Abstract
Purpose: Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume v(p), and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. Methods: Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and vp quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and B-1(+) error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and B-1(+) correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. Results: Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error = 4.48 x 10(-4) min(-1)). However, these were reduced (<= 0.56 x 10(-4) min(-1)) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change = 0.45 x 10(-4) min(-1)). Conclusion: Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 0740-3194 |
Sprache: | Englisch |
Dokumenten ID: | 100377 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:34 |
Letzte Änderungen: | 17. Okt. 2023, 15:04 |