Arterial input function estimation compensating for inflow and partial voluming in dynamic contrast‐enhanced MRI

Author:

Tseng Chih‐Hsien123ORCID,Nagtegaal Martijn A.14,van Osch Matthias J.P.234ORCID,Jaspers Jaap35,Mendez Romero Alejandra35,Wielopolski Piotr6,Smits Marion267,Vos Frans M.1236

Affiliation:

1. Department of Imaging Physics Delft University of Technology Delft the Netherlands

2. Medical Delta Delft the Netherlands

3. HollandPTC Consortium—Erasmus MC, Rotterdam, Holland Proton Therapy Center, Delft Leiden University Medical Center, Leiden and Delft University of Technology Delft the Netherlands

4. C.J. Gorter MRI Center, Department of Radiology Leiden University Medical Center Leiden the Netherlands

5. Department of Radiotherapy, Erasmus MC Cancer Institute University Medical Center Rotterdam Rotterdam The Netherlands

6. Department of Radiology and Nuclear Medicine Erasmus MC, University Medical Center Rotterdam Rotterdam the Netherlands

7. Brain Tumour Center, Erasmus MC Cancer Institute University Medical Center Rotterdam Rotterdam the Netherlands

Abstract

Both inflow and the partial volume effect (PVE) are sources of error when measuring the arterial input function (AIF) in dynamic contrast‐enhanced (DCE) MRI. This is relevant, as errors in the AIF can propagate into pharmacokinetic parameter estimations from the DCE data. A method was introduced for flow correction by estimating and compensating the number of the perceived pulse of spins during inflow. We hypothesized that the PVE has an impact on concentration–time curves similar to inflow. Therefore, we aimed to study the efficiency of this method to compensate for both effects simultaneously. We first simulated an AIF with different levels of inflow and PVE contamination. The peak, full width at half‐maximum (FWHM), and area under curve (AUC) of the reconstructed AIFs were compared with the true (simulated) AIF. In clinical data, the PVE was included in AIFs artificially by averaging the signal in voxels surrounding a manually selected point in an artery. Subsequently, the artificial partial volume AIFs were corrected and compared with the AIF from the selected point. Additionally, corrected AIFs from the internal carotid artery (ICA), the middle cerebral artery (MCA), and the venous output function (VOF) estimated from the superior sagittal sinus (SSS) were compared. As such, we aimed to investigate the effectiveness of the correction method with different levels of inflow and PVE in clinical data. The simulation data demonstrated that the corrected AIFs had only marginal bias in peak value, FWHM, and AUC. Also, the algorithm yielded highly correlated reconstructed curves over increasingly larger neighbourhoods surrounding selected arterial points in clinical data. Furthermore, AIFs measured from the ICA and MCA produced similar peak height and FWHM, whereas a significantly larger peak and lower FWHM was found compared with the VOF. Our findings indicate that the proposed method has high potential to compensate for PVE and inflow simultaneously. The corrected AIFs could thereby provide a stable input source for DCE analysis.

Publisher

Wiley

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