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Elisa Moya-Sáez^1,2, Rodrigo de Luis-García¹, Juan A. Hernández-Tamames², and Carlos Alberola-López^1
1University of Valladolid, Valladolid, Spain, ²Erasmus MC, Rotterdam, Netherlands

Keywords: MR Fingerprinting/Synthetic MR, Machine Learning/Artificial Intelligence

Gadolinium based contrast agents (GBCAs) have the ability to uncover blood brain barrier damage, which appears in the images as contrast enhancement caused by the leakage into the perivascular tissues. However, in clinical practice, this assessment is performed by visual comparison between the weighted images obtained before and after the GBCA injection; enhancement quantification is still an unmet need. In this work we propose a deep learning approach for the computation of pre- and post-contrast parametric maps from conventional T1 weighted images. Results show how those maps can enable an automatic quantification of the tumor enhancement.

Baohong Wen¹, Yong Zhang¹, Jingliang Cheng¹, Tianyong Xu², Xiaoxia Hua², and Lizhi Xie^2
1the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, ²GE Healthcare, Shanghai, China

Keywords: MR Fingerprinting/Synthetic MR, Head & Neck/ENT

Accurate determination of the preoperative classification of histology of head and neck tumor remains a challenge. The aim of the study was to evaluate the feasibility and capability of synthetic MRI and stimulus and fast spin echo diffusion-weighted imaging (FSE-PROPELLER duo-DWI) for the differentiation of malignant from benign head and neck tumors. The results quantitively demonstrated the feasibility and also showed that T2 value is comparable to ADC value, and the combination of T2 and ADC values could provide improved diagnostic efficacy. 

Yaping Wu¹, Qian Xie², Ge Zhang¹, Yan Bai¹, Xipeng Yue¹, Wei Wei¹, Fangfang Fu¹, Nan Meng¹, Xianchang Zhang³, Yusong Lin^4,5,6, and Meiyun Wang^1
1Department of Medical Imaging, Henan Provincial People’s Hospital, Zhengzhou, China, ²School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China, ³MR Collaboration, Siemens Healthineers Ltd., Beijing, China, ⁴School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China, ⁵Collaborative Innovation Center for Internet Healthcare, Zhengzhou University, Zhengzhou, China, ⁶Hanwei IoT Institute, Zhengzhou University, Zhengzhou, China

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting, Parkinson's disease

This study investigated the utility of 3D high resolution magnetic resonance fingerprinting (MRF) to detect potential brain changes in Parkinson’s disease (PD). MRF T1 and T2 maps of the brains of 22 PD patients and 22 volunteers were non-linearly normalized into the MNI space to explore the group differences using whole-brain analysis. PD patients had significantly higher T1 and T2 values in the right inferior temporal gyrus anterior/posterior division, right temporal fusiform cortex anterior division, right planum polare and red nucleus. Our findings suggest that quantitative parameters acquired from 3D MRF may provide additional information for precise diagnosis of PD.

Min Gao¹, Jun Liu¹, Liyun Zheng², and Yongming Dai^3
1Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China, ²Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China, ³MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

Multi-parametric MR imaging methods have been intensively developed and investigated throughout the last decade. The purpose of this study was to utilize the single-scan 3D multi-parametric MRI technique, MULTIPLEX, to characterize and grade intracranial tumors. According to the results, MULTIPLEX MRI can effectively decrease the scan time while obtaining multi-parametric images and mappings. Besides, the simultaneous quantitative estimation of multiple MR parameters can reliably characterize and grade intracranial tumors.

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Kaia Ingerdatter Sørland¹, Christopher George Trimble¹, Tone Frost Bathen^1,2, Mattijs Elschot^1,2, and Martijn A. Cloos^3
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway, ²Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway, ³Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia

Keywords: MR Fingerprinting/Synthetic MR, Artifacts

High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streaking artefacts from flow in the femoral blood vessels, distorting quantitative T₁ and T₂ measurements. We here compare two approaches to mitigate these artefacts, namely incorporating regional saturation bands in the MRF sequence (Sat-MRF) or applying region-optimized virtual coils to suppress signal from select spatial regions before image reconstruction (ROVir-MRF). Results from seven asymptomatic volunteers show that both methods efficiently reduce signal in the region of the femoral vessels, but there are differences in retained prostate signal to noise ratio and sensitivity to T₁.

Qi Zhao¹, Zhihua Pan¹, Mingli Jin¹, Kebin Yu¹, Yin Jiang¹, and Miaoqi Zhang^2
1The 2nd Affiliated Hospital of Chengdu Medical College Nuclear Industry 416 Hospital, Chengdu, China, ²GE Healthcare, Beijing, China

Keywords: MR Fingerprinting/Synthetic MR, MR Value

Clinical and pathological staging are vital for management of Cervical squamous carcinoma (CSC). In this study, using synthetic MR technique, we investigate quantitative T1, T2 and PD measurements in different clinical and pathological stage groups. Performance of those quantitative measurements in diagnosing poorly-differentiated CSC is also investigated. We find T2 values are higher in late clinical stage CSC. Results also show a correlation between quantitative measurements and the degree of pathological differentiation. ROC analysis demonstrate that T1 and T2 values can differentiate poorly-differentiated CSC from intermediate and well differentiated CSC¹.

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Mark Widmaier^1,2,3, Zirun Wang¹, Song-I Lim^1,2,3, Daniel Wenz^1,2, and Lijing Xin^1,2
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Animal Imaging and Technology, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, ³Laboratory of functional and metabolic imaging, Ecole Polytechniqe Federale de Lausanne (EPFL), Lausanne, Switzerland

Keywords: MR Fingerprinting/Synthetic MR, Machine Learning/Artificial Intelligence, MRS, Phosporus, Creatine Kinase, MRF

A new magnetization transfer ³¹P Magnetic Resonance Fingerprinting (31P-MRF) technique is emerging to measure the creatine kinase (CK) chemical exchange rate k_CK. The inherent obstacle of the exponential growth in the size of dictionaries with the number of free parameters, was overcome by introducing the nested iteration interpolation method (NIIM). To further reduce the processing time and cope with a nonlinear behaviour, we employed an artificial neuron network (ANN), instead of an interpolation method (IPM) as in the original approach. The nested iteration ANN method (NIAN) is compared with NIIM using simulation data and in vivo ³¹P-MRF data.

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Aurélien Delphin¹, Thomas Coudert¹, Audrey Fan², Michael E. Moseley³, Greg Zaharchuk³, and Thomas Christen^1
1Univ. Grenoble Alpes, INSERM U1216, Grenoble Institut Neurosciences, GIN, Grenoble, France, ²Biomedical Engineering, University of California Davis, Davis, CA, United States, ³Department of Radiology, Stanford University, Stanford, CA, United States

Keywords: MR Fingerprinting/Synthetic MR, Oxygenation

The MR vascular fingerprinting (MRvF) approach extends the concept of MR fingerprinting to the study of microvascular properties and functions. Encouraging results have been obtained in healthy human volunteers as well as in stroke and tumor models in rats. However, it has been suggested that the method has a low sensitivity to blood oxygenation measurements. We improved the MRvF approach by using simulations with 3D realistic blood vessels from animal microscopy, new fingerprint-pattern organization and machine learning tools. The method was tested in retrospective data acquired in healthy-human volunteers while breathing different gas mixtures (Hyperoxia (100%O₂), Normoxia (21%O₂), hypoxia (14%O₂)).

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Lukas Folle¹, Lorenz Kapsner^2,3, Andreas Maier¹, Michael Uder², Sabine Ohlmeyer², and Sebastian Bickelhaupt^2
1Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, ²Institute of Radiology, Universitätklinikum Erlangen-Nürnberg, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, ³Universitätklinikum Erlangen-Nürnberg, Friedrich-Alexander-Universität Erlangen-Nürnberg, Medizinisches Zentrum für Informations- und Kommunikationstechnik, Erlangen, Germany

Keywords: MR Fingerprinting/Synthetic MR, Breast

The training of neural networks for classification or segmentation of medical images requires large amounts of training data. Sharing of these datasets is commonly difficult due to legislation and privacy constraints of medical data. In this work, we demonstrate the utility of latent diffusion models that allow the generation of synthetic samples of dynamic contrast-enhanced breast MRI-derived maximum intensity projections of subtraction series. Whilst the image quality of the generated data is high as demonstrated by a radiologist evaluation, further steps are envisioned to derive specific compounds of data, e.g., BI-RADS, FGT, or BPE classes.

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Jesus Ernesto Fajardo¹, Anna Lavrova¹, Vikas Gulani¹, and Yun Jiang^1,2
1Department of Radiology, University of Michigan, Ann Arbor, MI, United States, ²Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting, prostate cancer

We developed a 3D MR Fingerprinting method with B₀ correction for imaging the prostate gland. T₁ and T₂ maps with the spatial resolution of 1 x 1 x 3 mm³ were obtained from phantom and in-vivo experiments, demonstrating the potential of performing accurate and high-resolution tissue quantification of prostate cancer.

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Madison Kretzler¹, Xinzhou Li², Leonardo Kayat Bittencourt^3,4, Mark Griswold¹, and Rasim Boyacioglu^1
1Radiology, Case Western Reserve University, Cleveland, OH, United States, ²MR R&D Collaborations, Siemens Medical Solutions USA, Inc., St. Louis, MO, United States, ³Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States, ⁴School of Medicine, Case Western Reserve University, Cleveland, OH, United States

Keywords: MR Fingerprinting/Synthetic MR, Liver, prospective, Free-breathing, Pilot tone

A Pilot Tone (PT) based comparison study is presented for abdominal free-breathing MRF using a previously validated PT extraction and vendor developed extraction methods. The initial steps towards prospective processing of the data for immediate availability of the free-breathing MRF quantitative maps on the console are demonstrated. In vivo comparison results for various free-breathing patterns are shown with consistent agreement between respiratory motion in PT extraction methods. Extraction of the respiration signal from PT via the vendor reconstruction software is the first step towards prospective free-breathing abdominal MRF.

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Marta Lancione¹, Matteo Cencini¹, Guido Buonincontri¹, Jan Kurzawski², Joshua D Kaggie³, Tomasz Matys³, Ferdia A Gallagher³, Graziella Donatelli^4,5, Paolo Cecchi^4,5, Mirco Cosottini⁶, Nicola Martini⁷, Francesca Frijia⁷, Domenico Montanaro¹, Pedro A Gómez⁴, Rolf F Schulte⁸, Alessandra Retico⁹, Laura Biagi¹, and Michela Tosetti^1
1IRCCS Stella Maris, Pisa, Italy, ²New York University, New York, NY, United States, ³University of Cambridge, Cambridge, United Kingdom, ⁴IMAGO7 Foundation, Pisa, Italy, ⁵Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy, ⁶University of Pisa, Pisa, Italy, ⁷Fondazione Toscana Gabriele Monasterio, Pisa, Italy, ⁸GE Healthcare, Munich, Germany, ⁹Istituto Nazionale di Fisica Nucleare, Pisa, Italy

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting, Myelin, Reproducibility

Myelin Water Fraction (MWF) can measure White Matter (WM) myelination and integrity and can be quantified using Magnetic Resonance Fingerprinting (MRF) which allows short scan time. In this work, we assessed the repeatability and the reproducibility of MWF using 3D SSFP MRF in a traveling head study performed on healthy volunteers scanned at five different scanners from the same vendor. We computed coefficients-of-variation to estimate voxelwise variability in WM and GLM analysis to measure biases. We reported a variability of ∼3% for repeated scans at the same site and ∼5% for different sites, with an average bias of 5%.

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Zhibo Zhu¹, Nam Gyun Lee², Ye Tian¹, and Krishna S. Nayak^1
1Department Of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ²Department Of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States

Keywords: MR Fingerprinting/Synthetic MR, Brain

We demonstrate FISP-MRF at 0.55T with improved efficiency using longer spiral readouts and concomitant field effect correction. 2D axial FISP-MRF is performed with 3 different readout durations and at 2 different off-isocenter locations, reconstructed without and with MaxGIRF concomitant field correction. Spatial blurring induced by concomitant field effect was successfully mitigated. In-vivo MRF white matter T₂ achieved tighter distribution with longer readouts, e.g., the coefficient of variation decreased from 9.9% to 4.9%.

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Alexander Fyrdahl^1,2, Jenny Castaings², Rebecka Steffen Johansson¹, Kelvin Chow³, Jannike Nickander^1,2, Nicole Seiberlich⁴, and Jesse I Hamilton^4
1Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden, ²Department of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden, ³MR R&D Collaborations, Siemens Medical Solutions USA Inc., Chicago, IL, United States, ⁴Department of Radiology, University of Michigan, Ann Arbor, MI, United States

Keywords: MR Fingerprinting/Synthetic MR, Cardiovascular

This work describes a pipeline for fully inline generation of T₁, T₂ and extracellular volume (ECV) maps from cardiac Magnetic Resonance Fingerprinting (MRF) data. Reconstruction of multi-parametric tissue property maps using cardiac MRF have recently been made possible directly on the scanner by replacing the need to perform Bloch equation simulations with a neural network. MRF-derived T₁, T₂ and ECV values were acquired and compared to MOLLI and T₂p-SSFP in 5 successive clinical patients.

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Carlos Velasco¹, Carlos Castillo-Passi^1,2, Nadia Chaher¹, Alkystis Phinikaridou¹, René M. Botnar^1,2, and Claudia Prieto^1,2
1School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, ²Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Keywords: MR Fingerprinting/Synthetic MR, Diffusion/other diffusion imaging techniques

In this study we present a golden-angle-radial efficient magnetic resonance fingerprinting approach that enables simultaneous T1, T2 and ADC quantification in a single scan of ~18s and offers the possibility to be extended to a multi-echo acquisition for additional water-fat separation estimation. A quantitative comparison between reference maps and the proposed MRF maps has shown excellent agreement, and a proof-of-concept brain MRF multiparametric T1, T2 and ADC has shown comparable image quality compared to the longer and sequential clinical reference scans.

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Jae-Yoon Kim¹, Jae-Hun Lee¹, Dongyeob Han², Moon Hyung Choi³, and Dong-Hyun Kim^1
1Department of Electrical and Electronic Engineering, Yonsei Univ., Seoul, Korea, Republic of, ²Siemens Healthineers Ltd, Siemens Korea, Seoul, Korea, Republic of, ³Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine,The Catholic University of Korea, Seoul, Korea, Republic of

Keywords: MR Fingerprinting/Synthetic MR, Image Reconstruction, Prostate

Magnetic Resonance Fingerprinting (MRF) is a technology that computes T1, T2 parameters from time-evaluated signals. However, long scanning time in obtaining fully-sampled data is a challenging point while reducing the sampling rate results in poor reconstructed data quality. Here, we propose a spatio-temporal deep learning network for reconstruction from the under-sampled MRF data. According to the retrospective reconstructed results, the proposed method could produce the T1 and T2 maps of high fidelity similar to the fully-sampled ground-truth.

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Rajiv G Menon¹, Hector L de Moura¹, Richard Kijowski¹, and Ravinder R Regatte^1
1Radiology, NYU Grossman School of Medicine, New York, NY, United States

Keywords: MR Fingerprinting/Synthetic MR, Tissue Characterization, Intervertebral disc

The goal of this study was to assess the effect of age and gender in IVD characterization using a multiparameter MR Fingerprinting technique that can quantify T1, T2 and T1rho in a clinically feasible time. Seventeen healthy subjects were recruited. The goal of this study was to assess the effect of age and gender in IVD characterization using a multiparameter MR Fingerprinting technique that can quantify T1, T2 and T1rho in a clinically feasible time. This study suggests that the use of MR fingerprinting is a useful tool to gain insights to pathology resulting in IVD degeneration.

Likai Yu¹, Xiaoqing Shi¹, Lishi Jie¹, Yibao Wei¹, Weiqiang Dou², Shaowei Liu³, and Nongshan Zhang^3
1Nanjing University of Chinese Medicine, Nanjing, China, ²GE Healthcare, MR Research China, Beijing, China, ³Jiangsu Province Hospital of Chinese Medicine, Nanjing, China

Keywords: Data Analysis, Osteoarthritis

The purpose of this study was to investigate whether prolonged overexertion can lead to cartilage degeneration through Synthetic MRI derived relaxation maps. In this study, 30 participants were recruited and measured with T1 and T2 mapping derived by Synthetic MRI. There was a statistically significant trend in cartilage T1 and T2 values in the long-term exercise group compared to the normal exercise group. Based on altered T1 and T2 relaxation properties of cartilage tissues, we conclude that chronic overexercise may lead to cartilage degeneration.

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Thomas Durantel¹, Julie Coloigner¹, Emmanuel Caruyer¹, Gabriel Girard^2,3, and Olivier Commowick^1
1Univ Rennes, INRIA, CNRS, INSERM, IRISA UMR 6074, Empenn ERL U-1228, F-35000, Rennes, France, ²Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ³Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada

Keywords: Data Processing, Tractography & Fibre Modelling

White matter fiber tracking using diffusion magnetic resonance imaging (DWI) provides a powerful approach to map brain connections, but they are not completely reliable both in academic and clinical context. This is because most methods infer global connectivity from local information,leading to a high rate of false positive. We propose a method to include anatomical prior in the tractography algorithm. We show on synthetic DiSCo data that including this prior on two state-of-the-art tractography algorithms could improve the overall shape of the tractograms.

Peng Wang¹, Shudong Hu², Weiqiang Dou³, Jie Shi³, and Heng Zhang^1
1Affiliated hospital of Jiangnan university, Wuxi, China, ²ffiliated hospital of Jiangnan university, Wuxi, China, ³GE Healthcare, MR Research China, Beijing, China

Keywords: Head & Neck/ENT, Quantitative Imaging

This study aimed to evaluate MAGiC imaging (one synthetic MRI technique, syMRI) and its combination with diffusion-weighted imaging (DWI) in discriminating benign from metastatic retropharyngeal lymph nodes (RLNs). With MAGiC derived relaxation parameters, 58 patients with 21 benign and 42 metastatic RLNs were measured. The resultant T1, T2, PD and T1_SD values showed significant different values between benign and metastatic RLNs with an optimal diagnostic performance from T1_SD. Moreover, the combination of MAGiC, DWI, and morphological features demonstrated a significantly improved performance on overall diagnosis.