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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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Wirestam R, Lundberg A, Chakwizira A, van Westen D, Knutsson L, Lind E. Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging. Heliyon 2022; 8:e12364. [PMID: 36590544 PMCID: PMC9801129 DOI: 10.1016/j.heliyon.2022.e12364] [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] [Received: 05/31/2022] [Revised: 10/18/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022] Open
Abstract
Background Estimation of the oxygen extraction fraction (OEF) by quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI) is promising but requires systematic evaluation. Extraction of OEF-related information from the tissue residue function in dynamic susceptibility contrast MRI (DSC-MRI) has also been proposed. In this study, whole-brain OEF repeatability was investigated, as well as the relationships between QSM-based OEF and DSC-MRI-based parameters, i.e., mean transit time (MTT) and an oxygen extraction index, referred to as apparent OEF (AOEF). Method Test-retest data were obtained from 20 healthy volunteers at 3 T. QSM maps were reconstructed from 3D gradient-echo MRI phase data, using morphology-enabled dipole inversion. DSC-MRI was accomplished using gradient-echo MRI at a temporal resolution of 1.24 s. Results The whole-brain QSM-based OEF was (40.4±4.8) % and, in combination with a previously published cerebral blood flow (CBF) estimate, this corresponds to a cerebral metabolic rate of oxygen level of CMRO2 = 3.36 ml O2/min/100 g. The intra-class correlation coefficient [ICC(2,1)] for OEF test-retest data was 0.73. The MTT-versus-OEF and AOEF-versus-OEF relationships showed correlation coefficients of 0.61 (p = 0.004) and 0.52 (p = 0.019), respectively. Discussion QSM-based OEF showed a convincing absolute level and good test-retest results in terms of the ICC. Moderate to good correlations between QSM-based OEF and DSC-MRI-based parameters were observed. The present results constitute an indicator of the level of robustness that can be achieved without applying extraordinary resources in terms of MRI equipment, imaging protocol, QSM reconstruction, and OEF analysis.
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Affiliation(s)
- Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Anna Lundberg
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Arthur Chakwizira
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Danielle van Westen
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
- Image and Function, Skåne University Hospital, Lund, Sweden
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Emelie Lind
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
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Markicevic M, Savvateev I, Grimm C, Zerbi V. Emerging imaging methods to study whole-brain function in rodent models. Transl Psychiatry 2021; 11:457. [PMID: 34482367 PMCID: PMC8418612 DOI: 10.1038/s41398-021-01575-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 08/05/2021] [Accepted: 08/23/2021] [Indexed: 02/07/2023] Open
Abstract
In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.
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Affiliation(s)
- Marija Markicevic
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Iurii Savvateev
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
- Decision Neuroscience Lab, HEST, ETH Zürich, Zürich, Switzerland
| | - Christina Grimm
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland.
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland.
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D'Alonzo RA, Gill S, Rowshanfarzad P, Keam S, MacKinnon KM, Cook AM, Ebert MA. In vivo noninvasive preclinical tumor hypoxia imaging methods: a review. Int J Radiat Biol 2021; 97:593-631. [PMID: 33703994 DOI: 10.1080/09553002.2021.1900943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 01/28/2021] [Accepted: 03/01/2021] [Indexed: 12/15/2022]
Abstract
Tumors exhibit areas of decreased oxygenation due to malformed blood vessels. This low oxygen concentration decreases the effectiveness of radiation therapy, and the resulting poor perfusion can prevent drugs from reaching areas of the tumor. Tumor hypoxia is associated with poorer prognosis and disease progression, and is therefore of interest to preclinical researchers. Although there are multiple different ways to measure tumor hypoxia and related factors, there is no standard for quantifying spatial and temporal tumor hypoxia distributions in preclinical research or in the clinic. This review compares imaging methods utilized for the purpose of assessing spatio-temporal patterns of hypoxia in the preclinical setting. Imaging methods provide varying levels of spatial and temporal resolution regarding different aspects of hypoxia, and with varying advantages and disadvantages. The choice of modality requires consideration of the specific experimental model, the nature of the required characterization and the availability of complementary modalities as well as immunohistochemistry.
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Affiliation(s)
- Rebecca A D'Alonzo
- School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, Australia
| | - Suki Gill
- School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, Australia
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Australia
| | - Pejman Rowshanfarzad
- School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, Australia
| | - Synat Keam
- School of Medicine, The University of Western Australia, Crawley, Australia
| | - Kelly M MacKinnon
- School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, Australia
| | - Alistair M Cook
- School of Medicine, The University of Western Australia, Crawley, Australia
| | - Martin A Ebert
- School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, Australia
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Australia
- 5D Clinics, Claremont, Australia
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Olsson E, Wirestam R, Lind E. MRI-Based Quantification of Magnetic Susceptibility in Gel Phantoms: Assessment of Measurement and Calculation Accuracy. Radiol Res Pract 2018; 2018:6709525. [PMID: 30155300 PMCID: PMC6091411 DOI: 10.1155/2018/6709525] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 07/05/2018] [Indexed: 11/17/2022] Open
Abstract
The local magnetic field inside and around an object in a magnetic resonance imaging unit depends on the magnetic susceptibility of the object being magnetized, in combination with its geometry/orientation. Magnetic susceptibility can thus be exploited as a source of tissue contrast, and susceptibility imaging may also become a useful tool in contrast agent quantification and for assessment of venous oxygen saturation levels. In this study, the accuracy of an established procedure for quantitative susceptibility mapping (QSM) was investigated. Three gel phantoms were constructed with cylinders of varying susceptibility and geometry. Experimental results were compared with simulated and analytically calculated data. An expected linear relationship between estimated susceptibility and concentration of contrast agent was observed. Less accurate QSM-based susceptibility values were observed for cylindrical objects at angles, relative to the main magnetic field, that were close to or larger than the magic angle. Results generally improved for large objects/high spatial resolution and large volume coverage. For simulated phase maps, accurate susceptibility quantification by QSM was achieved also for more challenging geometries. The investigated QSM algorithm was generally robust to changes in measurement and calculation parameters, but experimental phase data of sufficient quality may be difficult to obtain in certain geometries.
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Affiliation(s)
- Emma Olsson
- Department of Medical Radiation Physics, Lund University, Skåne University Hospital Lund, 22185 Lund, Sweden
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Skåne University Hospital Lund, 22185 Lund, Sweden
| | - Emelie Lind
- Department of Medical Radiation Physics, Lund University, Skåne University Hospital Lund, 22185 Lund, Sweden
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Ahlgren A, Wirestam R, Ståhlberg F, Knutsson L. Automatic brain segmentation using fractional signal modeling of a multiple flip angle, spoiled gradient-recalled echo acquisition. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2014; 27:551-65. [PMID: 24639095 DOI: 10.1007/s10334-014-0439-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2013] [Revised: 02/24/2014] [Accepted: 02/26/2014] [Indexed: 12/17/2022]
Abstract
OBJECT The aim of this study was to demonstrate a new automatic brain segmentation method in magnetic resonance imaging (MRI). MATERIALS AND METHODS The signal of a spoiled gradient-recalled echo (SPGR) sequence acquired with multiple flip angles was used to map T1, and a subsequent fit of a multi-compartment model yielded parametric maps of partial volume estimates of the different compartments. The performance of the proposed method was assessed through simulations as well as in-vivo experiments in five healthy volunteers. RESULTS Simulations indicated that the proposed method was capable of producing robust segmentation maps with good reliability. Mean bias was below 3% for all tissue types, and the corresponding similarity index (Dice's coefficient) was over 95% (SNR = 100). In-vivo experiments yielded realistic segmentation maps, with comparable quality to results obtained with an established segmentation method. Relative whole-brain cerebrospinal fluid, grey matter, and white matter volumes were (mean ± SE) respectively 6.8 ± 0.5, 47.3 ± 1.1, and 45.9 ± 1.3% for the proposed method, and 7.5 ± 0.6, 46.2 ± 1.2, and 46.3 ± 0.9% for the reference method. CONCLUSION The proposed approach is promising for brain segmentation and partial volume estimation. The straightforward implementation of the method is attractive, and protocols that already rely on SPGR-based T1 mapping may employ this method without additional scans.
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Affiliation(s)
- André Ahlgren
- Department of Medical Radiation Physics, Skåne University Hospital, Lund University, Barngatan 2B, 221 85, Lund, Sweden,
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