Print Email Facebook Twitter Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI Title Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI Author Tseng, C. (TU Delft ImPhys/Vos group; TU Delft ImPhys/Computational Imaging; Universiteit Leiden; Medical Delta) Jaspers, Jaap (Universiteit Leiden; Erasmus MC) Romero, Alejandra Mendez (Universiteit Leiden; Erasmus MC) Wielopolski, Piotr (Erasmus MC) Smits, M. (Erasmus MC; Medical Delta) van Osch, Matthias J.P. (Universiteit Leiden; Leiden University Medical Center; Medical Delta) Vos, F.M. (TU Delft ImPhys/Computational Imaging; TU Delft ImPhys/Vos group; Universiteit Leiden; Erasmus MC; Medical Delta) Date 2023 Abstract The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measured (Formula presented.) -weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC–AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC–AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE–AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE–AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI. Subject arterial input functioncerebral blood flowcerebral blood volumedynamic contrast enhanced MRIdynamic susceptibility contrast MRI To reference this document use: http://resolver.tudelft.nl/uuid:149af660-369a-46cc-81d5-e96e45be10a7 DOI https://doi.org/10.1002/nbm.5038 ISSN 0952-3480 Source NMR in Biomedicine, 37 (1) Part of collection Institutional Repository Document type journal article Rights © 2023 C. Tseng, Jaap Jaspers, Alejandra Mendez Romero, Piotr Wielopolski, M. Smits, Matthias J.P. van Osch, F.M. Vos Files PDF NMR_in_Biomedicine_2023_Tseng.pdf 1.95 MB Close viewer /islandora/object/uuid:149af660-369a-46cc-81d5-e96e45be10a7/datastream/OBJ/view