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Wu Y, Derks SHAE, Wood TC, de Blois E, van der Veldt AAM, Smits M, Warnert EAH. Improved postprocessing of dynamic glucose-enhanced CEST MRI for imaging brain metastases at 3 T. Eur Radiol Exp 2023; 7:78. [PMID: 38066225 PMCID: PMC10709288 DOI: 10.1186/s41747-023-00390-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 09/14/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Dynamic glucose-enhanced (DGE) chemical exchange saturation transfer (CEST) has the potential to characterize glucose metabolism in brain metastases. Since the effect size of DGE CEST is small at 3 T (< 1%), measurements of signal-to-noise ratios are challenging. To improve DGE detection, we developed an acquisition pipeline and extended image analysis for DGE CEST on a hybrid 3-T positron emission tomography/magnetic resonance imaging system. METHODS This cross-sectional study was conducted after local ethical approval. Static Z-spectra (from -100 to 100 ppm) were acquired to compare the use of 1.2 versus 2 ppm to calculate static glucose-enhanced (glucoCEST) maps in 10 healthy volunteers before and after glucose infusion. Dynamic CEST images were acquired during glucose infusion. Image analysis was optimized using motion correction, dynamic B0 correction, and principal component analysis (PCA) to improve the detection of DGE CEST in the sagittal sinus, cerebrospinal fluid, and grey and white matter. The developed DGE CEST pipeline was applied to four patients diagnosed with brain metastases. RESULTS GlucoCEST was strongest in healthy tissues at 2 ppm. Correcting for motion, B0, and use of PCA locally improved DGE maps. A larger contrast between healthy tissues and enhancing regions in brain metastases was found when dynamic B0 correction and PCA denoising were applied. CONCLUSION We demonstrated the feasibility of DGE CEST with our developed acquisition and analysis pipeline at 3 T in patients with brain metastases. This work enables a direct comparison of DGE CEST to 18F-fluoro-deoxy-D-glucose positron emission tomography of glucose metabolism in patients with brain metastases. RELEVANCE STATEMENT Contrast between brain metastasis and healthy brain tissue in DGE CEST MR images is improved by including principle component analysis and dynamic magnetic field correction during postprocessing. This approach enables the detection of increased DGE CEST signal in brain metastasis, if present. KEY POINTS • Despite the low signal-to-noise ratio, dynamic glucose-enhanced CEST MRI is feasible at 3 T. • Principal component analyses and dynamic magnetic field correction improve DGE CEST MRI. • DGE CEST MRI does not consequently show changes in brain metastases compared to healthy brain tissue. • Increased DGE CEST MRI in brain metastases, if present, shows overlap with contrast enhancement on T1-weighted images.
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Affiliation(s)
- Yulun Wu
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Sophie H A E Derks
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
- Departments of Neurology, Erasmus MC, Rotterdam, Netherlands
- Departments of Medical Oncology, Erasmus MC, Rotterdam, Netherlands
| | - Tobias C Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Erik de Blois
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
| | - Astrid A M van der Veldt
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
- Departments of Medical Oncology, Erasmus MC, Rotterdam, Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, Netherlands
- Medical Delta, Delft, Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, Netherlands.
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Seidemo A, Wirestam R, Helms G, Markenroth Bloch K, Xu X, Bengzon J, Sundgren PC, van Zijl PCM, Knutsson L. Tissue response curve-shape analysis of dynamic glucose-enhanced and dynamic contrast-enhanced magnetic resonance imaging in patients with brain tumor. NMR IN BIOMEDICINE 2023; 36:e4863. [PMID: 36310022 DOI: 10.1002/nbm.4863] [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: 06/27/2022] [Revised: 10/10/2022] [Accepted: 10/28/2022] [Indexed: 05/23/2023]
Abstract
Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p < 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.
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Affiliation(s)
- Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Gunther Helms
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | | | - Xiang Xu
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute, New York, New York, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Johan Bengzon
- Division of Neurosurgery, Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Lund Stem Cell Center, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Pia C Sundgren
- Lund University Bioimaging Center, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund and Malmö, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Knutsson L, Xu X, van Zijl PCM, Chan KWY. Imaging of sugar-based contrast agents using their hydroxyl proton exchange properties. NMR IN BIOMEDICINE 2023; 36:e4784. [PMID: 35665547 PMCID: PMC9719573 DOI: 10.1002/nbm.4784] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/30/2022] [Accepted: 06/03/2022] [Indexed: 05/13/2023]
Abstract
The ability of CEST MRI to detect the presence of millimolar concentrations of non-metallic contrast agents has made it possible to study, non-invasively, important biological molecules such as proteins and sugars, as well as drugs already approved for clinical use. Here, we review efforts to use sugar and sugar polymers as exogenous contrast agents, which is possible based on the exchange of their hydroxyl protons with water protons. While this capability has raised early enthusiasm, for instance about the possibility of imaging D-glucose metabolism with MRI in a way analogous to PET, experience over the past decade has shown that this is not trivial. On the other hand, many studies have confirmed the possibility of imaging a large variety of sugar analogues, each with potentially interesting applications to assess tissue physiology. Some promising applications are the study of (i) sugar delivery and transport to assess blood-brain barrier integrity and (ii) sugar uptake by cells for their characterization (e.g., cancer versus healthy), as well as (iii) clearance of sugars to assess tissue drainage-for instance, through the glymphatic system. To judge these opportunities and their challenges, especially in the clinic, it is necessary to understand the technical aspects of detecting the presence of rapidly exchanging protons through the water signal in MRI, especially as a function of magnetic field strength. We expect that novel approaches in terms of MRI detection (both saturation transfer and relaxation based), MRI data analysis, and sugar design will push this young field forward in the next decade.
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Affiliation(s)
- Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, US
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Peter CM van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, US
| | - Kannie WY Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering, Hong Kong, China
- Tung Biomedical Sciences Centre, City University of Hong Kong
- City University of Hong Kong Shenzhen Institute, Shenzhen, China
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Lehmann PM, Seidemo A, Andersen M, Xu X, Li X, Yadav NN, Wirestam R, Liebig P, Testud F, Sundgren P, van Zijl PCM, Knutsson L. A numerical human brain phantom for dynamic glucose-enhanced (DGE) MRI: On the influence of head motion at 3T. Magn Reson Med 2023; 89:1871-1887. [PMID: 36579955 PMCID: PMC9992166 DOI: 10.1002/mrm.29563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 11/09/2022] [Accepted: 12/07/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE Dynamic glucose-enhanced (DGE) MRI relates to a group of exchange-based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction. METHODS MPRAGE data from a tumor patient were used to simulate dynamic Z-spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head-motion-induced B0 -changes in presence of first-order shimming. The effect of retrospective motion correction was evaluated. RESULTS Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo-DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location. CONCLUSION DGE MRI studies can be corrupted by motion artifacts. Designing post-processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques.
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Affiliation(s)
- Patrick M Lehmann
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Mads Andersen
- Philips Healthcare, Copenhagen, Denmark
- Lund University Bioimaging Centre, Lund University, Lund, Sweden
| | - Xiang Xu
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Nirbhay N Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | | | | | - Pia Sundgren
- Lund University Bioimaging Centre, Lund University, Lund, Sweden
- Department of Radiology, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Kurz FT, Schlemmer HP. Imaging in translational cancer research. Cancer Biol Med 2022; 19:j.issn.2095-3941.2022.0677. [PMID: 36476372 PMCID: PMC9724222 DOI: 10.20892/j.issn.2095-3941.2022.0677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
This review is aimed at presenting some of the recent developments in translational cancer imaging research, with a focus on novel, recently established, or soon to be established cross-sectional imaging techniques for computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET) imaging, including computational investigations based on machine-learning techniques.
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Affiliation(s)
- Felix T. Kurz
- Department of Radiology, German Cancer Research Center, Heidelberg 69120, Germany,Correspondence to: Felix T. Kurz and Heinz-Peter Schlemmer, E-mail: and
| | - Heinz-Peter Schlemmer
- Department of Radiology, German Cancer Research Center, Heidelberg 69120, Germany,Correspondence to: Felix T. Kurz and Heinz-Peter Schlemmer, E-mail: and
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Breitling J, Korzowski A, Kempa N, Boyd PS, Paech D, Schlemmer HP, Ladd ME, Bachert P, Goerke S. Motion correction for three-dimensional chemical exchange saturation transfer imaging without direct water saturation artifacts. NMR IN BIOMEDICINE 2022; 35:e4720. [PMID: 35233847 DOI: 10.1002/nbm.4720] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/25/2021] [Accepted: 02/22/2022] [Indexed: 06/14/2023]
Abstract
In chemical exchange saturation transfer (CEST) MRI, motion correction is compromised by the drastically changing image contrast at different frequency offsets, particularly at the direct water saturation. In this study, a simple extension for conventional image registration algorithms is proposed, enabling robust and accurate motion correction of CEST-MRI data. The proposed method uses weighted averaging of motion parameters from a conventional rigid image registration to identify and mitigate erroneously misaligned images. Functionality of the proposed method was verified by ground truth datasets generated from 10 three-dimensional in vivo measurements at 3 T with simulated realistic random rigid motion patterns and noise. Performance was assessed using two different criteria: the maximum image misalignment as a measure for the robustness against direct water saturation artifacts, and the spectral error as a measure of the overall accuracy. For both criteria, the proposed method achieved the best scores compared with two motion-correction algorithms specifically developed to handle the varying contrasts in CEST-MRI. Compared with a straightforward linear interpolation of the motion parameters at frequency offsets close to the direct water saturation, the proposed method offers better performance in the absence of artifacts. The proposed method for motion correction in CEST-MRI allows identification and mitigation of direct water saturation artifacts that occur with conventional image registration algorithms. The resulting improved robustness and accuracy enable reliable motion correction, which is particularly crucial for an automated and carefree evaluation of spectral CEST-MRI data, e.g., for large patient cohorts or in clinical routines.
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Affiliation(s)
- Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Neele Kempa
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Philip S Boyd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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