1
|
Yildirim M, Kovalyk X, Scholtz P, Schütz M, Lindemeyer J, Lamerichs R, Grüll H, Isik EO. Fast 19 F spectroscopic imaging with pseudo-spiral k-space sampling. NMR IN BIOMEDICINE 2024; 37:e5086. [PMID: 38110293 DOI: 10.1002/nbm.5086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 10/30/2023] [Accepted: 11/19/2023] [Indexed: 12/20/2023]
Abstract
Fluorine MRI is finding wider acceptance in theranostics applications where imaging of 19 F hotspots of fluorinated contrast material is central. The essence of such applications is to capture ghosting-artifact-free images of the inherently low MR response under clinically viable conditions. To serve this purpose, this work introduces the balanced spiral spectroscopic imaging (BaSSI) sequence, which is implemented on a 3.0 T clinical scanner and is capable of generating 19 F hotspot images in an efficient manner. The sequence utilizes an all-phase-encoded pseudo-spiral k-space trajectory, enabling the acquisition of broadband (80 ppm) fluorine spectra free from chemical shift ghosting. BaSSI can acquire a 64 × 64 image with 1 mm × 1 mm voxels in just 14 s, significantly outperforming typical MRSI sequences used in 1 H or 31 P imaging. The study employed in silico characterization to verify essential design choices such as the excitation pulse, as well as to identify the boundaries of the parameter space explored for optimization. BaSSI's performance was further benchmarked against the 3D ultrashort-echo-time balanced steady-state free precession (3D UTE BSSFP) sequence, a well established method used in 19 F MRI, in vitro. Both sequences underwent extensive optimization through exploration of a wide parameter space on a small phantom containing 10 μL of non-diluted bulk perfluorooctylbromide (PFOB) prior to comparative experiments. Subsequent to optimization, BaSSI and 3D UTE BSSFP were employed to capture images of small non-diluted bulk PFOB samples (0.10 and 0.05 μL), with variations in the number of signal averages, and thus the total scan time, in order to assess the detection sensitivities of the sequences. In these experiments, the detection sensitivity was evaluated using the Rose criterion (Rc ), which provides a quantitative metric for assessing object visibility. The study further demonstrated BaSSI's utility as a (pre)clinical tool through postmortem imaging of polymer microspheres filled with PFOB in a BALB/c mouse. Anatomic localization of 19 F hotspots was achieved by denoising raw data obtained with BaSSI using a filter based on the Rose criterion. These data were then successfully registered to 1 H anatomical images. BaSSI demonstrated superior detection sensitivity in the benchmarking analysis, achieving Rc values approximately twice as high as those obtained with the 3D UTE BSSFP method. The technique successfully facilitated imaging and precise localization of 19 F hotspots in postmortem experiments. However, it is important to highlight that imaging 10 mM PFOB in small mice postmortem, utilizing a 48 × 48 × 48 3D scan, demanded a substantial scan time of 1 h and 45 min. Further studies will explore accelerated imaging techniques, such as compressed sensing, to enhance BaSSI's clinical utility.
Collapse
Affiliation(s)
- Muhammed Yildirim
- Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Xenia Kovalyk
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Patrick Scholtz
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Markus Schütz
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Johannes Lindemeyer
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | | | - Holger Grüll
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Esin Ozturk Isik
- Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey
| |
Collapse
|
2
|
Kang SH, Lee Y. Motion Artifact Reduction Using U-Net Model with Three-Dimensional Simulation-Based Datasets for Brain Magnetic Resonance Images. Bioengineering (Basel) 2024; 11:227. [PMID: 38534500 DOI: 10.3390/bioengineering11030227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 02/20/2024] [Accepted: 02/23/2024] [Indexed: 03/28/2024] Open
Abstract
This study aimed to remove motion artifacts from brain magnetic resonance (MR) images using a U-Net model. In addition, a simulation method was proposed to increase the size of the dataset required to train the U-Net model while avoiding the overfitting problem. The volume data were rotated and translated with random intensity and frequency, in three dimensions, and were iterated as the number of slices in the volume data. Then, for every slice, a portion of the motion-free k-space data was replaced with motion k-space data, respectively. In addition, based on the transposed k-space data, we acquired MR images with motion artifacts and residual maps and constructed datasets. For a quantitative evaluation, the root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient of correlation (CC), and universal image quality index (UQI) were measured. The U-Net models for motion artifact reduction with the residual map-based dataset showed the best performance across all evaluation factors. In particular, the RMSE, PSNR, CC, and UQI improved by approximately 5.35×, 1.51×, 1.12×, and 1.01×, respectively, and the U-Net model with the residual map-based dataset was compared with the direct images. In conclusion, our simulation-based dataset demonstrates that U-Net models can be effectively trained for motion artifact reduction.
Collapse
Affiliation(s)
- Seong-Hyeon Kang
- Department of Biomedical Engineering, Eulji University, Seongnam 13135, Republic of Korea
| | - Youngjin Lee
- Department of Radiological Science, Gachon University, Incheon 21936, Republic of Korea
| |
Collapse
|
3
|
Maxouri O, Bodalal Z, Daal M, Rostami S, Rodriguez I, Akkari L, Srinivas M, Bernards R, Beets-Tan R. How to 19F MRI: applications, technique, and getting started. BJR Open 2023; 5:20230019. [PMID: 37953866 PMCID: PMC10636348 DOI: 10.1259/bjro.20230019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 11/14/2023] Open
Abstract
Magnetic resonance imaging (MRI) plays a significant role in the routine imaging workflow, providing both anatomical and functional information. 19F MRI is an evolving imaging modality where instead of 1H, 19F nuclei are excited. As the signal from endogenous 19F in the body is negligible, exogenous 19F signals obtained by 19F radiofrequency coils are exceptionally specific. Highly fluorinated agents targeting particular biological processes (i.e., the presence of immune cells) have been visualised using 19F MRI, highlighting its potential for non-invasive and longitudinal molecular imaging. This article aims to provide both a broad overview of the various applications of 19F MRI, with cancer imaging as a focus, as well as a practical guide to 19F imaging. We will discuss the essential elements of a 19F system and address common pitfalls during acquisition. Last but not least, we will highlight future perspectives that will enhance the role of this modality. While not an exhaustive exploration of all 19F literature, we endeavour to encapsulate the broad themes of the field and introduce the world of 19F molecular imaging to newcomers. 19F MRI bridges several domains, imaging, physics, chemistry, and biology, necessitating multidisciplinary teams to be able to harness this technology effectively. As further technical developments allow for greater sensitivity, we envision that 19F MRI can help unlock insight into biological processes non-invasively and longitudinally.
Collapse
Affiliation(s)
| | | | | | | | | | - Leila Akkari
- Division of Tumor Biology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - René Bernards
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | |
Collapse
|
4
|
van Heeswijk RB, Bauer WR, Bönner F, Janjic JM, Mulder WJM, Schreiber LM, Schwitter J, Flögel U. Cardiovascular Molecular Imaging With Fluorine-19 MRI: The Road to the Clinic. Circ Cardiovasc Imaging 2023; 16:e014742. [PMID: 37725674 DOI: 10.1161/circimaging.123.014742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
Fluorine-19 (19F) magnetic resonance imaging is a unique quantitative molecular imaging modality that makes use of an injectable fluorine-containing tracer that generates the only visible 19F signal in the body. This hot spot imaging technique has recently been used to characterize a wide array of cardiovascular diseases and seen a broad range of technical improvements. Concurrently, its potential to be translated to the clinical setting is being explored. This review provides an overview of this emerging field and demonstrates its diagnostic potential, which shows promise for clinical translation. We will describe 19F magnetic resonance imaging hardware, pulse sequences, and tracers, followed by an overview of cardiovascular applications. Finally, the challenges on the road to clinical translation are discussed.
Collapse
Affiliation(s)
- Ruud B van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland (R.B.v.H.)
| | - Wolfgang R Bauer
- Department of Internal Medicine I, Universitätsklinikum Würzburg, Germany (W.R.B.)
| | - Florian Bönner
- Department of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty of Heinrich Heine University, University Hospital Düsseldorf, Germany (F.B.)
| | - Jelena M Janjic
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA (J.M.J.)
| | - Willem J M Mulder
- Laboratory of Chemical Biology, Department of Biochemical Engineering, Eindhoven University of Technology, the Netherlands (W.J.M.M.)
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands (W.J.M.M.)
| | - Laura M Schreiber
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center (CHFC), Wuerzburg University Hospitals, Germany (L.M.S.)
| | - Juerg Schwitter
- Division of Cardiology, Cardiovascular Department (J.S.), Lausanne University Hospital (CHUV), Switzerland
- CMR Center (J.S.), Lausanne University Hospital (CHUV), Switzerland
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Switzerland (J.S.)
| | - Ulrich Flögel
- Experimental Cardiovascular Imaging (U.F.), Heinrich Heine University, Germany
- Cardiovascular Research Institute Düsseldorf (CARID) (U.F.), Heinrich Heine University, Germany
| |
Collapse
|
5
|
Chen J, Pal P, Ahrens ET. Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing. NMR IN BIOMEDICINE 2022; 35:e4725. [PMID: 35262991 PMCID: PMC10655826 DOI: 10.1002/nbm.4725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 02/25/2022] [Accepted: 03/04/2022] [Indexed: 06/14/2023]
Abstract
Fluorine-19 (19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density-weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a "zero" echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and l 1 -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.
Collapse
Affiliation(s)
- Jiawen Chen
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California, USA
| | - Piya Pal
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California, USA
| | - Eric T. Ahrens
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| |
Collapse
|
6
|
Li S, Shen C, Ding Z, She H, Du YP. Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning. Magn Reson Med 2022; 88:1851-1866. [PMID: 35649172 DOI: 10.1002/mrm.29307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data. METHODS A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks. RESULTS Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling. CONCLUSIONS The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.
Collapse
Affiliation(s)
- Shuo Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chenfei Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiping P Du
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| |
Collapse
|
7
|
Delgado PR, Kuehne A, Aravina M, Millward JM, Vázquez A, Starke L, Waiczies H, Pohlmann A, Niendorf T, Waiczies S. B 1 inhomogeneity correction of RARE MRI at low SNR: Quantitative in vivo 19 F MRI of mouse neuroinflammation with a cryogenically-cooled transceive surface radiofrequency probe. Magn Reson Med 2021; 87:1952-1970. [PMID: 34812528 DOI: 10.1002/mrm.29094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 12/26/2022]
Abstract
PURPOSE Low SNR in fluorine-19 (19 F) MRI benefits from cryogenically-cooled transceive surface RF probes (CRPs), but strong B1 inhomogeneities hinder quantification. Rapid acquisition with refocused echoes (RARE) is an SNR-efficient method for MRI of neuroinflammation with perfluorinated compounds but lacks an analytical signal intensity equation to retrospectively correct B1 inhomogeneity. Here, a workflow was proposed and validated to correct and quantify 19 F-MR signals from the inflamed mouse brain using a 19 F-CRP. METHODS In vivo 19 F-MR images were acquired in a neuroinflammation mouse model with a quadrature 19 F-CRP using an imaging setup including 3D-printed components to acquire co-localized anatomical and 19 F images. Model-based corrections were validated on a uniform 19 F phantom and in the neuroinflammatory model. Corrected 19 F-MR images were benchmarked against reference images and overlaid on in vivo 1 H-MR images. Computed concentration uncertainty maps using Monte Carlo simulations served as a measure of performance of the B1 corrections. RESULTS Our study reports on the first quantitative in vivo 19 F-MR images of an inflamed mouse brain using a 19 F-CRP, including in vivo T1 calculations for 19 F-nanoparticles during pathology and B1 corrections for 19 F-signal quantification. Model-based corrections markedly improved 19 F-signal quantification from errors > 50% to < 10% in a uniform phantom (p < 0.001). Concentration uncertainty maps ex vivo and in vivo yielded uncertainties that were generally < 25%. Monte Carlo simulations prescribed SNR ≥ 10.1 to reduce uncertainties < 10%, and SNR ≥ 4.25 to achieve uncertainties < 25%. CONCLUSION Our model-based correction method facilitated 19 F signal quantification in the inflamed mouse brain when using the SNR-boosting 19 F-CRP technology, paving the way for future low-SNR 19 F-MRI applications in vivo.
Collapse
Affiliation(s)
- Paula Ramos Delgado
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany.,Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Mariya Aravina
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | - Jason M Millward
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | | | - Ludger Starke
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | | | - Andreas Pohlmann
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| | - Thoralf Niendorf
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany.,Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité-Universitätsmedizin Berlin, Berlin, Germany.,MRI.TOOLS, Berlin, Germany
| | - Sonia Waiczies
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility, Berlin, Germany
| |
Collapse
|