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Clement P, Mutsaerts HJ, Václavů L, Ghariq E, Pizzini FB, Smits M, Acou M, Jovicich J, Vanninen R, Kononen M, Wiest R, Rostrup E, Bastos-Leite AJ, Larsson EM, Achten E. Variability of physiological brain perfusion in healthy subjects - A systematic review of modifiers. Considerations for multi-center ASL studies. J Cereb Blood Flow Metab 2018; 38:1418-1437. [PMID: 28393659 PMCID: PMC6120130 DOI: 10.1177/0271678x17702156] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Quantitative measurements of brain perfusion are influenced by perfusion-modifiers. Standardization of measurement conditions and correction for important modifiers is essential to improve accuracy and to facilitate the interpretation of perfusion-derived parameters. An extensive literature search was carried out for factors influencing quantitative measurements of perfusion in the human brain unrelated to medication use. A total of 58 perfusion modifiers were categorized into four groups. Several factors (e.g., caffeine, aging, and blood gases) were found to induce a considerable effect on brain perfusion that was consistent across different studies; for other factors, the modifying effect was found to be debatable, due to contradictory results or lack of evidence. Using the results of this review, we propose a standard operating procedure, based on practices already implemented in several research centers. Also, a theory of 'deep MRI physiotyping' is inferred from the combined knowledge of factors influencing brain perfusion as a strategy to reduce variance by taking both personal information and the presence or absence of perfusion modifiers into account. We hypothesize that this will allow to personalize the concept of normality, as well as to reach more rigorous and earlier diagnoses of brain disorders.
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Affiliation(s)
- Patricia Clement
- 1 Department of Radiology and nuclear medicine, Ghent University, Ghent, Belgium
| | - Henk-Jan Mutsaerts
- 2 Cognitive Neurology Research Unit, Sunnybrook Healthy Sciences Centre, Toronto, Canada.,3 Academic Medical Center, Amsterdam, the Netherlands
| | - Lena Václavů
- 3 Academic Medical Center, Amsterdam, the Netherlands
| | - Eidrees Ghariq
- 4 Leiden University Medical Center, Leiden, the Netherlands
| | | | | | - Marjan Acou
- 1 Department of Radiology and nuclear medicine, Ghent University, Ghent, Belgium
| | - Jorge Jovicich
- 7 Magnetic Resonance Imaging Laboratory Center for Mind/Brain Sciences, University of Trento, Mattarello, Italy
| | | | | | | | - Egill Rostrup
- 10 Department of Diagnostics, Glostrup Hospital, University of Copenhagen, Denmark
| | | | | | - Eric Achten
- 1 Department of Radiology and nuclear medicine, Ghent University, Ghent, Belgium
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Stamatakis EA, Glabus MF, Wyper DJ, Barnes A, Wilson JT. Validation of statistical parametric mapping (SPM) in assessing cerebral lesions: A simulation study. Neuroimage 1999; 10:397-407. [PMID: 10493898 DOI: 10.1006/nimg.1999.0477] [Citation(s) in RCA: 44] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Simulated abnormalities were introduced in a normal SPECT with known and controllable characteristics (abnormality size and depth) in an attempt to provide validation for the analysis of SPECT lesion studies using SPM. Two simulations were carried out. The first determined the minimum hypoperfusion depth detectable using SPM by altering mean local intensity while keeping the size of the lesion constant. This was done by changing the mean local intensity in percentile increments of 10 down to -100 and up to 50. The second simulation determined the cluster size that SPM can detect by keeping the mean intensity of the lesion constant while altering its size from 4 voxels to 63,000 voxels in a total brain volume of 300, 000 voxels. Both simulations determined which method of normalization is most appropriate, what level of grey matter thresholding should be used, and at what statistical probability peak threshold (u) the results should be determined. Proportional scaling was found to be the most appropriate normalization method. ANCOVA was useful where very large abnormalities were present and normalization external to SPM was not available. In those cases, ANCOVA was used in conjunction with measurement of an unaffected part of the brain (in this case medial occipital lobe). For better results statistical probability peak threshold was set to p(u) = 0. 01 and grey matter threshold was set to a value below 0.5. SPM produced best results when the abnormality represented a decrease of about -50% from the normal or more and detected other decreases in an acceptable manner.
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Affiliation(s)
- E A Stamatakis
- Department of Psychology, University of Stirling, Stirling, Scotland
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Newberg AB, Alavi A. The study of the brain using PET and SPECT: implications for space and underwater neurology. J Neurol Sci 1996; 136:1-9. [PMID: 8815154 DOI: 10.1016/0022-510x(95)00288-d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Affiliation(s)
- A B Newberg
- Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA
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