonance Imaging Predict Prostate Cancer Metastatic Risk
Authors: Alhusseini Mohammad , Breto Adrian , Xu Isaac , Algohari Ahmad , Gaston Sandra , Abramowitz Matthew , Para Alan Dal , Punnen Sanoj , Pollack Alan , Stoyanova Radka
Published: August 2023

Circulating tumor cells (CTCs) have been shown to be an indicator for metastatic risk in prostate cancer. We investigated the association between radiomics features extracted from multiparametric MRI of the prostate and CTC counts in prostate cancer patients enrolled in two institutional clinical trials (n=71). We trained a neural network to predict the dichotomized CTCs counts, defined by a 5 CTCs threshold. The top seven features, ranked using maximum-relevance minimum-redundancy, were used as input to a neural network. The training and testing were repeated for 100 runs of 5-Fold cross validation, resulting in AUC 0.834 to predict CTCs ≥ 5.
The Open Science Initiative for Perfusion Imaging (OSIPI): Early Results from the DCE-MRI Challenge
Authors: Shalom Eve , Kim Harrison , van der Heijden Rianne A. , Ahmed Zaki , Patel Reyna , Hormuth David , DiCarlo Julie , Sisco Nicholas , Dortch Richard , Stokes Ashley , Inglese Marianna , Grech-Sollars Matthew , Toschi Nicola , Sahoo Prativa , Singh Anup , Verma Sanjay , Rathore Divya , Nabavizadeh Ali , Rad Hamidreza Saligheh , Hu Leland , Bell Laura , Sourbron Steven , Kazerooni Anahita Fathi
Published: August 2023

While there is growing evidence that DCE-MRI may provide insights about the response of patients to therapies, there is a lack of standardized software quantification tools, resulting in variability in reported Ktrans values across different studies and limiting its utility in clinical applications. We have designed and launched the Open Science Initiative for Perfusion Imaging (OSIPI)-DCE challenge to provide recommended and benchmarked analysis tools for Ktrans estimation in the brain, by evaluating and comparing DCE software tools in terms of accuracy, repeatability, and reproducibility. Here, we report on the preliminary results of this challenge.
Deep-learning-based raw data generation for deep-learning-based image reconstruction
Authors: Zijlstra Frank , While Peter
Published: August 2023

This study demonstrates the potential of using deep learning for generating raw data to augment raw datasets of limited size for use in deep-learning-based MR image reconstruction. Using an adversarial autoencoder architecture, variability in 10 T1-weighted raw datasets from the fastMRI database was learned and recombined into new, random raw data. We trained a deep-learning-based Compressed Sensing reconstruction using both conventional approaches with real raw data and compared the results to training with generated raw data. The reconstruction from generated raw data showed improved reconstruction results and better generalization to scans with slightly different echo times.
Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks
Authors: Peng Wei , Feng Li , Zhao Guoying , Liu Fang
Published: August 2023

This work proposes a novel optimization framework to learn k-space sampling trajectories using deep learning by considering it an Ordinary Differential Equation (ODE) problem that can be solved using neural ODE. Particularly, the sampling of k-space data is framed as a dynamic system, in which neural ODE is formulated to approximate the system with additional constraints on MRI physics. Experiments were conducted on different in-vivo datasets (e.g., brain and knee images) acquired with different sequences. Initial results have shown that our proposed method can generate better image quality in accelerated MRI than conventional undersampling schemes in Cartesian and non-Cartesian acquisitions.
Automated Sequence Design using Neural Architecture Search
Authors: An Hongjun , Ji Sooyeon , Oh Sehong , Kim Jiye , Shin Dongmyung , Lee Jongho
Published: August 2023

A new pulse sequence design method that requires no prior knowledge of MR physics or training dataset is proposed. This method utilizes neural architecture search, generating an optimal sequence for given properties (e.g., T2*, B1+) and target objectives. It successfully discovered FLAIR-like and spin-echo-like sequences. Furthermore, a less-intuitive sequence using three RF pulses was created when targeted for spin-echo. In an in-vivo experiment, this new sequence had almost identical contrasts and SNR with spin-echo (our SNR: 297.1±70.1; spin-echo SNR: 295.8±78.2) while utilizing 90% of RF energy of the spin-echo, suggesting a potential of the automated sequence design.
Comparing high resolution 7T MRSI and PET of glioma – a promising correspondence of glutamine to amino acid PET
Authors: Hangel Gilbert , Lazen Philipp , Sharma Sukrit , Hritoska Barbara , Cadrien Cornelius , Furtner Julia , Rausch Ivo , Traub-Weidinger Tatjana , Niess Eva , Hingerl Lukas , Gruber Stephan , Strasser Bernhard , Kiesel Barbara , Preusser Matthias , Roetzer-Pejrimovsky Thomas , Woehrer Adelheid , Bogner Wolfgang , Widhalm Georg , Rössler Karl , Trattnig Siegfried
Published: August 2023

We compared metabolic ratio maps of tCho, Gln, and Gly to tNAA and tCr derived from high-resolution 7T MRSI to clinical amino acid PET in 24 glioma patients. We achieved the highest DICE coefficient of 0.66±0.25 for Gln/tNAA, and further defined hot spot volumes and center of intensity distances between PET and MRSI. Overall, we showed that the information content of 7T MRSI results in a better correspondence to PET as clinical gold standard than previous MRSI studies.
Glycogen accumulation in the brain of classic-infantile Pompe patient measured with single-voxel 1H MRS and 2D-MRSI at 7T
Authors: Najac Chloé , Boer Vincent , van der Beek Nadine , van der Ploeg Ans , Ronen Itamar , van den Hout Johanna , Kan Hermien
Published: August 2023

Pompe disease is caused by an abnormal accumulation of glycogen in the lysosomes of multiple tissues including the brain due to a deficit in acid α-glucosidase (GAA). The development of enzyme replacement therapy with recombinant human GAA (rhGAA) has dramatically improved patients’ survival, however, rhGAA does not reach the brain which remains untreated. Consequently, classic-infantile Pompe patients may develop progressive white matter lesions and cognitive problems. Here, we used single-voxel 1H MRS and spectroscopic imaging and found an accumulation of glycogen and significant decrease in total-N-acetyl-aspartate in the brain of classic-infantile patients (n=3) when compared to age-matched healthy controls (n=3).
Quantification of cross-relaxation in human skeletal muscle using downfield 1H MRS at 7T
Authors: Swago Sophia , Cember Abigail , Bagga Puneet , Wilson Neil , Elliott Mark , Nanga Ravi Prakash Reddy , Reddy Ravinder , Witschey Walter
Published: August 2023

In the 1H magnetic resonance (MR) spectrum of human muscle, non-exchangeable proton resonances have been observed at 8.0, 8.2 and 8.5 ppm. While relaxation rate enhancement of these resonances was previously observed, their cross-relaxation rates with bulk water have not yet been determined. Knowledge of cross-relaxation rates could improve the design of MR techniques or serve as a potential biomarker. We quantify the cross-relaxation rate of these resonances with bulk water using selective and non-selective inversion-recovery downfield MRS at 7T. We observed the cross-relaxation rates of the 8.2 and 8.5 ppm resonances were significantly faster than the 8.0 ppm resonance.
MIITRA atlas: T1w and DTI templates of the older adult brain in a common space with 0.5mm resolution
Authors: Wu Yingjuan , Ridwan Abdur , Niaz Mohammad Rakeen , Bennett David , Arfanakis Konstantinos
Published: August 2023

As part of the Multichannel Illinois Institute of Technology & Rush university Aging (MIITRA) atlas project, the present work (A) developed high quality 0.5mm isotropic resolution T1-weighted (T1w) and diffusion tensor imaging (DTI) templates in common space using data from a large, diverse, community cohort of non-demented older adults, and (B) compared the new templates to existing templates of the older and younger adult brain. The new templates exhibited higher image quality, were more representative of the older adult brain, and allowed higher spatial normalization accuracy across subjects and across modalities compared to other templates.
Accelerated 2D PC-MRI using a Deep Learning-Based Reconstruction with Complex Difference Estimation: A Prospective Feasibility Study
Authors: Middione Matthew J. , Oscanoa Julio , Syed Ali , Vasanawala Shreyas , Ennis Daniel B.
Published: August 2023

We have previously demonstrated a Deep Learning (DL) reconstruction of highly accelerated 2D PC-MRI datasets. We trained a DL reconstruction by retrospectively undersampling fully-sampled 2D PC-MRI datasets to enable up to 9x accelerated images with <5% error in accuracy and precision. Herein, we compare the accuracy and precision of 2D PC-MRI measurements for our prospectively deployed sequence and DL reconstruction. In this initial feasibility study, we show that our DL reconstruction provides <5% error in the accuracy of peak velocity and total flow relative to 2x parallel imaging and better accuracy and precision compared to 8x compressed sensing.
Automated compensation of respiratory motion and bulk patient movement in free-running whole-heart 4D MRI
Authors: Roy Christopher , Yerly Jérôme , Prša Milan , Tenisch Estelle , Rutz Tobias , Piccini Davide , Stuber Matthias
Published: August 2023

A novel methodology for whole-heart 4D MRI with retrospective compensation of both respiratory motion and bulk patient movement is developed and its initial feasibility demonstrated. This approach enables imaging with high isotropic resolution and allows for retrospective evaluation of the dynamic cardiac anatomy creating a new way to significantly improve image quality in un-cooperative patients and potentially decreasing the need for sedation.
FlowSeg: Joint deep artifact suppression and segmentation network for low latency beat-to-beat assessment of cardiac aortic flow.
Authors: Jaubert Olivier , Montalt-Tordera Javier , Arridge Simon , Steeden Jennifer , Muthurangu Vivek
Published: August 2023

Real-time cardiac output monitoring is desirable but requires low latency reconstruction and segmentation. A framework based on a spiral real-time flow acquisition and joint deep artifact suppression and segmentation was developed to provide flow volumes with low latency at the scanner. The proposed network was characterized in simulations and the full framework tested at the scanner providing real-time monitoring of flow during exercise. Future work will aim to validate the method in a larger cohort.
Evaluation of operation pressure of a soft robotic extra-aortic cardiac assist device using MRI
Authors: Dual Seraina , Arduini Mattia , Schmittlein Brigitte , Zimmermann Judith , Roche Ellen , Ennis Daniel
Published: August 2023

MRI can be used to evaluate the interaction of soft robotic devices with biological tissues. The aim of this study was to use MRI to optimize the actuation pressure of an extra-aortic soft robotic cardiac assist device. We evaluated wall deformations, displaced fluid volumes and qualitative flows induced by the actuator on a fluid filled elastic vessel. Our results show that the displaced volume increases with the actuator pressure and decreases with increasing the vessel pressure. The maximum actuator pressures do not lead to buckling of the vessel wall given the current three-bladder design.
In Vitro 4D Flow MRI for the Analysis of Aortic Coarctation
Authors: Rice James , Shahid Labib , Berhane Haben , Rigsby Cynthia , Robinson Joshua , Griffin Lindsay , Markl Michael , Roldan-Alzate Alejandro
Published: August 2023

4D flow MRI can be used to assess aortic coarctation (COA) repair hemodynamics in-vivo, however, challenges arise depending on hemodynamics and clinical presentation. This study presents a modeling pipeline for in-vitro COA hemodynamic assessment. Three patient-specific in-vitro models were created representing pre- and post-repair COA geometries, connected to a pulsatile flow loop, and imaged with 4D flow MRI to assess model hemodynamics. In all cases, aortic flow profiles are shown to improve after intervention. This agrees with clinical expectation, suggesting in-vitro 4D flow MRI can be used to analyze COA hemodynamics.
High resolution motion compensated contrast-free free-breathing 3D CMRA at 7T using single transmit coil
Authors: Paul Shubhajit , Tomi-Tricot Raphael , Munoz Camila , Kunze Karl , Malik Shaihan , Hajnal Joseph , Bridgen Philippa , Wilkinson Thomas , Giles Sharon , Neji Radhouene , Razavi Reza , Prieto Claudia , Botnar René
Published: August 2023

3D cardiovascular MR imaging at ultra-high field (7T) is very challenging due to magnetic-field inhomogeneity (B0 and B1), SAR constraints and also the coil-depth issues of surface coils. To our best knowledge this is the first report demonstrating contrast-free ultra-high resolution (0.7mm3 isotropic) free-breathing 3D CMRA images with translational respiratory motion compensation. To avoid SAR constraints imposed by the use of T2-preparation pulses, high excitation flip-angles are exploited to obtain high contrast between the coronary arteries and myocardium. This technique may be adopted for clinical applications to produce high-resolution cardiac MR images at 7T scanners.
Cine Flow Measurements using Phase-Contrast bSSFP at 0.75 Tesla
Authors: Peper Eva , Dillinger Hannes , McGrath Charles , Guenthner Christian , Kozerke Sebastian
Published: August 2023

The use of balanced steady-state free precession sequences (bSSFP) is an approach to compensate for the signal-to-noise ratio (SNR) loss at lower-field systems (<1T). Low field MRI systems are cheaper, lighter, and less prone to system imperfections than regular 1.5-3T systems, used in clinical practice. In this work, the feasibility and accuracy of velocity encoding using phase-contrast balanced SSFP (PC-bSSFP) is demonstrated and tested on a clinical 3T MRI system ramped down to 0.75T. Phantom and in-vivo results are compared to a standard 2D spoiled gradient echo phase-contrast sequence (PC-GRE).
Extended and weight bearing wrist MRI using a positioning apparatus and flexible glove coil to explore the cause of dorsal pain
Authors: Wang Bili , Walczyk Jerzy , Ahmed Mohammed , Rocks Madeline , Elkowitz Stuart , Catalano Louis , Burke Christopher , Daniels Steven , Brown Ryan
Published: August 2023

Dorsal wrist pain during extension or weight bearing is a common symptom, the etiology of which often remains unclear. Clinical MRI often fails to reveal causative pathology in part because it is performed in the neutral position. We built an apparatus to guide motion and used a flexible coil to capture signal in a range of positions that better match the conditions during which pain is reported. Results in nine asymptomatic volunteers show excellent tissue structure delineation, strong measurement agreement among readers, and increases in dorsal capsule thickness and radiocapitate, radiolunate, capitolunate and extensor tendon angulation during weight bearing.
Accelerated High-Resolution 3D Isotropic Wrist MRI at 7 Tesla: Compressed Sensing vs. SENSE
Authors: Runderkamp Bobby , Caan Matthan , van der Zwaag Wietske , Hemke Robert , Maas Mario , Andersen Mads , Strijkers Gustav , Bloch Karin Markenroth , Nederveen Aart
Published: August 2023

Imaging of the intricate arrangement of small structures in the wrist benefits from high resolution imaging, which the increased SNR at 7 Tesla can enable. However, the increased resolution requires longer scan times, decreasing patient comfort and increasing risk of motion artifacts. In this work, we evaluated compressed sensing (CS) acceleration of a clinical wrist 7T MRI protocol, 0.45mm isotropic resolution, in comparison to SENSE-acceleration. We show that CS-acceleration can produce adequate to good image quality in significantly shorter scan times, not achievable by increasing SENSE-acceleration.
Deep-Learning-based contrast synthesis from MRF parameter maps in the knee
Authors: Nykänen Olli , Isosalo Antti , Inkinen Satu , Casula Victor , Nevalainen Mika , Lattanzi Riccardo , Cloos Martijn , Nissi Mikko , Nieminen Miika
Published: August 2023

In this study, deep convolutional neural networks (DCNN) are used to synthesize contrast-weighted magnetic resonance (MR) images from quantitative parameter maps of the knee joint obtained with magnetic resonance fingerprinting (MRF). Training of the neural networks was performed using data from 142 patients, for which both standard MR images and quantitative MRF maps of the knee were available. The study demonstrates that synthesizing contrast-weighted images from MRF-parameter maps is possible utilizing DCNNs. Furthermore, the study indicates a need to tune up the dictionary used in MRF so that the parameters expected from the target anatomy are well-covered.
3D Diffusion-prepared MRF (3DM) with cardiac gating for rapid high resolution whole-brain T1, T2, proton density and diffusivity mapping
Authors: Cao Xiaozhi , Liao Congyu , Zhong Zheng , Dai Erpeng , Iyer Siddharth , Hannum Ariel , Yurt Mahmut , Skare Stefan , Setsompop Kawin
Published: August 2023

In this work, a diffusion preparation was implemented in a 3D spiral-projection MRF framework to introduce additional diffusion weighting. Using MRF dictionary with diffusion terms, it enables whole-brain T1, T2, PD and additional diffusivity mapping with 1.25-mm isotropic resolution within 3min. To improve the image quality, cardiac gating and low-resolution navigator were also implemented to mitigate the signal variation caused by motion during diffusion encoding. Subspace reconstruction was used along with LLR regularization to improve the reconstruction conditioning as well as SNR.
Joint Generation of Multi-contrast Magnetic Resonance Images and Segmentation Map Using StyleGAN2-based Generative Network
Authors: Son Geonhui , Eo Taejoon , Jun Yohan , Shin Hyungseob , Hwang Dosik
Published: August 2023

Training deep neural networks for medical imaging commonly requires large image datasets and paired label datasets. However, in the medical imaging research field, labeling costs are very expensive. To overcome this issue, we propose a data generation method which is StyleGAN2-based architecture that jointly generates multi-contrast magnetic resonance (MR) images and segmentation maps. The effectiveness of our generation model is validated in terms of segmentation performance for tumors. We demonstrate that the segmentation model only trained with the fake data generated from our method achieves comparable performance to that trained with real data.
Advances in accelerated imaging at 9.4T with electronically modulated time-varying receive sensitivities
Authors: Glang Felix , Nikulin Anton , Bause Jonas , Heule Rahel , Steffen Theodor , Avdievich Nikolai , Scheffler Klaus
Published: August 2023

Previously, we have shown in simulations that electronically modulated time-varying receive sensitivities can improve parallel imaging reconstruction when fast modulations are applied during acquisition of k-space lines. Here, we demonstrate this concept experimentally with a prototype 8-channel reconfigurable receive coil, for which B1- modulation is achieved by fast switching PIN diodes in the receive loops. With this setup, MR measurements were performed in both phantom and human subject. Lower reconstruction errors and g-factors (~25% improvement for R=4) were observed for the case of rapidly switched sensitivities compared to conventional reconstruction with static sensitivities.
Simultaneous 3D T1- and T2-weighted imaging using RF phase-modulated GRE with retrospective contrast adjustment
Authors: Tamada Daiki , Field Aaron , Reeder Scott
Published: August 2023

A novel method to obtain simultaneous 3D T1- and T2-weighted imaging with retrospective contrast adjustment was developed. Acquisitions are performed using a 3D RF phase-modulated GRE acquisition with a small RF phase increment. After phase correction, real and imaginary components are separated into T2- and T1-weighted images, respectively. Image contrast can also be modified by modulating additional phase into the signals retrospectively. Simulation and in vivo examples are shown. The results suggested the proposed method successfully provides arbitrary image contrasts with clinically acceptable quality and short acquisition time.
Inversion Recovery Look-Locker T1-Mapping for Abdominal Imaging: How Many Slices Can One Fit in a Single Breath-Hold?
Authors: Goerke Ute , Ahanonu Eze , Keerthivasan Mahesh , Bilgin Ali , Deshpande Vibhas , Altbach Maria
Published: August 2023

In the inversion-recovery Look-Locker T1-mapping, the use of slice-selective inversion recovery pulse is explored to map the long T1-values of the spleen with as many slices as possible. The optimal slice gap in combination with interleaving the slices was determined. Artifact-free T1-maps of the spleen were obtained after parameter optimization with double the number of slices than using the standard approach in a single breath-hold. This new approach is an important step towards achieving complete coverage of abdominal organs within a single breath-hold.
T2* mapping for Fat and Water images using Two-Point Dixon method with intrinsic B0 updating
Authors: Chao Tzu-Cheng , Wang Dinghui , Pipe James
Published: August 2023

Accurate fat fraction and T2* evaluation offers useful diagnostic information. A data driven B0-update algorithm in conjunction with the Two-Point Dixon method is illustrated in this work, offering efficient computation to improve B0 accuracy to separate fat and water in the multiple TE acquisition. The individual fat and water signals are then used for T2* mapping. The reconstructed parametric maps have comparable quality to those of the existing methods. The results also show that the proposed method requires shorter computation time and is more stable in the presence of an inaccurate reference field map.
Free-Breathing Dual-Flip-Angle Multitasking Multi-Echo (MT-ME-dFA) MRI for Whole-Liver, B1+ Insensitive Quantification of T1, PDFF, and R2*
Authors: Wang Nan , Serry Fardad , Cao Tianle , Han Fei , Xie Yibin , Zhong Xiaodong , Ma Sen , Bi Xiaoming , Noureddin Mazen , Hussain Shehnaz , Deshpande Vibhas , Christodoulou Anthony , Li Debiao
Published: August 2023

Quantitative T1, fat fraction, and R2* show promise for characterizing chronic liver diseases. We develop a dual-flip-angle MultiTasking Multi-Echo (MT-ME-dFA) technique to achieve B1+ insensitive, whole-liver joint T1/water-specific T1(T1w), fat fraction(PDFF), and R2* quantification. Respiratory motion is resolved through multidimensional low-rank tensor imaging, and B1+ robustness is achieved by modeling the inversion recovery with two alternating flip angles. Compared to the previously published single-flip-angle MT-ME approach, intra-subject variation on T1/T1w maps was substantially reduced; stronger correlation was achieved for T1/T1w, PDFF and R2* with references on phantom; root-mean-square of intra-subject T1/T1w variation was substantially reduced from 72ms/63ms to 39ms/31ms.
Quantitative 23Na-MRI of the intervertebral disk at 3T
Authors: Cavusoglu Mustafa , Rossi Christina
Published: August 2023

Monitoring the tissue sodium content (TSC) in the intervertebral disk geometry by MRI is sensitive measure to diagnose degenerative disk disease (DDD) and of lumbar back pain (LBP) in intervertebral disks. However, application of quantitative sodium concentration measurements in 23Na-MRI is highly challenging due to the lower in vivo concentrations and smaller gyromagnetic ratio. Moreover, imaging the intervertebral disk geometry places higher demands because the necessary RF volume coils produces highly inhomogenous transmit field patterns. In this study, we reported for the first time quantitative sodium concentration in the intervertebral disks at clinical field strengths (3T).
Pilot Tone-guided focused navigation for free-breathing whole-liver fat-water quantification
Authors: Mackowiak Adèle , Roy Christopher , Falcaõ Mariana , Bustin Aurélien , Bacher Mario , Speier Peter , Piccini Davide , Stuber Matthias , Vietti-Violi Naïk , Bastiaansen Jessica
Published: August 2023

A free-breathing 3D radial multi-echo GRE acquisition for whole-liver fat-water separation and quantification was proposed, which integrated retrospective respiratory motion extraction with Pilot Tone and motion-compensated reconstruction with focused navigation. The proposed framework was tested in 10 healthy volunteers at 1.5T. Post-processing of the 8 reconstructed and denoised echoes with a graphcut algorithm provided fat-water separated images and fat fraction maps of isotropic resolution. Images and maps were compared to breath-held reference 3D and 2D Cartesian acquisitions for validation of the quality of both motion compensation and fat-water separation.
Influence of hepatic tissue water content on MRE-based biomarkers in clinical and preclinical studies
Authors: Li Jiahui , Zhu Zheng , Chen Jingbiao , Allen Alina , Venkatesh Sudhakar , Mounajjed Taofic , Glaser Kevin , Manduca Armando , Shah Vijay , Ehman Richard , Yin Meng
Published: August 2023

The water in hepatic tissue has intracellular, extracellular matrix bound, and extracellular interstitial free fluid components, which are affected by inflammation and fibrosis. This study assessed longitudinal changes in MRE-based biomarkers and their relationship with hepatic water content in clinical and preclinical models. In clinical studies, MRE-assessed loss modulus (LM) was elevated in obese patients and in NAFLD patients with severe inflammation. In preclinical models, changes in LM correlated with water content and disease progression in non-NAFLD mice. LM significantly increased with the development of NASH. MRE-assessed viscoelasticity strongly reflects extracellular free fluid associated with inflammation.
Self-Navigated Radial Free-Breathing Magnetic Resonance Elastography of the Liver with Rapid Motion Encoding in Children at 3T
Authors: Kafali Sevgi , Bolster Bradley , Shih Shu-Fu , Kim Grace , Yeh Joanna , Venick Robert , Ghahremani Shahnaz , Calkins Kara , Wu Holden
Published: August 2023

Hepatic stiffness measured by magnetic resonance elastography (MRE) is a biomarker for hepatic fibrosis. Conventional Cartesian gradient-echo MRE requires breath-holding (BH), which can be challenging for children. While radial free-breathing (FB) MRE overcomes the challenge of BH, the scan time is relatively longer (163 seconds/slice). This study’s objective was to reduce radial FB-MRE scan time by a factor of two with rapid motion encoding (81 seconds/slice) and to improve robustness by performing self-navigated motion compensation. Compared to Cartesian BH-MRE in children at 3T, the proposed rapid radial FB-MRE technique quantified hepatic stiffness with close agreement and similar repeatability.
Feasibility of compressed sensing accelerated Ristretto magnetic resonance elastography in the pancreas
Authors: van Schelt Anne-Sophie , Wassenaar Nienke , Runge Jurgen , Nelissen Jules , Troelstra Marian , Guenthner Christian , Sinkus Ralph , Stoker Jaap , Nederveen Aart , Schrauben Eric
Published: August 2023

Magnetic resonance elastography (MRE) allows for non-invasive determination of pancreatic visco-elastic properties in four consecutive breath-holds. The aim of this study was to develop and test a single breath-hold MRE acquisition accelerated using prospective undersampling and compressed sensing (CS) reconstruction. Testing was done on a retrospective undersampled phantom dataset and in-vivo. These showed that CS accelerated (R< 8.7), single breath-hold MRE is feasible without hampering visco-elastic reconstruction in tissues with low shear stiffness (|G*|<1.6kPa). Further research is necessary to guarantee accuracy of the measured shear stiffness, notably for high stiffness tissues such as tumors, and at higher acceleration factors.
Acquisition and data processing considerations in functional metabolic imaging using CEST
Authors: Bardin Solène , Boumezbeur Fawzi , Ciobanu Luisa
Published: August 2023

Accelerated acquisitions with a CEST-linescan sequence coupled with the estimation of the local baseline for the analysis of the Z-spectra allow to simultaneously monitor dynamic changes at several CEST contributions induced by a controlled pH decrease. This approach can be a promising strategy for detecting functional induced metabolic changes devoid of confounding BOLD effects.
Curve shape analysis of dynamic glucose enhanced (DGE) and dynamic contrast enhanced (DCE) MRI in patients with brain tumor
Authors: Seidemo Anina , Wirestam Ronnie , Helms Gunther , Bloch Karin Markenroth , Xu Xiang , Bengzon Johan , Sundgren Pia , van Zijl Peter , Knutsson Linda
Published: August 2023

Dynamic glucose-enhanced (DGE) MRI provides time intensity curves after D-glucose injection and is promising as a less invasive alternative or complement to dynamic contrast-enhanced (DCE) MRI. Here, we calculated non-model-based parameter maps from DGE and DCE MRI of human brain tumors, and created color-coded “curve maps”, a graphic representation of different curve shapes, to further investigate temporospatial enhancement patterns. The results show that DGE MRI can differentiate tumor from healthy brain tissue, that DGE and DCE give similar but not identical information, and that the proposed curve map approach has potential to aid in visual assessment of dynamic images.
A method to increase the resolution of sodium images from simultaneous 1H MRF/23Na MRI
Authors: Rodriguez Gonzalo , Yu Zidan , O'Donnell Lauren , Calderon Liz , Shaykevich Sarah , Cloos Martijn , Madelin Guillaume
Published: August 2023

In this work, we present an algorithm to generate a high-resolution 23Na image from simultaneously-acquired low-resolution 23Na density-weighted MRI (2.85×2.85×5 mm3) and high-resolution 1H density, T1, and T2 maps from MRF (1.5×1.5×5 mm3) in brain at 7 T. As a result, the mean value of the difference between the generated and ground truth high-resolution 23Na images is 0.5% with a standard deviation of 6.2% and multi-scale structural similarity index of 0.97.
Increased oxygen extraction fraction following acute multiple sclerosis (MS) lesion formation is associated with increased myelin repair.
Authors: Cho Junghun , Nguyen Thanh , Zexter Lily , Sweeney Elizabeth , Spincemaille Pascal , Gupta Ajay , Gauthier Susan , Wang Yi
Published: August 2023

Understanding the cause and progress of remyelination in MS is critical for developing potential therapeutic targets of remyelination to restore neural connectivity and brain functions. In this study, we utilized a novel MRI-based oxygen extraction fraction (OEF) mapping method, namely “QQ”, and found that early lesion oxygen metabolism increase, as measured by QQ-based OEF, is positively associated with lesion myelin recovery, as measured by myelin water fraction. This study suggests that QQ-based OEF mapping may be a useful tool readily and widely available for studying MS lesion oxygen metabolism and its association with MS lesion remyelination.
Imaging multiple sclerosis histopathology
using susceptibility source separation: a postmortem brain study
Authors: Shin Hyeong-Geol , Galbusera Riccardo , Seo Jincheol , Ji Sooyeon , Bahn Erik , Franz Jonas , Stadelmann-Nessler Christine , Lu Po-Jui , Jang Jinhee , Lee Youngjeon , Granziera Cristina , Lee Jongho
Published: August 2023

The pathology of multiple sclerosis (MS) is highly correlated with the dynamics of two susceptibility sources, paramagnetic iron and diamagnetic myelin. Various MRI methods sensitive to the substances have been developed for MS pathology. However, the collective effects of iron and myelin to an MRI signal have hampered monitoring individual changes of the substances. Here, we evaluated the effectiveness of 𝜒-separation, which estimates individual contributions of para-/dia-magnetic susceptibility, for visualizing MS pathology-related iron/myelin changes. The resulting paramagnetic and diamagnetic susceptibility conform to the histopathological features of MS lesion (iron-rim in Perls staining, and re-/de-myelinated lesions in myelin basic protein staining).
Acute Ischemic Stroke: Infarct Core Estimation from Threshold-based DWI Delineation Depends on the DWI protocol
Authors: Rafael-Patiño Jonathan , Fischi-Gomez Elda , Otálora Sebastian , Ravano Veronica , Saliou Guillaume , Hajdu Steven , Kober Tobias , Wiest Roland , Michel Patrik , McKinley Richard , Richiardi Jonas
Published: August 2023

In acute stroke assessment, reference clinical trials such as DEFUSE-3 use absolute thresholds on ADC maps to define the infarct core. Yet, the variance of ADC values, but not the mean, change with the number of diffusion directions and the specific directions in a 4-directions sampling scheme. The resulting shifts in ADC distribution tails result in an overestimation of the infarct core. This has implications for multi-centric trials, where infarct sizes and locations may be biased simply due to diffusion protocol differences and/or different head positions with respect to B0.
Sensing brain plasticity after stroke using magnetic resonance elastography
Authors: Annio Giacomo , Mangin Gabrielle , Barbero-Mota Marco , Caligiuri Giuseppina , Nicoletti Antonino , Schregel Katharina , Sinkus Ralph
Published: August 2023

Stroke is the leading cause of death globally. The infarcted area undergoes a deprivation of oxygen and energy, followed by multiple transient events and reorganization processes called ischemic cascade. MRI is the reference tool for accurate diagnosis, volumetric assessments and age determination of the lesion. The aim of the present study was to investigate the time course of changes in tissue biomechanics after an ischemic event in mice using MRE and study the relationship between stroke volume and tissue biomechanics, to explore a potential role of MRE in assessing the post stroke recovery.
Assessment and improvement of the quality of fat saturation in breast MRI using deep-learning with synthetic data
Authors: Kang Junghwa , Park Ga Eun , Kim Sung Hun , Nam Yoonho
Published: August 2023

We propose a fully automatic method to assess and improve the quality of the fat saturation in breast MR images. For this purpose, three deep neural networks were trained using both actual and synthetic breast MR data. Firstly, the poorly fat saturated cases were classified using a binary classification network. Then, the poorly fat saturated regions were localized using a segmentation network. Lastly, for the poor cases, the remaining fat signals were retrospectively suppressed using a correction network. The results showed that our networks successfully identified the poor cases and suppressed the remaining fat signals.
Deep Learning for Triage of Normal Breast MRI Exams to an Abbreviated Interpretation Worklist
Authors: Bhowmik Arka , Monga Natasha , Belen Kristin , Martinez Danny , Sutton Elizabeth , Pinker-Domenig Katja , Eskreis-Winkler Sarah
Published: August 2023

In this abstract, we develop and evaluate a deep learning model to identify completely normal screening breast MRIs for triage to an abbreviated interpretation worklist, a workflow that misses no cancers and markedly reduces radiologist interpretation times. In our held out test set, the algorithm triaged 20% of all screening exams to the abbreviated worklist and 80% to full interpretation worklist for radiologist without missing any cancer exams (100% sensitivity), which reduced the total projected reading time for exams from 148 hours to 119 hours.
Silicone Implant and Fibrous Capsule Assessment Based on Water-Fat-Silicone Images from a Chemical Shift Encoding-Based Species Separation
Authors: Borde Tabea , Wiedemann Antonia , Stelter Jonathan , Böhm Christof , Ruschke Stefan , Weiss Kilian , Wu Mingming , Makowski Marcus R. , Karampinos Dimitrios , Fallenberg Eva
Published: August 2023

With continuously rising breast augmentation procedures worldwide, there is an increasing clinical need for an early and accurate detection of implant complications. In clinical practice, silicone implants are mainly visualized by silicone-only acquisitions which can be limited by a low signal-to-noise ratio and poor resolution. The present work proposes chemical shift encoding-based multi-echo gradient-echo imaging in combination with a robust graph-cuts-based water-fat-silicone separation. The resulting multi-contrast imaging at high isotropic resolution enables a more precise delineation of the implant capsule and a better evaluation of the implant’s integrity compared to conventional silicone-only acquisition.
Field-Cycling imaging identifies breast cancer at low magnetic field strengths
Authors: Mallikourti Vasiliki , Ross James , Maier Oliver , Davies Gareth , Lip Gerald , Bödenler Markus , Stollberger Rudolf , Masannat Yazan , Broche Lionel
Published: August 2023

Field-Cycling imaging (FCI) can image over a range of low magnetic field strengths (0.2 T to 0.2 mT) through rapid switching between magnetic field levels. This allows measuring the field-depended changes of the longitudinal T1 relaxation time, known as T1 dispersion, exploring new approaches for breast tumour contrast. FCI images were acquired from patients with breast tumours to generate multi field-T1 maps and T1 dispersions. The T1 maps exhibited visible contrast of the tumour region. T1 dispersion profiles from tumours differed from those in healthy breast tissues, showing that FCI can detect breast tumours at low field strengths.
Evaluation of the lipid composition in mice transplanted with obese human microbiota using magnetic resonance spectroscopy
Authors: Piraquive Joao , Desmoulin Franck , Fernandez-Real José , Burcelin Rémy , Collet Xavier , Bouloumié Anne
Published: August 2023

In this project, mice devoid of microbiota were transplanted with human microbiota from obese patients. Our work focused on evaluating and comparing the lipid composition in the white adipose in mice with different gut microbiota backgrounds using MRS. Our findings showed differences in white adipose tissue storage, lipid composition, and fatty acid composition among the different groups. This suggests that MRS can be used as a noninvasive tool to monitor dysbiotic gut microbiota in obese patients and evaluate a potential therapeutic response for obesity.
Evaluation of perfusion effects on HP[1-13C]pyruvate imaging parameters in patients with glioblastoma
Authors: Vaziri Sana , Autry Adam , Lafontaine Marisa , Lupo Janine , Gordon Jeremy , Hu Jasmine , Chen Hsin-Yu , Kim Yaewon , Villanueva-Meyer Javier , Chang Susan , Clarke Jennifer , Bush Nancy Ann Oberheim , Xu Duan , Larson Peder , Vigneron Daniel , Li Yan
Published: August 2023

Dynamic hyperpolarized (HP) 13C metabolic imaging allows for non-invasive measurements of real-time enzymatic conversion of injected [1-13C]pyruvate to [1-13C]lactate. The HP signal depends on several factors, including perfusion and monocarboxylate transporter activity. Previously, a global increase of pyruvate-to-lactate apparent conversion rates values was found in patients with glioma after receiving anti-angiogenic therapies. To better understand the effects of tissue vasculature on HP signals, we investigated the relationship between HP[1-13C]pyruvate metabolism and 1H perfusion parameters in normal-appearing white matter patients with glioma.
BayesTract: Automated machine learning based brain artery segmentation, anatomical prior annotation and feature-extraction in MR Angiography
Authors: Faiyaz Abrar , Hoang Nhat , Finkelstein Alan , Zhong Jianhui , Doyley Marvin , Wang Henry , Uddin Md Nasir , Schifitto Giovanni
Published: August 2023

Brain arterial-blood-vessels can carry important information regarding cerebrovascular pathogenesis. Due to non-invasiveness, 3D-time-of-flight MR-angiography is widely used to depict arteries in clinical-exams. However, deemed limited for qualitative assessment in clinical setting. Although several post-processing approaches exist such as tool-based-manual segmentation and diameter-marking or deep-learning-based segmentations--these require huge-time and experienced-eyes or large manually-segmented training-sets, making performance variable. Since brain-artery-annotations are anatomically-inspired, anatomical-confidant-points identified with a Bayesian approach can be used to annotate major-brain-arteries, which circumvents the need for large-dataset from learning requirement. The approach will allow clinical evaluations of major-arteries and biomarker identifications for cerebrovascular pathogenesis with limited resource and time.
Quantitative Parameter Mapping of Prostate using Stack-of-Stars and QTI Encoding
Authors: Schulte Rolf , Pirkl Carolin , Garcia-Polo Pablo , Cencini Matteo , Tosetti Michela , Marti-Bonmati Luis , Menzel Marion
Published: August 2023

Quantitative MRI offers diagnostic insights into tissue and enables characterisation of diseases, while reducing variability between operators, sites and vendors. A stack-of-stars sequence using Quantitative Transient State Imaging (QTI) was optimised and implemented to map T1, T2 and Proton Density in human prostates. Resulting in vivo multi-parametric maps were of high quality, while validation in the NIST phantom show good agreement with T1 and T2 reference values.
Light Coils: MRI with Modular RF Coils Using
Optical Power and Data Transmission
Authors: Özen Ali , Taege Yanis , Lottner Thomas , Ilbey Serhat , Ataman Caglar , Bock Michael
Published: August 2023

An optically powered and broadcasted modular receive coil concept (Light Coils) is presented for MRI to simultaneously eliminate the challenges in MRI of pediatric or overweight patients, signal-to-noise ratio losses and potential safety hazards due to electro-magnetic interferences in the transmission cables, and Ohmic losses in the metallic wires. By combining innovative RF antenna architectures, low-noise-low-power front end electronics and state-of-the-art silicon photonics technology, Light Coils might offer a robust and scalable solution for MRI image acquisition. Preliminary experimental results on the power-on-fiber driving of LNAs, and optical active detuning of receive coils are also discussed.
Development of a Broadside-Coupled Split-Ring Resonator-Based Metasurface to Improve MRI at Ultra-High Fields
Authors: Alipour Akbar , Seifert Alan , Delman Bradley , Balchandani Priti
Published: August 2023

There is a growing interest in ultra-high field magnetic resonance neuroimaging because of the greater signal-to-noise ratio (SNR) compared with conventional field strengths. However, visualization at these higher field strengths and Larmor frequencies is challenged by wavelength effects, compromising anatomical coverage of commercial coils. A novel metasurface based on a hybrid structure consisting of an array of broadside-coupled split-ring resonators and high permittivity materials was designed to augment signal at the 7 Tesla 1H Larmor frequency. This reusable surface device markedly improves SNR in caudal head structures that have historically been limited by poor signal.
Multiple sclerosis T2 lesion volume correlates weakly with myelin water fraction
Authors: Joseph Tigris , Liu Hanwen , Zhao Guojun , Kolind Shannon , Carruthers Robert , Schabas Alice , Sayao Ana-Luiza , Devonshire Virginia , Tam Roger , Wayne Moore G. R. , Li David K. B. , Traboulsee Anthony , Vavasour Irene M. , Laule Cornelia
Published: August 2023

Multiple sclerosis (MS) lesion volume is commonly reported but is not pathologically specific or strongly associated with MS disability. Lesions are not necessarily demyelinated, which may be why lesion volume and disability are not strongly correlated. MS lesion volume was compared to Myelin Water Imaging (MWI) derived metrics related to myelin content (myelin water fraction) and inflammation (geometric mean T2) in MS normal appearing white matter and lesions. Weak correlations were observed between lesion volume and MWF, highlighting that the amount of lesional tissue does not reflect the degree of myelin damage within the brain.
Three dimensional multi-parameter brain mapping using MR fingerprinting for characterization of multiple sclerosis lesions
Authors: Menon Rajiv , Sharafi Azadeh , Muccio Marco , Smith Tyler , Kister Ilya , Ge Yulin , Regatte Ravinder
Published: August 2023

A 3D multi-parameter MRF imaging technique capable of quantifying 4 different parameters (T1, T2, T1ρ, B1) was developed for multiple sclerosis(MS) application. The 3D-MRF technique was tested with multiple shots on a standardized NIST/ISMRM phantom, and brain imaging in 5 healthy volunteers. The 3D-MRF was also tested on two MS patients with chronic and enhancing MS lesions. The phantom studies demonstrate that quantitative maps are in agreement with reference, healthy volunteer studies show the agreement between multiple shots and SNR improvement with increasing shots. The MS patient results demonstrate the potential use of mutli-parameter quantitative mapping for WM characterization.
BBB water exchange rate and permeability mapping with multi-delay diffusion weighted pseudo-continuous arterial spin labeling
Authors: Shao Xingfeng , Wang Danny JJ
Published: August 2023

We proposed a new sequence which improves the SNR of diffusion weighted ASL signals, and simultaneously estimates kw, water extraction ratio (Ew) and PSw using a multi-delay approach with PLDs ranging from 1500 to 2700 msec. Whole brain average CBF = 67.8±6.7 ml/100g/min, kw = 103.7±16.6 min-1, Ew = 94.8±1.3% and PSw = 202.2±41.3 ml/100g/min. These results match the recent literatures on kw and PSw studies. Ew ~95% suggests two long PLDs of 2400 and 2700 msec are sufficient to allow complete water extraction.
Mapping of Metabolite Profile of Urine of Patients with Chronic Prostatitis, Prostate Cancer and Healthy Controls: A Pilot NMR Metabolomic Study
Authors: Jagannathan Naranamangalam , Reddy R Ravikanth , Shirshetty Arun , Marwan Samsudeen , Masanam Deepak , Sivaraman Ananathakrishanan
Published: August 2023

The present study aims to evaluate a comprehensive metabolic profiling of patients with chronic prostatitis (PT) by investigating their urine samples and compare it with the prostate cancer (PCa) patients and healthy controls (HC) using 1H nuclear magnetic resonance (NMR) metabolomics. The metabolic profile of chronic prostatitis patients falls between that seen for PCa and HC. This pilot study showed that NMR metabolomics may be useful to differentiate patients with PT from PCa and HC.